THE INFLUENCE OF MARKETING STRATEGIES ON CONSUMER LOYALTY FOR AGRICULTURAL RETAIL STORES By LERATO BOGACWI Submitted in accordance with the requirements for the degree MAGISTER SCIENTIAE AGRICULTURAE Faculty of Natural and Agricultural Science Supervisor: Prof B J Willemse Department of Agricultural Economics Co-Supervisor: Dr A C Geyer Department of Agricultural Economics University of the Free State Bloemfontein 2017 DECLARATION I, Lerato Bogacwi, hereby declare that this dissertation represents my own work and findings except where indicated, and that all references are, to the best of my knowledge, accurately reported. I furthermore cede copyright of the dissertation in favour of the University of the Free State. _________________ Lerato Bogacwi Bloemfontein ii DEDICATION This thesis is dedicated to my magnificent and supportive family, especially my parents for their financial and spiritual support and encouragement throughout my education, not forgetting BKB Ltd for financial support. My grateful thanks to everyone for including me in their prayers, and to the Almighty for hearing them. iii ACKNOWLEDGEMENTS “Success is never final; failure is never fatal. It’s courage that counts.” John Woods My thanks to everyone who made this study possible: firstly, to God Almighty, for the strength and ability to further my education. Special thanks to my supervisors, Prof B J Willemse and Dr A C Geyer (co-supervisor) for guiding me throughout the whole research project and believing in me. An enormous thank you to BKB Ltd for financing my studies, including this particular study. Dr D Strydom, head of the Department of Agricultural Economics, University of the Free State, for his support and encouragement during the study. Mr E Owusu-Sekyere, my statistician, for his assistance in the data analysis process. His input is greatly appreciated. My appreciation to freelance editor, Elize Pretorius for the final language editing and formatting. Thanks for going the extra mile. My thanks also to my parents, Goitseone Bogacwi and Sothini Bogacwi, for being patient with me and giving me the encouragement and support to complete this project. iv And a special thank you to my son, Keaolopa, for always putting a smile on my face, especially when times were hard. Special thanks to the entire staff of the University of the Free State’s Department of Agricultural Economics for your continued support and guidance throughout the project. May God Almighty bless you all for being so kind to me. v ABSTRACT The main focus is on agricultural retail stores and on how these stores can retain the current market share they have and improve on gaining an even bigger market share. The study focused on 12 main attributes with their main marketing strategies to achieve customer loyalty. This study alternated between a descriptive and an explorative type of research, using the qualitative method describing the agricultural sector. The structured questionnaires, comprising closed-ended questions were distributed in all the focus areas of the nine provinces of South Africa. Even though not all provinces responded this study is significant and could assist further researches with a base framework to build from or create a better framework for the implementation in the industry. The results of this study will assist cooperatives and the new-generation cooperatives, as well as agribusinesses to improve where is needed to achieve better customer loyalty and to achieve a competitive advantage. The agricultural retail stores are competing not only among themselves but also with big hyper- and superstores. Customers are moving towards the “one-stop-shop” concept where they can purchase all their goods in one place. Agricultural stores can use this to their advantage. New business opportunities like online catalogues and sending customers and members special alerts and notifications are vital as customers are now becoming more technologically minded. Keeping customers and members informed will work to the benefit of the store. Building lasting relationships through innovative vi memberships and social media would increase the profitability of the agricultural retail store. This study is significant to the management within cooperatives in South Africa to provide them with a model to implement and assist their individual organisations to achieve or support competitiveness. vii Table of Contents DECLARATION ii DEDICATION iii ACKNOWLEDGEMENTS iv ABSTRACT vi Chapter 1 Introduction 1 1.1 Introduction 1 1.2 Background 1 1.3 Research area 7 1.3.1 Brief characteristics of each province 8 Free State 8 Eastern Cape 8 KwaZulu-Natal 9 Mpumalanga 9 Western Cape 10 1.4 Problem statement 12 1.5 Research objectives 16 1.6 Limitations 17 1.7 Outline of chapters 17 1.8 Conclusion 19 Chapter 2 Literature review 20 2.1 Introduction 20 2.2 Physical attributes 22 viii 2.2.1 Store appearance and image 23 2.2.2 Merchandise display 27 2.2.3 Product assortment 35 2.2.4 Store location 38 2.3 Market analysis 40 2.3.1 Customer service 40 2.3.2 Quality 41 2.3.3 Promotion 41 2.3.4 Advertising 41 2.3.5 Price points and other channel members 43 2.4 Qualitative factors 43 2.4.1 Customer loyalty 43 2.5 Differentiation focus strategy 47 2.6 Conclusion 48 Chapter 3 Data and research methodology 49 3.1 Introduction 49 3.2 Research design 49 3.3 Background data of the South African agricultural sector 51 3.3.1 Livestock production 51 3.3.2 Beef farming 51 3.3.3 Sheep and goat farming 51 3.3.4 Dairy farming 52 3.3.5 Poultry and pig farming 52 3.3.6 Game farming 53 3.3.7 Aquaculture 53 ix 3.4 Field crops and horticulture 54 3.4.1 Grain and oilseeds 54 3.4.2 Maize production 54 3.4.3 Wheat production 55 3.4.6 Potatoes 56 3.4.7 Cotton 57 3.4.8 Tea 57 3.5 Profile of respondents who participated in the survey 58 3.6 Sampling method 60 3.7 Population and sample 61 3.8 Instruments for data collection 62 3.8.1 Atmosphere attribute 62 3.8.2 Convenience attribute 62 3.8.3 Merchandise attribute 63 3.8.4 Structural attribute 63 3.8.5 Institutional attribute 63 3.8.6 Promotion attribute 64 3.8.7 Service attribute 64 3.8.8 Sales attribute 64 3.8.9 Credit attribute 64 3.8.10 Assistance attribute 65 3.8.11 Administration attribute 65 3.8.12 Loyalty attribute 65 3.9 Data analysis 67 Chapter 4 Results, discussion and conclusion 69 x 4.1 Introduction 69 4.2 Physical attributes 73 4.2.1 Atmosphere attribute rating 73 4.2.1.1 Highest ranking by province 74 4.2.1.2 Second-highest ranking by province 74 4.2.1.3 Third-highest ranking by province 74 4.2.1.4 Lowest rankings 75 4.2.2 Pearson’s correlation 76 4.2.3 Correlations of atmospheric sub-attributes 77 4.3 Convenience attribute rating 79 4.3.1 Definition of convenience 79 4.3.1.1 Highest ranking by province 79 4.3.1.2 Second-highest ranking by province 80 4.3.1.3 Third-highest ranking by province 80 4.3.1.4 Lowest rankings 80 4.3.2 Convenience attribute correlations 81 4.3.2.1 Workplace 81 4.3.2.2 Distance from home or farm 82 4.3.2.3 Distance to preferred store 82 4.3.2.4 Accessibility of store 83 4.3.2.5 Flow of customers 83 4.3.2.6 Walking required in-store 83 4.3.2.7 Variety of merchandise 84 4.3.2.8 Crowdedness of store 84 4.3.2.9 Store business hours 85 xi 4.4 Merchandise attribute rating 87 4.4.1 Definition of merchandise 87 4.4.1.1 Highest ranking by province 87 4.4.1.2 Second-highest ranking by province 88 4.4.1.3 Third-highest ranking by province 88 4.4.1.4 Lowest rankings 88 4.4.2 Merchandise attribute correlation 89 4.4.2.1 Merchandise category 89 4.4.2.2 Availability of imported merchandise 90 4.4.2.3 Latest products on the market 90 4.4.2.4 Type of farming 91 4.5 Structural attribute rating 93 4.5.1 Definition of structural 93 4.5.1.1 Highest ranking by province 94 4.5.1.2 Second-highest ranking by province 94 4.5.1.3 Third-highest ranking by province 94 4.5.1.4 Lowest rankings 94 4.5.2 Structural attribute correlation 96 4.5.2.1 Accessibility of store 96 4.5.2.2 Adequate parking 96 4.5.2.3 Connection to road network 97 4.5.2.4 Location 97 4.5.2.5 Tills 97 4.5.2.6 Point of sale 98 4.5.2.7 Payment options 98 xii 4.6 Institutional attributes 101 4.6.1 Definition of institutional 101 4.6.1.1 Highest ranking by province 101 4.6.1.2 Second-highest ranking by province 102 4.6.1.3 Third-highest ranking by province 102 4.6.1.4 Lowest rankings 102 4.6.2 Institutional attribute correlation 104 4.6.2.1 Relationships 104 4.6.2.2 Store image 104 4.6.2.3 Store Identity 105 4.6.2.4 Appearance of sales staff 105 4.6.2.5 Store appeal 106 4.6.2.6 Luxury versus convenience 106 4.7 Promotion attribute rating 109 4.7.1 Definition of promotion 109 4.7.1.1 Highest ranking by province 109 4.7.1.2 Second-highest ranking by province 110 4.7.1.3 Third-highest ranking by province 110 4.7.1.4 Lowest rankings 110 4.7.2 Promotions attribute correlation 111 4.7.2.1 Advertising credibility 111 4.7.2.2 Advertising methods used 112 4.7.2.3 Brochures in the mail 113 4.7.2.4 In-store display 113 4.7.2.5 Marked-down items 113 xiii 4.7.2.6 Stock on sale 114 4.8. Service attribute rating 116 4.8.1 Definition of service 116 4.8.1.1 Highest ranking by province 116 4.8.1.2 Second-highest ranking by province 117 4.8.1.3 Third-highest ranking by province 117 4.8.1.4 Lowest rankings 117 4.8.2 Service attribute correlations 118 4.8.2.1 Adequate sales staff 118 4.8.2.2 Delivery service 119 4.8.2.3 Inter-store transfers 119 4.8.2.4 Courier service 119 4.9 Sales attribute rating 122 4.9.1 Definition of sales 122 4.9.1.1 Highest ranking by province 122 4.9.1.2 Second-highest ranking by province 123 4.9.1.3 Third-highest ranking by province 123 4.9.1.4 Lowest rankings 123 4.9.2 Sales attribute correlation 124 4.9.2.1 Presentability of staff 124 4.9.2.2 Friendliness of staff 125 4.9.2.3 Product knowledge or orientation 125 4.9.2.4 Helpfulness of staff 125 4.9.2.5 Gender representation 126 4.10 Credit attribute rating 128 xiv 4.10.1 Definition of credit 128 4.10.1.1 Highest ranking by province 128 4.10.1.2 Second-highest ranking by province 129 4.10.1.3 Third-highest ranking by province 129 4.10.1.4 Lowest rankings 129 4.10.2 Credit attribute correlation 130 4.10.2.1 Credit influence 130 4.10.2.2 Availability of credit options 131 4.10.2.3 Financial product range 131 4.10.2.4 Ease of obtaining credit at a store/business 132 4.11 Assistance attribute rating 134 4.11.1 Definition of assistance 134 4.11.1.1 Highest ranking by province 134 4.11.1.2 Second-highest ranking by province 135 4.11.1.3 Third-highest ranking by province 135 4.11.1.4 Lowest rankings 135 4.11.2 Assistance attribute correlation 136 4.11.2.1 Special assistance 136 4.11.2.2 Moving purchased goods 137 4.11.2.3 Disability parking 137 4.11.2.4 Availability of visible security 138 4.12 Administration attribute rating 140 4.12.1 Definition of administration 140 4.12.1.1 Highest ranking by province 140 4.12.1.2 Second-highest ranking by province 141 xv 4.12.1.3 Third-highest ranking by province 141 4.12.1.4 Lowest rankings 141 4.12.2 Administration attribute correlation 142 4.12.2.1 Receiving invoices on time 142 4.12.2.2 Customers’ understanding of their own accounts 143 4.12.2.3 On time receipt of accounts and letters 143 4.12.2.4 Condition of a client’s account 144 4.13 Loyalty attribute rating 146 4.13.1 Definition of loyalty 146 4.13.1.1 Highest ranking by province 146 4.13.1.2 Second-highest ranking by province 147 4.13.1.3 Third-highest ranking by province 147 4.13.1.4 Lowest rankings 147 4.13.2 Correlation of loyalty sub-attribute 148 4.13.2.1 Earning points 148 4.13.2.2 Redeeming points 149 4.13.2.3 Customer loyalty 149 4.13.2.4 Access to internet 150 4.13.2.5 Self-service 150 4.13.2.6 Online purchases 151 4.14 Conclusion 153 Chapter 5 Summary and recommendations 159 5.1 Introduction 154 5.2 Summary of the theoretical study 154 5.3 Empirical study 154 xvi 5.3.1 Discussion of stages followed in carrying out the research: 155 5.3.1.1 Planning and framing 155 5.3.1.2 Gathering of primary and secondary data 155 5.3.1.3 Analysis of data and interpretation of results 156 5.4 Determining the marketing strategies for an agricultural retail store 157 5.5 Limitations of the study 157 5.6 Sample – research area 157 5.7 Stratified sampling 158 5.8 Discussion of results 158 5.8.1 Atmosphere 158 5.8.1.1 Highest ranking by province 158 5.8.1.2 Correlation 158 5.8.2 Convenience 159 5.8.2.1 Highest ranking by province 159 5.8.3 Merchandise 160 5.8.3.1 Highest ranking by province 160 5.8.3.2 Correlation 160 5.8.4 Structural 160 5.8.4.1 Highest ranking by province 160 5.8.4.2 Correlation 161 5.8.5 Institutional 161 5.8.5.1 Highest ranking by province 161 5.8.5.2 Correlation 161 5.8.6 Promotions 162 5.8.6.1 Highest rankings by province 162 xvii 5.8.6.2 Correlation 162 5.8.7 Service 163 5.8.7.1 Highest ranking by province 163 5.8.7.2 Correlation 163 5.8.8 Sales 164 5.8.8.1 Highest ranking by province 164 5.8.8.2 Correlation 164 5.8.9 Credit 164 5.8.9.1 Highest ranking by province 164 5.8.9.2 Correlation 165 5.8.10 Assistance 165 5.8.10.1 Highest ranking by province 165 5.8.10.2 Correlation 166 5.8.11 Administration 166 5.8.11.1 Highest ranking by province 166 5.8.11.2 Correlation 166 5.8.12 Loyalty 167 5.8.12.1 Highest ranking by province 167 5.8.12.2 Correlation 167 5.9 Recommendations 168 5.11 Recommendations for further research 170 Reference list 171 Appendix 1: Questionnaire 178 xviii List of tables Table 1.1: South African agricultural retail business and their registered status 15 Table 2.1: Main attributes with respective sub-attributes 23 Table 3.1: Geographical location of each agricultural retail store 51 Table 3.2: Provinces and the respective towns 62 Table 4.1: Mean of atmosphere attribute rating by province 75 Table 4.2: Correlation of atmosphere sub-attribute 79 Table 4.3: Mean of convenience attribute rating by province 80 Table 4.4: Correlation of convenience sub-attribute 87 Table 4.5: Mean of merchandise attribute rating by province 88 Table 4.6: Correlation of merchandise sub-attribute 93 Table 4.7: Mean of structural attribute rating by province 95 Table 4.8: Correlation of structural sub-attribute 102 Table 4.9: Mean of institutional attribute rating by province 104 Table 4.10: Correlation of institutional sub-attributes 108 Table 4.11: Mean of promotion attribute rating by province 108 Table 4.12: Correlation of promotion sub-attributes 116 Table 4.13: Mean of service attribute rating by province 118 Table 4.14: Correlation of service sub-attributes 120 Table 4.15: Mean of sales attribute rating by province 121 Table 4.16: Correlation of sales attribute rating 125 Table 4.17: Mean of credit attribute rating by province 126 Table 4.18: Correlation of credit sub-attributes 130 Table 4.19: Mean of assistance attribute rating by province 131 Table 4.20: Correlation of assistance sub-attributes 136 Table 4.21: Mean of administration attribute rating by province 137 Table 4.22: Correlation of administration sub-attributes 142 Table 4.23: Mean of loyalty attribute rating by province 143 Table 4.24: Correlation of loyalty sub-attribute 149 xix List of figures Figure 1.1: Customer behaviour 4 Figure 1.2: Presentation of all towns of study area 12 Figure 2.1: S-M-R Model of customer retail purchase behaviour 25 Figure 2.2: Store image influence satisfaction, loyalty and trust 27 Figure 2.3: Factors affecting micromarketing merchandising 39 Figure 2.4: Variables towards retail stock-out situations 47 Figure 3.1: Gender of respondents 59 Figure 3.2: Marital status of respondents 60 Figure 3.3 Occupation of respondents 61 Figure 4.1: Scatter plot examples of correlations 73 Figure 4.2: Atmosphere attribute rating (pool sample) 76 Figure 4.3: Representation of "extreme" correlation values of -1, 0 and 1 77 Figure 4.4: Convenience attribute rating (pool sample) 82 Figure 4.5: Merchandise attribute rating by customers 90 Figure 4.6: Structural attribute by customers 97 Figure 4.7: Institutional attribute rating by customers 104 Figure 4.8: Promotions attribute rating by customers 111 Figure 4.9: Service attribute rating by customers 117 Figure 4.10: Sales attribute rating by customers 122 Figure 4.11: Credit attribute rating by customers 128 Figure 4.12: Assistance attribute rating by customers 133 Figure 4.13: Administration attribute rating (pool sample) 140 Figure 4.14: Loyalty attribute rating by customers 145 xx Chapter 1 Introduction 1.1 Introduction Chapter one provides a brief background to the agricultural retail stores in South Africa. It also explains the outcome of marketing strategies on customer loyalty. This chapter also discusses the research problem of the study, the aims and objectives of the study furthermore, the rationale, research methodology, limitations and an overview. 1.2 Background Around the world, people have developed various ways of co-operating in the production and issuing of goods and services across different economic systems (Jacobs, 2007). Cooperatives started to prosper because of the initial commitment of their members. An agricultural marketing cooperative also called a “new-generation cooperative," is an association of farmers who willingly cooperate to join their production for sale. That production is marketed and distributed jointly through the cooperative, which is owned and controlled by the farmers themselves. Globally, farmers are increasingly encouraged to join marketing cooperatives, and cooperatives hold a significant market share in the agricultural product distribution from farms to final customers (Agbo, 2014). This type of cooperative slightly differs from the traditional cooperative. The traditional cooperative structure is limited in effectiveness due to “unclear definition of property rights, this can have a negative impact on productivity." Goods go from farm to customer. Not 1 much is done to market the goods. The cooperative is more farm approach-oriented than market approach-oriented. This happens because the decision-maker no longer bears the full brunt of his/her choice (Beverland, 2006). Finance is made available to farmers (who had little or none), through the cooperative structure, which adds to the loyalty factor of these farmers for their cooperatives. The loyalty factor can be described as a lack of competition for business and the members. Loyalty can also be defined in that members are satisfied with the operation of the business and are to a large extent not aware of developments that can influence these market players. The banking sector has offered loans to members so that they can obtain financing, which has led to increased competition in the market, credit facilities, and other modern attractions. These developments forced those once satisfied cooperative members into a new, different playing field with greater demand for competition, and an altered struggle for survival (Jacobs, 2007). Marketers have recognised the need for cooperatives to move from a farmer-centric to a market-centric approach. Previous research has revealed that traditional cooperatives struggle to support innovative marketing programmes in the long-run due to complications in the ownership structure. Additionally, new-generation cooperatives are able to succeed in the long-term and have the ability to capture the equity of intangible assets such as brand value. New-generation cooperatives take vital action in ensuring and establishing long-term positioning (Beverland, 2006). Cooperative stores are converting into retail stores to accommodate the non-farming customers, who form a large percentage of their overall clientele. In addition to the traditional feed and farm supplies, they offer garden centre supplies, pet supplies, farm clothing, lawn equipment and hunting supplies. These are combinations of the facilities 2 catered for. These stores also render extra services like pet grooming, lawn, and garden equipment maintenance and repair (Wilson, Hall and Fields 2011). Customers live in a world filled with ambiance (Machado, 2013). The design of more effective and efficient strategies will assist marketers in understanding the way people shop. The factors affecting their behaviour are of utmost importance. Customer understanding and market segmentation are vital for organisations; these factors are affected by an increase in competition (Purushottom, 2011). Knowledge of customer behaviour can assist business providers in the agricultural retail business in maximising returns, preventing customer disappointments, and diversifying their products to develop customer satisfaction and influence customers to continue doing business and become loyal customers (Abd Wahab, 2015). Customer behaviour is defined as the study of individuals, groups or organisations and the processes used in securing and selecting available products. It also includes the services, experiences or ideas used to satisfy the needs of customers. These processes have a considerable effect on customers and on society (Machado, 2013). 3 Figure 1.1: Customer behaviour Source: Machado (2013) Figure 1.1 illustrates that customer behaviour is made up of customer activities and customer response, each of which affects the other. Thus a customer’s emotional, mental .and behavioural responses can affect his or her purchase, usage and disposing activities, and vice versa. The emotional response reveals the customer’s passions, feelings and frame of mind. Figure 1.1 also indicates mental responses that form the customer’s thought processes, judgements, attitudes and values, and could direct a customer’s feelings towards a specific retail store (Machado, 2013). A customer’s perception of a retailer is determined by the store image (Bèzes, 2014). For (Wilson, Hall and Fields 2011), store layout, appearance, and convenience are the crucial features in determining the appeal of a store offering farm supplies to members. Jacobs (2007) argues that agricultural businesses should put more effort into: 4 ● Creativity in presenting their products, ● Spending on marketing, ● Implementing growth strategies that would showcase the seriousness and aggressiveness of their retail approach, ● In the process, they would be protecting their market share and increasing their skill levels from top to bottom, ● This would include the provision of appropriate training to staff at all levels, and ● Lastly, a well-formulated strategic vision. Customer loyalty is a topic that has received much attention since the 1990’s and as a result the field of relationship marketing has developed in the marketing landscape. Consequently, loyalty marketing has attracted the irreducible attention of marketers who are still trying to explore new ways to enhance the effectiveness of their relationship engagement with the customers. “Relationship or loyalty marketing assists in forming a reservoir of goodwill towards the brand image of companies.” Hence, loyalty marketing can assist in protecting companies from a market decline in times of uncertainty and economic turmoil. When loyalty marketing is applied, the benefit can be measured and observed through the observed restraining action, for example expected drop in sales or time required to regain the financial markets’ esteem (Tsolakis, 2014). Customer loyalty is a global goal for companies wanting to stay competitive. Gaining loyal customers helps businesses so that the occasional purchase of a particular brand will develop into repeat purchases, so creating customer satisfaction. This is the prime objective of a marketing strategy. In the current economic climate, it is of the utmost importance for stores to focus on their customers. Retaining loyal customers becomes of 5 crucial significance (Orth and Green, 2008). Retailers tend to implement the private label strategy. This strategy needs cautions, especially about the risky nature of product categories. Hence, the variation in customers’ purchase behaviour that may depend on prior trust in the retailer or loyalty to the store (Gonzela-Benito, 2012). For cooperatives the process of investing in marketing and breaking the commodity cycle has been very slow. Outside forces, like changes in customer demand, retail and the competitive landscape have also driven firms to take a more market-oriented approach. This includes the use of brands. Yet research on repositioning commodities as brands remains scarce, and to date, research has been silent on the effectiveness of agricultural cooperatives in developing market-oriented brand programmes (Abd Wahab, 2015) The recent economic decline may encourage the contemporary growth of store brands and has a consequential influence on the retail industry, with much focus on non-durable customer goods. “Various research efforts have analysed the potential of store brands to improve the retail performance.” This includes how effectively marketing of store brands might differentiate retail in the marketplace. This in turn enhances customer loyalty, sales and eventually retailers’ profitability (Purushottom, 2011). The South African market is a dynamic one when compared with the rest of Africa. In 2011 retail sales exceeded R1 trillion, which made history in the South African retail industry. It is also expected that the amount will increase to R1.46 trillion in 2016’s figures. Large holding companies dominate the market, collectively owning most of the country’s biggest brands. These companies are Shoprite, Spar, and Pick n Pay. These companies were all domestically owned before the arrival of Walmart (Price Water Cooper, 2012). The South 6 African retail market’s attractiveness is caused mainly by the growing population and the “positive long-term economic outlook” (Purushottom 2011). 1.3 Research area The research of the study was only conducted in five provinces of South Africa, although the questionnaires were dispatched to all provinces. The researcher had no influence on the composition of the sample respondents. With the geographical information system (GIS) system, the locations of the towns in question were plotted on the map. A geographic information system or geographical information system (GIS) is a system designed to capture, store, manipulate, analyse, manage, and present all types of spatial or geographical data (Robert, 1987). Initially the focus would have been on all 60 branches of BKB. Ten (10) questionnaires were sent to each branch, so it would have been 600 questionnaires. Questionnaires were sent out to all branches and of the 60 branches, only 19 responded. From that, some branches had more than 10 respondents. A total of 110 questionnaires were filled in. Only five branches participated and assisted in getting clients to partake in the survey. The focus of the study was in five provinces: The Free State, the Eastern Cape, Mpumalanga, KwaZulu-Natal and the Western Cape. The study took place at agricultural retail stores in these provinces. The data were collected in 19 towns/cities: Bloemfontein, Brandfort, Jacobsdal and Zastron (Free State); Aliwal North, Burgersdorp, Matatiele, Cradock, Elliot, Graaff-Reinet, Port Elizabeth and Sterkstroom (Eastern Cape); Standerton (Mpumalanga); Cedarville, Paulpietersburg, Utrecht, Vryheid, Volksrust (KwaZulu-Natal) 7 and Murraysburg (Western Cape). The study was focused on the South African context, as there is not much research done in this particular area of study in this country. Most of the research relevant to the study has been done abroad. 1.3.1. Brief characteristics of each province Free State The Free State takes up 10.6% of South Africa’s land area and has an area of about 13 000km2. The province is the country’s third biggest. Census South Africa estimated a population of 2.8 million people in the province (2011). Two-thirds of the population in the Free State speak Sotho (Sesotho SA Borwa), as well as in the neighbouring Lesotho, followed by Afrikaans. Fewer than 10% in the Free State speak Xhosa (isiXhosa) (www.southafrica.co.za). Bloemfontein is the capital of the Free State. The province is dominated by agriculture, with natural veld and grazing land. Field crops produce nearly two-thirds of the province’s gross agricultural income. Animal products add a further 30%, with the balance created by horticulture (www.southafrica.co.za). Eastern Cape The Eastern Cape is in the south-eastern part of South Africa. With an area of about 17 000km2, the Eastern Cape has a rich history, a reasonable climate, a wealth of natural resources and a superior lifestyle. It is the second-biggest province after the Northern Cape, taking up 13.9% of South Africa’s land area. Census South Africa estimated a 8 population of 6.5 million people in the province. The languages most spoken are Xhosa (isiXhosa) (78.8%), Afrikaans (10.6%) and English (5.6%) (www.dedea.gov.za) Port Elizabeth is the largest city in the province and lies on Algoa Bay. It also has two significant harbours – Port Elizabeth itself, and Ngqura. The province is rich in natural resources, from grazing land to forests and aquatic life. The soil is rich for farming purposes. The climate is excellent for the production of a variety of crops like pineapples, tea, tomatoes and chicory (www.dedea.gov.za). KwaZulu-Natal KwaZulu-Natal is South Africa’s third-smallest province. While it takes up 7.7% of the country’s land area, it has the country’s second-largest population, estimated at 10.3 million people, of whom most are Zulu (isiZulu-speaking). The principal language is Zulu (isiZulu), followed by English and lastly Afrikaans. Additionally, there is a lively Indian culture in the province, which gives KwaZulu-Natal an even richer cultural diversity. (www.southafrica.info.co.za). The soils of KwaZulu-Natal are very fertile due to the good rainfall, and some areas of the province experiences more than 1 000mm of rain a year. KwaZulu-Natal, in earlier times called Natal, is a major producer of sub-tropical fruit and especially sugar. The farmers also produce vegetables and practice dairy and stock farming. Forestry is also a major contributor to the income of the province (www.southafrica.info.co.za). Mpumalanga Mpumalanga, “the place where the sun rises," is a province with remarkable scenic beauty 9 and a great deal of wildlife, lying in the north-east of South Africa. It is the second-smallest province after Gauteng, taking up 6.3% of South Africa's land area, and has a population of just over four million people. Most of the population speak Swati (siSwati), which is also spoken in neighbouring Swaziland, followed by isiZulu. Tsonga (Xitsonga) and Ndebele (isiNdebele) are also spoken in the province (www.southafrica.info.co.za). Mbombela, (formerly Nelspruit) is the capital of the province. The city is the centre of the second-largest citrus-producing area in South Africa and is responsible for one-third of the country's exports of oranges. Groblersdal is an important irrigation area, yielding crops like citrus, cotton, tobacco, wheat and vegetables. The sheep farming area is Carolina, Bethal and Ermelo. However, potatoes, sunflowers, maize, and peanuts are also produced in that region (www.southafrica.info.co.za). Western Cape Note from researcher: Not enough respondents from this province and thus, not included in the analysis. It is included here as relevant information about South Africa and as comparison with the other provinces. The Western Cape is the country’s fourth-largest province, taking up 10.6% of South Africa's land area. It has a population of 5.8 million people. The capital is Cape Town, which is also South Africa’s parliamentary capital. The province has a cosmopolitan flavour created by the diverse cultures found there. The language most spoken is Afrikaans. Xhosa (IsiXhosa) and English are the other main languages (www.southafrica.info.co.za) The coast forms the southern and western boundaries and is fringed with mountains, where the dominant vegetation type is fynbos (meaning fine leaved bush). It is also the 10 main agricultural zone. The northern part is Karoo, rich in wool and mutton, mostly from Merino sheep. The province also produces broiler chickens, eggs, dairy products, beef and pork, not forgetting the fisheries (www.southafrica.info.co.za). Figure 1.2: Presentation of all towns of study area Source: (Geographical Information System, 2016) 11 1.4 Problem statement For businesses to survive in an increasingly competitive environment, constant adaptation to new and changing trends and circumstances are vital. Cooperatives can play a bigger role by helping producers to earn a larger share of the customer’s spending. Customers in the food industry are challenging the food industry to produce food products that are specific to market niches – niches that individual producers cannot always fill, but are attainable with the coordination of producer groups and alliances. This however, puts producers in a position to seek options for continued success in the industry (Coltrain, Barton and Boland, 2000). With so much competition in the market, retailers need to differentiate themselves from each other and try to stand out. Retailers need to be one step ahead of customers and know the latest trends in the market. Most cooperatives are making use of the new-generation cooperative (NGC) model. This model is vertically integrating and provides producers with larger earnings by selling processed products instead of raw products (Coltrain, Barton and Boland, 2000). Brands are universal features of modern markets. Intangible assets like brands provide firms with strong returns, awareness among customers and trade buyers like retailers, and provide firms with assets that are difficult to imitate. Brands represent the opposite of some commodity – products that have little differentiation in the eyes of the marketplace, and whose value is determined solely by the forces of supply and demand. Commodity suppliers are typically price takers. Agribusinesses have often been slow to develop brands, preferring instead to seek government protections, improve efficiency, or reduce buyer power through collective supply and marketing arrangements like cooperatives or producer boards (Beverland, 2006). 12 In 2007, more than 50% of global agricultural output was marketed through cooperatives in Finland, Italy and the Netherlands. Five years earlier in 2002, agricultural cooperatives accounted for 27% of total US (United States) farm marketing expenditure. New- generation cooperatives or marketing cooperatives comprise about 53% of all cooperatives, and product distribution represents 64% of the net business volume of cooperatives in the US. The rationale is those marketing cooperatives allow small farmers to get better or secure prices by overcoming the “dominant” oligopolistic investor-owned firms (IOFs). With marketing cooperatives, farmers are in a much better position in price negotiation and can have access to markets they cannot access individually. Cooperatives also enable farmers to face uncertainty about agricultural market prices. (Agbo, 2014). A company strategy must combine all the marketing goals into one comprehensive plan. A good marketing strategy should be drawn from market research and focus on the right product mix to achieve the maximum potential turnover and sustain the business (www.businessdirectry.com, 2016). Though questions have been raised about the viability of traditional cooperative arrangements to support a market-oriented strategy (Beverland, 2006), research on repositioning commodities like brands remains scarce, and so far research has been silent on the effectiveness of agricultural cooperatives in developing market-oriented brand programmes (Abd Wahab, 2015) Many cooperatives in South Africa converted to companies after the deregulation of the agricultural sector in 1995. The conversion involved a change of ownership and had the advantages of widening the product range and services offered by the companies. AFGRI 13 (Pty) Ltd and Senwes Ltd are examples of these conversions. In addition, due to deregulation many mergers and acquisitions have developed within the agricultural sector to respond to the changes in market structure and competitors. Regarding retail outlets, most of the mergers were horizontal integrations, so the core of the business remained the same (Jacobs, 2007). Table 1.1: South African agricultural retail businesses and their registered status Cooperatives Private companies Public companies (mostly listed) Coastal Farmer AFGRI Oranje Edms Bpk BKB Beperk Co-op Ltd Obaro MGK Bedryfsmaatskappy East Cape Agric Co-op Ltd Kaap AFGRI Bedryf (Edms) Bpk Griekwaland-Wes Korp Bpk Suidwes Landbou (Edms) Bpk KLK Landbou Bpk Karoo-Oranje Landbou Koöp BNK Landbou (Edms) Bpk NTK Limpopo Agric Bpk Moorreeseburgse Koringboere Kat River Citrus Cooperative NWK Beperk (Edms) Bpk Noord-Boland Landbou (Edms) Langkloof Boere Koöp OVK Bedryf Bpk Bpk Oranje Koöp Bpk VKB (Vrystaat Koöp Bpk) Senwes Bpk Humansdorp Koöp TWK Landbou Bpk Sentraal Suid Koöp Bpk CRK Landbou Bpk Klein Karoo Koöp Bpk Kaap AFGRI Bedryf Bpk Wes Karoo Koöperasie Bpk KLK Landbou Bpk Overberg AgriBedrywe Bpk Tuinroete AFGRI Bpk AFGRI Operations Ltd (listed) Source: (Jacobs, 2007) Due to the mergers and conversions of cooperatives into companies, the term agricultural retail business refers to current agricultural cooperative retail outlets. Table 1.1 gives insight into the South African agricultural retail businesses and their registered status. The product ranges of these outlets are hardware, irrigation, paint products, building materials and outdoor products. (Jacobs, 2007). These include converted companies fuel, fertiliser, 14 chemical products and crop seeds that are available, of which a good example is BKB Ltd. Cooperatives can make use of marketing strategies employed by different industries to assist them in gaining as many loyal customers as possible. In the food industry, companies study their current client base, then develop a market segmentation, analyse it and from there drawing up a marketing plan to attract an even greater client base. An agribusiness would have to employ contract-farming agreements with farms, and take the responsibility to sell products to manufacturing and retail clients (Barnard, Akridge, Dooley, Foltz and Yeager, 2016). Market segmentation is the process of taking the company's current client base, as well as potential customers, and wisely assessing three sets of criteria regarding the groups namely; ● Physical attributes: These refer to the client base size, location, and evaluated interest in or need of the products offered, in addition to other distinguishing factors. ● Analysis: Companies need to study the behaviour of their clients, which can include information about how frequently they visit the store, products the clients purchase and the quantity normally purchased. The methods used here are e-mail advertisements, pamphlets and direct contact with clients. ● Quantitative factors: Deals with the overall feeling of the client about a company’s brand offered, intentions to purchase and sometimes the service the client receives from the company (McKechnie, 2014). With all these factors mentioned, the problem remains in the South African context, whether agricultural retail stores have an effective marketing strategy to stay relevant and 15 competitive in the market, understand customer behaviour and meet customer demand retain current customers, accurately target potential customers and gain customer loyalty. 1.5 Research objectives The main objective of the study is to investigate marketing strategies for agricultural retail stores in the five identified provinces of South Africa. Primary objectives:  To determine essential attributes for an agricultural retail store.  To determine customer loyalty.  To determine the marketing strategies for an agricultural retail store in South Africa. The study should serve as a powerful tool for retailers in the agricultural sector to develop their stores with the right marketing strategies as well as in gaining customer loyalty in the same regard. This study is significant to the management within cooperatives in South Africa to provide them with a model to implement and assist their individual organisations to achieve or support competitiveness. It could assist further researches with a base framework to build from or create a better framework for the implementation in the industry. The study also aims to assess a number of attributes: atmosphere, convenience, merchandise, structural factors, institutional factors, promotions, service, sales, credit, assistance available, administration and loyalty. The problems related to each of these attributes will be discussed in the last chapter. It is important that the participants in the survey provide the researcher with the information needed and respond to each question with honesty. The questionnaire is for the benefit of 16 the customer and the retailer, with the customer providing information and the retailer using that information to provide efficient and excellent customer service. 1.6 Limitations Limitations in this study were identified in terms of the sample size, which was limited to 110 respondents. According to Trochim (2015), sampling is the “process of selecting units from a population of interest so that in studying the sample the researcher can fairly generalise results back to the population from which they were chosen” (Trochim, 2015). Natural sampling was used as the researcher had little influence on the composition of the sample respondents. Other limitations: ● Illiteracy or inadequate literacy among older customers. ● The travel distance between the provinces. ● Some customers are not willing to cooperate. ● The period set for data collection was extended due to unforeseen circumstances. The study was conducted in only five provinces in South Africa, so the results of the study cannot be generalised to all agricultural retail stores. 1.7 Outline of chapters The report of this study is made up of five chapters, covering these areas: Chapter One This chapter presents an introduction to the study. It provides an overview of the research problem, the research objectives, the rationale behind the research methodology and the limitations. 17 Chapter Two This chapter discusses the literature on marketing strategies, theories and attributes of an agricultural retail store. It also touches on customer behaviour and perceptions of what a cooperative retail store can do to attract customers and create customer loyalty. This chapter examines various concepts relating to the attributes of an agricultural store, ranging from atmosphere to loyalty. Chapter Three The research methodology is presented in this chapter. It shows how the data were collected and gives insight into sampling methods used, the questionnaire, and various techniques used to analyse the results. It also contains a review of the validity and reliability of the research investigation, including areas where errors might have occurred. Chapter Four The purpose of this chapter is to present the statistical analysis of the data obtained. The data has been processed into meaningful results that the reader is able to interpret and understand. Chapter Five This is the final chapter of the research paper and contains the conclusions drawn from the findings in Chapter Four. Recommendations and suggestions for further research are provided. 18 1.8 Conclusion Chapter one provides a brief background about agricultural retail stores in South Africa. It also explains the effect of marketing strategies on customer loyalty. It discusses the research problem of the study, the aims and objectives, the rationale, research methodology, limitations and an overview. The next chapter will review the literature in more detail and cover the theme of the significant characteristics relating to the study. 19 Chapter 2 Literature review 2.1 Introduction This chapter gives an overview of the relevant literature on marketing strategies for an agricultural store in South Africa. The main objective of retailing is to: connect supply and demand; and provide customers with a selection of goods and services that satisfy their needs profitably. The contributing elements of retail success are key success factors that can be used as a benchmark to determine individual company performance against market performance because these factors are present in all retail environments (Jacobs, 2007). The literature will cover more than just a survey of information that comprises items constituting some literature on the area of study. Examining the literature will give a theoretical understanding of the study and also of what past researchers have discovered. It should be taken into consideration that the literature examined relates to studies done in countries other than South Africa, but nonetheless relates to the study at hand. The literature will cover the marketing strategies, linking them up with store attributes that will help cooperatives improve their marketing. Marketing cooperatives assist producers with these functions: ● balancing the market where prices are too low or buyers have exited the market: ● providing a service not available otherwise; ● gaining market power (negotiating power) against much larger buyers; 20 ● spreading risks and costs; and ● having enough volume to meet the needs and demands of buyers (Rural Business and Cooperative Service, 2000). Brands can be an easy feature for current markets. With the use of brands, cooperatives can move in a hierarchy of becoming price makers. This is because brands represent differentiation (Beverland, 2006). Customer value is very important for any agribusiness to understand the customers. The term customer value describes the emotional bond created between the customer and the producer. This is after the customer has made use of the good or service provided by the producer and has added value to the customer. Marketing operates within a dynamic global environment. The key to success in the rapidly changing marketing environment will be a strong focus on the marketplace and a total marketing commitment to providing value to customers. This, however, will be divided into three sections. Each section will have the sub-sections, which relate to the main division. The outlay will be that of the objectives of the study and the competitive attributes will be discussed in detail as follows: The main attributes to be competitive is depicted in Table 2.1 followed with a short description of each attribute. This refer to the client base size, location, and evaluated 21 interest in or need of the products offered, in addition to other distinguishing factors: Table 2.1: Main attributes with respective sub-attributes and marketing strategy Main attributes Sub-sections Marketing strategy Physical attributes Atmosphere attribute Merchandise attribute Convenience attribute Structural attribute Sales attribute Credit attribute Differentiation focus strategy Assistance attribute Administration attribute Market analysis Promotions attribute Service attribute Qualitative factors Loyalty attribute Source: (Author, 2016) 2.2 Physical attributes As mentioned in Chapter 1, client base size, location and the evaluated interest of products offered all fall under physical attributes, in addition to other distinguishing factors. Under physical attributes: store appearance and image, merchandise display, product assortment as describe in the following. 22 2.2.1 Store appearance and image The significance of maintaining a competitive advantage lies in the development of a strong positive appearance (Tlapana, 2009). A store is characterised by the descriptive features that are aspects of store image; what a customer thinks a store is or has; and what is involved with the patronage (Dhurup and Oosthuyzen, 2010). Further research material advocated that attributes of store image and appearance affect customers’ preference for particular stores. The stimuli that apply to store attributes include merchandising, store atmosphere, in-store service, accessibility, reputation, promotion, facilities and post- transaction service. Post-visit ranking of stores hinges on the customer’s preference. A customer’s visit to a store also depends on the level of service provided in- store. In-store service quality may have an enormous influence on customers’ purchasing behaviour: if it clashes with the values or beliefs of target customers, this could inhibit attraction. The diagram below depicts the components of a good store appearance (Tlapana, 2009). 23 STIMULUS MECHANISM RESPONSE (S-M-R) Store image Merchandising Store atmosphere Consumer Accessibility Preference Reputation perception for store Promotion Facilities Post-transaction Figure 2.1: S-M-R Model of customer retail purchase behaviour Source: (Tlapana, 2009) Figure 2.1 shows the S-M-R model, initially the S-O-R Stimulus – Organism - Response model, adapted from previous studies. This model focuses on the important elements needed for the success of a store’s appearance and image. In a business-oriented environment, management needs to familiarise itself with each element in the model (Tlapana, 2009). Kim and Jin (2009) has reviewed the S-O-R or S-M-R framework, focusing on the components of the retail environment and the effect they have on customers. The main thrust of the S-O-R framework is that environments contain stimuli (incentive or motivator) that contribute to changes in the state of an organism, which in turn shape that organism’s/mechanism’s (action) behaviour. The letter S relates to “some stimulus external to the actor”, M refers to the “actor or human organism”, and R represents the 24 “actor’s response or behaviour (reaction)”. The S refers to the thrill of entering a store, the M to the internal decision-making of the customer and the R to the response of the customer to the store’s environment. Previous research revealed that the importance of store choice lies with the emphasis placed on the physical features of a retail environment (Dhurup and Oosthuyzen, 2010). The research also revealed that the physical environment of a store could extend the duration of a customer’s visit and increase the initial amount of money spent. This could mean that the physical environment intensifies customer emotions and reduces negative mood states (Dhurup and Oosthuyzen, 2010). In addition to this, Visser and Du Preez (2006) revealed that merchandise, and after that convenience, is regarded by customers as very significant store image dimensions. Zentes, Morschett, and Schramm-Klein, (2007) argued that it was of utmost importance for the staff to be visible, competent and friendly and to deliver quality service, even in self- service sectors. Marketing and constant communication can be strengthened by the skill and knowledge of the staff. This can influence the customer’s perception of store image and his/her patronage intention (Hu and Jasper, 2006). Al-Awadi (2002) argued that the exterior design of a cooperative building has a substantial positive psychological influence on the customer and is a factor in the decision to enter the building to shop. Shamiyyah, Rawdhah and Mishref give good examples of complexes that are appropriate to environmental and weather conditions in the State of Kuwait. Customer loyalty depicted in Figure 2.2: 25 Figure 2.2: Store image influence satisfaction, loyalty and trust Source: (Orth and Green, 2009) Figure 2.2 was used in a study as a conceptual framework to determine customer loyalty to family businesses as against non-family businesses. The aims of store image are: ● Trust, and ● Satisfaction The results revealed that family business stores excelled in service and were poor in terms of price/value. Family businesses scored high in social consciousness and problem solving. Store image had a positive influence on satisfaction and this led to trust and loyalty. Facets contributing to the distinctiveness of a store are the image, merchandising and store 26 appearance. Various messages are transmitted to customers through the store’s internal and external design. The building that houses the establishment (new or old) and the external design of the store are significant aspects of the design. When it comes to the interior design of a store, the management of space is always of utmost concern and the first dynamic retailers always thinking about. The most inadequate and costly resource is always space. It is always important to allocate adequate space for various merchandise categories within the store (Tlapana, 2009). 2.2.2 Merchandise display Merchandise display can be described as distinctive presentations of a store’s products to draw customers and persuade them to buy. The nature of the display may vary from industry to industry, but the entire merchandise display is based on basic principles formulated to raise product purchases. Without a doubt, merchandise display is an intrinsic element largely merchandising concept, which seeks to encourage product sales by coordinating marketing, advertising, and sales strategies. The main focus of merchandising is display, on selecting the product and how it will be presented; this will be aligned with the overall store design, store layout, and other features of the store environment. This results in the parallel functions of in-store marketing and store design (Zentes, Morschett and Schramm-Klein, 2007) Two main aims of in-store marketing are: ● Easy internal direction. The store must be designed in such a way that customers find it uncomplicated to move around in. ● Creating a positive emotional state of mind for the customer. This can be achieved 27 by creating a positive atmosphere for people visiting the store. Both facets, stores and customer segments, are essential in different degrees. The retailer’s main concern is for the store orientation to be user-friendly and to simplify the search process for customers. So the shopping situation needs to be less confusing for customers and to create a safe and self-confident atmosphere where shopping is pleasant, thanks to the way the merchandise is displayed (Zentes, Morschett and Schramm-Klein, 2007). A retailer’s complete offerings are known as a merchandise mix or product range. Merchandise management is in charge of the selecting the correct product for the store; this is done at a strategic level. At operational level, customers are assured that products are available for purchase (Tlapana, 2009). Small business owners who are new entrants may view merchandise and display as additional vapid expenditure while marketing, rent, inventory, utilities and staffing are heavy expenses. Merchandising and display, which in fact form a fundamental aspect of the retail environment, are viewed as frills. Provision should be made for merchandise and display for any given budget, big or small. Every competitor is competing for the customer’s money. Therefore, accounting for merchandising in a retail plan and budget will make a difference between selling the product and having it accumulate dust on the shelf (Mclntosh, 2007). The use of captivating displays by retailers can lead shoppers to sacrifice time, effort and distance travelled to go shopping at other stores (Kim and Jin 2001). “This technique proposes that customers shop at stores where they maximise their satisfaction (efficiency), 28 taking into account both retail attributes and shopping expenses.” A welcoming shopping environment has a positive influence on the time and money shoppers spend in the store and the emotion of shopping (Kim and Jin, 2001). Thang and Tan (2003) states the merchandising of a store is the most crucial aspect, contributing to a customer preference for that store. This authenticates the statements by (Hanson, 1980), Nevin, and Houstan (1980) on the need for retail agglomeration – it makes reference to the “shopping under one roof” concept to draw customers as a vital element of store management (Huff, 1962). Olson (2007) states that due to the changing times customers are less dictated to, their changing tastes and preferences being more complex than before and the profit life cycle shorter. This requires retailers to be on the alert to the changing tastes and preferences of customers. This has led smart merchants to combine the art and science of merchandising to build a new design of merchandising using computer programmes as a resource and support system. Whalin (2001) states that retailers must be able to stand out. They can do this with unique merchandise, giving customers a fascinating and thrilling environment that will create an enjoyable, unforgettable shopping experience. There should be creative ways of displaying the regular change in the mix and the distinctiveness of merchandise. Impulse buying and product consciousness can be stimulated by the use of merchandising “hot spots” where traffic flow is concentrated. With the addition of excellent appearance, the presence of friendly staff can have a positive effect on customer loyalty and growth in sales. Winning retailers are normally proactive in anticipating customer preferences and customer expectations in their merchandising practices. When allocating products to particular shelves, one places them in reach of the eyes, the 29 hands and the feet. Shelf strategy is focused on the collocation of products on the shelves (how supermarkets place or organise them). Hita (1997) states that supermarket shelves make use of the three strategies mentioned above. First level: The most important is eye level, because the customer is able to see the product clearly. Supermarkets and hypermarkets use this level for placing the most expensive products that are usually the best-known brands Second level: The level of the hands is also easily accessed by the customer. Here, the products are frequently cheaper than at eye level, but more expensive than those lower down. The brands are also well-known. Third level: At the level of one’s feet, the cheaper products are placed. Access is more difficult than the other levels, and the customer has to make an effort to pick the product up. The “private label brands” are frequently placed at this level. “Private label brands” (also called “private brands”) are those owned not by a manufacturer or producer but by a retailer or supplier that has the goods made by a contract manufacturer under the own label. Where shelves are arranged horizontally, the most expensive products are placed at the beginning and at the end. In this way customers wanting to buy inexpensive products have to walk past the expensive ones they are tempted to buy, from both directions. In research conducted by the Food Marketing Institute (FMI) it was found that products positioned at eye level or slightly below appear to be the most purchased. Eye level is explained as being 1.3 metres from the floor. As a result, companies prefer to place their products at eye level or within the reach of children. Leading brands or popular items are 30 usually placed at eye level. New products are often placed on eye level shelves for promotion; to generate awareness customers are invited to try them out and by doing so also purchase them. Normally heavier products are placed on the bottom shelf and the lighter products on the top shelves (Aghazadeh, 2005) Hefer (2014) confirms Aghazadeh (2005) where he states that displays put at eye level were physically displayed products, meaning that these products could be bought by making use of mannequins or half-mannequins. Images, posters and pictures create a lesser intention and interest to buy, as they do not create a sensory experience. Further findings by Hefer (2014) reveal that distinguishable visual stimulant is a significant element of visual merchandising displays – for instance, colour creates visual attraction and stimulation in a clothing retail store. The positioning of visual merchandising displays and the use of space and lighting inside a store are significant. Tidiness is also essential, and visual merchandising displays must provide information about the merchandise sold in the store. Diversity of products on display should be focused or be kept at a minimum to reduce customer confusion. In essence, visual merchandising displays should reflect the needs of customers as individuals Dhurup and Oosthuyzen, (2010) conducted a study that revealed the links between merchandise variety, quality, assortment and the reliability of products offered. This affirms the findings of Sinha and Banerjee (2004), who found in his study that more than 70% of respondents viewed merchandise quality and variety as strong reasons for store selection. These two findings go in parallel with the findings of Thorpe and Avery (1983) and Mahoney and Sternquist, (1989) in which store selection was made based on high quality merchandise and merchandise assortment. These were seen as appealing characteristics for a store selection decision. 31 Customers prefer to visit stores with a wider and more comprehensive variety of products. In grocery stores, it is usual to stress the significance of the customer’s level of comfort with the retailer. Shoppers are more than prepared to trade off the additional distance to other outlets against the experience. An experience is created through services and merchandise. For customers to be able to touch and feel products is a good consideration. This can also be achieved through good display. Therefore, stores stocking up and displaying an adequate variety of brands and models will guarantee visits from shoppers (Sinha and Banerjee, 2004) Merchandise display focuses on how the product or brand is communicated to the customer visually. These themes are coupled to purchase intention: ● Awareness of fixtures, ● Path finding, ● Sensory qualities of materials, and ● Lighting. The diversity in merchandise display methods comes from the large assortment of goods and services sold by retailers (Kerfoot, Davies and Ward, 2003). An appealing and enticing merchandise display prompts the customer to browse through the store, which leads to purchasing. Previous research studies support this pattern, with results seen in rising purchasing patterns (Kerfoot, Davies and Ward, 2003). In addition to visual merchandising, retailers want to provide customers with an enjoyable shopping experience (Levy and Weitz, 2007). In service stores merchandise their products strategically, staple products included. This 32 type of merchandising makes customers walk around looking for items and requires them to walk past higher-profit items, like luxury goods. Such a display can often result in higher sales and higher profits (Merchandise display, 2008). These elements form part of merchandising: ● Correct strategic placement in the store; ● Eye-catching and appealing display; ● Appropriate point of sale support media (e g labels, signs); and ● Legal requirements satisfied. Customers would prefer to shop at a store with enough stock available. Market basket analysis has an effect on the design of a store. A store must be designed in such a way that it accommodates the shoppers (Jacobs, 2007). Krishnan, Koelemeijer and Rao (2002 argues that there should be consistency in product assortment – that is, product availability. Consistency of assortment is explained as the tactical promise a retailer makes to carry a certain set of brands, sizes, flavours, and colours from one period to the next. This will enable the customer to find his/her preferred brand in the preferred retail store. The retailer’s location and the merchandise display have an effect on the customer’s final choice. Therefore, the retailer’s reaction is not yet clear, given that businesses compete in a competitive environment in a vast segment of a market that seeks consistent merchandise assortment. To respond to sudden changes in trends and consumption patterns, retailers need to have the correct measures in place, which are either lean or responsive. Through these measures, a retailer will respond by having the precise product at a particular place, at a 33 given time, in smaller volume sizes, with increasing frequency. Excellent merchandise display leads simultaneously to delighted customers and profitability. This leads to higher levels of distribution for retailers who achieve efficient merchandise displays (Azuma and Fernie, 2001). In most retail outlets, a premium is paid for merchandise display. Most retail stores depend on a high volume of sales. Display space is used according to the contribution of other product lines to sales and profitability. The most challenging part in retail is selecting the most suitable product mix and layout of various product lines and categories from which shoppers can choose from with limited shelf space (Mitchell and Ingram, 2002). Factors that determinate optimal product display assortments are: ● The value the market places on each available product, including products viewed as completely unacceptable; and ● How the market assesses sustainability across products based on price. 34 2.2.3 Product assortment While members of an agribusiness or cooperative are different as a whole, they all can benefit from understanding the needs of the customers. As customers’ tastes and preferences are forever evolving from production agriculture to homeowners, part-time farmers and wildlife enthusiasts, so should the local cooperatives change and familiarise itself with the new clientele. This will lead to a change in the products offered and services offered by the agribusiness or cooperative. The level of service quality from the appearance, policies, reliability and personal interaction with the clients will also not be the same (Wilson, Hall and Fields, 2011). Big rewards can be reaped in today’s marketplace through effective merchandising strategies. Effective category management is vital for retailing (Clark, 2003). It is of utmost importance that retailers supply customers with the right products in the quantity required. Customers will shy away from retailers with a limited number or unsatisfactory range of products. Retailers must also make an effort to present products of the right quality for the particular market in which they operate (Jacobs, 2007). Rewards arising from taking a more strategic approach to merchandising are: ● boosting sales ● increasing footfalls and ultimately ● increasing turnover (Clark, 2003). The purpose of a merchandise assortment is for customers to look through the store and 35 purchase more than they initially intended. The method used is exposing customers to a layout that facilitates a particular traffic pattern. Providing a variety of products in-store will result in customers moving around the store. This can be encouraged by using small nooks and crannies that entice customers to wander around. A well-balanced layout should provide customers with enough shopping space. The breadth and depth of the assortment in a merchandise category can affect the retailer’s brand image. The norm of a merchandise category is for retailers to satisfy the customer’s needs through effective merchandise display and brand image. The general belief is that improvement in assortment results in increased customer purchases (Levy and Weitz, 2007). Amine and Cadenat (2003) stated that customers’ perception of the assortment range stems from the combination of a few indicators, mainly the number of stock-keeping units proposed and the availability of favourite brands." In addition, customer evaluation of the overall store assortment draws on perceived choice within the product categories where they are highly sensitive to the assortment range. Convenience stores are required to assess shoppers’ assortment perceptions so that what the store offers can be modified to meet customers’ needs and expectations. Retailers have realised that customers prefer stores with a wider product assortment for various reasons. For instance, the more variety in the product assortment there is, the more likely it is for customers to find products that meet their exact specification. Consequently, having more products signal flexibility, significant for customers with unsure preferences. Recent research reveals that the customer’s choice is affected by the perception of the variety within the selection, which depends on more than just the number of distinct products on the shelves. Models of what influences customers’ perception of 36 variety: ● space allocated to the category, ● the presence or absence of the customer’s preferred item, ● the arrangement of an assortment and the repeat of items, ● A number of suitable alternatives. Hence, spectators in both the academic and industrial worlds advise retailers to plan their merchandise assortment properly. In addition, this will increase the overall retail sales with the help of customer contribution (Boatwright and Nunes, 2001). Competition has intensified down the years and it is vital that retailers satisfy the needs of the customer. Furthermore, assortment planning is a key element in merchandising. Generally, “the assortment of products depends on store location, store size, and lifestyle of the local customers." Figure 2.3 gives an indication of what is needed for an organisation to earn customer loyalty (Halapete, Hathcote, and Peters 2005). 37 Figure 2.3: Factors affecting micromarketing merchandising Source: Halapete, Hathcote, and Peters (2005) Figure 2.3 shows the variables managers need to consider when merchandising their stores. Each variable is attuned to suit certain stores best – this is based on where the store is located. By applying information from the diagram above, sales will increase and hence profits, too. 2.2.4 Store location The location of a store is one of the common components that save time for customers. Often customers would want to optimise their visit to the desired retail store and are less inclined to switch stores because of the risk in finding parking, availability of stock, travel cost and inconvenience. Stores should be easily located and accessible to their target market (Tlapane, 2009). Retailers are required to invest a sizeable amount into store 38 location as a long-term commitment (Jaravaza and Chitando, 2013). It is advisable for retailers to allocate space within the store for non-selling areas like offices, storage space, toilets, dispatch and bagging (Buttle, 1984). Customers make use of different attributes to decide on a particular store (Dhurup and Oosthuyzen, 2010). Location, atmosphere, parking and the friendliness of staff are all store choice attributes (Dhurup and Oosthuyzen, 2010). Additionally, cheaper parking, lower prices, a wider range of assortment, shorter travelling time and a faster check-out time are also store selection attributes (Dhurup and Oosthuyzen, 2010; Peter, 2001). The main objective of store location is to attract patrons to the store (Dhurup and Oosthuyzen, 2010; Kim, 2001). Al-Awadi (2002) stated sufficient parking could also attract customers to the establishment and so increases customer loyalty. An average strategy mix can be a success given that it is implemented in a good location. The opposite is also true: a poor location can be a liability that even the ablest retailer may be unable to overcome. A trading area plays a significant role in deciding on a store’s location. A trading area is defined as the geographical area where supplier meets buyer (Jaravaza and Chitando, 2013). A study revealed that store choice was decided on based on convenience. Especially in poverty-stricken areas, many customers are only able to shop after work. Such customers rely on stores that offer convenience, shorter travelling distance and complementary services, for instance public transport. A bus stops or taxi rank helps lower the fatigue of moving around after work. The study also found that various locations offer different trade area characteristics, leading to varying traffic volumes. Downtown Mbuya (where the study was conducted) had high traffic volumes all day long, chiefly pedestrian traffic. This traffic 39 had a large influence on store traffic patterns. In the second area where the study was conducted, high traffic flows were experienced only during lunch hour. It was concluded from the study that store traffic is a function of store location (Jaravaza and Chitando, 2013). 2.3 Market analysis Market analysis focuses on the need to study the behaviour of clients. Cooperatives need to include information about their clients – for instance, how frequently clients visit their stores, the products clients buy, and the quantity. Communication methods are very important for market analysis. E-mail advertisements, pamphlets and face-to-face interaction are of great significance to any business or cooperative (Kotler, Burton, Deans, Brown and Armstrong, 2015). There has been growth in managing the retail mix over the years. The reason for this is that retailers are on a quest to build and sustain distinctive trading images that attract and retain customers. Rivalry is no longer merely between products, but includes the fundamentals of the retail mix (Lowson, 2005), namely: 2.3.1 Customer service The term customer service refers to the practice of providing people with a positive, helpful experience before, during and after a sale. Some companies have a department within the organisation that focuses on these processes. Preferably, every employee in the department is able to provide assistance and no client experiences discrimination. Employees can engage with individuals face-to-face, by phone, e-mail or through written 40 communications. Many businesses spend a great deal of the time obtaining feedback and training their employees for this purpose, because it makes a client more likely to become loyal (Kanter, 2011). New-generation cooperatives should invest in their retail staff to have a vast knowledge of the products the stores offer, interpersonal skills and post-sale service. 2.3.2 Quality A cooperative can decide to advertise the product in such a way that the price of the good is a determinant of quality. In recent years, words like premium and top of the range in advertising can communicate that the product is of high quality, hence the high price (Bidgoli, 2010). 2.3.3 Promotion Promotion strategies can involve having prize draws to bring more attention to the business and attract new customers. Promoting a new product can include a radio promotion with discount coupons and free meal giveaways to create a "buzz" to invite customers in through the doors. Word of mouth has always been the fastest way of spreading the word. Cooperatives can now make use of technology, sending special alerts to their customers’ cell phones and placing adverts in local newspapers as a marketing strategy to attract more customers (Kotler, Burton, Deans, Brown and Armstrong, 2015). 2.3.4 Advertising A solid client base is very important when it comes to developing a good advertising 41 strategy or for advertising. Like most companies, cooperatives need to know and understand their clients, their needs and preferences. This will help cooperatives use the correct tools, the right time and the right place when advertising (Pride, Hughes and Kapoor, 2014). There are key factors to look at when advertising; ● The target market the advertisement must reach. ● Demographics of target markets and their characteristics (age, gender, level of education and location) just to mention a few. ● Know your competition, competitive brands, their reputation and how they reach their core clients. ● All this information will give cooperatives a guide in choosing which advertising strategy to use. In the past, print media used to be the ideal way to advertise for many businesses – newspapers and magazines. However, this was no longer the case when radios and television advertising started to take over. These media, too, are no longer seen as ideal, and internet advertising is the modern way of advertising, as it is relatively inexpensive and reaches a larger target market. The type of advertising strategy or method a cooperative decides on rests on the preferences of the target market. 42 2.3.5 Price points and other channel members Price also plays a role in customers’ decision-making process. Cooperatives need to include it in their marketing strategy, as lower prices of similar products can also attract customers to a store. The price must represent the value of the product. The product as a whole must be presented to customers effectively. Advertising, pricing and other parts of the marketing mix strategy must work together to create branding that draws and compels the target market to purchase the product. Branding is key to a marketing strategy because it differentiates a product from the competitors (Heaton, 2011). 2.4 Qualitative factors Qualitative factors deal with the client’s overall feeling about a company’s brand offering, intentions to purchase and sometimes the service the client receives from the company (Purushottom, 2011). 2.4.1 Customer loyalty Customer loyalty is defined as “a deeply held commitment to repurchase or re-patronise a preferred product offering consistently in the future, despite situational influences and marketing efforts having the potential to cause switching behaviour” (Tweneboah-Koduah and Yuty Duweh Farley 2015). Strong customer loyalty to a store is a positive indication of store health. Miranda, Kõnya, and Havrila (2005) favours the argument that increased rates of customer retention signal increased profitability. In fact, a study of retailing in Kuwait highlighted the significance of creating a corporate retail strategy to focus on customer loyalty and stop customers from switching stores (Al-Awadi, 2002). Store 43 satisfaction is of vital importance for earning store loyalty. Previous research showed a strong link between store image attributes and customer loyalty. Perceptions of quality and services rendered by the store contribute to the customer’s intention of returning to the store (Dhurup and Oosthuyzen, 2010). According to the literature on customer loyalty, there are three main schools of thought namely; ● the attitudinal, ● the behavioural and ● the composite. (Tweneboah-Koduah and Yuty Duweh Farley, 2015). The attitudinal approach accounts for the perception of loyalty on the part of the customer. This definition measures loyalty in terms of the customer’s strength of affection towards the brand or product. The behavioural definition refers to the customer’s action as opposed to his/her mindset. Loyalty is measured in terms of actual consumption, repeat purchases, duration (time spent in the store), frequency (the number of store visits), the proportion of market share, and word of mouth recommendations. The composite approach is a combination of the attitudinal and behavioural approach. It holds that loyalty is measured by taking into account the customer’s product preference, buying frequency, the total purchase amount and the probability of brand switching. 44 However, some researchers digress from these definitions, saying loyalty can be measured by means of only one indicator – the willingness to recommend. Loyal customers are less likely to switch to a competitor brand just because of price or special promotions. They bring in new customers through positive word of mouth and cost less to retain. Customers select and/or patronise a store on three criteria: ● Customer perception (Rani and Velayudhan, 2008); ● Images and attitudes towards store experiences; and ● Information and customer needs. Location and travel cost are key influencers in a customer’s choice of store. Customers visit a store to minimise total cost. Therefore, a customer will not revisit a store that has items out of stock. The visit will be an extra travel expense, raising stress levels into frustration, which is directly connected with a negative attitude towards a store. Below is a diagram that examines variables towards retail stock-out situations (Rani and Velayudhan, 2008). 45 Attitude towards retail store in stock-out-situations Customer variable Situational variables Store variables Product variables General time constraint Specific time constraint Perceived inter-store Availability of Store loyalty Type of shopping trip distance acceptable alternative Customers’ attitudes to Perceived store price items shopping Deal proneness Shopping frequency Brand loyalty Availability of acceptable alternative store Store distance Figure 2.4: Varia bles towards retail stock-out situations 46 Source: (Rani and Velayudhan, 2008) Figure 2.4 explains that customers with higher store loyalty within positive shopping variables will have a more positive distinctive sense that the retailer’s inventory decisions should account for the results of the substitution effect. Nonetheless, a large number of inventory models assume that demand processes for various variants are dependent. Therefore, demand is independent of inventory levels but depends on the primary choice variant offered in the assortment (Mahajan and Van Ryzin, 2001). 2.5 Differentiation focus strategy The aim of a business strategy is to accomplish a sustainable long-run competitive advantage over the rivals and to allow the firm to create a better value for the customers and higher profits for itself (Porter, 1998). There are four business strategies that businesses can choose from to align the business to the strategy; ● Competitive advantage: the advantage a firm has over competition by offering the customers greater value, either by selling products at lower prices (cost advantage) or by offering greater benefits and service justifying higher prices (differentiation advantage). ● Cost advantage: the advantage of selling goods at a lower price than the opposition. This strategy is also focused on a niche market or smaller market. ● Differentiation strategy: this strategy can be distinguishable by higher prices or premiums offered to the customer. This strategy, like the cost advantage strategy, 47 is only focused on a selected target market. ● Differentiation focus strategy: this is usually used by businesses that focus on a smaller market segment. The criteria for this strategy are the same as those of differentiation. Differentiation strategy involves one or more criteria that customers in the market demand and positioning the business distinctively to meet the needs of the customers. This strategy is usually linked with supplying a differentiated product and charging a premium for the product, often because of either greater production costs or value-added features provided for customers. For the purpose of this study, the differentiation strategy is ideal. It will assist cooperatives that sell similar products to competitors in differentiating themselves. The 12 sub- attributes will assist in this regard. 2.6 Conclusion For the purpose of this study, most of the customers buying from the store are farmers, part-time or full-time, who farm in a particular activity or mixed farming. This is because the focus is on agricultural retail stores. The demographics of customers are also an important focus area because then the product needs will also be different depending on the farming activity, tastes, and preferences. In the end, the attributes of the marketing strategy need to merge to build customer loyalty or establish what makes customers of these stores loyal. Chapter two gave insight into literature about marketing strategies for an agricultural store, as well as touching on effective marketing strategies aimed at customer loyalty. The following chapter will give a clear background to the research methodology. 48 Chapter 3 Data and research methodology 3.1 Introduction The purpose of this chapter is to describe the data and methodology used in the study. The first section entails a discussion of the data, which includes a description of the study area, the manner in which the questionnaire was formulated and the sampling approach used in the study. Part of the data section is the execution of the survey and a discussion of the questionnaire contents. The remaining part of the data section gives the procedures used in analysing the specific objectives of the study, followed by a conclusion. 3.2 Research design This study alternates between a descriptive and an explorative type of research, using a qualitative method. Qualitative methods are used mostly to describe the problem and perhaps the hypothesis. Qualitative research includes information-gathering through fieldwork: the researcher needs to go to the people personally, to the research area or institution to witness. This makes the research descriptive in a sense that the researcher is interested in the process, meaning and understanding. The research is aimed at gaining a better understanding of individuals’ interpretations of events as this is very important in a qualitative method aimed at gathering a full description of marketing strategies for an agricultural retail store. A structured questionnaire comprising closed- ended questions was used. Additionally, descriptive, correlational, casual comparative 49 and experimental research substantiates that the study is qualitative (Tlapana, 2009). Since agricultural retail stores first emerged, shareholders in these stores have always been farmers. This has brought a great deal of commitment and loyalty to these stores. These farmers have also been suppliers of agricultural goods to those stores, especially in rural areas where farmers also supply complementary goods to the farming community. A good competitor type for agricultural retail stores is hardware stores, as these stores trade in much the same product range as agricultural retail stores. This creates a threat for agricultural stores, that once loyal customers can now purchase from a hardware store, leaving agricultural retail stores to supply only agricultural goods (Jacobs, 2007). The Table below gives an outline representation of agribusinesses in almost every province of South Africa. Table 3.1: Geographical location of each agricultural retail store Province Private and Public Companies Eastern Cape AFGRI, BKB, OVK, Senwes, VBK Free State AFGRI, BKB, OVK, Senwes, VBK Gauteng AFGRI, Obaro, Senwes KwaZulu-Natal AFGRI, Coastal Farmers Limpopo AFGRI, NTK, Obaro Mpumalanga AFGRI, BKB, TWK North West AFGRI, NWK, Obaro, Senwes Northern Cape GWK, OVK, Senwes Western Cape Kaap AFGRI, MBK, Overberg AFGRI, SSK Source: Jacobs (2007). 50 3.3 Background data of the South African agricultural sector 3.3.1 Livestock production The biggest agricultural sector in South Africa is the livestock sector, with a population estimate of 13.8 million cattle and 28 million sheep. Breeders in this sector focus on developing breeds that will adapt well to a diverse climate and environmental conditions (www.southafrica.info.co.za). A report by Statistics South Africa (referred to as Stats SA, 2011) revealed that the Eastern Cape was ranked the province in South Africa with the highest cattle ownership, 30.1%. KwaZulu-Natal ranked the highest in two areas; poultry production (27.5%) and vegetable production (30.3%). 3.3.2 Beef farming Eighty-five percent of South African meat requirements are produced domestically, with 15% coming from Namibia, Botswana, Swaziland, Australia, New Zealand and the European Union (EU) combined. Domestic demand is generally greater than the supply, even though there are unexploited reserves in the communal farming areas. Cattle farms are predominantly found in the Eastern Cape, parts of the Free State and KwaZulu-Natal, Limpopo and the Northern Cape. Common beef breeds include the native Afrikaner and Nguni and the domestically developed Bonsmara and Drakensberger. European and American breeds like Charolais, Hereford, Aberdeen-Angus, Simmentaler, Sussex, Brahman and Santa Gertrudis are preserved as pure breeds or used in cross- breeding (www.southafrica.info.co.za). 3.3.3 Sheep and goat farming Provinces characterised by sheep farming in South Africa are the Northern Cape, the 51 Eastern Cape, the Western Cape and Mpumalanga. According to Stats SA (2011), the Eastern Cape is the leading province in sheep ownership at 54.4%. Half of South Africa’s sheep are wool-rich Merinos. More breeds include the domestically produced Afrino, a wool-rich mutton breed adapted to dry conditions. The same applies to the South African Mutton Merino, the Dohne Merino and the Merino Landrace. Karakul sheep are farmed in very dry areas. The Dorper, South Africa’s main mutton producer, is highly productive. It is a South African cross between the Dorset Horned sheep and the haired black-head Persian breed (www.southafrica.info.co.za). Thirty percent of all commercial goats is derived from the native Boer goat, which is also a meat-producing goat. Mohair production is mostly from the Angora goat (www.southafrica.info.co.za). The Eastern Cape and KwaZulu-Natal are ranked the highest in goat ownership (Stats SA, 2011). 3.3.4 Dairy farming Dairy is produced all over South Africa, with most of the farms located in the eastern and northern Free State, North West, the KwaZulu-Natal Midlands, the Eastern and Western Cape, Gauteng and the southern parts of Mpumalanga. The most common dairy- producing breeds are the Holstein or Frisian, Jersey, Guernsey and Ayrshire. The dairy industry plays a big role in South Africa’s employment market. More than 4 000 dairy farmers employ about 60 0000 labourers and provide employment indirectly to about 40 0000 people (www.southafrica.info.co.za). 3.3.5 Poultry and pig farming Unlike sheep and livestock farming, poultry and pig farming are more intensive. This type 52 of farming is mostly practised around the metropolitan areas of Gauteng, Durban, Pietermaritzburg, Cape Town and Port Elizabeth. The main pig breeds are the South African Landrace, the large white, the Duroc and the Piétrain (www.southafrica.info.co.za). The annual poultry meat production for South Africa is estimated at 960 000 tonnes. Eighty per cent of the production is derived from broiler production; the remainder is made up of mature chicken slaughter (culls), and small-scale and backyard poultry production. This includes ducks, geese, turkeys and other specialised white meat products. South Africa takes up an estimated of 65% of the world’s sales of ostrich products: meat, leather and feathers (www.southafrica.info.co.za). KwaZulu-Natal, the Eastern Cape and Gauteng ranked the highest in the country in pig ownership, at 23.6%, 18.7% and 15.9% respectively (Stats SA, 2011). 3.3.6 Game farming South Africa is very rich in wildlife and has a greater variety of it than many other countries. The game industry has grown over the years and has great economic potential. There are many significant game areas, from the Karoo and the Kalahari of the Northern Cape to the thorn scrub of KwaZulu-Natal. This industry has the potential to increase the global production of venison by between 8% and 15% (www.southafrica.info.co.za). 3.3.7 Aquaculture The aquaculture industry in South Africa continues to make significant growth in farming technology, marketing strategy, marketing practices and scientific improvement. Major 53 species cultivated under aquaculture on the South African coast include mussels, trout, tilapia, catfish, oysters and waterblommetjies (Cape pondweed, Aponogeton distachyos). Saldanha Bay in the Western Cape is famous for mussel farming (www.southafrica.info.co.za). 3.4 Field crops and horticulture 3.4.1 Grain and oilseeds The grain industry is one of the major agricultural production sectors in South Africa. The industry contributes 25% to 33% to the total gross value of the country’s agricultural production. 3.4.2 Maize production Maize is the leading crop planted on farmland, then wheat, followed by sugarcane and sunflower. Maize is a staple food in Southern Africa and is also the largest domestically produced crop. South Africa leads in maize production in the Southern African Development Community (SADC) (www.southafrica.info.co.za). The Limpopo province takes the lead in maize crop production (Stats SA, 2011) More than 9 000 commercial farmers are responsible for maize production in South Africa. The rest are small-scale farmers who also aid in producing this crop. These provinces and regions are well-known areas of maize production: North West, Free State, the Mpumalanga Highveld and the KwaZulu-Natal Midlands. “Local consumption of maize amounts to 8 million tonne and the surplus is exported” (www.southafrica.info.co.za). 54 3.4.3 Wheat production Wheat is the second most important grain crop produced in South Africa after maize. It added an estimated 3% to the total gross value of agricultural production during. Most of the wheat produced domestically is for human consumption – bread, biscuits, breakfast cereal and rusks, among other uses. The rest is used for seed and animal feed. Wheat is also used for making ethanol alcohol, starch on coatings, and as an absorbent agent for disposable nappies. Wheat producers are estimated to number between 3 800 and 4 000 (www.nda.agric.za) Wheat is mostly produced in the winter rainfall areas of the Western Cape, and in the eastern parts of the Free State. More than 90% of the Lucerne seed produced in South Africa is grown in the Western Cape’s Oudtshoorn district. Sorghum is cultivated in the drier parts of the summer rainfall area in Mpumalanga, Free State, Limpopo, North West and Gauteng (www.southafrica.info.co.za). 3.4.4 Sugar South Africa is ranked as the world’s 13th-biggest sugar producer. Sugarcane is grown in 15 distinct areas, stretching from northern Pondoland in the Eastern Cape, through the coast and Midlands of KwaZulu-Natal to the Mpumalanga Lowveld. From the 2.5 million tonne that is produced each season, half is marketed in Southern Africa, while the rest is exported all over Africa, the Middle East, North America and Asia (www.southafrica.info.co.za). Due to the drought that has left South Africa in a state of emergency, the lack of rainfall has injured the maize and sugar-producing regions. Sugar came under so much pressure 55 that producers had to import less expensive sugar, forcing some mills to remain closed, which reduced jobs in the sector. The decline in the availability of sugar in the country led producers to export less, to ensure sufficient sugar for the domestic market. 3.4.5 Fruit Deciduous fruit is mostly produced in the Western Cape and in the Langkloof valley of the Eastern Cape, the banks of the Orange River in the Northern Cape, and in the Free State, Mpumalanga and Gauteng. The fruit industry makes up 12% of total agricultural exports from South Africa. Irrigated areas are most famous for citrus production, in the Western Cape, Mpumalanga, Limpopo, KwaZulu-Natal and the Eastern Cape. Sub-tropical fruits like avocados, bananas, litchis, guavas, mangoes, pawpaw’s, granadillas, and pecan and macadamia nuts, are grown in Mpumalanga, Limpopo and the coastal areas of KwaZulu-Natal and the Eastern Cape (www.southafrica.info.co.za). 3.4.6 Potatoes Potatoes account for 40% of the gross income of vegetable farmers, followed by tomatoes, onions, green mealies and sweetcorn, contributing 38%. Potatoes are grown in high-lying areas of Mpumalanga, Limpopo, the Eastern, Western and Northern Cape, as well as the Free State and KwaZulu-Natal. The potato processing industry has grown well over the past 10 years, with 18% of all fresh produce being processed potatoes. Tomatoes are grown in most parts of South Africa, stretching from the Pongola area of KwaZulu-Natal, the Mpumalanga Lowveld and Middleveld, the southern Eastern Cape and the Western Cape. 56 Mpumalanga, Western Cape and the Free State are known for onion production, while cabbage production is concentrated in Mpumalanga and in the Camperdown and Greytown districts of KwaZulu-Natal (www.southafrica.info.co.za). 3.4.7 Cotton Cotton is produced under irrigated and dry land conditions. With 75% of domestically produced cotton harvested by hand in South Africa, Mpumalanga, Northern Cape, KwaZulu-Natal and North West produce 74% (natural fibre) of all cotton in South Africa, of which 42% is processed. 3.4.8 Tea Honeybush tea is an indigenous plant of the fynbos, found in coastal and mountain areas, especially in the Western Cape and parts of the Eastern Cape. About 100 tonnes of honeybuns is processed each year. The tea has become a commercial crop, with exports increasing due to the quality and a high foreign demand for the tea. Local demand also increased. Rooibos is over 100 tonnes per year, processed. 57 3.5 Profile of respondents who participated in the survey Figure 3.1: Gender of respondents Figure 3.1 above gives an indication of the gender of the respondents who took part in the survey. Of the 110 questionnaires returned, 84 (76.4%) were men and 26 (23.6%) were women. 58 Figure 3.2: Marital status of respondents The above Figure 3.2 gives the marital status of each and every respondent. Out of the110 respondents 20% were single, 68.2% married, 2.7% divorced, 6.4% widowers and 2.7% stated that their relationships were complicated. 59 Figure 3.3 Occupation of respondents Figure 3.3 gives a clear indication of the occupations of the respondents. Out of the 110 respondents from all five provinces, 46.5% are full-time farmers, 30.9% are part-time farmers and 22.7% are non-farmers or not in the agricultural business. 3.6 Sampling method The sample size is defined as the number of elements to include in a study. In this research, 110 respondents were sampled. The first sampling method used was stratified random sampling. The reason for this is that the population was divided into groups based on provinces. Respondents were sampled randomly from the selected provinces as shown in Table 3.2. 60 Table 3.2: Provinces and the respective towns Province Town Number of Percentage respondents distribution (%) Eastern Burgersdorp, Cradock, Elliot, Graaff- 62 56.36% Cape Reinet, Matatiele, Port Elizabeth, Sterkstroom Free State Bloemfontein, Brandfort, Jacobsdal, 30 27.27% Zastron, Aliwal North Mpumalanga Standerton 5 4.55% KwaZulu- Cedarville, Paulpietersburg, Utrecht, 12 10.91% Natal Volksrust, Vryheid Western Murraysburg 1 0.91% Cape Total 110 100% The data were analysed by means of frequencies, using the statistical programme SPSS version 16.0. 3.7 Population and sample The population is the aggregate total number of all potential participants who could be included in the study. The targeted population for this research was all customers who shop at agricultural retail stores in the Free State, Eastern Cape, Mpumalanga, KwaZulu- Natal and Western Cape. Out of the initial 150 questionnaires, only 110 were completed by respondents. The larger the population the better it is to generalise to the population. The population of any study needs to be properly defined to avoid variants like age, educational level, gender and location. These were included since the researcher believes that these factors could have an influence on the results. It is unfortunate that there was only one respondent in the Western Cape Province. This is not adequate to represent the province. Therefore, the Western Cape Province will not be included in the statistical analysis of the research project. 61 3.8 Instruments for data collection The survey method was used for data collection. Questionnaires were distributed to the selected sample to gain comprehensive information on the topic and to simplify difficult questions. Store managers assisted by asking customers to take part by completing the questionnaires. These managers were briefed about the questionnaires so that they were able to clarify difficult questions. Tlapane (2009) stated that the survey method is a systematic way of assembling information from a large number of people through the use of questionnaires. The results of the analysis of the completed questionnaires, meet the objectives of the study, together with a discussion of those results, are presented in this chapter. The analysis of the store attributes and marketing strategies is categorised and discussed under 12 sections. Each attribute will be covered briefly. 3.8.1 Atmosphere attribute The term atmosphere can be defined as the physical characteristics and surroundings of a retail store that are used to create an image that will attract customers (www.retail.about.com). 3.8.2 Convenience attribute The general definition of a convenience store is the 24/7 trading hours, selling in small quantities and generally high prices. The store is in most cases part of a filling station alongside a busy road in an urban area According to the National Association of 62 Convenience Stores (NACS), an international trade association, the definition of a convenience store is: "...a retail business with primary emphasis placed on providing the public with a convenient location to quickly purchase from a wide array of consumable products (predominantly food or food and gasoline) and services" (NACS Online Research, 2015). 3.8.3 Merchandise attribute The real attributes of the merchandise are the characteristics of the product. This can be divided into two parts: the actual physical characteristics and the assessable characteristics. The customer wants the actual physical product or service, whereas the assessable characteristics can be derived through the use of the product. It is vital that retailers produce benefits of this kind totally different from their competition (www.coursehero.com). 3.8.4 Structural attribute This is the set-up of the location, from where the store is, to the accessibility, whether on foot or by car (or any other form of transport) to the store interior. This can, however, vary from store to store, given the target market. An example of this can be that the fuel pump at store A is different from the location of the same pump at store B. 3.8.5 Institutional attribute This can be defined as the overall impression the store gives the customers through the sales staff, the clientele and the social class (Amirani and Gates, 1993). This encompasses the store’s self-image and the customers being able to identify with the store (Al-wadi, 2002). 63 3.8.6 Promotion attribute Various methods of advertising can be used to describe this attribute in finer detail. Promotions are listed as advertising, personal contact with customers and advertising promotion as realistic models to use for advertising. 3.8.7 Service attribute The service of the store comprises after-sales service, return policy, inter-store transfers and delivery options (Thang and Tan, 2003). In this particular study, only certain aspects are assessed – courier service, delivery service, adequacy of sales staff and inter-store transfers. 3.8.8 Sales attribute Sales cover the selling of the product and in most cases, a great deal of it is done by the sales staff. Thang and Tan (2003) states that when one has enough sales staff to do the job, people who are product-orientated and who can actually give product advice, positive sales can be achieved. 3.8.9 Credit attribute This is the ability of the customer to obtain goods or services before payment, based on trust that payment will be made in the near future. Previous research has looked at payment options, bankcards, credit, lay-bye accounts and store cards (Burns, 2005). 64 3.8.10 Assistance attribute Assistance can be explained as what the store caters for the customer’s shopping experience. Self-service, service, trolley/basket service and phone orders (Tan, 2003). 3.8.11 Administration attribute This is the process or activity of running a business or organisation – the day-to-day administration (paperwork) involved. This includes customer accounts, payment dates and letters. 3.8.12 Loyalty attribute Customer loyalty is the commitment the customer has to the retailer. It is a willingness to recommend the store to others (word of mouth). For the purpose of the study at hand, the internet is also incorporated into customer loyalty, and loyalty programmes are also looked into. The questionnaire is in both English and Afrikaans (see Annexure 1). The questionnaire consists of three sections. Section A - Gives the personal profile of the respondent ● district of the respondent, ● town of the respondent, ● age, ● gender, ● marital status, ● race, ● level of education, 65 ● occupation, ● type of farming, ● household size, ● household monthly income. Section B – Gives rating of each sub-attribute with the use of the Likert scale rating is as follows; one (1) to five (5) where: 1= strongly disagree, 2= Disagree, 3= Neutral (no opinion), 4= Agree, 5= strongly agree. ● Atmosphere attribute (consists of 8 questions, 1 - 8) ● Convenience attribute (consists of 9 questions, 9 - 17) ● Merchandise attribute (consists of 5 questions, 18 - 22) ● Structural attribute (consists of 7 questions, 23 - 29) ● Institutional attribute (consists of 6 questions, 30 – 35) ● Promotion attribute (consists of 6 questions, 36 - 41) ● Service attribute (consists of 6 questions, 42 – 47) ● Sales attribute (consists of 5 questions, 48- 52) ● Credit attribute (consists of 4 questions, 53 – 56) ● Assistance attribute (consists of 5 questions, 57- 61) ● Administration attribute (consists of 4 questions, 62- 65) Section C – Gives rating of the loyalty attribute with the use of the Likert scale rating is as follows; one (1) to five (5) where: 1= strongly disagree, 2= Disagree, 3= Neutral (no opinion), 4= Agree, 5= strongly agree. 66 ● Loyalty program (consists of 3 questions, 66 - 68) ● Online purchasing (consists of 3 questions, 69 - 71) Lastly, the suggestions also fall under section c. 3.9 Data analysis The data were captured onto the SPSS computer package. A thorough count was done to ensure that all the respondents had answered and completed the questions satisfactorily. Questionnaires were placed according to their geographical areas. After the data were captured, it was analysed. Descriptive statistics such as means, frequencies and percentages were analysed. The results were presented in charts and tables. Pearson’s correlation was used to test how the identified attributes are related in influencing customer loyalty. Mean scores were used to rate the attributes in order of their importance in customer purchasing decisions. The use of descriptive statistics is vital for simplifying the basic features of the data in the study. They give insight about the sample and the measure. Graphs form the basis of almost all quantitative analysis of data (Tlapane, 2009). The level of reliability and internal consistency was measured in this study using the Cronbach Alpha and a sufficient or good level of reliability was attained for all measured variables. Content and face validity was supported in this study through the construction of a questionnaire that was based solely on the characteristics determined from the literature. The confidentiality and anonymity of all the respondents that took part in this study was 67 strictly applied, and participation in the study was voluntary. 3.10 Conclusion Chapter three provides the study’s data research methodology with regard to the research area, population, sample size and number of respondents. The next chapter will analyse the data and discuss the results of the data at hand. 68 Chapter 4 Results, discussion and conclusion 4.1 Introduction The results of the analyses that were completed to meet the objectives of the study, together with a discussion of those results, are presented in this chapter. The results of the store attributes are categorised and discussed under 12 sub-sections as related to the literature review. Section 4.1 gives a brief introduction to the chapter. The next section discusses the rating of atmospheric attributes by respondents and how the attributes correlated with influencing the customers’ decisions. Section 4.3 outlines the ratings of convenience attributes from the perspective of the respondents, as well as correlations between the attributes. These are followed by merchandise attributes, ratings and correlations. Structural attributes, ratings and correlations are discussed under Section 4.4. Section 4.5 discusses how the institutional attributes identified are rated by respondents, together with their correlation coefficients. Promotion, service, and sales attributes are rated and discussed under sections 4.6, 4.7 and 4.8 respectively. Credit and assistance attribute ratings and correlations are presented in sections 4.9 and 4.10. These are followed by the ratings and correlations of administrative attributes and, lastly, loyalty attributes rating and correlations. These results will give an indication of which store attributes have an influence on customer loyalty. The results also give indications as to which attributes agricultural retailers can strive for to gain customer loyalty. 69 Definitions of the keywords used to interpret the data are given below: Mean: A mean is a statistical term that refers to the average that is used to derive the central tendency of the data in question. It is calculated by adding all data points in a population and then dividing the aggregate by the number of points. This number is then the mean or average. The statistical mean has a wide range of applicability in different experiments. A mean is also used for interpretation of statistical data, which eliminates random errors and assists in deriving more precise outcomes than that from a single experiment (www.techopedia.com) Likert scale: Likert scales are commonly used for rating questionnaires. “Respondents rank quality from high to low or best to worst using five or seven levels.” The scale sorts a group of categories, asking people to indicate how much they agree 70 or disagree, like or dislike, believe to be true or false. There is a correct way of constructing a Likert scale. The most crucial aspect or feature when constructing a Likert scale is to include a minimum of five response categories (www.proquest.com). For the purpose of the study, the Likert scale is divided in five response categories. These are: Scale: 1= Disagree strongly, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Agree strongly A 5-point Likert scale was used on all questions pertaining to the measurement of construct variables and where the relative magnitude was important. Multiple choice Likert scale questions, based on characteristics determined from literature and intended to determine and measure the level of significance of that variable in the overall construct. Pearson’s correlation: A measure that is frequently used to match quantitative variables against each other in a sample. In such instances, the interest lies in establishing a relationship between the variables of perhaps two to understand whether variables correlate. The Pearson correlation was used to determine the existence, strength and direction of relationships between the variables under study. There are three types of correlation: ● Positive correlation – the other variable has a chance of also increasing; ● Negative correlation – the other variable has a chance of decreasing; ● No correlation – no chances of either an increase or decrease in the other variable. 71 Figure 4.1: Scatter plot examples of correlations. Source: (www.ssc.wisc.edu) As mentioned in the previous chapters, the sub-attributes are divided into three main attributes. The Table below will give the outlay of this current chapter (Chapter 4) is as follows: 1. Physical attributes ● Atmosphere attribute ● Convenience attribute ● Merchandise attribute ● Structural attribute ● Sales attribute 72 ● Credit attribute ● Assistance attribute ● Administration attribute 2. Market analysis ● Promotion attribute ● Service attribute 3. Qualitative factors ● Loyalty attribute 4. Marketing strategy ● Differentiation focus strategy 4.2 Physical attributes 4.2.1 Atmosphere attribute rating The results of responses regarding these attributes are presented in Table 4.1. Each attribute was rated by the respondents in order of importance and purchase intention. Mean ranks were calculated and presented in Table 4.1. The analysis was done for all the stores that formed part of the research area. 73 Table 4.1: Mean of atmosphere attribute rating by province Row labels Eastern Cape Free State KwaZulu- Natal Mpumalanga Attractiveness 3.2 3.26 2.58 4** Colours 3.37*** 3.52** 2.92*** 3.6 Fashion ability 3.1 3.32*** 2.92*** 4** Furnishing material 3.3 3.32*** 3.08** 3.2 Music and lights 3.3 3.24 2.5**** 3.6 Shopping experience 3.73* 3.98* 4* 4.4* Style 3.1 3.27 2.58 3.8*** Ventilation system 3.67** 3.27 2.92*** 3.8*** Grand total 26.77 27.18 23.50 30.40 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.2.1.1 Highest ranking by province Shopping experience took first place ranking in all five provinces in the study area. This is followed by respondents ranking fashion ability and ventilation system as important 4.2.1.2 Second-highest ranking by province Respondents in Free State ranked attractiveness in this category, followed by respondents in Mpumalanga. Style, decor and ventilation system were also ranked in this category. 4.2.1.3 Third-highest ranking by province Colours and furnishing material were ranked in the third-highest category by respondents in the Free State and KwaZulu-Natal. Respondents in the Eastern Cape only ranked colours in this category. Fashionability is ranked in the third--highest category by respondents in the Free State and the sub-attribute music and lights are ranked in this 74 category. 4.2.1.4 Lowest rankings These attributes were ranked lower than the rest (overall): ● Music and lights, which scored 2.5 (mean score). Although this attribute is seen as important in total, it is ranked lower in comparison with the other attributes. Figure 4.2: Atmosphere attribute rating (pool sample) This figure shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the atmosphere attributes. Fashionability ranked highest with 15%, followed by style and decor with 13%. All the remaining attributes were ranked and equal 12% 75 4.2.2 Pearson’s correlation Pearson’s correlation coefficient is a statistical measure of the strength of a linear relationship between two variable data. In a sample, it is denoted by r and is presented as follows −1 ≤ 𝑟 ≤ 1 Furthermore: ● Positive values denote positive linear correlation; ● Negative values denote a negative linear relationship; ● A value of zero (0) denotes no linear correlation; ● The closer the value is to 1 or -1, the stronger the linear correlation”. Figure 4.3: Representation of "extreme" correlation values of -1, 0 and 1 For the purpose of this study, the Pearson’s correlation coefficients will be used for all 12 sub-attributes and for each sub-attribute a brief conclusion will be given as to the correlation. 76 4.2.3 Correlations of atmospheric sub-attributes Table 4.2 presents Pearson correlation coefficients of the atmospheric attributes identified in the study. The emphasis is placed on the direction or sign of the correlation coefficients since this indicates how the attributes come together to influence customers’ purchase intentions. The results show that fashion attribute correlates positively with the style, attractiveness, colours, ventilation and furnishing material of the shop at the conventional level of significance. This implies that for shops to be highly recognised in terms of fashion, much attention must be given to these attributes so as to gain competitive advantage. The style attribute significantly correlates positively with attractiveness, colours and ventilation, suggesting that for shops to possess a unique style different from other shops, they should consider the attractiveness of the shop through the choice of colours and the ventilation systems in place. The attribute of attractiveness has a significantly positive correlation with store colours and ventilation, alongside fashion and attractiveness. In addition, the colours attribute further correlated positively and significantly with furnishing materials and ventilation. Furnishing material and shopping experience correlated positively and significantly with ventilation. However, the results show that music in the shop has no significant correlation with any of the atmospheric attributes. This implies that music in shops is an independent or separate attribute and does not relate to atmospherics. More importantly, the results show that ventilation correlated with all the attributes except music. This indicates that much attention should be given to ventilation in shops, considering the current environmental changes and heat stress. 77 Table 4.2: Correlation of atmosphere sub-attribute Atmosphere attribute correlations Fashion Style Attractiveness Colours Finishing Shopping Music, Ventilation material experience lighting Fashion Pearson 1 0.910** 0853* 0.838* 0.823* 0.606 0.236 0.838* Correlation Sig. (1-tailed) 0.006 0.015 0.019 .022 0.101 0.326 0.019 Style Pearson 0.910** 1 0.987** 0.918** 0.691 0.554 0.603 0.797* Correlation Sig. (1-tailed) 0.006 0.000 0.005 0.064 0.127 0.103 0.029 Attractiveness Pearson 0.853* 0.987** 1 0.894** 0.613 0.565 0.675 .0780* Correlation Sig. (1-tailed) 0.015 0.000 0.008 0.098 0.121 0.071 0.034 Colours Pearson 0.838* 0.918** 0.894** 1 0.848* 0.701 0.480 0.903** Correlation Sig. (1-tailed) 0.019 0.005 0.008 0.016 0.060 0.167 0.007 Finishing Pearson 0.823* 0.691 0.613 0.848* 1 0.688 -0.004 0.918** material Correlation Sig. (1-tailed) 0.022 0.064 0.098 0.016 0.066 0.497 0.005 Shopping Pearson 0.606 0.554 0.565 0.701 0.688 1 -0.035 0.800* experience Correlation Sig. (1-tailed) 0.101 0.127 0.121 0.060 0.066 0.474 0.028 Music, lighting Pearson 0.236 0.603* 0.675 0.480 -0.004 -0.035 1 0.212 Correlation Sig. (1-tailed) 0.326 0.103 0.071 0.167 0.497 0.474 0.344 Ventilation Pearson 0.838* 0.797* 0.780* 0.903** 0.918** 0.800* 0.212 1 Correlation Sig. (1-tailed) 0.019 0.029 0.034 0.007 0.005 0.028 0.344 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 78 4.3 Convenience attribute rating 4.3.1 Definition of convenience The general definition of a convenience store is that 24/7 trading hours, selling in small quantities and generally high prices. The store is in most cases part of a filling station alongside a busy road in an urban area (www.wikipedia.org). For the purposes of this study, the services rendered at these stores are analysed and will be recommended for agricultural retail stores. These services include trading hours, a variety of product range and shorter customer lines. The results of these attributes are presented in Table 4.3. Each respondent in an order of importance rated these attributes. Mean scores were calculated and are presented in Table 4.3. The analysis was done for all the stores, which formed part of the research area. Table 4.3: Mean of convenience attribute rating by province Row labels Eastern Cape Free State KwaZulu-Natal Mpumalanga Accessibility of store 3.5*** 3.68** 3.58 4.4** Crowding 3**** 3.35 3.08 3**** Distance to the store 3.47 3.42 3.83*** 3.4 Flow 3.2 3.6 3.42 3.8*** Home/farm 3.33 3.34 3.25 3.4 Merchandise 3.53** 3.6*** 3.92** 4.6* Store business hours 3.93* 3.97* 4* 3.4 Walking required 3.53** 3.45 3.92** 3.4 Workplace 3.1 3.55 3.5 3.8*** Grand total 30.59 31.96 32.5 33.2 (*)Highest rating, (**) Second-highest rating, (***) Third-highest-rating, (****) Overall lowest 4.3.1.1 Highest ranking by province The results show that in KwaZulu-Natal, respondents’ rate store business hours (4) as 79 the highest convenience attribute. In Mpumalanga, respondents rated merchandise as the highest convenience attribute with a mean score of 4.6, followed by the accessibility of the store 4.4. 4.3.1.2. Second-highest ranking by province Walking required was rated the second-highest convenience attribute with a mean score of (3.92) by respondents in KwaZulu-Natal. This is followed by a variety of merchandise with a mean score of (3.92), also ranked by respondents from KwaZulu-Natal in this category. Accessibility of stores is ranked as second-highest by respondents in Mpumalanga at a mean score of (4.4). 4.3.1.3 Third-highest ranking by province Distance to the store was rated the third-highest convenience attribute (3.83), while flow and workplace were rated as third-highest convenience attributes with a mean score of 3.8 each. 4.3.1.4 Lowest rankings Crowding is ranked at the lowest level by respondents in the Eastern Cape and Mpumalanga with a mean score of (3). 80 Figure 4.4: Convenience attribute rating (pool sample) Figure 4.4 shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the convenience attributes. The distance of store from the workplace, distance of store from home/farm and the distance to one’s favourite store compared with other stores, were all ranked an equal highest of 12%. The accessibility of the store, the flow of people where the store is located, the amount of walking required while in the store and the variety of merchandise all ranked an equal high of 11%. Store business hours and the crowd at the store ranked an equal high of 10%. 4.3.2 Convenience attribute correlations 4.3.2.1 Workplace The distance from the customer’s workplace is correlated positively at 5% with a p-value 81 of 0.045 and 10% with a p-value of 0.045 level of significance with the distance from the customers’ home or farm, accessibility of the store and the flow in the store. This means that these sub-attributes are parallel with the customer’s workplace and have a positive influence on customer decisions and customer loyalty. Sub-attributes insignificantly correlated are the customer’s workplace, the distance to the selected store (in comparison with other stores), the amount of walking required while in the store, merchandise variety, store crowds, and the store’s trading hours. 4.3.2.2 Distance from home or farm The distance from the customer’s home or farm is positively correlated with the distance from the customer’s workplace at 5% level of significance with a p-value of 0.045, distance to preferred store, accessibility, of the store and the flow of people in the store at 10% level of significance with a p-value of 0.085. The amount of walking required in the store is positively correlated at 5% level of significance while the crowdedness of the store also correlates positively at 1% significance level with a p-value of 0.007 with distance from the customer’s home or farm. This means that these sub-attributes, together with distance from customer’s home or farm, have a positive influence on the customer’s decision and on customer loyalty in terms of convenience. 4.3.2.3 Distance to preferred store The distance to the preferred store (in comparison with others) correlates positively with the distance from the customer’s home or farm and the flow of people in the store at 10% level of significance with a p-value of 0.641. This attribute further correlates positively with the amount of walking required in the store, the crowdedness of the store and lastly business hours at the conventional levels of significance. This suggests that the sub- 82 attributes mentioned are in parallel with distance to a preferred store to influence customer decisions and loyalty positively. There is a positive correlation for these sub- attributes. 4.3.2.4 Accessibility of store The store’s accessibility correlates positively with the distance the customer walks, the distance from the customer’s home or farm, the flow of people in the store, the amount of walking required in the store, merchandise variety and the crowdedness of the store at the conventional levels of significance. This means that these sub-attributes move in a parallel direction with the accessibility of the store and have a positive influence on customer decisions and loyalty. 4.3.2.5 Flow of customers The flow of customers in the store correlates positively with distance from the customer’s workplace, distance from the customer’s home or farm, distance to the preferred store, the store’s accessibility, the crowdedness and lastly business hours at the conventional levels of significance. This implies that the sub-attributes mentioned move in parallel with the flow of customers to influence customer decisions and loyalty. 4.3.2.6 Walking required in-store The distance from the customer’s home or farm is positively correlated with distance to the preferred store, accessibility to the store, the flow of the customers’ in-store, the crowdedness of the store, the variety of merchandise and business hours at the three levels of significance. This means that these sub-attributes move in parallel with the amount of walking in-store to influence customer decisions and loyalty. 83 4.3.2.7 Variety of merchandise The accessibility of the store correlates positively at 1% level of significance with a p- value of 0.001. The flow of customers in the store positively correlates to the variety of merchandise at 5% level of significance with a p-value of 0.014. The amount of walking required in-store is correlated positively at 10% level of significance with a p-value of 0.0157. The crowdedness of the store correlates positively at 10% significance level with a p-value of 0.079. All this means that the sub-attributes mentioned move in parallel with the variety of merchandise in the store and have a positive influence on customer decisions and loyalty. Sub-attributes insignificantly correlated to the variety of merchandise in-store are: distance from the customer’s workplace, distance from the customer’s home or farm, distance to the preferred store and store business hours. This means that these sub- attributes together have no influence on customer decisions or loyalty 4.3.2.8 Crowdedness of store The distance to a preferred store correlates positively to the crowdedness at 5% level of significance with a p-value of 0.048. The store’s accessibility correlates positively at 5% level of significance with a p-value of 0.035. The flow of customers in the store correlates positively at 1% level of significance with a p-value of 0.003. The amount of walking required in-store is positive at a 5% level of significance with a p-value of 0.005. The variety of merchandise correlates positively at 10% significance level with a p-value of 0.079. Lastly, business hours are correlated positively at 5% significance level with a p- value 0.025. All this means that these sub-attributes move in parallel with store crowdedness and have a positive influence on customer decisions and loyalty. 84 One sub-attribute is insignificantly correlated to the crowdedness of a store: distance from the customer’s workplace. This means that this sub-attribute has no influence on customer decisions and loyalty 4.3.2.9 Store business hours Distance to a preferred store correlates positively to store business hours at 10% level of significance with a p-value of 0.097. The flow of customers in-store correlates positively at 5% level of significance with a p-value of 0.048. The amount of walking required in- store is positively correlated at 5% level of significance with a p-value of 0.007. The crowdedness of the store correlates positively at 5% significance level with a p-value of 0.025. All this means that these sub-attributes move in parallel with store crowdedness and have a positive influence on customer decisions and loyalty. Four sub-attributes are insignificantly correlated to a store’s business hours: distance from the customer’s workplace, distance from the customer’s home or farm, accessibility of the store and lastly the variety of merchandise. This means that these sub-attributes together have no influence on customer decisions or loyalty. For the convenience attribute, it is clear that shopping experience, fashion ability and a ventilation system is important for customers as these were highly ranked by respondents. Crowdedness is positively correlated with most of the sub-attributes that fall under convenience 85 Table 4.4: Correlation of convenience sub-attributes Convenience attribute correlations Workplace Home or Distance Accessibility Flow Walking Merchandise Crowding Store business farm from store to store required hours Workplace Pearson 1 0.744* 0.442 0.619 0.673 0.397 0.533 0.581 0.061 correlation Sig. (1-tailed) 0.045 0.190 0.095 0.072 0.218 0.138 0.113 0.454 Home or farm Pearson 0.744* 1 0.641 0.712 0.844* 0.733* 0.553 0.899** 0.496 correlation Sig. (1-tailed) 0.045 0.085 0.056 0.017 0.049 0.127 0.007 0.158 Distance from Pearson 0.442 0.641 1 0.435 0.629 0.873* 0.454 0.734* 0.656 store correlation Sig. (1-tailed) 0.190 0.085 0.194 0.090 0.012 0.183 0.048 0.079 Accessibility to Pearson 0.619 0.712 0.435 1 0.939** 0.732* 0.963** 0.777* 0.596 store correlation Sig. (1-tailed) 0.095 0.056 0.194 0.003 0.049 0.001 0.035 0.106 Flow Pearson 0.673 0.844* 0.629 0.939** 1 0.867* 0.859* 0.940** 0.735* correlation Sig. (1-tailed) 0.072 0.017 0.090 0.003 0.013 0.014 0.003 0.048 Walking required Pearson 0.397 0.733* 0.873* 0.732* 0.867* 1 0.710 0.914** 0.899** correlation Sig. (1-tailed) 0.218 0.049 0.012 0.049 0.013 0.057 0.005 0.007 Merchandise Pearson 0.533 0.553 0.454 0.963** 0.859* 0.710 1 0.655 0.568 correlation Sig. (1-tailed) 0.138 0.127 0.183 0.001 0.014 0.057 0.079 0.120 Crowding Pearson 0.581 0.899** 0.734* 0.777* 0.940** 0.914** 0.655 1 0.810* correlation Sig. (1-tailed) 0.113 0.007 0.048 0.035 0.003 0.005 0.079 0.025 Store business Pearson 0.061 0.496 0.656 0.596 0.735* 0.899** 0.568 0.810* 1 hours correlation Sig. (1-tailed) 0.454 0.158 0.079 0.106 0.048 0.007 0.120 .025 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 86 4.4 Merchandise attribute rating 4.4.1 Definition of merchandise The real attributes of the merchandise are the characteristics of the products. This can be divided into two parts: the actual physical characteristics and the assessable characteristics. The customer wants the actual physical product or service. The assessable characteristics can be derived through the use of the product. It is very important that retailers produce benefits of this kind totally different from their competition (www.coursehero.com). The results for this attribute are presented in Table 4.5. Each respondent in an order of importance rated it. Mean ranks were calculated and presented in Table 4.5. The analysis was done for all the stores that formed part of the research area. Table 4.5: Mean of merchandise attribute rating by province Row labels Eastern Free KwaZulu-Natal Mpumalanga Cape State Branded merchandise 3.03 3.19 2.83 3.4 Imported merchandise 3.22 3.94* 3.08 3.4 Merchandise categories 3.6** 3.61*** 3.67* 3.6*** Products on the market 3.33*** 3.53 3.5*** 3.8** Type of farming 3.67* 3.74** 3.58** 4.2* Grand total 16.85 18.01 16.66 18.40 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.4.1.1 Highest ranking by province Respondents in the Eastern Cape and Mpumalanga ranked products, which suit their 87 farming type as very important and in the highest-ranked category. Imported merchandise was placed in this high-ranking category by respondents in the Free State. 4.4.1.2 Second-highest ranking by province Respondents in the Free State and KwaZulu-Natal ranked products that suit their farming type as being in the second-highest category. Mpumalanga respondents ranked the availability of the latest farming products on the market in the second-highest category. The variety of merchandise categories was ranked in this category by respondents in the Eastern Cape. 4.4.1.3 Third-highest ranking by province The respondents in the Free State and Mpumalanga ranked the variety of merchandise in the third-highest category. Respondents in KwaZulu-Natal and the Eastern Cape ranked the availability of the latest products on the market in the same category. 4.4.1.4 Lowest rankings This attribute was ranked lowest (overall). • Branded merchandise scored 2.83 (18% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 88 Figure 4.5: Merchandise attribute rating (pool sample) This figure shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the merchandise attribute. The variety of merchandise category and imported merchandise were ranked equally at 23% each. Branded merchandise was scored 21%, the latest product on the market scored 18% and farming products suitable to the style of farming 15%. 4.4.2 Merchandise attribute correlation 4.4.2.1 Merchandise category Merchandise variety or category is positively correlated to the latest products on the market at a significance level of 1% with a p-value of 0.010. Products suiting a farmer’s farming type are significant at 1% with a p-value of 0.089. These sub-attributes move in parallel with merchandise variety/category and have a positive influence on customer 89 decisions and loyalty. Imported merchandise and branded merchandise is correlated negatively to merchandise variety/category and has an insignificant effect on merchandise variety/ category. This implies that these sub-attributes (availability of imported and branded merchandise) move in the opposite direction from the merchandise category and have no influence on customer decisions or loyalty. 4.4.2.2 Availability of imported merchandise The availability of branded and imported merchandise is positively correlated at a significance level of 10% with a p-value of 0.087. These sub-attributes move in parallel with the availability of imported merchandise and have a positive influence on customer decisions and loyalty. Merchandise variety/category, the latest products on the market, and products that suit a farmer’s farming style are all correlated negatively to the availability of imported merchandise. This means they have an insignificant outcome on the availability of merchandise. It implies that these sub-attributes move in the opposite direction from the availability of imported merchandise and have no influence on customer decisions or loyalty. 4.4.2.3 Latest products on the market Merchandise variety/category is correlated positively to the latest products on the market at a significance level of 1% with a p-value of 0.01. Products suiting a farmer’s farming type are significant at 1% with a p-value of 0.006. These sub-attributes move in a parallel direction with the latest products on the market and have a positive influence on customer 90 decisions and loyalty. The availability of imported merchandise and branded merchandise are correlated negatively with the latest products on the market and have an insignificant effect on the latest products on the market. This implies that these sub-attributes (availability of imported and branded merchandise) move in the opposite direction from the latest products on the market and have no influence on customer decisions or loyalty. 4.4.2.4 Type of farming Merchandise variety/category is positively correlated to products that suit a farmer’s farming type at a significance level of 10% with a p-value of 0.089. The latest products on the market are significant at 1% with a p-value of 0.006. These sub-attributes move in a parallel direction with the latest products on the market and have a positive influence on customer decisions and loyalty. The availability of imported merchandise, branded and otherwise, is correlated negatively to the latest products on the market and have an insignificant effect on products that suit the farmer’s farming type. This implies that these sub-attributes (availability of imported and branded merchandise) move in the opposite direction from the latest products on the market and have no influence on customer decisions or loyalty. The correlation of merchandise sub-attribute is depicted in Table 4.6 below. 91 Table 4.6: Correlation of merchandise sub-attribute Merchandise attribute correlations Merchandise Imported Branded Product Type of farming category Merchandise Merchandise marketing Merchandise Pearson correlation 1 -0.514 -0.288 0.884** 0.631 category Sig. (1-tailed) 0.149 0.290 0.010 0.089 Imported Pearson correlation -0.514 1 0.637 -0.523 -0.489 Merchandise Sig. (1-tailed) 0.149 0.087 0.144 0.162 Branded Pearson correlation -0.288 0.637 1 -0.296 -0.331 Merchandise Sig. (1-tailed) 0.290 0.087 0.284 0.261 Marketing of Pearson correlation 0.884** -0.523 -0.296 1 0.911** products Sig. (1-tailed) 0.010 0.144 0.284 0.006 Type of Pearson correlation 0.631 -0.489 -0.331 0.911** 1 Farming Sig. (1-tailed) 0.089 0.162 0.261 0.006 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 92 4.5 Structural attribute rating 4.5.1 Definition of structural This is merely the set-up of the location. From the location of the store it is the accessibility, whether on foot or by car (or any other form of transport) to the store interior. This could however, vary from store to store, given the target market. An example of this can be that the fuel pump at store A is different from the location of the same pump at store B. The results of this attribute are presented in Table 4. 7. This attribute was rated by each respondent in an order of importance. Mean ranks were calculated and presented in Table 4.7. The analysis was done for all the stores, which formed part of the research area. Table 4.7: Mean of structural attribute rating by province Row labels Eastern Free KwaZulu-Natal Mpumalanga Cape State Accessibility for customers 3.67 3.82 3.92*** 4** Connection to road network 3.6 3.74 3.75 3.2 Location 3.77 3.84*** 4.0** 4.2*** Payment options 3.9** 4.06** 3.25 4.4* Point of sale 3.93* 4.16* 3.67 3.4 Adequate parking 3.8*** 3.61 3.58 4** Tills available 3.8*** 3.5 4.17* 3.4 Grand total 26.47 26.73 26.34 26.60 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 93 4.5.1.1 Highest ranking by province Respondents in the Free State and Eastern Cape ranked the point of sale in the highest ranking category. There is a strong need for payment points in the store, so respondents in KwaZulu-Natal ranked the availability of working tills highest. Respondents in Mpumalanga ranked favourable payment options as very important and in the highest ranking category. The store’s accessibility to customers and adequate parking were ranked as very important and placed in the highest ranking category. 4.5.1.2 Second-highest ranking by province The location was ranked in the second-highest category by respondents in the KwaZulu- Natal. Respondents in the Free State and Eastern Cape ranked payment options in this category. Adequate parking and accessibility for customers were also ranked in this category by respondents in Mpumalanga. 4.5.1.3 Third-highest ranking by province Respondents in Mpumalanga and the Free State ranked the location of a store in the third-highest ranking. The accessibility of a store to customers was ranked in this category by respondents in KwaZulu-Natal. Adequate parking and the availability of tills were ranked in the third-highest category by respondents in the Eastern Cape. 4.5.1.4 Lowest rankings These attributes were ranked lower than the rest (overall): • The availability of tills, which scored 3.5 (13% mean score). • Connection to the road network scored the lowest with 2 (mean score). 94 Although they are important attributes in total, they were ranked lower in comparison with the other attributes. Figure 4.6 Structural attribute rating (pool sample) This figure shows feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the structural attribute. The accessibility of a store is very important for customers and scored the highest ranking, 16%. Adequate parking, connected to the road network, the location of a store and the availability of working tills were ranked equally at 15% each. The point of sale ranked sixth-highest at 14%. Lastly, the payment option scored 10%. 95 4.5.2 Structural attribute correlation 4.5.2.1 Accessibility of store Adequate parking and store accessibility are correlated positively at a significance level of 1% with a p-value of 0.003. The availability of enough tills also correlates positively with accessibility at a significance level of 5% with a p-value 0.22. The attractiveness of the point of sale is correlated positively at 5% significance level with a p-value 0.05. This means that an increase or decrease in one sub-attribute will lead to an increase or decrease in the other. This however, shows that sub-attributes have an effect on each other. Connection to the road network is correlated negatively to the accessibility of the store. This implies that it is insignificant and moves in the opposite direction from accessibility. The same goes for the location and payment options, suggesting that these sub-attributes have no influence in customer decision-making or loyalty. 4.5.2.2 Adequate parking The store’s accessibility and adequate parking are correlated positively at 1% significance level with a p-value of 0.003. The availability of enough tills is also correlated positively with adequate parking at a level of 5% significance with a p-value of 0.037, followed by the point of sale correlating at 5% significance level with a p-value of 0.043, and payment options at 10% significance level with a p-value of 0.084. These sub-attributes move in parallel with adequate parking and have a positive influence on customer decisions and loyalty. 96 Connection to the road network is correlated negatively with adequate parking at the store. This implies that it is insignificant and moves in the opposite direction from adequate parking. The location is also not correlated to adequate parking, suggesting that these sub-attributes have no influence in customer decision-making or loyalty. 4.5.2.3 Connection to road network Accessibility, adequate parking, location, sufficient tills, the point of sale and payment options are all correlated negatively with a connection to the road network. This means it is insignificant and moves in the opposite direction from connection to the road network. The location is also not correlated to adequate parking, suggesting that these sub- attributes have no influence in customer decision-making or loyalty. 4.5.2.4 Location Accessibility, adequate parking, availability of sufficient tills and payment options are all insignificant and uncorrelated to location. This suggests that these sub-attributes have no influence in customer decision-making or loyalty. These sub-attributes move in non- parallel directions from location, so they have no influence at all on location, with a connection to the road network correlating negatively to location. 4.5.2.5 Tills Accessibility and the availability of sufficient tills are correlated positively at a significance level of 5% with a p-value of 0.022. Adequate parking is also correlated positively with a significance level of 5% with a p-value of 0.037. Next is the point of sale, which also correlates positively to sufficient tills available at a 5% significance level with a p-value of 0.03. These sub-attributes move in a parallel direction with tills and have a positive 97 influence on customer decisions and loyalty. Location and payment options are not correlated with tills, which means that they are insignificant and move in a non-parallel direction to tills. This suggests that these sub- attributes have no influence in customer decision-making or loyalty. Connection to the road network is correlated negatively to tills. 4.5.2.6 Point of sale Accessibility is positively correlated to point of sale at 5% level of significance and a p- value of 0.050. This is followed by adequate parking, which is also correlated positively to point of sale and has a significance level 5% with a p-value of 0.043. The availability of enough tills correlates positively at 5% significance level with a p-value of 0.03. Lastly, payment options are also correlated positively at 10% level of significance and a p-value of 0.08. Connection to the road network and location are correlated negatively. This means they are insignificant and move in the opposite direction from point of sale. This suggests that these sub-attributes have no influence in customer decision-making or loyalty. 4.5.2.7 Payment options Adequate parking is positively correlated with payment options at a significance level of 10% with a p-value of 0.084. The point of sale is also positively correlated with payment options at a 10% significance level with a p-value of 0.08. These sub-attributes move in a parallel direction with the tills and have a positive influence on customer decisions and loyalty. 98 Accessibility, location and adequate tills are all not correlated with payment options. This means they are insignificant and have no influence on payment options. In turn, that means to move in the opposite direction from point of sale. This suggests that these sub- attributes have no influence on customer decision-making or loyalty. 99 Table 4.8: Correlation of structural sub-attributes Structural attribute correlations Accessibility Adequate Connection Location Tills Point of Payment Parking to sale option roads Accessibility Pearson correlation 1 0.941** -0.907** 0.270 0.822* 0.729 0.482 Sig. (1-tailed) 0.003 0.006 0.302 0.022 0.050 0.166 Adequate Pearson correlation 0.941** 1 -0.974** 0.289 0.770* 0.750* 0.644 Parking Sig. (1-tailed) 0.003 0.000 0.289 0.037 0.043 0.084 Connection Pearson correlation -0.907** -0.974** 1 -0.451 -0.771* -0.768* -0.777* to roads Sig. (1-tailed) 0.006 0.000 0.185 0.036 0.037 0.034 Location Pearson correlation 0.270 0.289 -0.451 1 0.131 -0.018 0.597 Sig. (1-tailed) 0.302 0.289 .0185 0.402 0.487 0.105 Tills Pearson correlation 0.822* 0.770* -0.771* 0.131 1 0.794* 0.406 Sig. (1-tailed) 0.022 0.037 0.036 0.402 0.030 0.212 Point of sale Pearson correlation 0.729 0.750* -0.768* -0.018 0.794* 1 0.653 Sig. (1-tailed) 0.050 0.043 0.037 0.487 0.030 0.080 Payment Pearson correlation 0.482 0.644 -0.777* 0.597 0.406 0.653 1 Options Sig. (1-tailed) 0.166 0.084 0.034 0.105 0.212 0.080 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 100 4.6 Institutional attributes 4.6.1 Definition of institutional This can be defined as the overall impression the store gives the customers through the sales staff, the clientele, and the social class (Amirani and Gates, 1993). This encompasses the store’s self-image and the customers being able to identify with the store (Al-Awadi 2002). The results for this attribute are presented in Table 4.9. This attribute was rated by each respondent in an order of importance. Mean ranks were calculated and appear in Table 4.9 below. The analysis was done for all the stores that formed part of the research area. Table 4.9: Mean of institutional attribute rating by province Row labels Eastern Cape Free State KwaZulu-Natal Mpumalanga (Luxury vs convenience) 3.73* 3.59*** 4.17* 4.2* Appearance of sales staff 3.63** 3.69* 4** 3.6*** Store identity 3.3 3.55 3.83*** 4** Relationship 3.17*** 3.39 3.25 3.2 Store image & self-image 3.17*** 3.52 3.42 3.4 Store's appeal 3.53*** 3.61** 3.67 3.6*** Grand total 20.53 21.35 22.34 22 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.6.1.1 Highest ranking by province Respondents in the Eastern Cape, KwaZulu-Natal and Mpumalanga ranked luxury against convenience (do customers shop at stores, which cater for luxury or convenience? – customers rated this as equally important when shopping) as very 101 important and in the highest-ranking category. The appearance of sales staff is very important for customers and was ranked in this category by respondents in the Free State. 4.6.1.2 Second-highest ranking by province The appearance of the sales staff is important for customers and was ranked in the second-highest category by respondents in the Eastern Cape and KwaZulu-Natal. The store’s appeal to friends and family was ranked in this category by respondents in the Free State. The ability to identify the store out of all other stores was ranked in this category by respondents in Mpumalanga. 4.6.1.3 Third-highest ranking by province Respondents in the Eastern Cape and Mpumalanga ranked the store’s appeal to friends and family in the third-highest category. Respondents in KwaZulu-Natal ranked the ability to identify the store from all other stores in this category. The appearance of the sales staff was ranked in the third-highest category by respondents in Mpumalanga. Respondents in the Free State ranked luxury against convenience (do customers shop at stores, which cater for luxury or convenience?). Customers rated this as equally important when shopping, and in the third-highest-ranking category. 4.6.1.4 Lowest rankings These attributes were ranked lower than the rest (overall). ● Manager/staff building relationships with customers scored 3.17 (16% mean score). ● The link between store image and self-image also scored 3.17 (16% mean score). Although it is an important attribute overall, it was ranked lower in comparison with the other attributes. 102 Figure 4.7: Institutional attribute rating (pool sample) The figure above shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the institutional attribute. Building relations with customers was ranked as very important and scored the highest ranking of 18%. Next was the link between store image and self-image, being able to identify the store from all other stores and the appearance of the sales personnel scored an equal share of 17% each. The store’s appeal to friends and family ranked fifth highest and scored 16%. Lastly, luxury v convenience ranked sixth-highest at 15%. 103 4.6.2 Institutional attribute correlation 4.6.2.1 Relationships Building relationships with customers and building a good store image are correlated positively at 1% level of significance with a p-value of 0.000. The identity of the store and its customer relationships are also correlated positively at 5% significance level with a p- value of 0.021. Store appeal to friends and family correlates positively at 10% significance level with a p-value of 0.057. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. The appearance of sales staff and luxury versus convenience sub-attributes are not correlated to relationships, making them insignificant. They move in the opposite direction from the point of sale. This means that a change in one sub-attribute will not have any effect on the other. The sub-attributes are independent of each other. 4.6.2.2 Store image Building relationships with customers and a good store image are correlated positively at 1% level of significance with a p-value of 0.000. Store identity and customer relationship are also correlated positively at 1% significance level with a p-value of 0.006. The store’s appeal to friends and family correlates positively at 10% significance level with a p-value of 0.057. Lastly, there is a positive correlation between store image and luxury versus convenience (social status of store v convenience) at 10% level of significance with a p- value of 0.055. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. The appearance of the sales staff is insignificant because it does not correlate with store 104 image. This means it moves in a non-parallel direction and has no effect on store image. This suggests that these sub-attributes have no influence in customer decision-making or loyalty. 4.6.2.3 Store identity Building relationships with customers and the identity of the store are correlated positively at 5% level of significance with a p-value of 0.021. The identity of the store and store image are also correlated positively at 1% significance level with a p-value of 0.006. The appearance of sales staff correlates positively at a significance level of 10% with a p- value of 0.081. Store appeal to friends and family correlates positively at 1% significance level with a p-value of 0.007. Lastly, there is a positive correlation between store identity and luxury v convenience (social status of store v convenience) at 1% level of significance with a p-value of 0.006. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. 4.6.2.4 Appearance of sales staff The identity of the store and the appearance of sales staff are also correlated positively at 10% significance level with a p-value of 0.081. Store appeal to friends and family correlates positively at 5% significance level with a p-value of 0.024. Lastly, there is a positive correlation between identity of the store and luxury v convenience (social status of store v convenience) at 5% level of significance with a p-value of 0.041. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. 105 4.6.2.5 Store appeal Building relationships with customers and the store’s appeal to friends and family are correlated positively at 10% level of significance with a p-value of 0.057. Store image and store appeal are also correlated positively at 5% significance level with a p-value of 0.022. The identity of the store is also correlated positively at 1% significance level with a p- value of 0.007. The appearance of sales staff to friends and family correlates positively at 5% significance level with a p-value of 0.024. Lastly, there is a positive correlation between store appeal to friends and family and luxury v convenience (social status of store v convenience) at 1% level of significance with a p-value of 0.003. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. 4.6.2.6 Luxury versus convenience Store image and luxury versus (v) convenience (social status of store versus convenience) are also correlated positively at 10% significance level with a p-value of 0.055. The identity of the store is also correlated positively at 1% significance level with a p-value of 0.006. The appearance of sales personnel to friends and family correlates positively at 5% significance level with a p-value of 0.041. Lastly, there is a positive correlation between store appeal to friends and family and luxury v convenience (social status of store v convenience) at 1% level of significance with a p-value of 0.003. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Building relationships with customers is insignificant because it does not correlate to 106 luxury v convenience (social status of store v convenience). This means it moves in a non-parallel direction and has no effect on store image. This means that a change in one sub-attribute will not have any impact on the other. Sub-attributes are independent of each other. Respondents ranked luxury versus convenience as equally and highly important for an agribusiness, followed by the appearance of staff members. The effort by the staff members and or manager at building customer relationships also came in with a high- ranking. Store identity is also highly favoured by respondents. The most positively correlated sub-attribute is store identity, as this correlates positively with almost all the other sub-attributes in the institutional attribute. 107 Table 4.10: Correlation of institutional sub-attributes Institutional attribute correlations Relationship Store Store identity Sales staff Store Luxury vs Image appearance Appeal convenience Relationship Pearson correlation 1 0.981** 0.829* 0.454 0.709 0.592 Sig. (1-tailed) 0.000 0.021 0.183 0.057 0.108 Store image Pearson correlation 0.981** 1 0.911** 0.558 0.822* 0.715 Sig. (1-tailed) 0.000 0.006 0.125 0.022 0.055 Store identity Pearson correlation 0.829* 0.911** 1 0.650 0.903** 0.907** Sig. (1-tailed) 0.021 0.006 0.081 0.007 0.006 Sales staff Pearson correlation 0.454 0.558 0.650 1 0.815* 0.755* appearance Sig. (1-tailed) 0.183 0.125 0.081 0.024 0.041 Store appeal Pearson correlation 0.709 0.822* 0.903** 0.815* 1 0.937** Sig. (1-tailed) 0.057 0.022 0.007 0.024 0.003 Luxury vs Pearson correlation 0.592 0.715 0.907** 0.755* 0.937** 1 convenience Sig. (1-tailed) 0.108 0.055 0.006 0.041 0.003 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 108 4.7 Promotion attribute rating 4.7.1 Definition of promotion Various methods of advertising can be used to describe attribute in finer detail. DuFrene et al (2005) listed promotions as advertising, personal contact with customers and advertising promotion as realistic models to use for advertising. The results for this attribute are presented in Table 4.11. Each respondent in an order of importance rated this attribute. Mean ranks were calculated and are presented in Table 4.11. The analysis was done for all the stores that formed part of the research area. Table 4.11: Mean of promotion attribute rating by province Row labels Eastern Cape Free State KwaZulu-Natal Mpumalanga Advertising 3.67** 3.63** 3.92* 3.6*** Brochures 2.43 3.24*** 2.33 3.2 Displays 3.67** 3.6*** 3.42 4.2* Markdowns 3.47 3.48 3.67*** 3.6*** Advertising methods 3.53*** 3.71* 3.58 3.8** Stock on sale 3.8* 3.58 3.75** 3.8** Grand total 20.57 21.24 20.67 22.20 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.7.1.1 Highest ranking by province Respondents in KwaZulu-Natal agreed that the credibility of the advertising of a store or business was very important and ranked it in the highest-ranking category. Respondents in Mpumalanga felt that in-store displays were important. Respondents in the Free State ranked the advertising methods used as very important and in the highest-ranking category. The availability of stock on sale was very important for customers and was 109 ranked second by respondents in the Eastern Cape. 4.7.1.2 Second-highest ranking by province Respondents in the Free State and Eastern Cape ranked the credibility of advertising by stores or businesses in the second-highest category. Respondents in Mpumalanga and KwaZulu-Natal ranked the availability of stock on sale in this category. The Mpumalanga respondents ranked the methods used by stores to advertise in the second-highest ranking category. In-store displays were ranked in this category by respondents in the Eastern Cape. 4.7.1.3 Third-highest ranking by province The availability of marked-down stock was ranked in the third-highest category by respondents in Mpumalanga and KwaZulu-Natal. In-store displays were also ranked in the same category by respondents in the Free State. The credibility of advertising by the store or business was ranked in the third-highest category by respondents in Mpumalanga. Respondents in the Eastern Cape ranked the methods used to advertise in this category. 4.7.1.4 Lowest rankings This attribute was ranked lower than the rest (overall): • The inclusion of brochures in the mail scored 3.24 (15% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 110 Figure 4.8: Promotions attribute rating (pool sample) This figure shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores for the institutional attribute. Building relations with customers was ranked as very important and scored the highest ranking of 18%. Next the link between store image and self-image, being able to identify the store out of all other stores and the appearance of sales staff scored equally at 17% each. The store’s appeal to friends and family ranked fifth highest and scored 16%. Lastly, luxury versus convenience ranked sixth-highest at 15% 4.7.2 Promotions attribute correlation 4.7.2.1 Advertising credibility The credibility of advertising and the methods used to advertise are correlated positively 111 at 1% level of significance with a p-value of 0.003. In-store displays also correlated positively at a significance level 5% with a p-value of 0.029. This is followed by the availability of marked-down items at 1% significance level with a p-value of 0.000. Lastly, the availability of stock correlated positively at 1% with a p-value of 0.008. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Brochures in the mail were correlated negatively against the credibility of advertising, which makes them insignificant. This means that this moves in a non-parallel direction and has no influence on the credibility of advertising. This suggests that these sub- attributes have no influence in customer decision-making or loyalty. 4.7.2.2 Advertising methods used The credibility of advertising and the methods used for advertising are correlated positively at 1% level of significance with a p-value of 0.003. In-store displays also correlated positively at a significance level 1% with a p-value of 0.003. This was followed by the availability of marked-down items at 1% significance level with a p-value of 0.000. Lastly, the availability of stock correlates positively at 1% with a p-value of 0.005. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Brochures in the mail are not correlated to advertising methods, which makes them insignificant. This means that this factor moves in a non-parallel direction and has no effect on advertising methods. This suggests that this sub-attribute has no influence in customer decision-making or loyalty. 112 4.7.2.3 Brochures in the mail The credibility of advertising, the availability of marked-down items and the availability of stock on sale are all correlated negatively to brochures in the mail. This means they move in a non-parallel direction and have no effect on brochures in the mail. This suggests that these sub-attributes have no influence in customer decision-making or loyalty. In addition, the in-store display is also not correlated and is insignificant. 4.7.2.4 In-store display The credibility of advertising and in-store displays are correlated positively at 5% level of significance with a p-value of 0.029. Advertising methods used also correlate positively at a significance level of 1% with a p-value of 0.003. These are followed by the availability of marked-down items at 1% significance level with a p-value of 0.009. Lastly, the availability of stock correlates positively at 1% with a p-value of 0.008. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Brochures in the mail are not correlated to the in-store display, which makes them insignificant. This means they move in a non-parallel direction and have no effect on the in-store display. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 4.7.2.5 Marked-down items The credibility of advertising and the availability of marked-down items are correlated positively at 1% level of significance with a p-value of 0.000. Advertising methods used also correlate positively at a significance level 1% with a p-value of 0.000. In-store 113 displays also correlate positively at a significance level 1% with a p-value of 0.009. Lastly, the availability of stock correlates positively at 1% with a p-value of 0.002. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Brochures in the mail are correlated negatively to the availability of marked-down items that make them insignificant. This means they move in a non-parallel direction and have no effect on the availability of marked-down items. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 4.7.2.6 Stock on sale The credibility of advertising and the availability of stock on sale are correlated positively at 1% level of significance with a p-value of 0.008. Advertising methods used also correlate positively at a significance level 1% with a p-value of 0.005. In-store displays also correlate positively at a significance level 1% with a p-value of 0.008. Lastly, the availability of stock correlates positively at 1% with a p-value of 0.002. These sub- attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Brochures in the mail are correlated negatively to the availability of stock on sale, which makes them insignificant. This means they move in a non-parallel direction and have no effect on stock on sale. This suggests that this sub-attribute has no influence in customer decision-making or loyalty. 114 Table 4.12: Correlation of promotion sub-attributes Promotions attribute correlations Advertising Advertising method Brochures Displays Marked-down Stock sale Advertising Pearson 1 0.939** -0.040 0.798* 0.981** 0.894** correlation Sig. (1-tailed) 0.003 0.470 0.029 0.000 0.008 Advertising Pearson 0.939** 1 0.150 0.936** 0.979** 0.917** method correlation Sig. (1-tailed) .003 0.389 0.003 0.000 0.005 Brochures Pearson -0.040 0.150 1 0.157 -0.018 -0.235 correlation Sig. (1-tailed) 0.470 0.389 0.383 0.486 0.327 Displays Pearson 0.798* 0.936** 0.157 1 0.890** 0.894** correlation Sig. (1-tailed) 0.029 0.003 0.383 0.009 0.008 Marked-down Pearson 0.981** 0.979** -0.018 0.890** 1 0.947** correlation Sig. (1-tailed) 0.000 0.000 0.486 0.009 0.002 Stock on sale Pearson 0.894** 0.917** -0.235 0.894** 0.947** 1 correlation Sig. (1-tailed) 0.008 0.005 0.327 0.008 0.002 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 115 4.8. Service attribute rating 4.8.1 Definition of service The service of the store comprises after-sales service, return policy, inter-store transfers and delivery options (Thang and Tan, 2003). In this particular study, only certain aspects are assessed – courier service, delivery service, adequacy of sales staff and inter-store transfers. The results for this attribute are presented in Table 4.13. Each respondent in an order of importance rated it. Mean ranks were calculated and are presented in Table 4.13. This analysis was done for all the stores that formed part of the research area. Table 4.13: Mean of service attribute rating by province Row labels Eastern Cape Free State KwaZulu-Natal Mpumalanga Courier service 3.53 3.31 2.75**** 3.6** Deliveries 3.57*** 3.37*** 3.33*** 3.2*** Sufficient sales staff 3.73* 3.58* 3.58* 3.2*** Transfers 3.67** 3.47** 3.42** 4* Grand total 14.5 13.73 13.08 14 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.8.1.1 Highest ranking by province Respondents in the Eastern Cape, Free State and KwaZulu-Natal ranked the need for stores to have sufficient sales staff in the highest-ranking category. Inter-store transfers were ranked in this category by respondents in Mpumalanga. 116 4.8.1.2 Second-highest ranking by province Respondents in the Eastern Cape, Free State and KwaZulu-Natal placed inter-store transfers in the second-highest ranking. 4.8.1.3 Third-highest ranking by province Respondents in the Eastern Cape, Free State, Mpumalanga and KwaZulu-Natal rated the availability of deliveries in the third-highest ranking. Respondents in Mpumalanga ranked sufficient sales personnel in this category. 4.8.1.4 Lowest rankings This attribute was ranked lower than the rest (overall). • Availability of a courier service scored 2.75 (24% mean score). Although it is an important attribute overall, it was ranked lower in comparison with the other attributes. 117 Figure 4.9: Service attribute rating (pool sample) This figure shows feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores for the service attribute. Having enough sales staff and the availability of deliveries were both placed the highest-ranking category and each scored 26%. Inter-store transfers store and the availability of courier service both scored 24%. 4.8.2 Service attribute correlations 4.8.2.1 Adequate sales staff An adequate number of sales personnel and delivery services are correlated positively at a significance level of 1% with a p-value of 0.005. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Inter-store transfers and courier services are not correlated to an adequate number of sales staff. This means that these sub-attributes move in a non-parallel direction and have 118 no effect on whether sales staff numbers are adequate. This suggests that this sub- attribute has no influence in customer decision-making or loyalty. 4.8.2.2 Delivery service Adequacy of sales personnel and delivery services are correlated positively at a significance level of 1% with a p-value of 0.005. So are inter-store transfers and delivery service at a 10% significance level and a p-value of 0.056. Courier service and delivery service also correlate positively at 5% significance level with a p-value of 0.024. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. 4.8.2.3 Inter-store transfers Inter-store transfers and delivery service are also at a 10% significance level and a p- value of 0.056. Courier service and delivery service also correlate positively at 5% significance level with a p-value of 0.024. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Inter-store transfers are not correlated with an adequate number of sales personnel. This means that these sub-attributes move in a non-parallel direction and have no effect on inter-store transfers. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 4.8.2.4 Courier service Courier services and delivery services are correlated positively at a significance level of 5% with a p-value of 0.024. So are inter-store transfers and delivery service at a 1% 119 significance level and a p-value of 0.002. These sub-attributes move in a parallel direction with relationships and have a positive influence on customer decisions and loyalty. Courier services are not correlated with an adequate number of sales personnel. This means that these sub-attributes move in a non-parallel direction and have no effect on courier services. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 120 Table 4.14: Correlation of service sub-attributes Service attribute correlations Adequate Deliveries Transfers Courier services sales staff Adequate Pearson correlation 1 0.921** 0.490 0.586 sales staff Sig. (1-tailed) 0.005 0.162 0.111 Deliveries Pearson correlation 0.921** 1 0.712 0.815* Sig. (1-tailed) 0.005 0.056 0.024 Transfers Pearson correlation 0.490 0.712 1 0.954** Sig. (1-tailed) 0.162 0.056 0.002 Courier Pearson correlation 0.586 0.815* 0.954** 1 services Sig. (1-tailed) 0.111 0.024 0.002 **Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 121 4.9 Sales attribute rating 4.9.1 Definition of sales Sales cover the selling of the product and in most cases, a great deal is it is done by the sales staff. Thang and Tan (2003) states that when one has enough sales staff to do the job, people who are product-orientated and can actually give product advice, positive sales can be achieved. The results for this attribute are presented in Table 4.15. Each respondent in an order of importance rated this attribute. Mean ranks were calculated and are presented in Table 4.15. The analysis was done for all the stores that formed part of the research area. Table 4.15: Mean of sales attribute rating by province Row labels Eastern Free KwaZulu-Natal Mpumalanga Cape State Gender representative 3.87*** 3.89 3.5**** 4.4** Staff friendly 4.1** 4.1 4.33** 4.4** Staff helpful 4.27* 4.24* 4.58* 4.6* Staff presentable 3.73 4.03** 4.25*** 4*** Product-orientated 3.83 4.02*** 4.25*** 3.8 Grand total 19.8 20.28 20.91 21.2 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.9.1.1 Highest ranking by province Respondents in the Free State, Eastern Cape, KwaZulu-Natal and Mpumalanga ranked staff helpfulness as very important and in the highest-ranking category. Respondents 122 ranked these in the highest-ranking category representation of both genders, friendly staff, staff present ability and the product knowledge or orientation of staff members. 4.9.1.2 Second-highest ranking by province Respondents in the Eastern Cape, KwaZulu-Natal and Mpumalanga ranked the present ability of staff in the second-highest ranking category. Respondents in Mpumalanga ranked the representation of both genders in this category. Free State respondents ranked the present ability of personnel in the second-highest ranking category. 4.9.1.3 Third-highest ranking by province Respondents in KwaZulu-Natal and Mpumalanga ranked personnel present ability in the third-highest ranking category. Respondents in KwaZulu-Natal and the Free State ranked the product orientation or product knowledge of staff third highest. In the Eastern Cape, respondents ranked gender representation in this category. 4.9.1.4 Lowest rankings This attribute was ranked lowest (overall). • Representation of both genders 3.5 (19% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 123 Figure 4.10: Sales attribute rating (pool sample) This figure shows feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores of the sales attribute. The present ability of staff scored 21%. Respondents rated the staff’s friendliness, product knowledge and helpfulness equally (20%). Finally, gender representation among the staff scored 19%. 4.9.2 Sales attribute correlation 4.9.2.1 Present ability of staff The present ability of staff and their friendliness are correlated positively at 5% level of significance with a p-value of 0.012. The product orientation or product knowledge of staff and their present ability are correlated positively at 1% level of significance at a p-value of 0.002. The helpfulness of the staff is also positively correlated at 10% significance level 124 with a p-value 0.089. The representation of both genders in a store correlates positively at 10% significance level with a p-value of 0.079. These sub-attributes move in a parallel direction with the present ability of staff and have a positive influence on customer decisions and loyalty. 4.9.2.2 Friendliness of staff The present ability and friendliness of the staff are correlated positively at 5% level of significance with a p-value of 0.012. The product orientation or product knowledge of staff is positively correlated at 5% level of significance at a p-value of 0.012. The helpfulness of the staff is also correlated positively at 1% significance level with a p-value of 0.007. The representation of both genders in a store correlates positively at 5% significance level with a p-value of 0.018. These sub-attributes move in a parallel direction with the friendliness of the staff and have a positive influence on customer decisions and loyalty. 4.9.2.3 Product knowledge or orientation The present ability of staff and their product knowledge are correlated positively at 1% level of significance with a p-value of 0.002. The friendliness of the staff is correlated positively at 5% level of significance with a p-value of 0.012. Staff helpfulness is also correlated positively at 10% significance level with a p-value 0.061. The representation of both genders in a store correlates positively at 10% significance level with a p-value of 0.098. These sub-attributes move in a parallel direction with product knowledge or orientation and have a positive influence on customer decisions and loyalty. 4.9.2.4 Helpfulness of staff The present ability and helpfulness of staff are correlated positively at 10% level of 125 significance with a p-value of 0.089. Staff friendliness is correlated positively at 1% level of significance with a p-value of 0.007. The product orientation or product knowledge of staff and their present ability are correlated positively at 10% level of significance at a p- value of 0.061. The representation of both genders in a store correlates positively at 10% significance level with a p-value of 0.068. These sub-attributes move in a parallel direction with staff helpfulness and have a positive influence on customer decisions and loyalty. 4.9.2.5 Gender representation The present ability of personnel and the representation of both genders are correlated positively at 10% level of significance with a p-value of 0.079. The friendliness of the staff is correlated positively at 5% level of significance with a p-value of 0.018. The product orientation or product knowledge of staff and their present ability are correlated positively at 10% level of significance at a p-value of 0.098. Staff helpfulness is also correlated positively at 10% significance level with a p-value of 0.068. These sub-attributes move in a parallel direction with the representation of both genders and have a positive influence on customer decisions and loyalty. 126 Table 4.16: Correlation of sales attribute rating Sales attribute correlations Staff Staff friendly Product-oriented Staff helpful Gender- presentable representative Staff present Pearson correlation 1 0.868* 0.955** 0.632 0.656 ability Sig. (1-tailed) 0.012 0.002 0.089 0.079 Friendly staff Pearson correlation 0.868* 1 0.870* 0.905** 0.839* Sig. (1-tailed) 0.012 0.012 0.007 0.018 Product- Pearson correlation 0.955** 0.870* 1 0.700 0.613 oriented Sig. (1-tailed) 0.002 0.012 0.061 0.098 Staff helpful Pearson correlation 0.632 0.905** 0.700 1 0.682 Sig. (1-tailed) 0.089 0.007 0.061 0.068 Gender- Pearson correlation 0.656 0.839* 0.613 0.682 1 representative Sig. (1-tailed) 0.079 0.018 0.098 0.068 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 127 4.10 Credit attribute rating 4.10.1 Definition of credit This is the ability of the customer to obtain goods or services before payment, based on trust that the payment will be made in the near future. Previous research has looked at payment options, bankcards, credit, lay-bye accounts and store cards (Burns, 2005). The results for this attribute are presented in Table 4.17. This attribute was rated by each respondent in an order of importance. Mean ranks were calculated and are presented in Table 4.17. The analysis was done for all the stores that formed part of the research area. Table 4.17: Mean of credit attribute rating by province Row Labels Eastern Free State KwaZulu-Natal Mpumalanga cape Availability of credit influence 3.27** 3.11*** 3.42 4.4 Credit options 3.3 2.77**** 3.33** 2.8 Financial product range 3.23*** 3.13** 3.42 3.8** Ease of obtaining credit 3.2 3.24 3.42 3.2*** Grand total 13 12.25 13.59 14.2 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.10.1.1 Highest ranking by province Respondents in the Free State and KwaZulu-Natal ranked the ease of obtaining credit in the highest ranking category. Respondents in KwaZulu-Natal ranked the availability of a diverse financial product range in this category. The availability of credit influences the customer’s choice of store and respondents in Mpumalanga and KwaZulu-Natal ranked this in the highest ranking category. In the Eastern Cape, respondents ranked a variety of credit options in the highest ranking category. 128 4.10.1.2 Second-highest ranking by province The availability of credit influences a customer’s choice of store and respondents in the Eastern Cape ranked this in the second-highest ranking category. Respondents in KwaZulu-Natal ranked a variety of credit options in this highest ranking category. Respondents in the Free State and Mpumalanga ranked the availability of a diverse financial product range in the same category. 4.10.1.3 Third-highest ranking by province The availability of credit does influence a customer’s store choice, and respondents in the Free State ranked this in the third-highest category. Respondents in the Eastern Cape ranked the availability of a diverse financial product range in the same category. Respondents in Mpumalanga ranked the ease of obtaining credit in the third-highest- ranking category. 4.10.1.4 Lowest rankings This attribute was ranked lower than the rest (overall). • Availability of credit options scored 2.77 (23% mean score). Although it is an important attribute overall, it was ranked lower in comparison with the other attributes. 129 Figure 4.11: Credit attribute rating (pool sample) This figure shows feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores for the credit attribute. Respondents ranked the availability of credit at a store or business a choice influence and the availability of a variety of credit option in the highest-ranking category. Both sub-attributes scored an equal 26%, followed by the availability of a diverse financial product range, which scored 25%. Lastly, the ease of obtaining credit from the business or store scored 23%. 4.10.2 Credit attribute correlation 4.10.2.1 Credit influence Availability of credit influence and the financial product range are correlated positively at 10% level of significance with a p-value of 0.052. The ease of gaining credit also 130 correlated positively with credit influence at a significance level of 5% with a p-value of 0.024. These sub-attributes move in parallel with credit influence and have a positive influence on customer decisions and loyalty. The different credit options and credit influence do not correlate. This means that these sub-attributes move in a non-parallel direction and have no credit influence. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 4.10.2.2 Availability of credit options The financial product range is correlated positively to credit options at 10% level of significance with a p-value of 0.067. This sub-attribute moves in a parallel direction with the availability of credit options and has a positive influence on customer decisions and loyalty. Credit influence and the ease of obtaining credit from stores/businesses are not correlated with credit options. This means these sub-attributes move in a non-parallel direction and have no effect on the availability of credit options. This suggests that this sub-attribute has no influence in customer decision-making or loyalty. 4.10.2.3 Financial product range The variety in the financial product range correlates positively to credit influence at a significance level of 10% with a p-value of 0.052. The availability of credit options correlates positively at 10% significance level with a p-value of 0.067. Ease of obtaining credit from a store/business also correlates positively at 1% significance level with a p- value of 0.003. 131 4.10.2.4 Ease of obtaining credit at a store/business Availability of credit influence and the ease to gain credit are positively correlated at 5% level of significance with a p-value of 0.024. The variety in the financial product range correlates positively to ease of obtaining credit from stores/businesses at a significance level of 1% with a p-value of 0.003. These sub-attributes move in parallel direction with credit influence and have a positive influence on customer decisions and loyalty The different credit options and ease of gaining credit do not correlate. This means that these sub-attributes move in a non-parallel direction and have no influence on credit. This suggests that this sub-attribute has no influence in customer decision-making or loyalty. 132 Table 4.18: Correlation of credit sub-attributes Credit attribute correlations Credit Credit Financial product Easy credit availability Credit Pearson correlation 1 0.122 0.724 0.816* Sig. (1-tailed) 0.409 0.052 0.024 Credit availability Pearson correlation 0.122 1 0.684 0.412 Sig. (1-tailed) 0.409 0.067 0.209 Financial product Pearson correlation 0.724 0.684 1 0.937** Sig. (1-tailed) 0.052 0.067 0.003 Easy credit Pearson correlation 0.816* 0.412 0.937** 1 Sig. (1-tailed) 0.024 0.209 0.003 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 133 4.11 Assistance attribute rating 4.11.1 Definition of assistance Assistance can be explained as what the store caters for the customer’s shopping experience. Self-service, service, trolley/basket service, phone orders et cetera (Thang and Tan, 2003). The results for this attribute are presented in Table 4.19. Each respondent in an order of importance rated this attribute. Mean ranks were calculated and are presented in Table 4.19. The analysis was done for all the stores that formed part of the research area. Table 4.19: Mean of assistance attribute rating by province Row labels Eastern Free State KwaZulu- Mpumalanga Cape Natal Different types of trolleys 2.83 2.55 2.83 3.2*** Disability car parking 3.23** 3.48* 3.67** 3.6* Moving purchased goods 3.2*** 3.29** 3.75* 3.6* Special assistance 2.9 2.61*** 1.83**** 2.08 Visible security 3.4* 1.9 3.5*** 3.4** Grand total 15.56 13.83 15.58 15.88 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.11.1.1 Highest ranking by province Respondents in the Free State and Mpumalanga ranked the need for a disability car parking area in the highest-ranking category. Respondents in KwaZulu-Natal and Mpumalanga ranked moving purchased goods from the store to the car at no or minimal charge. To have visible security in the store or at the parking area is ranked in this 134 category by respondents in the Eastern Cape. 4.11.1.2 Second-highest ranking by province Respondents in the Eastern Cape and KwaZulu-Natal ranked the need for a disability car parking area in the second-highest ranking category. Respondents in the Free State and Western ranked moving purchased goods from the store to the car at no or minimal charge. Having visible security in the store or parking area is ranked in this category by respondents in Mpumalanga. 4.11.1.3 Third-highest ranking by province Respondents in Mpumalanga ranked the availability of different types of trolleys in the third-highest ranking category. Respondents in the Eastern Cape ranked moving purchased goods from the store to the car at no or minimal charge in this category. Respondents in the Free State ranked the need for special assistance to the elderly in the third-highest category. Having visible security in the store or the parking area is ranked in this category by respondents in KwaZulu-Natal. 4.11.1.4 Lowest rankings These attributes were ranked lowest than the rest (overall). • Availability of special assistance 1.83 (19% mean score). • Availability of visible security 1.9 (14% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 135 Figure 4.12: Assistance attribute rating (pool sample) This figure shows feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores for the credit attribute. Respondents ranked the availability of special assistance, especially for the elderly, and moving purchased goods from the store to the car at no or minimal charge in the highest ranking category. Both sub-attributes scored an equal 22%. The third-highest sub-attribute was the need for disability car parking, which scored 20%, followed by the need for visible security and the need for different types of trolleys, which each scored 18%. Lastly, the easy of gaining credit from the business or store scored 23%. 4.11.2 Assistance attribute correlation 4.11.2.1 Special assistance Special assistance and moving purchased goods are correlated negatively at 5% level of 136 significance with a p-value of 0.023. This means moving purchased goods has an insignificant effect on special assistance, meaning that these two sub-attributes move in the opposite direction and have no influence on customer decision-making or loyalty. The same applies to the availability of disability parking, visible security and the availability of special trollies for people with special needs. 4.11.2.2 Moving purchased goods Special assistance and moving purchased goods are correlated negatively at 5% level of significance with a p-value of 0.023. This means moving purchased goods has an insignificant effect on special assistance, meaning that these two sub-attributes move in opposite direction and have no influence on customer decision-making or loyalty. The same applies to the availability of disability parking, visible security and the availability of special trolleys for people with special needs. 4.11.2.3 Disability parking The availability of disability parking and visible security are correlated positively at 5% level of significance with a p-value of 0.023. This means that the availability of visible security does have a significant effect on the availability of disability parking, meaning that these two sub-attributes move in opposite direction and have an influence on customer decision-making and loyalty. The same does not apply to the availability of special assistance, moving purchased goods and the availability of special trollies for people with special needs. As these sub- attributes have no influence on customers, decision-making or loyalty due to the opposite direction they move into the availability of disability parking. 137 4.11.2.4 Availability of visible security Availability of credit influence and the ease of obtaining credit are correlated positively at 5% level of significance with a p-value of 0.024. The variety in the financial product range correlates positively to ease of obtaining credit from the store/business at a significance level of 1% with a p-value of 0.003. These sub-attributes move in a parallel direction with credit influence and have a positive influence on customer decisions or loyalty. The different credit options and ease of obtaining credit do not correlate. This means that these sub-attributes move in a non-parallel direction and have no credit influence. This suggests that this sub-attribute has no influence on customers’ decision-making or loyalty. The availability of imported and branded merchandise is correlated negatively to the latest products on the market and has an insignificant effect on the latest products on the market. This implies that these sub-attributes (availability of imported and branded merchandise) move in the opposite direction from the latest products on the market and have no influence on customer decisions or loyalty. 138 Table 4.20: Correlation of assistance sub-attributes Assistance attribute correlations Special Moving Disability Visible Different assistance purchased parking security trolleys goods Special assistance Pearson correlation 1 -0.820* 0.031 0.029 -0.309 Sig. (1-tailed) 0.023 0.477 0.478 0.275 Moving purchased Pearson correlation -0.820* 1 -0.433 -0.296 0.164 goods Sig. (1-tailed) 0.023 0.195 0.284 0.378 Disability parking Pearson correlation 0.031 -0.433 1 0.802* 0.396 Sig. (1-tailed) 0.477 0.195 0.027 0.219 Visible security Pearson correlation 0.029 -0.296 0.802* 1 0.672 Sig. (1-tailed) 0.478 0.284 0.027 0.072 Different trolleys Pearson correlation -0.309 0.164 0.396 0.672 1 Sig. (1-tailed) 0.275 0.378 0.219 0.072 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 139 4.12 Administration attribute rating 4.12.1 Definition of administration This is the process or activity of running a business or organisation – the day-to-day administration (paperwork) involved. This includes customer accounts and payment dates. The results for this attribute are presented in Table 4.21. Each respondent in an order of importance rated this attribute. Mean ranks were calculated and are presented in Table 4.21. The analysis was done for all the stores that formed part of the research area. Table 4.21: Mean of administration attribute rating by province Row labels Eastern Free KwaZulu- Mpumalanga Cape State Natal Accounts or letters 3.43*** 3.5 4*** 3.6* Condition of one’s account 3.1 3.73** 3.75 3.4** Invoice 3.93* 3.82 4.17** 2.6*** Understanding one’s account 3.45** 3.63*** 4.58* 2.4**** Grand total 13.91 14.68 16.5 12 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.12.1.1 Highest ranking by province Receiving invoices on time is very important for customers and the store/business, and respondents in the Free State and Eastern Cape ranked invoices in the highest ranking category. Understanding one’s account is very important for both business and customer, and respondents in KwaZulu-Natal ranked understanding one’s account in this highest ranking category. Respondents in Mpumalanga ranked accounts and letters in this category. 140 4.12.1.2 Second-highest ranking by province Respondents in the Free State and Mpumalanga ranked condition of one’s account in the second-highest ranking category. Receiving invoices on time is important for customers and the store/business, and respondents in KwaZulu-Natal ranked invoices in this ranking category. Understanding one’s account is very important for both business and customer, and respondents in the Eastern Cape ranked understanding one’s account in this category. 4.12.1.3 Third-highest ranking by province Respondents in KwaZulu-Natal ranked accounts and letters in the third-highest ranking category. Receiving invoices on time is important for customers and the store/ business, and respondents in Mpumalanga ranked invoices in this ranking category. Understanding one’s account is very important for both business and customer, and respondents in the Free State ranked understanding the account in this category. 4.12.1.4 Lowest rankings These attributes were ranked lower than the rest (overall). • Understanding one’s account 2.4 (25% mean score). • Accounts and letters 3.43 (24% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 141 Figure 4.13: Administration attribute rating (pool sample) Out of all the respondents, 26% stated that they did receive their invoices on time. Only 24% of the respondents understood the conditions of their accounts (increase in credit limit) and if any changes were made the business did notify them sometimes. Only 25% of respondents received their letters on time, while 25% of the respondents actually understood their accounts as customers of the business. 4.12.2 Administration attribute correlation 4.12.2.1 Receiving invoices on time The receiving of invoices and the ability of clients to understand their own account are correlated positively at a significance level of 1% with a p-value of 0.002. The same applies for receipt of invoices and the receipt on time of accounts and letters by clients of the business. This correlates positively at a 10% level of significance with a p-value of 0.053. The conditions of the account are also significant to invoice receipt at a 10% significance level with a p-value of 0.053. 142 This simply means that these sub-attributes all move in a parallel direction with on time receipt of invoices. This has a significant influence on customer decision-making and loyalty. 4.12.2.2 Customers’ understanding of their own accounts The receipt of invoices and the ability of clients to understand their own accounts are correlated positively at a significance level of 1% with a p-value of 0.002. Receiving letters and accounts on time and the conditions of client accounts are both correlated positively to clients understanding their accounts at a 5% significant level. However, the p-values are not the same: accounts and letters have a p-value of 0.769 and conditions have a p- value of 0.751. Both these sub-attributes move in the same direction as the sub-attribute at hand (clients understanding their own accounts). This means that these sub-attributes have a significant effect on customer decision-making and loyalty. 4.12.2.3 On time receipt of accounts and letters For clients to receive accounts, letters and invoices on time correlated positively at a significance level of 10% with a p-value of 0.053. Understanding the account is correlated positively at 5% with a p-value 0.037 to the receipt of accounts and letters. The condition of client accounts is also correlated positively to accounts and letters at a 1% level of significance with a p-value of 0.002. All these sub-attributes move in the same direction as the sub-attribute at hand (clients understanding their own accounts), which means that these sub-attributes have a significant effect on customer decision-making and loyalty. 143 4.12.2.4 Condition of a client’s account The condition of a client’s account and the receipt of invoices on time by clients are correlated positively at a significance level of 10% with a p-value of 0.053. Understanding of the account is correlated positively at 5% with a p-value 0.043 to receipt of accounts and letters. Lastly, the condition of a client’s account is also correlated positively to accounts and letters at a 1% level of significance with a p-value of 0.002. All these sub-attributes move in the same direction as the sub-attribute at hand (condition of client’s account), which means that these sub-attributes have a significant effect on customer decision-making and loyalty. 144 Table 4.22: Correlation of administration sub-attributes Administration attribute correlations Invoice Understand Accounts Conditions of account account Invoice Pearson correlation 1 0.952** 0.722 0.720 Sig. (1-tailed) 0.002 0.053 0.053 Understand Pearson correlation 0.952** 1 0.769* 0.751* account Sig. (1-tailed) 0.002 0.037 0.043 Accounts Pearson correlation 0.722 0.769* 1 0.952** Sig. (1-tailed) 0.053 0.037 0.002 Conditions of Pearson correlation 0.720 0.751* 0.952** 1 account Sig. (1-tailed) 0.053 0.043 0.002 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 145 4.13 Loyalty attribute rating 4.13.1 Definition of loyalty Customer loyalty is the commitment the customer has to the retailer. It is a willingness to recommend the store to others (word of mouth). For the purpose of the study at hand, the internet is also incorporated into customer loyalty, and loyalty programmes are also looked into. The results for this attribute are presented in Table 4.23. Each respondent in an order of importance rated this attribute. Mean ranks were calculated and are presented in Table 4.23. The analysis was done for all the stores that formed part of the research area. Table 4.23: Mean of loyalty attribute rating by province Row Eastern Free KwaZulu- Mpumalanga Cape State Natal Access to internet 3.67*** 3.77 4* 3.8*** Earning points 3.53 3.97** 3.92** 2.6 Loyal customer 3.87** 4.26* 3.75*** 4.4* Purchase/order goods online 4* 3.77 3.33 2.6 Redeem points 3.63 3.92*** 3.92** 2.2**** Self-service 4* 3.89 3.92** 4.2** Grand total 22.7 23.58 22.84 19.8 (*) Highest rating, (**) Second-highest rating, (***) Third-highest rating, (****) Overall lowest 4.13.1.1 Highest ranking by province Respondents in KwaZulu-Natal placed access to the internet in the highest-ranking category. Respondents in the Free State and Mpumalanga ranked themselves as being loyal customers hence customer loyalty is in the highest-ranking category. Respondents in the Eastern Cape placed use of the internet in the highest-ranking category. Eastern 146 Cape respondents ranked the option of online purchases in this category. 4.13.1.2 Second-highest ranking by province The system of earning loyalty points with every purchase was placed in the second- highest ranking category by respondents in the Free State and KwaZulu-Natal. Respondents in Mpumalanga and KwaZulu-Natal ranked use of the internet in this category. Respondents in the Eastern Cape ranked customer loyalty in the second- highest category. The system of redeeming points for discounts was ranked in this category by respondents in KwaZulu-Natal. 4.13.1.3 Third-highest ranking by province Respondents in the Eastern Cape and Mpumalanga placed access to the internet in the third-highest ranking category. Respondents in KwaZulu-Natal ranked customer loyalty in this category. Free State respondents placed the system of redeeming points for discounts in the third-highest ranking category. 4.13.1.4 Lowest rankings This attribute was ranked lower than the rest (overall): ● The system of redeeming points for discount scored 2.2 (17% mean score). Although it is an important attribute in total, it was ranked lower in comparison with the other attributes. 147 Figure 4.14: Loyalty attribute rating (pool sample) This figure shows the feedback from all the respondents who took part in the survey. The percentages presented are of all the mean scores for the loyalty attribute. Respondents placed customer loyalty in the highest ranking at 18%. Use of the internet and the system of earning points with every purchase ranked as very important and scored the second- highest ranking of 17% each. Following use of the internet, purchasing goods online and redeeming points for cash discounts had an equal share at 16%. 4.13.2 Correlation of loyalty sub-attribute 4.13.2.1 Earning points Earning and redeeming points is correlated positively at 1% level of significance with a p- value of 0.000. Access to the internet by customers and a system of earning points are 148 also correlated positively at a significance level of 5% with a p-value of 0.036. The same applies to online purchases and a system of earning points. These two sub-attributes correlate at a significance level of 5% with a p-value of 0.042. These sub-attributes move in a parallel direction with earning points and have a positive influence on customer decisions and loyalty. Two sub-attributes, online purchases and customer loyalty, do not correlate with a system of earning points. This means that these sub-attributes move in a non-parallel direction and have no influence on a system of earning points. This suggests that this sub-attribute has no influence on customer decision-making and loyalty. 4.13.2.2 Redeeming points Earning and redeeming points are correlated positively at 1% level of significance with a p-value of 0.000. These sub-attributes move in a parallel direction with earning points and have a positive influence on customer decisions and loyalty. Three sub-attributes – online purchases, customer loyalty, access to the internet and self- service – do not correlate with a system of redeeming points. This means these sub- attributes move in a non-parallel direction and has no influence on a system of redeeming points. This suggests that this sub-attribute has no influence on customer decision- making or loyalty. 4.13.2.3 Customer loyalty In the questionnaire, customers were asked whether they were loyal. With that, a number of sub-attributes related to loyalty were also made part of the loyalty options to determine whether these sub-attributes had an effect on loyalty. However, none of these sub- attributes affected loyalty. None of these five sub-attributes – online purchases, loyal 149 customer, access to the internet, and self-service – correlated with customer loyalty. This means that these sub-attributes move in a non-parallel direction and have no influence on customer loyalty. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 4.13.2.4 Access to internet Access to the internet and a system of earning points are correlated positively at 5% level of significance with a p-value of 0.036. A system for redeeming points is also correlated positively to internet access at 10% significance level with a p-value of 0.064. The same applies to self-service with a p-value of 0.003 that is significant at 1%. These sub- attributes move in a parallel direction with access to the internet and have a positive influence on customers’ decision and customer loyalty. Customer loyalty and online purchases do not correlate with access to the internet. This means that these sub-attributes move in a non-parallel direction and have no influence on credit. This suggests that this sub-attribute has no influence on customer decision- making or loyalty. 4.13.2.5 Self-service Access to the internet correlates positively to self-service at a significance level of 1% with a p-value of 0.003. This sub-attribute moves in a parallel direction with self-service and has a positive influence on customer decisions and loyalty. Customer loyalty, online purchases, a system of earning points and a system of redeeming points are not correlated to use of the internet. This means that these sub- attributes move in a non-parallel direction and have no influence on self-service. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. 150 4.13.2.6 Online purchases A system of earning points and redeeming them is correlated positively to online purchases at a significance level of 5%. Earning points has a p-value of 0.042 and redeeming points has a p-value of 0.022. These sub-attributes move in a parallel direction with online purchases and have a positive influence on customer decisions and loyalty. Customer loyalty, self-service and internet access are not correlated to online purchases. This means that these sub-attributes move in a non-parallel direction and have no influence on online purchases. This suggests that this sub-attribute has no influence on customer decision-making or loyalty. A system where customers earn points for every purchase came out as the most positively correlated sub-attribute, meaning that customers would welcome such a system as a loyalty measure for the agribusiness. Furthermore, majority access to the internet was also in a high-ranking by respondents in all of the five provinces. This gives an indication to agribusinesses to perhaps consider making use of technology to reach and inform customers of specials at the store and or send customer statements via e-mail (if the agribusiness is not yet doing so) instead of the postal service. 151 Table 4.24: Correlation of loyalty sub-attribute Loyalty attribute correlations Earning Redeemin Customer Access to Use of Online points g points loyalty internet internet purchases Earning points Pearson 1 0.989** -0.843* 0.771* 0.564 0.754* correlation Sig. (1-tailed) 0.000 0.018 0.036 0.122 0.042 Redeeming Pearson 0.989** 1 -0.826* 0.692 0.478 0.824* points correlation Sig. (1-tailed) 0.000 .021 0.064 0.169 0.022 Loyal Pearson -0.843* -0.826* 1 -0.892** -0.782* -0.554 customer correlation Sig. (1-tailed) 0.018 0.021 0.008 0.033 0.127 Access Pearson 0.771* 0.692 -0.892** 1 0.932** 0.295 internet correlation Sig. (1-tailed) 0.036 0.064 0.008 0.003 0.285 Use internet Pearson 0.564 0.478 -0.782* 0.932** 1 0.192 correlation Sig. (1-tailed) 0.122 0.169 0.033 0.003 0.358 Purchase Pearson 0.754* 0.824* -0.554 0.295 0.192 1 online correlation Sig. (1-tailed) 0.042 0.022 0.127 0.285 0.358 ***Correlation is significant at the 0.1 level (1-tailed). **Correlation is significant at the 0.01 level (1-tailed). *Correlation is significant at the 0.05 level (1-tailed). 152 4.14 Conclusion There are attributes, which respondents placed in higher rankings that in turn have an effect on customer decision-making. However, the correlations give an indication of whether the sub-attributes have negative or positive influences on each other. A positive correlation means that an action in sub-attribute A will have an effect in sub-attribute B. Within this chapter, there are a few sub-attributes that score higher than 10% (confidence interval), which means they have no significant influence on each other and are therefore independent. 153 Chapter 5 Summary and recommendations 5.1 Introduction As the previous chapter discussed statistical information that resulted from the questionnaires being filled in, a more detailed discussion of the results is required. This chapter discusses in detail the results with respect to the objectives of the study. Recommendations for future studies are also given. 5.2 Summary of the theoretical study The aim of the research was to investigate the influence of marketing strategies on customer loyalty for agricultural retail stores. According to the main problem and sub- problems that came up, the research design and chapter outline were recognised. Chapter Two gave an overview of the related literature regarding marketing strategies. The literature discussed the characteristics of the ideal store in relation to customer loyalty. It was found that agricultural retail stores are slowly losing their significance in their niche market The researcher believed therefore, that investigating marketing strategies for an agricultural retail store would help outline changes that would lead to better customer service from retailers and assist in customer loyalty. 5.3 Empirical study Chapter Four has analysed, interpreted, and presented the results of the study 154 undertaken. The study was quantitative in nature, as 110 questionnaires were used to extract information from respondents from North West, Free State, the Eastern Cape, Mpumalanga, KwaZulu-Natal. From the results, it became obvious that important aspects like having a variety of merchandise, good store location, product-orientated staff and a wider financial product range would help agricultural retail stores in these provinces with regard to changes needed to assure customer loyalty. The reasoning procedures against the argument base that favours the conclusion of the study are prepared with the use of scientific research methods of inductive logic. The conclusion of the study is as follows with regard to the planning and framing; a gathering of primary and secondary data; analysis of data from respondents and interpretation of study results plus report writing. 5.3.1 Discussion of stages followed in carrying out the research: 5.3.1.1 Planning and framing Problems were identified by the researcher, which give rise to the topic. Goals and objectives were set, leading to a formal research proposal being developed. The preliminary reading of articles, books assisted in the formulation of the research structures and the questions asked in the survey. 5.3.1.2 Gathering of primary and secondary data Questionnaires were formulated by the researcher with the help of reading books, articles and the use of the internet. Questionnaires were drawn up and delivered by the researcher to the respondents in the relevant provinces at selected agricultural retail outlets. This was done to acquire the primary data. 155 5.3.1.3 Analysis of data and interpretation of results The nature of the research is quantitative, with the data collected by means of questionnaires filled in by the respondents. The analysis was simplified with the use of tables, bar and pie charts. This gave a clear indication of trends. In line with the problem statement, the findings of the study and the results of the findings are included in the final report. The research objectives are the essential part of the entire study. The accomplishments of the research objectives and sub-objectives are discussed briefly below. The main objective of the study was to investigate the marketing strategies for agricultural retail stores. Chapter two covers the research literature of the study. It provides an understanding of the important characteristics and mechanisms that are related to marketing strategies and customer loyalty. Thus, the first objective was achieved. For the purpose of the study, customer loyalty was analysed, using these sub-attributes: earning points, ● redeeming points, ● customer loyalties, ● access to the internet, ● self-service and ● online purchases. 156 5.4 Determining the marketing strategies for an agricultural retail store This is explained in detail with the correlation of each of the 12 attributes in the chapter. 5.5 Limitations of the study 5.5.1 Distance to travel 5.5.2 People reluctant to complete questionnaire 5.5.3 Staff members not supportive enough 5.5.4 Limited funding 5.5.5 Limited information as similar not done in South Africa 5.5.6 Expensive exercise 5.6 Sample – research area The focus of the study was in five provinces: the Free State, Eastern Cape, Mpumalanga, KwaZulu-Natal and Western Cape. The study took place at agricultural retail stores in the provinces named. The data were collected in 19 towns: Bloemfontein, Brandfort, Jacobsdal and Zastron (Free State), Aliwal North, Burgersdorp, Matatiele, Cradock, Elliot, Graaff-Reinet, Port Elizabeth and Sterkstroom (Eastern Cape), Standerton (Mpumalanga), Cedarville, Paulpietersburg, Utrecht, Vryheid and Volksrust (KwaZulu- Natal) and Murraysburg (Western Cape, which only had one respondent and was not included in the statistical analysis). The study was focused on the South African context as not much research has been done on this topic in this country. Most of the research relevant to the study was done abroad. 157 For the purpose of the study, respondents were selected from the Free State, Eastern Cape, Mpumalanga, KwaZulu-Natal. The stores used in the study are found in these provinces. The results of the study will be beneficial to companies and store managers. This information will assist with marketing strategies that will influence customer loyalty. The views of customers in these areas will enable the researcher to link and compare the results between these geographical areas. 5.7 Stratified sampling Stratified random sampling is used in the study. This technique is applicable in that it allows the researcher to compare the results across different provinces. This technique is also known as convenience sampling. According to Tlapane (2009), stratified sampling is the probability sampling of mutually exclusive and exhaustive subsets. 5.8 Discussion of results 5.8.1 Atmosphere 5.8.1.1 Highest ranking by province The shopping experience was ranked the highest in and Mpumalanga, followed by KwaZulu-Natal, Eastern Cape and the Free State. Mpumalanga also ranked fashionabilityas important. 5.8.1.2 Correlation Most sub-attributes under atmosphere positively correlated with each other that contribute significantly to customer purchase intention and customer loyalty. Sub- attributes, which did not correlate and did not have much influence on shoppers, were music and lights, followed by shopping experience and ventilation systems. 158 These non-correlating sub-attributes are viewed as problems that customers face when visiting agricultural retail outlets. Some of the stores neither play music nor use suitable lightning. The same applies to ventilation systems, which respondents felt rendered their shopping experience unsatisfactory. 5.8.2 Convenience 5.8.2.1 Highest ranking by province Respondents in the Eastern Cape, Free State, and KwaZulu-Natal rated convenient store business hours highest. Respondents in Mpumalanga also ranked the variety of merchandise highly. 5.8.2.2 Correlation Most of the sub-attributes under convenience were rated positively, which means they contribute significantly towards the customer’s intention of purchasing, as well as customer loyalty. Sub-attributes that did not correlate and had little influence were the distance to the preferred store, the business hours, the variety of merchandise, amount of walking required while in the store. These are the most non-correlating sub-attributes. These non-correlating sub-attributes are viewed as problems that customers face when visiting these agricultural retail outlets. With regard to the distance to the preferred store, customers stated that stores nearby were preferable to stores further away from their farm or home. The location of a store is very important. Unfavourable business hours are the next item. Customers want longer trading hours. A wider variety of merchandise is also a preference, as customers want more items from a given store. 159 5.8.3 Merchandise 5.8.3.1 Highest ranking by province Respondents the Eastern Cape and Mpumalanga ranked products that suit their type of farming as very important and in the highest ranking category. The variety of merchandise categories were ranked in the second-highest category by respondents in KwaZulu-Natal. Imported merchandise was placed in this high-ranking category by respondents in the Free State. 5.8.3.2 Correlation Most of the sub-attributes under merchandise work positively with each other, contributing significantly to customers’ purchase intentions and loyalty. A sub-attribute that did not correlate and had little influence was the availability of imported or branded merchandise. These non-correlating sub-attributes are seen as challenges that customers face when visiting agricultural retail outlets. Customers would prefer to have imported merchandise to buy, and such merchandise should be available. The same applies to branded merchandise. 5.8.4 Structural 5.8.4.1 Highest ranking by province Respondents in the Free State and Eastern Cape placed the point of sale in the highest ranking category. There is a pressing need for tills in the store, and respondents in KwaZulu-Natal e ranked the availability of working tills as being most important. Respondents in Mpumalanga ranked favourable payment options as very important and in the top category. 160 5.8.4.2 Correlation Most of the sub-attributes under structural worked positively with each other, contributing significantly to the customer’s intention of buying and his/her loyalty to the store. Sub- attributes that did not correlate and lacked significance were location, connection to the road network, accessibility, the availability of enough tills and adequate parking. These non-correlating sub-attributes are seen as problems customers encounter when they visit agricultural retail outlets. The store’s location showed up as a major problem for customers. Connection to the road network for other stores is also a problem for some customers, who access the store with the use of public transport. Next, is accessibility in terms of entrance and exit doors. Customers also brought up the problem of insufficient parking. Customers also mentioned points of sale and the presence of sufficient tills. 5.8.5 Institutional 5.8.5.1 Highest ranking by province Respondents in the Eastern Cape, KwaZulu-Natal and Mpumalanga ranked luxury versus convenience (do customers shop at stores that cater for luxury or for convenience – customers rated this as equally important when shopping) as very important and in the top category. The appearance of sales staff is very important for customers and was ranked in this category by respondents in the Free State. 5.8.5.2 Correlation Most of the sub-attributes under institutional relate positively to each other, contributing significantly to the customer’s purchase intentions and loyalty. Sub-attributes that did not 161 correlate and had little influence were luxury versus convenience, the appearance of sales staff and lastly building relationships with customers. These non-correlating sub-attributes are seen as problems customers face when visiting agricultural retail outlets. Customers rated the need to have both luxury and convenience items in the stores highly. Luxury versus convenience (do customers shop at stores that cater for luxury or convenience? – Customers rated these as equally important when shopping). The appearance of the sales staff was also a problem where customers were unable to tell whether the staff was working there or not. This problem could be caused by either the lack of a distinguishable uniform or by staff not interacting with customers. Customers felt there was a great need for managers and staff to build relationships with customers, something that gave customers a sense of belonging. 5.8.6 Promotions 5.8.6.1 Highest rankings by province Respondents in KwaZulu-Natal agreed that the credibility of advertising by a store or business was very important and placed it in the highest ranking category. In-store displays were ranked in this category by respondents in the Mpumalanga. Respondents in the Free State and Western Cape placed advertising methods in the highest ranking category. The availability of stock on sale is very important for customers and was ranked second by respondents in the Eastern Cape. Eastern Cape respondents also felt that marked-down stock was important and placed it in the highest ranking category. 5.8.6.2 Correlation Most of the sub-attributes under promotions interact positively with each other, 162 contributing significantly to the customer’s purchase intention and loyalty. Sub-attributes that did not correlate and had little influence were the credibility of adverts, the availability of brochures in the mail, the availability of marked-down items and stock on sale. These non-correlating sub-attributes are regarded as problems that customers face when visiting agricultural retail outlets. Customers questioned the credibility of adverts – this could be due to stores being out of stock. The availability of brochures in the mail also came up as a problem, as some customers did not receive them. Most customers complained that it was rare for them to find marked-down items at these stores. 5.8.7 Service 5.8.7.1 Highest ranking by province Respondents in the Eastern Cape, Free State and KwaZulu-Natal placed the need for stores to have enough sales staff in the highest ranking category. The inter-store transfer was ranked in this category by respondents in Mpumalanga. The availability of a courier service was placed in the highest ranking category by respondents in the Eastern Cape. 5.8.7.2 Correlation Most of the sub-attributes under service interact positively with each other, contributing significantly to customers’ purchase intentions and loyalty. Sub-attributes that did not correlate and had little influence were courier service, inter-store transfers and the perceived absence of sales personnel. These non-correlating sub-attributes are seen as problems customers face when visiting agricultural retail outlets. There is a great need for agricultural retail stores to provide 163 courier service for their customers. Inter-store transfers are also becoming a need for customers visiting these stores. A lack of sales staff is also a problem customers encounter when visiting these stores. Customers questioned the credibility of adverts – this could be due to stores being out of stock. The availability of brochures in the mail also was a problem for some customers who did not receive them. Most customers complained that it was rare for them to find marked-down items at these stores. 5.8.8 Sales 5.8.8.1 Highest ranking by province Respondents in the Free State, Eastern Cape, KwaZulu-Natal and Mpumalanga placed helpfulness on the part of sales staff as very important and in the highest ranking category. Eastern Cape respondents also placed these factors in the highest ranking category: representation of both genders, friendliness of staff, staff presentability, and the product knowledge or orientation of staff members. 5.8.8.2 Correlation All the sub-attributes under sales correlate positively with each other, contributing significantly to customers’ purchase intentions and loyalty. There were no sub-attributes that did not correlate, meaning that all the sub-attributes influenced each other. 5.8.9 Credit 5.8.9.1 Highest ranking by province Respondents in the Free State and KwaZulu-Natal, placed ease of obtaining credit in the highest ranking category. KwaZulu-Natal respondents ranked the availability of a diverse financial product range in this category. The availability of credit does influence 164 customers’ choice of store, and respondents in Mpumalanga and KwaZulu-Natal placed this in the highest ranking category. In the Eastern Cape, respondents placed a variety of credit options in this highest ranking category. 5.8.9.2 Correlation Most of the sub-attributes under credit interact positively with each other, providing significant motivation for customers’ purchase intentions and loyalty. Sub-attributes that did not correlate and had little influence were credit options, the ease of obtaining credit and credit influence. These non-correlating sub-attributes are seen as problems customers face when visiting agricultural retail outlets. There is a great need for agricultural retail to make it easier for customers to obtain credit (bearing in mind that not all customers will be able to qualify for credit). Some customers are not entirely happy with the current credit options of these stores, and managers need to investigate this. All these problems would have an influence on a customer’s decision to support the store. 5.8.10 Assistance 5.8.10.1 Highest ranking by province Respondents in the Free State and Mpumalanga placed the need for a disability car parking area in the highest ranking category. Respondents in KwaZulu-Natal and Mpumalanga ranked moving purchased goods from the store to the car at minimal charge or none at all. Having a visible security in the store or in the parking area was ranked in this category by respondents in the Eastern Cape. 165 5.8.10.2 Correlation Most of the sub-attributes under assistance interact positively with each other, contributing significantly to customers’ purchase intentions and loyalty. Sub-attributes that did not correlate and did not have much influence were special assistance to customers with special needs, special trolleys and moving goods to the parking area. These non-correlating sub-attributes are regarded as challenges customers face when visiting agricultural retail outlets. There is a great need for agricultural retail to start catering for people with special needs. There is also a great need for special trolleys and for assistance for people with special needs when shopping. Assistance in carrying purchased items to the parking area or for free is a definite need. All these problems could affect a customer’s decision to support the store. 5.8.11 Administration 5.8.11.1 Highest ranking by province Receiving invoices on time is very important for customers as well as for the store/business and respondents in the Free State and Eastern Cape placed invoices in the highest ranking category. Understanding one’s account is important for both the business and customer, and respondents in KwaZulu-Natal Cape ranked understanding one’s account in this highest category. Respondents in Mpumalanga ranked accounts and letters in this category. This is followed by Eastern Cape respondents who ranked conditions of one’s account in the same category. 5.8.11.2 Correlation All the sub-attributes under administration correlate positively with each other, 166 contributing significantly to customers’ purchase intentions and loyalty. There were no sub-attributes that did not correlate, which means that all the sub-attributes affect each other. 5.8.12 Loyalty 5.8.12.1 Highest ranking by province Respondents in KwaZulu-Natal placed access to internet in the highest ranking category. Free State and Mpumalanga respondents ranked themselves as being loyal customers, so rating customer loyalty is in the highest ranking category. Eastern Cape respondents placed self-service in the highest ranking category. Eastern Cape respondents ranked the option of online purchases in this category. 5.8.12.2 Correlation Most of the sub-attributes under loyalty correlate positively with each other, contributing significantly to customer purchase intentions and loyalty. Sub-attributes that did not correlate and had little influence were the system of earning points, self-service, purchasing goods online and customer loyalty. These non-correlating sub-attributes are seen as problems that customers face when visiting agricultural retail outlets. There is a great need for agricultural retail stores to start using the internet in a bid to move with the times. Customers encounter problems with purchasing goods online because stores do not have such a system in place. The same goes for a loyalty card system of buying goods and earning points from the purchase. Some customers suggested online self-service, which would be convenient for them. All these problems would affect the customer’s decision to support the store. 167 5.9 Recommendations What is clear from these findings is that 5.9.1 The store location is vital. Retailers need to understand where and how the store operates. 5.9.2 Also important is giving customers first-class service, 5.9.3 a variety of merchandise, 5.9.4 online catalogues and, 5.9.5 a decent store environment, not forgetting 5.9.6 a positive store image. 5.9.7 Retailers need to sell goods and services that are relevant to their target market, which will also satisfy the needs of the customer. The strategies that retailers use must cover these customer needs. 5.9.8 With regard to purchasing behaviour, customers assess their own attitudes, beliefs, and behaviour. This is however, weighed against the opinion or advice of others (friends, family and others). Retailers need to realise that the actual purchase counts as much as the first impression. 5.9.9 Staff in the store needs to be product-orientated, friendly, helpful and efficient at all times. 5.9.10 It was also found that respondents complained about out of stock situations. 168 This cannot completely be eliminated by retailers, but it can usually be avoided by doing a weekly spot-check and ordering stock depending on the demand for it. 5.9.11 Game farming is becoming more and more attractive to farmers, and respondents specialising in game raised concerns that their needs were not being catered for by their local store. 5.9.12 Stores should also consider keeping general stock, for instance, bicycle parts, as some respondents requested them. 5.9.13 Customers also felt that agricultural retail stores should invest in online catalogues. This would also help stores with regard to advertising, as customers are now becoming more technologically minded. 5.9.14 Additionally, sending customers “special alerts”, climate alerts regarding possible hail, rain, cold storms, fires and floods and notification of marked-down items or new arrivals will also assist in gaining customer loyalty. Keeping customers informed will work to the benefit of the store. 5.9.15 Build lasting relationships through innovative memberships and social media. 5.10 Conclusion The agricultural retail stores are competing not only among themselves but also with big hyper- and superstores. This competition, however, centres on groceries and farming equipment. Customers are moving towards the “one-stop-shop” concept where they can purchase all their goods in one place. Agricultural stores can use this to their advantage, as the stores used in the questionnaire all provide customers with fuel facilities. Stores do stock groceries, which is a step in the right direction. Maybe over time they could 169 consider widening the product range to give the customer more options. Establishing new business opportunities like online catalogues and sending customers and members special alerts and notifications as mentioned above, because customers are now becoming more technologically minded are vital. Keeping customers informed will work to the benefit of the store. Building lasting relationships through innovative memberships and social media could increase the profitability of the agricultural retail store. 5.11 Recommendations for further research It is recommended that further research been done of a qualitative nature that will explore: ● More about the quality of service in depth, as there is always room for improvement. ● New business opportunities for agricultural retail stores regarding “Sports” to tap into a broader sales base and boosting domestic competition. ● Fuel is an essential commodity. Agricultural retailers could look into providing fuel stations open 24/7, linked to the “one-stop-shop” concept. 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