The Influence of Micro Environment Factors on Marketing Mix Strategy: a Case of Retail Businesses Within Shopping Malls in Nairobi

THE INFLUENCE OF MICRO ENVIRONMENT FACTORS ON MARKETING MIX STRATEGY: A CASE OF RETAIL BUSINESSES WITHIN SHOPPING MALLS IN NAIROBI

MAUREEN WANJIKU GICHIRI

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

SUMMER 2020 THE INFLUENCE OF MICRO ENVIRONMENT FACTORS ON MARKETING MIX STRATEGY: A CASE OF RETAIL BUSINESSES WITHIN SHOPPING MALLS IN NAIROBI

MAUREEN WANJIKU GICHIRI

A Research Project Submitted to the Chandaria School of Business in Partial Fulfilment of the Requirement for the Degree of Masters in Management and Organizational Development (MOD)

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

SUMMER 2020

STUDENT’S DECLARATION

I, the undersigned, declare that this is my original work and has not been submitted to any other college, institution or university other than the United States International University Africa for academic credit.

Signed: ______Date: ______

Maureen Wanjiku Gichiri (659170)

This project has been presented for examination with my approval as the appointed supervisor.

Signed: ______Date: ______Dr. Peter Kiriri

Signed: ______Date: ______Dean, Chandaria School of Business

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Maureen 2020©

ABSTRACT Companies develop and execute marketing strategies to understand the customer and competition and devise ways of persuading the customer to purchase and consume their products and services. In the face of dynamic changes in their micro and macro environments, this has become a complex and difficult exercise. The purpose of the study was to investigate the influence of micro environment factors on marketing mix strategy among retail business in shopping malls in Nairobi. The objectives were to investigate the influence of customers on marketing mix strategy among retail business in shopping malls in Nairobi; to establish the influence of competition on marketing mix strategy among retail business in shopping malls in Nairobi; and to determine the influence of distribution channels on marketing mix strategy among retail business in shopping malls in Nairobi. A descriptive research design was used in the study. The population encompassed retailers operating in Village Market Mall. There were 239 retailers operating in the mall. Simple random sampling was used to generate a sample size of 150 retailers for the study. Data was collected using a validated and standardized questionnaire. The questionnaire was self- administered to the respondents at their place of work. Collected data was cleaned and analyzed using SPSS 23 for descriptive and inferential statistics. The descriptive measures included frequencies, percentages, means and standard deviations. To establish the influence of micro environment factors on market mix strategy, the study used multiple regressions. The results were presented using charts, graphs, and tables, accompanied by narrative descriptions. Findings on the influence of customers on marketing mix strategy show that with regard to customer behavior, customers were concentrated around where the outlet was operating. Customers were also attracted to the stores due to the outlet’s design aesthetics and display. The store was situated in a neighborhood where customers had disposable income that could allow them to access products and services at the prices offered at the mall. Findings on customer preferences indicated that customers made decisions based on the prices offered, and that the preference of one retailer to the other was dependent on the prices of the products. Customers also preferred the malls due to high perception of product quality and benefits of effective product promotions, since they were mainly drawn to recognizable brands. Customer satisfaction levels were comparatively high and driven by product quality, staff responsiveness, and customer loyalty. Multiple regressions demonstrated that all the dimensions of customers, notably, customer satisfaction, customer preferences, and customer satisfaction had a positive and statistically significant influence on marketing mix strategy. Findings on the influence of competitive forces on marketing mix strategy show that in terms of the threat of entry, retailers moderately agreed that goods they sold were from patented innovations and that competitors enjoyed economies of scale. A significant amount of capital was also needed to enter the market, and government regulation and levels of profitability influenced competition among retailers. On competitive rivalry, retailers noted that there were many small competitors in the mall, rather than big competitors. The prices were comparable with retailers dealing in similar products. Most products had substitutes drawn from the same group of suppliers. The retailers contended that the price and performance attributes were competitive. However, the competitiveness of the retailers was greatly dependent on the competitiveness of the mall. As a result, even though the study reported a positive relationship between the threat of entry and competitive rivalry, these did not have a statistically significant

v influence on marketing strategy. The abundance of substitutes had a negative but not statistically significant influence on the retail outlet’s marketing strategy. Findings on the influence of distribution on marketing strategy decisions indicate that direct distribution channels were characterized by delivering products faster to customers, possessing considerable control over product marketing and selling, building direct relationships with customers and accessing goods only in fixed positions. The level of agreement with these characteristics was slightly above average. Indirect distribution was characterized by distributing products through agents, building relationships primarily with distributors, leveraging existing brand recognition, and interacting more with end-users. Findings indicated comparatively low levels of agreement when compared to direct distribution. Extensive distribution, characterized by characteristics from the two channel strategies, reported moderate level of agreement among respondents. Overall, multiple regression demonstrated that direct distribution was the main predictor of marketing mix strategy, as opposed to indirect or extensive distribution. The study concludes that customer related micro-environment factors have a positive and statistically significant influence on market mix strategy among retail outlets in Kenya. Multiple regressions showed that customer behavior, customer preferences, and customer satisfaction had a statistically significant effect on marketing mix strategy. Competition related micro-environment factors have a positive but not significant effect on marketing strategy among retail outlets in Kenya. Competition was conceptualized based on Michael Porter’s five forces theory. Multiple regressions revealed a positive but not significant relationship between threats of entry and the choice of market mix strategies, a positive but not statistically significant relationship between competitive rivalry and marketing mix strategies, and a negative non-significant effect on the choice of marketing mix strategies. Distribution channels, as micro-environment factors, have a positive and statistically significant influence on the marketing mix strategy of retail outlets in Kenya. The regression results showed that direct distribution had a positive and statistically significant effect on marketing mix strategies. Indirect distribution had a positive effect on marketing mix strategies, but the effect was not statistically significant, while there was a negative relationship between intensive distribution and marketing mix strategies. The study recommends that the retail outlets should upgrade store designs and product display formats, increase the availability of store information online to aid information searches, and align operational hours according to customers shopping habits such as time of the day, weather, or season. The retail outlets should establish competitive prices, increase the quality of products offered, increase promotions, and stock highly established brands. Finally, with regard to customer satisfaction, the firm’s marketing strategies should focus on improving the quality of service, staff responsiveness, and product quality. The retail outlets should innovate, exploit economies of scale, and build capital reserves in anticipation of changing market conditions and to respond to market opportunities before other competitors. Retail outlets should improve the efficiency of product delivery to customers, investing additional resources in marketing of stores and products.

ACKNOWLEDGEMENT

I am thankful to my employer, fellow classmates and my family.

Special thanks to my supervisor Dr. Kiriri.

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DEDICATION

I dedicate this project to my family and friends. A special feeling of gratitude to my parents Joseph and Cecilia Gichiri whose words of encouragement and push for tenacity ring in my ears.

Special thanks to my siblings Martin Kiruthi, Maryann Wanjiru and my cousin Dennis Njiiri who have supported me throughout the process.

I also dedicate this work to my MOD 2019 classmates for being the best cheerleaders during the course of the entire Masters program.

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TABLE OF CONTENTS

STUDENT’S DECLARATION ...... iii COPYRIGHT ...... iv ABSTRACT ...... v ACKNOWLEDGEMENT ...... vii DEDICATION ...... viii LIST OF TABLES ...... xi LIST OF FIGURES ...... xii CHAPTER ONE ...... 1 1.0. INTRODUCTION ...... 1 1.1. Background of the Problem ...... 1 1.2. Statement of the Problem ...... 6 1.3. General Objective ...... 8 1.4. Specific Objectives ...... 8 1.5. Significance of the Study ...... 9 1.6. Scope of the Study ...... 10 1.7. Definition of Terms ...... 10 1.8. Chapter Summary ...... 11 CHAPTER TWO ...... 12 2.0. LITERATURE REVIEW ...... 12 2.1. Introduction ...... 12 2.2. Customers and Marketing Mix Strategy ...... 12 2.3. Competition and Marketing Mix Strategy ...... 19 2.4. Distribution Channels and Marketing Mix Strategy ...... 25 2.5. Chapter Summary ...... 30 CHAPTER THREE...... 32 3.0. RESEARCH METHODOLOGY ...... 32 3.1. Introduction ...... 32 3.2. Research Design ...... 32 3.3. Population and Sampling Design ...... 33 3.4. Data Collection Methods ...... 35 3.5. Research Procedures ...... 35

3.6. Data Analysis Methods ...... 37 3.7. Chapter Summary ...... 38 CHAPTER FOUR ...... 39 4.0. RESULTS AND FINDINGS ...... 39 4.1. Introduction ...... 39 4.2. Demographic Information ...... 39 4.4. The Influence of Competition on Marketing Mix Strategy ...... 47 4.5. The Influence of Distribution Channels on Marketing Mix Strategy ...... 51 4.6. Chapter Summary ...... 56 CHAPTER FIVE ...... 57 5.0. DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ...... 57 5.1. Introduction ...... 57 5.2. Summary...... 57 5.3. Discussions ...... 59 5.4. Conclusion ...... 65 5.5. Recommendations ...... 66 REFERENCES ...... 68 APPENDICES ...... 74 APPENDIX I: INTRODUCTION LETTER ...... 74 APPENDIX 2: QUESTIONNAIRE ...... 75 APPENDIX 3: LIST OF RETAIL OUTLETS ...... 79 APPENDIX 4: IRB APPROVAL ...... 86 APPENDIX 5: NACOSTI PERMISSION ...... 87 APPENDIX 6: NACOSTI RESEARCH LICENSE ...... 88

LIST OF TABLES

Table 3.1: Reliability Coefficients……………………………………………………………36 Table 4.1: Customer Behavior……………………………………………………………….42 Table 4.2: Customer Preferences…………………………………………………………….44 Table 4.3: Customer Satisfaction…………………………………………………………….45 Table 4.4: Model Summary for Customer…………………………………………………...45 Table 4.5: ANOVA for Customer Model……………………………………………………46 Table 4.6: Regression Coefficients for Customer Model……………………………………46 Table 4.7: Threat of Entry……………………………………………………………………47 Table 4.8: Competitive Rivalry……………………………………………………………....48 Table 4.9: Substitutes………………………………………………………………………...49 Table 4.10: Model Summary for Competition Model……………………………………….50 Table 4.11: ANOVA for the Competition Model……………………………………………50 Table 4.12: Regression Coefficients for the Competition Model……………………………51 Table 4.13: Direct Distribution………………………………………………………………52 Table 4.14: Indirect Distribution…………………………………………………………….53 Table 4.15: Intensive Distribution…………………………………………………………...54 Table 4.16: Mode Summary for the Distribution Channel Model……………………………55 Table 4.17: ANOVA for Distribution Channel Model………………………………………55 Table 4.18: Regression Coefficients for Distribution Channel Model………………………56

LIST OF FIGURES

Figure 4.1: Age of Respondents………………………………………………………………40 Figure 4.2: Gender of Respondents………………………………………………………….40 Figure 4.3: Level of Education……………………………………………………………….41

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CHAPTER ONE

1.0. INTRODUCTION

1.1.Background of the Problem Companies are increasingly operating in a dynamic and competitive environment, which demand that they must pay attention not only to the needs and desires of consumers and their ever-rising demands and expectations, but also understand the competition. In such an environment, developing and executing an effective marketing strategy is key to profitability and growth (Egboro, 2015). Companies employ marketing strategies to understand the customer and competition and devise ways of persuading the customer to purchase and consume their products and services (Maqin & Hendri, 2017).

Enterprises are influenced by dynamic changes in their micro and macro environments (Yam, 2016). Macro environment factors consist of the economic environment, the political environment, the socio-cultural environment and the technological environment. These factors determine variables such as income, living standards, interest rates, savings, and borrowing, which affect an individual’s level of participation in the market. On the other hand, micro environment factors consist of the people directly involved in the market and linked to companies in ways that affect their capability to serve the market. The micro environment includes customers, competitors, suppliers, distributors and other marketing intermediaries, as well as the public itself (Yam, 2016).

Customers is the main component of the micro environment since the success of any good or service in the market. Customers can be examined in terms of customer behavior, customer experiences, and customer satisfaction (Datta, 2016). Customers are the people who buy the product or service and enable a company to achieve its profitability objectives (Maqin & Hendri, 2017). A customer refers to a person or entity that buys a product or service from a seller (Nugroho & Irena, 2017). Studies such as Nugroho and Irena (2017) found out that customer behavior is related to marketing mix and contribute to purchase intention. In the study, customer behavior is captured as the cultural, social and personal psychological indicators, and marketing mix is measured in terms of the marketing mix components: product, price, place, and promotion. Arbaina and Suresh (2018) noted that marketing mix strategy can

1 also incorporate price, interior, promotional tool, location, range of products, experiential zone, quality and availability dimensions. Using quantitative data analysis, researchers have established a significant link between marketing strategies and consumer behavior (Mehrizi & Zahedi, 2013).

Customer preferences are associated with marketing strategies. Customers with a high level of preference have a lower likelihood of switching brands because high levels of satisfaction build loyalty (Solaiman & Masri, 2017). Consumer preferences can be determined by consumers’ education level (Getzner & Grabner-Krauter, 2015) and also moderated by factors such as market turbulence, technology, general economy, information of customer needs, intelligence responsiveness, competition and management competency (Egboro, 2015). Miriti (2016) established that consumer preferences have a positive and significant effect on marketing mix strategies: product, price, place, and promotion, on consumer preference. On the contrary, Sulaiman and Masri (2017) indicated that three components of marketing mix strategy, notably; product, place, and promotion has a significant effect on consumer preference, while the fourth component of marketing mix: price, did not have a significant effect on customer preference for supplements and cosmetics in Malaysia. These studies show that the relationship between consumer preferences and marketing mix strategies may differ according to industry or country context.

Customer satisfaction is central to company performance. Consumers are happy when they fulfil their desires. Shaw (2012) notes that consumer satisfaction can be achieved through effective marketing strategies. The level of consumer satisfaction influences not only the resources allocated to marketing but also the objectives and activities included in the marketing strategy (Ebitu, 2014). According to Agyapong (2017), satisfied customers can spread word- of-mouth communication about the company. Therefore, companies should identify, anticipate and satisfy customer requirements (Azizi, Bagherzadeh, & Mombeini, 2015). There is a significant relationship between the marketing mix and customer satisfaction and loyalty; however, caution should be exercised in generalization of results (Wahab, Hasan, & Maon, 2016).

The second microenvironment factor under investigation is competition. Competition is inevitable in every business environment. At the basic level, competition refers to an attempt

2 at winning something. Companies do this by attempting to achieve a higher level of success comparative to other players (Kaunyangi, 2014). According to Michael Porter’s five forces theory, the competitive forces are: threat of new entrants, competitive rivalry, threat of substitutes, bargaining power of buyers and bargaining power of suppliers (Bukirwa & Kisingu, 2017). The threat of new entrants has been found to influence how companies develop their marketing strategies (Lawrence, 2011). A firm can threaten the market share of existing firms if they have substantial resources to show up production and marketing, adopt pricing strategies that can force bigger competitors to reduce their prices, and execute strategies that allow it to tap into the market share of competitors (Chiteli, 2013).

Competitive rivalry depends on several factors such as differentiation between the products in the market, brand loyalty by the buyers and price comparisons by the media. Companies will apply the necessary strategies so as to retain their share of the market. A highly competitive business environment results in competitiveness in prices, profitability and performance of firms in the industry (Kaunyangi, 2014). The main strategies are low cost and differentiation (Lawrence, 2011). There is a positive and significant relationship between industry competition and corporate strategy (Ogaga, 2017). An industry’s competitive intensity has a positive impact on marketing capability (Ocass & Weerawardena, 2017). Takata (2016) found out that marketing capabilities is the strongest driver of business performance, followed by competitive rivalry and the power of suppliers (Takata, 2016).

Substitutes influence how a brand performs in the market (Moriasi, Asienyo, & Okao, 2014). A company’s marketing function entails the identification of substitutes in the market (Mwaluma, 2014). Firms must invest in marketing strategies to identify the areas of growth, in terms of possible but related products and services, or making a foray into an industry that is not the traditional focus of the firm (Azzam, 2018). Introduction of new products or modification of existing products are important in creating competitive advantage (Camison & Lopez, 2010). Innovation allows firms to design substitutes that appeal to customers having a special sensitivity to a particular attribute in the product (Karuoya, 2014). Studies have showed that substitution influences marketing strategies such as pricing (Okelue, Uchenna, Obinne & Nonye, 2012).

Distribution is the third dimension of microenvironment. Companies must consider the channels necessary for delivering goods and services to the target markets. A distribution channel is the route along which goods and services travel from the manufacturer/producer, through market intermediaries, to the final user, the consumer (Segetlija, Mesaric, & Dujak, 2015). A distribution system is the network of organizations that link producer to customer (Karanja, Muathe, & Kuria, 2015). A distribution channel can also be understood as an inter- organizational network or a pathway that provides product flows from the producers to the consumers. The distribution channel includes various intermediaries such as retailers and wholesalers. The primary objective of a distributional channel is to bridge the gap between the place of production and the place of consumption (Singh, 2016). Distribution can either be direct, indirect, or intensive.

Direct distribution refers to a situation where the producer sells directly to the consumer without passing the goods through intermediaries (Mwanza & Ingari, 2015). Direct distribution implies that a company has made a marketing decision on how it wants to connect with the customer. Koster (2018) investigated the direct distribution strategies for online retailers, and found out that the choice of distribution strategy was mainly influenced by the complexity of the product assortment (Koster, 2015). Karanja et al., (2017) demonstrated that distribution strategy had a significant influence on intermediary performance.

Indirect distribution is where there are intermediaries such as retailers and wholesalers that obtain products from the producer and sell these to the consumers (Mwanza & Ingari, 2015). It is used by manufacturers of products such as TVs, scooters, refrigerators, washing machines, cars, industrial machinery and equipment, among others. Kafaerpour (2015) showed that the distribution strategy of Samsung Company in Iran influenced their choice of promotional strategies. Aleksandra, Nada, and Marija (2107) reported that the efficiency of the distribution channel has a significant effect on performance. Mwanza and Ingari (2015) established that distribution strategies create competitive advantage, with direct distribution having greater impact than indirect and intensive distribution strategies.

Intensive distribution is where a firm uses all available outlets to distribute a product. Examples of products that use this strategy are bread, sweets, newspapers, chewing gums, soda, among others are distributed to as many available outlets as possible. Intensive distribution informs

4 marketing since the objective is to sell products to as many outlets and consumers as possible. Aila, Ondiek, Mise, and Odera (2015) investigated the impact of channel strategy on customer value of soft drink companies in Kenya and found a strong correlation between stock availability and sales. Marmullaku and Ahmeti (2015) showed that distribution channels have a significant effect on marketing strategies: pricing, channel structure, and advertising strategies.

Marketing strategy can be defined as a set of activities or processes for creating, communicating, delivering and exchanging goods and services in the market. The purpose of marketing strategy is to enhance purchase intention, and subsequently improve a company’s sales volumes which can aid in achieving profit objectives in the long term (Nugroho & Irena, 2017). Marketing is done to increase awareness on products and services produced and delivered in the market (American Marketing Association, 2013).

The marketing mix strategy incorporates four elements, the 4Ps, also known as the marketing mix. These four controllable variables: product, price, place, and promotion, are manipulated by a company in the creation of marketing strategies (Nugroho & Irena, 2017). A product is the tangible good or intangible service that fulfils customer’s needs and expectations. The price is the value of product offering, and pricing decisions influence supply and demand, product positioning and profit margins. Promotion refers to the dissemination of product information to customers, and these include activities such as advertising, public relations, and social media marketing activities, among others. Finally, the place refers to the ideal locations where customers can get the right product at the right place. In the digital world, the place also refers to online platforms where interaction between the customer and the product occurs (Thieu, Hieu, Binh, Huyen, & Hoang, 2017).

Shopping malls offer a variety of tenant mix, service offerings, and continually run promotional and advertising campaigns. Thus, shopping malls aspire to provide the totality of functional and emotional qualities to customers (Kiriri, 1, 2019a). They can be understood as an aggregation of retail and other commercial establishments that are owned and managed as a single property (Kotler & Armstrong, 2018). Shopping malls can also be defined as closed, climate-controlled, lighted shopping centers having retail stored on both sides of an enclosed walkways (Levy, Weitz, & Pandit, 2014).

At the core of a shopping mall is an anchor tenant, who is expected to attract both human and vehicular traffic into the establishment. It is the traffic to the anchor tenant that is expected to spill over and benefit non-anchor tenants (Kiriri, 2019a). A shopping mall is designed to attract the attention of customers to product or service offerings, while also offering a convenient access to an expanded mix of retailers in a safe, satisfying, and leisurely experience. In addition to retail centers, shopping malls also provide restrooms, parking, playgrounds and other amenities to enhance the shopping experience (Kushwaha, Ubeja, & Chatterjee, 2017). Studies have showed that the performance of retailers in a shopping mall is significantly influenced by the performance of the anchor tenant. Poor performance by the anchor tenant leads to reduced business activities in the mall, reduced occupancy rates, low rental income, and general decline as a result of reduced traffic (Kiriri, 2019a).

The origin of shopping malls can be traced to the United States; however, the phenomenon has spread to other parts of the world. According to Kiriri (2019b) there have been a massive growth of shopping malls in Africa over the last decade. An analysis by Sagaci Research (2018) revealed that from 2011 to 2018, the number of malls increased from 225 to 581. South Africa has the highest number of malls in Africa, followed by Egypt and Kenya. It was projected that by 2020, there number of shopping malls in Kenya will grow to 73, making the country the second largest provider of shopping center space in Sub-Saharan Africa (Sagaci Research, 2018). The shopping malls are concentrated in Nairobi, responsible for 60% of gross leasable area (GLA), followed by Mombasa (10%) and Kisumu (7.4%) (Kiriri, 2019b).

1.2.Statement of the Problem One of the key elements of a company’s success is developing the appropriate marketing mix strategy. However, the marketing mix strategy is affected my micro environment factors; however, companies continue to face challenges. First, companies cannot implement a one- size-fits all market strategy as a result of continued differentiation in local markets. This is due to the changing dynamics in the macro and micro environments. Secondly, the lower costs due to competition and wider product offerings in the market have made it very difficult for companies to capture and retain the attention of consumers (Yam, 2016).

Shopping malls provide a unique challenge for businesses. While shopping malls offer a variety of tenant mix and service offerings, they are also placed where customers have a high

6 bargaining power. This is because the greater diversity of alternatives increases competition among retailers in the malls, an aspect which can cause price sensitivity. In the absence of increased customer demand, buyer bargaining power can push down profits. Further, according to Kiriri (2019a) the performance of retailers in the shopping malls is related to the performance of the anchor tenant. Poor performance of the anchor tenant as a result of reduced traffic spills over to other retailers in the shopping mall.

While the understanding the competitive environment is important to strategic marketing, Ocass and Weerawardena (2017) reiterates that there has been limited research in this area and that research has failed to examine how the competitive environment affects the greater understanding about its customers and competitors and how such knowledge can be used to serve customers better. Further, few studies that have looked at micro environmental factors. However, even for these studies, very few have studied the relationship between micro environment factors and marketing mix strategy.

With regard to customers, Mehrizi and Zehedi (2013) examined how customer behavior is related to marketing strategies in the household appliances market in Japan; Nugroho and Irene (2017) focused on how consumer characteristics relate to marketing mix and purchase intention in Indonesia; Arbaina and Suresh (2018) studied the link between consumer behavior and purchase intention in Bangalore India; and Getzner and Grabner-Krauter (2015) looked at the relationship between consumer preferences and marketing strategies in Austria. In Kenya, Miriti (2016) examined the link between marketing strategy and consumer preference. In general, there are few studies on customers, as a micro environment factor, and how it relates to marketing mix strategy.

With regard to competition, a majority of studies drew the conceptualization of competition from Michael Porter’s five competitive forces: threat of entry, threat of substitutes, power of buyers, power of suppliers, and rivalry between firms. While there are studies on competition, most of these are focused on how competition is related to business performance as opposed to marketing strategy. Takata (2016) studied how competitive forces and marketing capabilities influenced business performance, while Ocass and Weerawardena (2017) looked at how competitive intensity affected marketing capabilities in a firm. In Kenya, Ogaga (2017) studied the link between competitive forces and corporate strategy, Bukirwa and Kisingu

(2017) investigated the effect of competitive strategies on financial performance of hotels, and Kaunyangi (2014) explored how competition was affecting the performance of telecommunication firms.

With regard to distribution channel, Aila, Ondiek, Mise, and Odera (2015) tested whether distribution factors such as order cycle time and stock availability had an effect on customer value, measured as sales volumes and found a positive correlation. Kafaerpour (2015) studied the influence of the distribution strategy on sale promotion at Samsung Company in Iran. Mwanza and Ingari (2015) examined the role of distribution as a source of competitive advantage in the FMCG market in Kenya. Marmullaku and Ahmeti (2015) studied factors affecting three marketing strategies: pricing, market structure and advertising. These factors were both macro and micro environment factors, as such the study was not limited to micro environment factors or marketing mix strategy.

The analysis of existing literature shows that there is a research gap in studies focusing on the influence of micro environmental factors on marketing mix strategy. This study will bridge the gap in literature on the influence of micro environment factors: customers, competition, and distribution channels on marketing mix strategy.

1.3.General Objective

The objective of the study was to investigate the influence of micro environment factors on marketing mix strategy among retail business in shopping malls in Nairobi.

1.4.Specific Objectives

1.4.1. To investigate the influence of customers on marketing mix strategy among retail business in shopping malls in Nairobi. 1.4.2. To establish the influence of competition on marketing mix strategy among retail business in shopping malls in Nairobi. 1.4.3. To determine the influence of distribution channels on marketing mix strategy among retail business in shopping malls in Nairobi.

1.5.Significance of the Study

The findings of the study were beneficial for the retailers in shopping malls, policymakers, and academicians and researchers.

1.5.1. Retailers and Shopping Mall Owners

To beat the stiff competition in shopping malls, retailers must execute effective marketing strategies in order to capture the customers, increase sales volumes and generate profitability. This study examines the extent to which micro environmental factors influence marketing mix strategy, hence insights generated from the study can be used by retailers to enhance their marketing strategies and achieve profitability objectives.

1.5.2. Shopping Mall Owners/Investors

Since the shopping mall is an aggregation of retail and commercial establishments that provide a closed, climate-controlled, shopping experience, studies on the relationship between micro environment and marketing strategy provides important insights on the overall competitiveness of the shopping mall. Highly performing constituent retailers, especially the anchor tenant, is an indicator of the performance of the mall. The combination of individual marketing strategies employed by retailers directly positions the mall in the market and can be used as a proxy determinant of return on investment.

1.5.3. Policymakers

The shopping mall is an emerging development in Kenya. There has been a rapid expansion in gross leasable area (GLA), particularly in Nairobi. Understanding the factors that influence marketing strategies adopted by retailers in shopping malls and relationships with financial performance can offer policymakers information necessary for building an enabling business environment for retailers.

1.5.4. Academicians and Researchers

There is a paucity of research on how various macro environment and micro environment factors affect the adoption and execution of various marketing strategies, particularly in Kenya.

The results of the study will also bridge the current gap in literature and inform the necessity of further research.

1.6.Scope of the Study

The scope of the study was limited to an investigation of the relationship between three micro- environment factors: customers, competition, and distribution channels, and marketing mix strategies, with particular focus on 4P market-mix strategies. The study was geographically limited to retailers operating in Nairobi County. The population was drawn from retailers operating at the Village Market Mall. A total of 239 retailers operated in the mall. Data was collected from the retailers using questionnaires. The data collection period was between April and May 2020. The data collection phase encountered challenges originating from the coronavirus pandemic. Due to the containment measures such as transport restrictions, business closures, and social distancing, the researcher was unable to physically administer the questionnaires to retailers. The problem of face-to-face administration of questionnaires was mitigated by designing the questionnaire on Google Forms and administering the tool online, by sending the respondents the link through emails.

1.7.Definition of Terms

1.7.1. Micro Environment Factors

Refers to the people or entities directly involved in the market and linked to companies in ways that affect their capability to serve the market. The micro environment includes customers, competitors, suppliers, distributors and other marketing intermediaries, as well as the public itself (Yam, 2016).

1.7.2. Customer A customer refers to a person or entity that buys a product or service from a seller (Nugroho & Irena, 2017).

1.7.3. Competition Competition can be understood as rivalry or simply two or more companies acting independently to achieve greater success relative to others, with respect to the goods and services they deliver in the market to satisfy customer needs and demands (Kaunyangi, 2014).

1.7.4. Distribution Channel A distribution channel to an inter-organizational network or a pathway that provides product flows from the producers to the consumers. The distribution channel includes various intermediaries such as retailers and wholesalers (Singh, 2016).

1.7.5. Marketing Mix Strategy Marketing strategy are the set of activities or processes for creating, communicating, delivering and exchanging goods and services in the market. The marketing mix strategy incorporates four elements, the 4Ps, also known as the marketing mix. These are controllable variables that can be used by a company in the creation of marketing strategies (Nugroho & Irena, 2017).

1.7.6. Shopping Malls These are closed, climate-controlled, lighted shopping centers having retail stored on both sides of an enclosed walkways, that provide a variety of tenant mix, service offerings, as well as restrooms, parking, playgrounds and other amenities to enhance the shopping experience (Kushwaha, Ubeja, & Chatterjee, 2017).

1.8.Chapter Summary

Chapter One introduces the study. It presents the background of the problem by describing the relationship between micro environment factors and marketing strategy. The chapter defines and elucidates the relationship between three micro environment factors; notably, customers, competition, and distribution channels, on marketing strategy, with particular interest in shopping malls. After presenting the background of the problem, the chapter describes the statement of the problem, outlines the purpose of the study and the research objectives, and detail the significance of the study.

Chapter Two, is the literature review, and presents an empirical review of existing literature. The review is aligned with the objectives presented in Chapter One and cover analysis on customers and marketing mix strategy, competition and marketing mix strategy, and distribution channels and marketing mix strategy. Chapter Three is the methodology chapter. It details the research design, population and sample, data collection, and data analysis. Chapter Four presents the results and findings of the study. Finally, Chapter Five presents the summary of findings, discussions, conclusions and recommendations of the study.

CHAPTER TWO

2.0. LITERATURE REVIEW 2.1. Introduction

This chapter presents the empirical review, research gap, and summary of the chapter. The empirical review is divided to capture the variables in the research objectives, with sub-sections covering customers and marketing mix strategy, competition and marketing mix strategy, and distribution channels and marketing mix strategy.

2.2. Customers and Marketing Mix Strategy

2.2.1. Customer Behavior

Consumer behavior can be defined as the characteristics relating to choosing, buying, using and disposing a product or service in order to meet the needs of a customer (Nugroho & Irena, 2017). The American Marketing Association defines consumer behavior as “the dynamic interaction of affect and cognition, behavior, and the environment by which human beings conduct the exchange aspects of their lives” (Peter & Olson, 2010). Studies on consumer behavior are not only interested in understanding the characteristics of a product that consumers are more likely to purchase, but also the reasons why the consumer is making the purchase. Knowledge of consumer behavior can be used to influence consumer decisions in a number of social fields. Companies must understand consumer behavior in order to respond to their needs and desires (Bakator, Ivin, Vukovic, & Petrovic, 2016).

One of the current fundamental assumptions in consumer behavior research is that individuals often purchase products based on a subjective perception of product value. While this does not mean that the basic functions of a product are not taken into account by individuals, these core attributes of a product that relate to its primary utility are less important compared to the subjective perception of the value of the product. What this means is that there is greater focus on intangible attributes. As a result, consumer behavior research is interested in the profile of consumers, what they want in a product, how they use a product, and how they react to a product (Furaiji, Latuszynska, & Wawrzyniak, 2012). There are several characteristics of

12 consumer behavior, and they differ with regard to cultural, social, and personal factors (Nugroho & Irena, 2017).

Customer behavior therefore encompasses all activities related to acquiring, consuming and disposing products and services. It is concerned with problem recognition, information search, alternative evaluation, purchasing and post-purchase evaluation (Lin, Li, & You, 2012). As a result, understanding consumer behavior is critical in the building of a strong company. Companies must collect information about different consumers so as to understand how they are making purchasing decisions. In doing so, the questions or interest are: consumers’ opinion about the products of companies and competitors, opinion about possible improvements of the products, reaction to new products, thoughts about the products in use, attitudes about the products, and hopes and dreams of the consumers about new, present and past products they used (Hawkins, 2011). This information can inform changes in the market segments, capture overall trends, and give the company an opportunity to respond and capitalize on consumer demands (Hawkins, 2011).

Understanding customer behavior is also important because a company must consider the value of a product or service from the viewpoint of the consumer. This means that even though companies can set a price depending on various factors, they cannot be blind to the customers’ perceptions about the pricing. A higher price, in the absence of sales, does not lead to a bigger profit. As a result, companies can focus on increasing sales volumes as a better strategy. However, to do that, they must keep tab of the reactions and needs of the consumers. It is on this basis that consumer behavior relates to the formulation of marketing strategy (Bakator, Ivin, Vukovic, & Petrovic, 2016).

In a study by Nugroho and Irena (2017), the researchers looked at the various psychological factors as indicators of consumer behavior and investigated how they relate with the marketing mix and contribute to purchase intention. The product of interest in the study was a brand designated as “W” which was the biggest brand in the Halal cosmetics market in the Asia Pacific region, with particular focus on Indonesia. The researchers used a mixed method incorporating both the qualitative and quantitative elements. Questionnaires were used to collect data from a sample size of 114 respondents. Using multiple regressions, the results show that the marketing mix components (product, price, place, promotion) and the customer

13 characteristics (cultural, social, and personal influences) had a significant effect on purchase intention.

In the same vein, Arbaina and Suresh (2018) studied the determinants of consumer behavior in the sports wear market in India and how it affects purchase intention. The researchers selected a sample size of 207 participants. All the participants were drawn from Bangalore city. Data was collected using questionnaires and analyzed using SPSS for descriptive and inferential statistics. The determinants under study included price, interior, promotional tool, location, range of products, experiential zone, quality and availability. The findings revealed that all these determinants have a significant effect on consumer behavior.

Other researchers have looked into the association between customer behavior and marketing strategies. In Mehrizi and Zahedi (2013), marketing strategies was held as the independent variable while customer behavior was the dependent variable. The study focused on marketing strategies and how they are applied in internet driven markets. The e-markets in question was the household appliances market in Japan. The objectives of the study were to identify the patterns of consumer behavior in e-markets, identify the market strategies that were being used, and use a model to determine how marketing strategies relate to customer behavior. The three strategies identified were trade-oriented, cooperative and intelligent e-marketing strategies. A qualitative research method was applied, with grounded theory and Atlas TI software used in analysis. Additionally, quantitative data was collected and analyzed using SPSS-15 software. Hierarchical cluster analysis, partial correlation, and stratified regression were employed to establish relationships. Qualitative data analysis revealed that consumers of household appliances could be categorized as sentimental, rational and intelligent consumers. Using quantitative data analysis to establish the relationship between the three marketing strategies and three categories of consumers, found that there is a significant link between marketing strategies and consumer behavior (Mehrizi & Zahedi, 2013).

2.2.2. Consumer Preferences

Customer preferences is a related construct to customer behavior. According to Sulaiman and Masri (2017), preference refers to feelings of pleasure or disappointment that results from the consumption of a product relative to other products. Businesses aim achieve higher levels of

14 consumer preference for their products, because consumers may switch to other competitive offers if they are delivered by competitors in the market. Customers with a high level of preference have a lower likelihood of switching brands because high levels of satisfaction build loyalty (Solaiman & Masri, 2017). Marketers must understand customer preference as it influences the effectiveness of the marketing strategy.

Consumer preferences are influenced by a number of underlying factors. Getzner and Grabner- Krauter (2015) investigated the relationship between consumer preferences and marketing strategies, with regard to the market for green products in Austria. The study was interested in socially responsible investments in green shares. It looked at the underlying consumer characteristics such as demographic variables (education) and individual attitude variables and how they relate to shares for green companies. The findings revealed that consumers’ education level was significantly associated with green shares investment. Further, consumers’ willingness to invest in green shares was also significantly associated with the increase in green shares investment.

A study based in Nigeria examined marketing challenges, identify factors influencing changing consumer preferences and expectations, and ascertain the relationship between marketing strategies and consumer preferences and expectations. Egboro (2015) investigated the marketing challenges influencing the satisfaction of changing consumer preferences and expectations. Data was collected from a stratified sample of 120 senior staff from a roofing sheet firm in Enugu state. The study found out that the challenges included market turbulence, technology, general economy, information of customer needs, intelligence responsiveness, competition and management competency. All these factors had a significant effect on consumer preferences.

In terms of the relationship between consumer preferences and marketing mix strategies, Miriti (2016) studied the influence of marketing strategy on consumer preference. The study focused on private retail brands in Nairobi City. The objectives entailed determining the influence of the components of the marketing mix strategy: product, price, place, and promotion, on consumer preference. Simple random sampling was used to select 90 respondents and questionnaires were administered to collect data, which were then analyzed using SPSS 20.

The findings indicated that the marketing mix strategies had a positive and significant effect on consumer preferences (Miriti, 2016).

Further, Sulaiman and Masri (2017) investigated the influence of marketing mix on consumer preference. The researchers focused on the supplements and cosmetics market in Malaysia. The study was conducted at the University Utara Malaysia. Probability sampling was used to select a sample size of 379 students from a population of 27,945 students at the University. Data was analyzed using Pearson correlations and regression analysis. Correlation analysis indicated that there was a moderate correlation between marketing mix and consumer preference, while regression analysis indicated that three components of marketing mix strategy, notably; product, place, and promotion has a significant effect on consumer preference, while the fourth component of marketing mix: price, did not have a significant effect on customer preference for supplements and cosmetics in Malaysia.

2.2.3. Customer Satisfaction

Consumer satisfaction refers to the perceived fulfilment of the desires of the consumer after utilizing a product or a service. Companies are interested in consumer satisfaction because it is an indicator that is used to allocate budgets to marketing activities. Shaw (2012) notes that consumer satisfaction can be achieved through effective marketing strategies. These marketing strategies must be based on identifying the expectations of consumers in terms of product, price, promotion and place dimensions of the marketing mix strategy. Marketers understand that adequately satisfying the demands of consumers while attracting new customers is crucial for overall financial performance of the company. This means that the level of consumer satisfaction influences not only the resources allocated to marketing but also the objectives and activities included in the marketing strategy (Ebitu, 2014).

To this end, strategy then is the set of specific plans put in place to achieve specific goals and objectives over a given period of time. Strategy is the broad statement on how an organization allocates resources for the achievement of certain ends. Marketing strategy must align with the demands and satisfaction of consumers to generate insights into competitiveness, achieve increased sales volumes and forecast future performance. Marketing strategy can be long term or short term, however, irrespective of the duration, the organization, formulation, evaluation

16 and selection of market-oriented strategies as well as the successful implementation of these strategies is determined by the level of customer satisfaction (Youjae, 2010).

Customer satisfaction is therefore an indicator of marketing strategy as well as being a performance indicator. In a competitive marketplace where business organizations compete for customers, consumer satisfaction is seen as a key differentiator and increasingly has become a key element of business strategy. Consumer satisfaction provides leading indicator of consumers purchase intention and loyalty. The central focus of consumer satisfaction on the part of the supplier is to narrow the gap between consumers’ expectations and perceived performances of the product or service. The concept is emphasizes delivering satisfaction to consumers and obtaining profits in return (Ebitu, 2014).

Customer satisfaction can influence a company to grow its competitiveness and occupy a market leader position in the industry. Customer satisfaction can have a positive effect on customer loyalty, which is an essential part of keeping a company competitive in the long term. Customers who are satisfied with the products can help in spreading positive word-of-mouth communication about the company. This can increase not only performance but also the corporate reputation of the company (Agyapong, 2017). Companies that cannot satisfy their customers cannot succeed in overtaking competitors with higher customer satisfaction levels.

The importance of customer satisfaction has brought into the fore the concept of relationship marketing. The idea of relationship marketing holds that companies should identify, anticipate and satisfy customer requirements (Azizi, Bagherzadeh, & Mombeini, 2015). According to a model developed by Hao and Ngo (2012), relationship marketing requires trust, links, communication, joint ventures, and empathy as determinants of customer satisfaction.

Trust is a key component of a trading relationship and shows that to what extent each part can count on the other party. Trust is a central variable in long terms exchanges. The success of a relationship is in fact highly depended on the trust between customer and service provider. Links relate to the link established between both parties of a relationship (seller and buyer) and plays a vital role in an integrated status to achieve desired aims. Its existence in relationship marketing develops customer’s loyalty and it directly creates the feeling of belonging to the relationship and indirectly to the organization. Empathy allows both

17 parties of a relationship to study the status quo in the view of other party. Empathy is to understand demands and aims of the other party. Empathy is a necessary condition to foster mutual relations. Tendency to answer other people’s emotional mood by a similar emotional mood is called empathy. It means that an individual can understand the problems of other people even when he/she is not under such circumstances and to respect and value their opinions and feelings (Azizi et al., 2015). In terms of communications, relationship marketing is profitable when the management of interactions, relations and networks are changed to a fundamental issue. Relationship marketing plans to communicate targeted customers and to keep and foster such relationship by which the goals of both parties are met (Amini et al., 2010). Another component of relationship marketing is the mutual relation which causes that each party provides special facilities in next steps based on received advantages. Finally, joint values include joint beliefs of both parties one behaviors, goals and policies whether they are important, proper and right or lower important, improper and wrong. Such joint values and goals lead into more commitment to relationship (Ogechukwu, Umukoro, & Oboreh, 2013).

Customer satisfaction is also related to customer loyalty. Marketers need to know the needs and preferences of customers, build products and services that can satisfy them, and focus on maintaining and retaining a long-term relationship with customers. For customers to be satisfied, marketers must know the elements of the marketing mix that are more important for attracting and maintaining the customers. An example of this is the Wahab, Hasan, and Maon (2016) study that looked into the customer satisfaction for hijab. The researchers note that, over the past years, the demand for hijab has increased rapidly, and with several brands of hijab in the market, marketers must consider the designs, patterns, fabrics, colors, labels, and brands, that would appeal to customer shopping both on online ecommerce sites and physical shops. As a result, marketers must understand the demands of customers while also evaluating the hijab delivered by competitors in the market. To establish whether there was any link between customer loyalty and marketing mix strategy, a total of 234 Alam outlets selling hijab products participated in a survey. The findings revealed that there was a significant relationship between the marketing mix and customer satisfaction and loyalty. However, the researchers cautioned against generalizing the results, calling for more investigations of other outlets, other than the

Shah Alam, for a more in-depth understanding of the phenomenon (Wahab, Hasan, & Maon, 2016)

2.3. Competition and Marketing Mix Strategy

2.3.1. Threat of New Entrants

The threat of new entrants is a component of the Porters five forces theory. It refers to the threat that is caused by new competitors in the market. Profitability in the industry attracts more competitors with the intention of also gaining from the profit opportunities. When the barriers of entry are low or does not exist, it means that it is easy for new competitors to enter the market and this poses a threat to existing players. Increased competition spurs production, and in the absence of increased consumer demand, it is likely that the profit levels will decrease. In cases where the barriers of entry are high, new entrants will find it difficult to enter and exploit profit opportunities in the market (Lawrence, 2011).

The level of the threat posed by new entrants is influenced by several factors. The presence of well-established brand names increases the level of barriers. High upfront capital investments lower the threat of new entrants. Markets that have high consumer costs also have higher barriers to entry. In the opposite cases, markets that do not have well-established and highly competitive brand names, require low initial capital investments and have low consumer switching costs have higher threats of entry. Further, if the market does not require economies of scale and products are undifferentiated, new entrants find it easy to penetrate and exploit profit opportunities. In summary, the threat of entry is influenced by the levels of production, differentiation of products, initial capital, switching costs, access to distribution channels, presence of proprietary technology, and government policy regulations, among other things (Kaunyangi, 2014).

A firm can threaten the market share of existing firms if they have substantial resources to show up production and marketing, adopt pricing strategies that can force bigger competitors to reduce their prices, and execute strategies that allow it to tap into the market share of competitors (Chiteli, 2013). Mergers and acquisitions also present an alternative through which resources can be deployed to achieve economies of scale and shake up an industry.

2.3.2. Competitive Rivalry

The relative position of a firm in the industry is influenced by its ability to withstand, survive, and over-compete other companies in the same industry. Withstanding competitive rivalry ensures that a firm can get above average profitability in the long term. Competitive rivalry depends on several factors such as differentiation between the products in the market, brand loyalty by the buyers and price comparisons by the media. Competitive rivalry will also be high where it‘s costly to leave the industry hence they fight to just stay in (exit barriers); where the market growth rates are low (growth of a particular company is possible only at the expense of a competitor); where high strategic stakes are tied up in capital equipment, research or marketing and where capacity can only be increased by large amounts. In such a scenario, companies will apply the necessary strategies so as to retain their share of the market. A highly competitive business environment results in competitiveness in prices, profitability and performance of firms in the industry (Kaunyangi, 2014).

There are various ways through which a firm can achieve competitive advantage in an environment of highly competitive intensity. The main strategies are low cost and differentiation. A firm should pursue cost leadership, differentiation and focus in order to win competitive rivalries (Lawrence, 2011). Ogaga (2017) investigated the relationship between industry competition and corporate strategy. Industry competition was measured via entry barriers, rivalry, buyer’s bargaining power, suppliers’ bargaining power, substitutes, government, logistics and power play, while the measures of strategy were differentiation, cost leadership, focus and strategic alliance. In essence, this study focused on corporate strategy as opposed to marketing strategy. The sample included 63 companies listed at the Nairobi Securities Exchange as at June 2015. Using hierarchical regression, the results revealed that industry competition has a moderating effect on the association between corporate strategy and organizational performance (Ogaga, 2017).

There are various studies that have been done to test the relationship between competitive rivalry and marketing in various industries across the world. O’Cass and Weerawardena (2017) sought to determine whether there was a link between an industry’s competitive intensity and marketing related capabilities. The conceptualization of competitive intensity was based on Porter’s theoretical framework, which held that an industry’s competitive intensity is

20 determined by the five competitive forces: threat of entry, threat of substitutes, power of buyers, power of suppliers, and rivalry between firms. In the research marketing abilities are conceptualized as capabilities built on the premise that all capabilities have common underlying characteristics. As such, it implies capabilities that are built upon processes that are developed by firms depending on their internal people and resources. The sample included CEOs from the IncNet Business Database. From a population of 1000, 247 respondents proceeded to the study. The regression results revealed that an industry’s competitive intensity has a positive impact on marketing capability (Ocass & Weerawardena, 2017).

Another study, Takata (2016), tested the effect of industry forces, market orientation, and marketing capabilities on business performance among Japanese manufacturers. The industry forces in these cases were the five forces of competition outlined by Porter’s five forces theory: threat of new entrants, competitive rivalry, threat of substitutes, bargaining power of buyers and bargaining power of suppliers. The marketing capabilities captured in the study were new product development, pricing, channel management, and marketing communication. The survey comprised of 568 Japanese manufacturing companies drawn from a population of 1000 firms listed at the Tokyo Stock Exchange. Data covered the 2009 to 2011 period. Hypotheses were tested using PLS-SEM and the study found out that marketing capabilities is the strongest driver of business performance, followed by competitive rivalry and the power of suppliers (Takata, 2016).

Githaiga, Namusonge, and Kihoro (2016) explored empirical data on the relationship between marketing strategies and competitiveness among micro and small entrepreneurs in Kenya. The core of the study was on how entrepreneurial marketing orientation of SMEs help them to achieve competitiveness. The researchers presented a systematic review of studies that have used Michael Porter’s Diamond Analysis Model, and how marketing strategies and competitiveness have been conceptualized in research. The findings showed that adopting a certain marketing strategy can have a significant effect on firm competitiveness. The study was a review of empirical literature and therefore did not present statistical analysis of primary data (Githaiga, Namusonge, & Kihoro, 2016).

2.3.3. Threat of Substitutes

A substitute can be defined as a good or service that performs the same function to the buyer. Substitution comes in different forms and serves various functions in the industry, due to the fact that they influence the buyer in a different way (Moriasi, Asienyo, & Okao, 2014). Identification of substitutes in the market is a primary function of market analysis so as to generate accurate and reliable information for developing a market strategy (Mwaluma, 2014).

Every organization needs to identify the current and future marketing opportunities. This identification usually involves analysis of the current products that a company delivers and the markets where they are delivered. No firm can depend on the same products and the same markets forever, they must invest in marketing strategies to identify the areas of growth, in terms of possible but related products and services, or making a foray into an industry that is not the traditional focus of the firm (Azzam, 2018). Increased competitive pressures force companies to establish new strategies that can enable them to achieve competitive advantage and enhance performance. One of the ways of doing this is innovating new products. Introduction of new products or modification of existing products are important in creating competitive advantage (Camison & Lopez, 2010).

There are various factors that can increase the number of substitutes in the market. These include the dynamic changes in the economy at large, population demographics, societal values and lifestyles, governmental legislation and regulation, technological factors, and the company’s immediate industry and competitive environments (Moriasi, Asienyo, & Okao, 2014). Substitutes are designed to appeal to customers having a special sensitivity to a particular attribute in the product. In such cases, customers are willing to pay a premium price in order to get a particular attribute in a product (Karuoya, 2014). As such, substitution is central to a firm’s profitability because it determines demand. The entry of a substitute from a competitor can either lead to firm growth or cause a decline in profits. This means that substitution influences competitive scope because it widens or narrows down the range of product segments that are available in the market. Substitutes also limit the potential returns of an industry by placing a ceiling on the prices that firms in that industry can profitably charge (Chiteli, 2013).

In a broad sense, all firms in an industry are competing, in a broad sense, with industries producing substitute products. Substitutes limit the potential returns of an industry by placing a ceiling on prices firms in the industry can profitably charge. The more attractive the price performance alternative offered by substitutes, the firmer the lid on industry profits (Porter, 1998). Substitutes not only limit profits in normal times, but they also reduce the bonanza an industry can reap in boom times. Substitutes are bound to be an ever stronger limit on profitability once capacity is boosted enough to meet demand. Evidence from the banking sector shows that the intensity of competition influences the price of products and services, which are, in turn, assumed to determine firms’ profits (Okelue, Uchenna, Obinne & Nonye, 2012).

The competitive advantage from product price-performance is almost short term, especially in an era where technologies are altering the existing business boundaries. Advantages can only be sustained through competence that is enjoyed at the very roots of products. Position vis-à- vis substitute products is a matter of collective industry actions such that for example although advertising by one firm may not be enough to bolster the industry’s position against a substitute, heavy and sustained advertising by all industry participants may well improve the industry’s collective position. Similar arguments apply to collective response in areas like product quality improvement, marketing efforts, providing greater product availability (Chiteli, 2013).

Substitute products that deserve the most attention are those that are subject to trends improving their price performance trade off with the industry’s product, or are produced by industries earning high profits. In the latter case, substitutes often come rapidly into play if some development increases competition in their industries and causes price reduction or performance improvement. Analysis of such trends can be important in deciding whether to try to head off a substitute strategically or to plan strategy with it as inevitably a key force. Pressure from substitute products because substitute products limit the potential returns of an industry by placing ceilings on prices firms in the industry can charge. Suppliers can exert bargaining power over participants by threatening to raise prices or reduce quality of purchased goods and services. They can thus squeeze profitability out of an industry (Moriasi, Asienyo, & Okao, 2014).

The threat of substitution is downstream or indirect, when a substitute replaces a buyer industry's product. Substitutes are always present, but they are easy to overlook because they may appear to be very different from the industry's product. It is a substitute to do without, to purchase a used product rather than a new one, or to do it yourself (bring the service or product in-house). When the threat of substitutes is high, industry profitability suffers. Substitute products or services limit an industry's profit potential by placing a ceiling on prices. If an industry does not distance itself from substitutes through product performance, marketing, or other means, it will suffer in terms of profitability and growth potential (O’Cass & Weerawardena, 2017).

The threat of a substitute is high if: it offers an attractive price-performance trade-off to the industry's product. The better the relative value of the substitute, the tighter is the lid on an industry's profit potential, the buyer's cost of switching to the substitute is low. Strategists should be particularly alert to changes in other industries that may make them attractive substitutes when they were not before. In this way, technological changes or competitive discontinuities in seemingly unrelated businesses can have major impacts on industry profitability. Customer loyalty also protects a firm from threat of new entrants and threat of substitute products. The firm adopting focus strategy can easily stay closer to its customers and effectively monitor their needs (Mutai, 2012).

The focus of strategy should be to target market segments that are less vulnerable to substitutes or where a competition is weakest to earn above-average return on investment. Organizations can make use of the focus strategy by focusing on a specific niche is sometimes referred to as the niche strategy. Firms pursuing this strategy are willing to serve isolated geographic areas, satisfy needs of customers with special financing, inventory or servicing problems or even to tailor the products to somewhat unique (Moriasi et al., 2014).

Established firms have brand identification and customer loyalties, which stem from past advertising, customer service, product differences or simply being first into the industry. Differentiation creates a barrier to entry by forcing entrant to spend heavily to overcome existing customer loyalties (Mutai, 2012). This effort usually involves startup losses and often takes an extended period of time. Such investments in building a brand name are particularly risky since they have no salvage value if entry fails. Product differentiation will thus enhance

24 the overall capability of the organization in terms of improving on its products, which will in turn attract more customers and consumers (Githaiga et al., 2016).

Products in the hospitality industry and telecommunications are mainly substitutes. In a study of the hotel industry, Bukirwa and Kisingu (2017) looked at those competitive strategies that firms are adopting to enhance performance. The study was focused on hotels operating in Mombasa County in Kenya. The study was also founded on Porter’s competitive forces, with strategies being cost leadership and differentiation. The population consisted of 24 classified hotels under the Kenya Association of Hotel Keepers and Caterers, from which 144 respondents were drawn. The respondents were administered questionnaires, the responses from which proceeded to analysis using SPSS 22. Linear regression results demonstrated that competitive strategies have a positive and significant effect on organizational performance (Bukirwa & Kisingu, 2017).

With regard to the mobile telecommunications sector in Kenya, Kaunyangi (2014) studied competition how it affected performance. It looked at three out of the five competitive forces in Porter’s framework: threat of new entrants, competitive rivalry, and bargaining power of buyers. The data was collected from the main telecommunications firms in Kenya in 2014: Airtel Kenya, Orange Kenya, Safaricom, and Yu Mobile. Descriptive statistics showed that there was a moderately high level of agreement that the competitive forces were affecting performance. However, the study did not run inferential statistics making it difficult to establish the relationship between the competitive forces and measures of financial performance in the industry.

2.4. Distribution Channels and Marketing Mix Strategy

2.4.1. Direct Distribution

The ability to develop a successful strategy in distribution is critical in today’s complex and fierce competitive environment (Mwanza & Ingari, 2015). Direct distribution refers to a situation where the producer sells directly to the consumer without passing the goods through intermediaries. Direct distribution typically entails face-to-face selling, selling over the internet or mails, so long as there is no distributor, other than the producer. Distribution channels that

25 involve producers selling to nonaffiliated retailers cannot be direct distribution because such unaffiliated retailers and wholesalers are not the final consumers of the goods.

The choice of direct distribution is informed by a strategy that wants to connect the producer directly with the consumer so as to lower the overhead. Since, the producer does not share profits with distributors such as retailers and wholesalers, companies that use direct distribution have comparatively higher rates of profit (Aleksandra et al., 2017). However, direct distribution has the disadvantage that it cannot compete with companies that have an extensive global reach and distribution channel that includes many wholesalers and retailers. Further, there are limitations with regard to the kind of products that can be sold directly by the producer to the consumer (Singh, 2016).

Distribution strategies have the overall goal of improving customer experiences. As a result, distribution is planned with the objective of increasing positive consumer experiences through the selection of a channel mix, including physical stores, that enrich the experience of consumers at the point of service, offer value-added services, and serve as a point of research that can be used to collect information from consumers. It should be noted that distribution offers companies the opportunity to partner with upstream and downstream activities so as to enhance efficiencies and control costs. Further, consumers can also partner with other actors in the supply chain to support process and product innovation (Mwanza & Ingari, 2015).

A study by Koster (2018) looked at the direct distribution strategies for online retailers. The study noted that online retailers continue to face challenges in organizing their logistic fulfilment processes after a transaction has been made. The study sampled 55 online retailers, including those that were exclusively online and those that were traditional with an online component. The distribution variables studied were delivery lead times, assortments choice, and the number of online orders. The results showed that the choice of distribution strategy was mainly influenced by the complexity of the product assortment (Koster, 2015).

Most direct distribution channels utilize the internet to deliver the products. In the mobile and telecommunications sector, this is the channel of choice for distributing products such as airtime. Karanja et al., (2017) sought to establish the influence of the distribution strategy on mobile service providers (MSP) intermediaries. There have been attempts by MSPs to bypass

26 their intermediaries who distribute scratch cards by providing the same services through web- based recharge platforms. However, MSP intermediaries have also been implementing different channel strategies have not been studied. The sample selected for the study consisted of 219 respondents out of 397 intermediary companies operating in Nairobi County and servicing the four major telecommunications companies: Safaricom, Airtel, Essar and Orange Telkom. The distribution strategies captured in the study were choice of distribution strategy, warehousing, operations administration, manpower, customer service and routing. The regression analysis showed that distribution strategy had a significant influence on intermediary performance (Karanja et al., 2017).

2.4.2. Indirect Distribution

Indirect distribution refers to a channel where there are intermediaries such as retailers and wholesalers that obtain products from the producer and sell these to the consumers. Indirect distribution means that a product moves from the producer, through the distributors, wholesalers, and retailers, before it can reach the consumer (Koster, 2018). The difference between direct and indirect distribution is that while there is a direct link between producer and consumer in direct distribution, there is no direct link between producer and consumer in indirect distribution (Kafaerpour, 2015).

Most manufacturers of consumer durables such as TVs, scooters, refrigerators, washing machines, cars, industrial machinery and equipment, among others, use indirect channel of distribution (Singh, 2016). Other goods include consumer products like cosmetics, detergents, and soaps. Other consumables such as food grains, clothes, edible oil, sugar, among others also uses this strategy. It is a convenient strategy that allows goods to be distributed to large scale retailers. The products that are mostly distributed through this channel enjoy a scattered demand. Compared to direct distribution, it is the longest distribution channel as a result of distributors, wholesalers and retailers. As a result of the number of intermediaries, the producer loses control of the distribution. The speed of delivery may also be slow before the goods reach the consumers (Marmullaku & Ahmeti, 2015).

In a study by Kafaerpour (2015), which focused on the influence of the distribution strategy on sale promotion at Samsung Company in Iran, can be understood to primarily focus on direct

27 distribution. The elements of distribution incorporated in the study were stock (in terms of stock availability, supervision of distribution agents, supervision on product delivery time), and distribution channels (in terms of sales offices of the company, distribution agents of the company, supervision of products delivery companies). The findings showed that there is a slight difference in the importance of stock attributes and distribution attributes at Samsung Company, but all the attributes had a positive effect on sales promotion (Kafaeipour, 2015).

Indirect distribution typically involves reliance on large retail outlets. Aleksandra, Nada, and Marija (207) examined the success of distribution channels of retail chains in Republic of Serbia. The focus was on the 10 largest retail chains in the country. The researcher noted that distribution channels are becoming increasingly sophisticated, and the performance of the entire channel has an effect on the manufacturer and the consumer. The study focused on retailers, as a core intermediary in the distribution channel, in order to understand the partner’s view, and whether their performance can be used as an indicator of the success of a distribution channel. The regression results showed that the performance and the role of the retailers depends on the size of the sales network and the number of sales facilities. The findings also showed that the largest retail chains are under performing, meaning that the efficiency of the distribution channel has a significant effect on performance (Aleksandra, Nada, & Marija, 2017).

In the same way, Mwanza and Ingari (2015) examined the role of distribution as a source of competitive advantage in the FMCG market in Kenya. The study tested how the different types of distribution: direct distribution, indirect distribution, and intensive distribution, affected the ability of a firm to create and maintain competitive advantage. Descriptive statistics was used to analyze the data collected using questionnaires. The findings showed that all the three strategies were responsible for creating competitive advantage, with direct distribution having greater impact than indirect and intensive distribution strategies.

Sameer Africa is a manufacturer of vehicle tires and their choice of distribution is the indirect channel. Adimo and Osodo (2017) was interested in the association between distribution channel differentiation and organizational performance. The study focused on Sameer Africa Limited. A sample of 134 respondents were drawn from the company, which included senior management, heads of department, junior staff and dealers based in Nairobi. The data collected

28 using questionnaires was analyzed using correlation and regression analysis. The findings revealed that an improvement in channel differentiation strategy by using market trends in determining the most appropriate channel; using different channels so as to minimize distribution costs; selling products through intermediary and complimentary firms; and using different distribution channels to satisfy unique consumer needs, resulted in improved performance, as measured by market share, revenue growth, sales growth, and customer satisfaction (Adimo & Osodo, 2017).

2.4.3. Intensive Distribution

Intensive distribution, as the name suggests, means utilizing all available outlets to distribute a product. Intensive distribution is pursued so as to increase consumer convenience and satisfaction. Goods such as bread, sweets, newspapers, chewing gums, soda, among others are distributed to as many available outlets as possible. It informs marketing strategy, when the objective is to sell the product to as many outlets and customers as possible (Aila et al., 2015). The primary characteristics of intensive distribution are: maximum number of outlets covered to maximize availability; target outlets in as many as geographical regions as possible; consumer convenience products; high number of purchasers; high purchase frequency; impulsive purchase and low price (Marmullaku & Ahmeti, 2015). Intensive distribution is pursued when the manufacturer wants to establish a dominant position in the geographic markets that it serves. This, however, is not limited to indirect distribution. In general, companies develop distribution strategies with the intention of pursuing dominance and building long-term commitments with partners on the supply chain and customers. It is these relationships that influence marketing decisions (Segetlija et al., 2015).

An example of an intensive distribution strategy is that of soft drinks. Aila et al. (2015) investigated the impact of channel strategy on customer value of soft drink companies in Kenya. The study sought to establish the link between distribution strategies such as order cycle time, stock availability, and sales on customer value. The sample consisted of 88 soft drink companies that were contracted by Equator Bottlers Limited to distribute their products in Kenya. Using Pearson’s product moment correlations, stock availability and sales were found to have a strong correlation, while there was a weak correlation between delivery speed

29 and sales. The correlation between order cycle time and sales was negative and weak. In essence, higher sales were linked to higher stock availability (Aila et al., 2015).

Distribution represents a complex, specialized, sophisticated and coordinated supply chain in developed countries and increasingly in many developing countries. The distribution sector includes commission agents, wholesalers and retailers who act as enablers of trade. The distribution strategy must be carefully integrated with all components of the marketing program. Before a manufacturer formulates a distribution strategy, two decisions should occur. These are determining whether the firm will sell directly to end-users or will utilize intermediaries and selecting the type of channel. Distribution channels evolved through the utilization of national resources contained within an area of trade. The need to move the resources to other areas where they were in demand brought about the need for distribution channels (Singh, 2016).

Marmullaku and Ahmeti (2015) studied the factors affecting marketing strategies; pricing, channel structure, and advertising strategies. The distribution channels identified as challenges were classified as traditional merchant wholesaler with global operations, foreign distributors, export merchants, export management company, manufacturer’s export agents, resident buyer, and third-party logistics provider. The study found out that as a result of the segmentation of markets, product positioning and adoption of different strategies in different countries, the execution of the marketing mix strategies differs and determine success (Marmullaku & Ahmeti, 2015).

2.5. Chapter Summary

Micro environment factors influence various aspects of business performance; however, there is minimal focus on how it influences marketing strategies. The literature review delves into the three components of micro environment factors selected for this study, and critically evaluates empirical studies that have been published so as to identify the nature of the relationship between customers and marketing strategy, competition and marketing strategy, and distribution channels and marketing strategy. In general, while studies have studied various dimensions of customers, such as customer behavior and customer preference, these are mostly correlated with measures of business performance, with a few touching on marketing

30 capabilities. With regard to competition, a majority of studies rely on Porter’s five forces competitive forces and how these relate to business performance. Where the competitive forces have been related to marketing dimensions, the focus has been on marketing capabilities of a firm and rarely on marketing mix strategies. There were few studies that examined how distribution strategies affected market mix strategy, most studies were interested in tackling the link between distribution channel strategy and performance. The literature analysis shows that there is a research gap in investigating the influence of micro environment factors on market mix strategy. The next chapter is the methodology chapter that describes the research design, population, sample, data collection and data analysis techniques.

CHAPTER THREE

3.0.RESEARCH METHODOLOGY 3.1.Introduction Research methodology is a systematic way of applying the relevant methods to a field of study. It is built on theoretical analysis within the branch of knowledge on which the study is grounded. This chapter highlights the research design that will be adopted in the study and justification, target population, sample, data collection techniques, and data analysis methods.

3.2.Research Design

Research design refers to the strategy used by the researcher in collecting and analyzing data. It is the plan and structure of investigation conceived to obtain answers to research questions. It also provides the guide for collecting and analyzing data. This study adopted a descriptive design. Descriptive designs address specific characteristics of a selected population of subjects at a point in time, or at varying times for the purpose of comparing the relationship between variables (Leavy, 2017). Descriptive studies are concerned with finding out who, what, where, when, and how much. They try to measure the types of activities, how often, when, where and by whom. Descriptive cross-sectional surveys are helpful in revealing patterns and connections that might otherwise go unnoticed. Unlike exploratory studies, descriptive studies are structured, have clear hypothesis, and are guided by research questions (Creswell & Creswell, 2017). Descriptive research measures variables or set of variables as they exist naturally. The goal of descriptive research is not primarily concerned with relationships between variables but rather with the description of individual variables (Cooper & Schindler, 2014).

The study investigated the relationship between micro-environment factors and market mix strategies. The micro-environment factors captured by the independent variables: customers, competition, and distribution factors. Customers was measured in terms of customer behavior, customer experience, and customer satisfaction. Competition factors covered were threat of entry, competitive rivalry, and substitutes. Distribution factors focused on direct distribution, indirect distribution, and intensive distribution. The dependent variable was marketing-mix strategies, measured based on the 4Ps conceptualization.

3.3.Population and Sampling Design

3.3.1. Population

A population element is the subject such as a person an organization, customer database, or the amount of quantitative data on which the measurement is being taken. According to Ngechu (2004), a population is a well-defined or set of people, services, elements, events, group of things, or households that are being investigated. In this study, the target population are retail businesses in shopping malls in Nairobi.

The shopping mall selected in this study was Village Market. The Village Market is one of the oldest and largest shopping, recreation and entertainment complex in Nairobi Kenya. The shopping complex opened its doors in 1995 and currently hosts 239 retail outlets. These stores are categorized as food & restaurants, essentials & other services, health & beauty, arts, crafts & gifts, furniture & furnishings, fashion & accessories, financial institutions, family entertainment & recreation center, and & Hotel Tribe (Village Market, 2020). In this study, the population was the number of all retail outlets at the Village Market Mall.

3.3.2. Sampling Design

3.3.2.1.Sampling Frame

Sampling frame refers to the list of all items in the population (Creswell & Creswell, 2017). In this case, sampling frame is the list of all the 239 retail outlets identified in the population for this study. The list presented in Appendix 2 was obtained from the management of Village Market Mall (Village Market, 2020). While a population is general, the sample frame lists the specific outlets, from which the sample size will be drawn, excludes retail outlets that will not be included in the study and includes accurate information about each retail outlet.

3.3.2.2.Sampling Techniques

Sampling is the process of determining the number of respondents or observations to be taken from the larger population. There are three main types of sampling techniques: probability sampling, non-probability sampling, and mixed sampling. Probability sampling is one in which each sample has the same probability of being chosen; non-probability sampling does not

33 follow the theory of probability when sampling from the population; and mixed sampling uses a combination of the two. variables (Cooper & Schindler, 2014). This study used probability sampling techniques. According to Creswell & Creswell (2017), the types of probability sampling include random sampling, stratified sampling, cluster sampling, and systematic sampling. Each of these sampling techniques have their strengths and limitations and are adopted depending on the characteristics of the population.

The study used simple random sampling. Simple random sampling is the sampling procedure for selecting respondents in a population. It is a probability sampling technique where every unit in the population has an equal chance of being selected. Simple random sampling was chosen because it generated a sample size that is representative and unbiased, and provided a valid foundation for estimating a phenomenon in a population.

3.3.2.3.Sample Size

A sample refers to a set of individuals, objects, or observations selected from a statistical population using a specific procedure (Mugenda & Mugenda, 2003). The sample size is the number of individual samples or observations measured and selected to participate in a survey (Mugenda & Mugenda, 2003). The sample was drawn from retail businesses operating in shopping malls in Nairobi County. The shopping mall selected for this study was the Village Market Mall. There are 239 retail shops at the mall. To derive the sample size for the study, Yamane’s (1967) formula was used: n = N

[1+N (e)2]

Where n is the sample size, N is the population sample and e is the sampling error tolerance. n = 239

[1+239 (0.05)2]

= 149.61.

The sample size for the study was calculated as 150 retail outlets at Village Market Mall.

3.4.Data Collection Methods The primary data was collected using questionnaires. The instrument comprised of closed- ended questions to capture the conceptualization of the variables. Questionnaires were preferred because they were inexpensive and easy to administer to the respondents. They also gave the respondents adequate time to read, understand, and complete the questions and are therefore a more reliable data collection tool.

The questionnaire was divided into sections. Section A collected demographic information about the respondents. Section B, C, and D collected information on independent variables. Section B collected responses to questions on customers and covered customer behavior, consumer preference, and customer satisfaction. Section C collected responses to questions on competition, covering threat of entry, competitive rivalry, and substitutes. Section D collected responses to questions about distribution, and cover direct distribution, indirect distribution, and intensive distribution. Section E focused on the dependent variable, marketing mix strategy, and cover questions on the 4Ps dimensions. The questionnaire used 5-point Likert scales to rank responses to the questions covering the independent and dependent variables.

3.5.Research Procedures

The researcher carried out a pre-test to collect data for refining the questionnaire before the final administration of the questionnaire. The importance of pre-testing is to detect ambiguity, evaluate the type of answers given to determine whether they help the researcher to achieve the laid down objectives. Pre-tests are also crucial for ensuring the validity and reliability of the research process and findings (Creswell & Creswell, 2017).

A pre-test sample of 10% of the sample size was used in the study, as recommended by Mugenda and Mugenda (2003). The questionnaires were administered to the pre-test sample at their retail shops. The completed questionnaires were used for reliability analysis. Questions that are not clear and ambiguous were restructured to eliminate ambiguity and improve clarity. All problems encountered in the pilot testing were addressed and the questionnaire refined in preparation for the actual data collection exercise.

The tools were tested through validity and reliability techniques. The validity of a questionnaire is the degree to which it measures what it purports to measure (Bolarinwa, 2015). The validity

35 was established by subjecting the questionnaire to a panel of experts and academic colleagues to establish whether the constructs represents what is being measured. Peer review was used to attract responses on the questionnaire which are then used to improve it before administration (Seyyedamiri & Faghih, 2015).

On reliability testing, the researcher employed a test, retest method to establish internal consistency. The process entailed repeated administration of the same questionnaire to respondents and testing the reliability. In this case, the reliability was established by determining the internal consistency of items representing each construct using the Cronbach’s Alpha Index. Scores above 0.7 were judged as satisfactory, implying that the questionnaire had achieved the desired reliability level necessary for the generation of valid results (Olanye & Eromafuru, 2016).

The results showed that the coefficient for customer factors was 0.755, competition factors was 0.928, distribution channel factors was 0.764, and marketing mix strategy was 0.9. Overall, the instrument Cronbach’s alpha coefficient was 0.837. According to Nunally (1978), Cronbach’s alpha values above 0.7 meet the threshold for instrument reliability. Therefore, the instrument reliability score of 0.837 indicated a satisfactory reliability needed for the generation of valid results.

Table 3.1: Reliability Coefficients Variables Number of items Cronbach’s Alpha Customer factors 15 0.755 Competition factors 15 0.928 Distribution channel factors 15 0.764 Marketing mix strategy 12 0.900 Questionnaire 57 0.837

Owing to the closure of businesses and healthcare interventions such as social distancing to reduce the spread of Covid-19 as well as the risk of contamination of printed questionnaires, the survey tool was administered online as opposed to the prior proposed plan of face-to-face administration. The questionnaire was transformed into an online data collection tool using

Google Forms and administered to the pre-test sample through their emails. The questionnaires were completed online a 14-day data collection period.

Research ethics is concerned with protecting the dignity of the respondents and the information obtained in the process of research. The researcher obtained authorization from the University and appropriate government authorities to ensure that the research complies with ethical considerations. These ethical authorizations were presented to each respondent so that they can get an understanding of the nature of the research, the objectives, and the use of the research findings. The researcher obtained informed consent from the respondents, respected their anonymity and confidentiality, upheld their privacy, and ensured that there were no data collection processes that violated established ethical considerations, including preventing harm and protecting dignity, and defending the rights of the respondents.

3.6.Data Analysis Methods

Data from the questionnaires was entered into an excel sheet, to capture the variables. The data was cleaned and uploaded in SPSS (version 23) for descriptive and inferential analysis. Descriptive statistics was used to summarize the measures for the variables into percentages, means, and standard deviations. Multiple regressions were used to establish the relationship between the independent variables and the dependent variable, and test whether micro environment factors have a positive or negative influence on marketing mix strategies employed by retail businesses in shopping malls in Nairobi.

The study adopted a basic regression model:

The regression model took the form of: y = α + β1x1 + Ɛ

Where: y intercept is the endogenous variable

α denotes the y intercept where x is zero; β1 is regression weights attached to the exogenous variables: x1 and Ɛ is the error term.

Replacing for the variables:

MS = α + β1CUST + Ɛ

MS = α + β2 COMP + Ɛ

MS = α + β3 DIST + Ɛ

Where

MS denotes marketing mix strategy

CUST denotes customers, COMP denotes competition, and DIST denotes distribution channels. The findings for both descriptive and inferential statistics were presented in tables and figures in addition to an analytical and narrative description of the results.

3.7.Chapter Summary

The chapter presents the methodology of the study. The study adopted a descriptive research design. The population included the 250 retail outlets at the Village Market Mall. Probability sampling techniques, specifically, simple random sampling was used to generate the sample size. Data was collected using questionnaires that have undergone validity and reliability testing. The questionnaires were administered to respondents in their places of work and the data collected analyzed using descriptive and inferential statistics. The next chapter presents data analysis results, findings and interpretations.

CHAPTER FOUR

4.0. RESULTS AND FINDINGS

4.1. Introduction

The chapter presents the results and findings of the study. The results contain descriptive and inferential statistics covering demographic information and the relationship between each of the independent variables and the dependent variables. All the results are presented using tables, graphs and pie charts. The findings are accompanied by narrative descriptions which explain and situate the results within the context of the study.

4.2. Demographic Information

4.2.1. Response Rate

The researcher administered 150 questionnaires to retail businesses at the Village Market Mall. Out of these, 114 completed and returned the questionnaires. The 114 completed questionnaires were cleaned and proceeded to analysis. The response rate was calculated as 76.0%. This response rate is interpreted as satisfactory based on Babbie (2007) recommendations indicating that a response of 50% is adequate for analysis, a response rate of 60% is good, and a response of 70% is very good. As such, the study’s response rate of 76.0% is very good and was considered adequate for statistical analysis.

4.2.2. Age of Respondents

The descriptive analysis indicate that a majority of respondents were within the productive age group: 25 years to 54 years. For instance, 32.5% (37) were aged between 25-34 years, 28.1% (32) were aged between 35-44 years and 30.7% (35) were aged between 45-54 years old. Only a small number were aged 18-24 years old, 2.6% (3) and above 55 years old, 6.1% (7).

Age distribution (%)

35.00% 32.50% 30.70% 30.00% 28.10%

25.00%

20.00%

15.00%

10.00% 6.10% 5.00% 2.60%

0.00% 18-24 years old 25-34 years old 35-44 years old 45-54 years old Over 55 years old

Figure 4.1: Age of Respondents

4.2.3. Gender of Respondents

The ratio of male to female was nearly 1:1, with female respondents being slightly more. From the total number of respondents, 114, 47.4% (54) were male while 52.6% (60) were female. The distribution of respondents is presented using a pie chart below.

Gender distribution (%)

47.40% 53.60%

Male Female

Figure 4.2: Gender of Respondents

4.2.4. Education Level

The respondents were characterized based on their education level. A majority of the respondents had a higher educational achievement, with 50.9% (58) having a bachelor’s degree, 29.8% (34) having a master’s degree, and 0.9% (1) having a PhD level of education. A minority had a diploma level of education, 16.7% (19) and secondary school level of education, 1.8% (2).

Level of education (%)

PhD 0.90%

Masters degree 29.80%

Bachelors degree 50.90%

Diploma 16.70%

Secondary school certificate 1.80%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%

Figure 4.3: Level of Education

4.3. The Influence of Customers on Marketing Mix Strategy

4.3.1. Customer Behavior In terms of customer behavior, 17.5% strongly agreed, 48.2% agreed, 24.6% were neutral, 3.5% disagreed, and 6.1% strongly disagreed with the statement that customers were concentrated where the retail outlet was operating (M=3.70, SD=0.981). Customers were greatly attracted to the retail store’s design and product display, as indicated by the number of people who strongly agreed (29.8%) and agreed (57.0%) (M=4.12, SD=0.810). The level of agreement with customers having adequate disposable income to afford prices at the mall was slightly above average, at 15.8% strongly agreeing and 58.8% agreeing (M=3.78, SD=0.890). The same level of agreement was reported for customers going the extra step to search for information about the retail outlets and the products they offer, as showed by the 8.8% who strongly agreed and 58.8% who agreed (M=3.65, SD=0.831).

Table 4.1: Customer Behavior

SA A N D SD Means Std. Deviation

Customer Behavior Our customers are highly 17.5% 48.2% 24.6% 3.5% 6.1% 3.70 0.981 concentrated where we operate our retail outlet Our customers are attracted 29.8% 57.0% 8.8% 1.9% 2.6% 4.12 0.810 to the store design and how we display our products Our customers have 10.5% 58.8% 24.6% 3.5% 2.7% 3.76 0.726 adequate disposable income to afford the prices we offer Our customers’ shopping 15.8% 58.8% 15.8% 7.0% 2.6% 3.78 0.890 habits are influenced by time and seasons Our customers take 8.8% 58.8% 23.7% 6.1% 2.6% 3.65 0.831 initiative to search for information on products

4.3.2. Customer Preferences In terms of customer preferences, there was an above-average level of agreement with the position that customers make purchase decisions based on prices. Findings indicate that 14.0% strongly agreed, 56.1% agreed, 15.8% were neutral, 7.0 % disagreed, and 7.0% strongly disagreed with the statement (M-3.65, SD=1.034). A comparatively higher number of customers agreed that they made purchasing decisions because they preferred the retail outlets in the mall, as indicated by the 17.5% who strongly agreed, 55.3% agreed, and who were 21.9% neutral in their opinion (M=3.82, SD=0.844). In the same vein, a higher proportion of customers noted that they bought products from retail outlets in the mall due to comparatively higher quality of products, with 43.0% strongly agreeing and 45.6% agreeing (M=4.28, SD=0.796). A moderate number of respondents noted that their purchasing decisions was mainly influenced by product promotions. Of those surveyed, 14.9% strongly agreed, 53.5% agreed, 21.1% were neutral, 7.0% disagreed, and 3.5% strongly disagreed with the statement that their preferences were driven by product promotions (M=3.69, SD=0.932). Similar responses were obtained for purchasing decisions influenced by product brand identity (M=3.89, SD=0.870).

Table 4.2: Customer Preferences

SA A N D SD Means Std. Deviation

Consumer Preferences Customers buy from us 14.0% 56.1% 15.8% 7.0% 7.0% 3.65 1.034 because of the prices of our products Customers buy from us 17.5% 55.3% 21.9% 2.6% 2.6% 3.82 0.844 because they prefer our stores Customers buy from us 43.0% 45.6% 7.9% 1.8% 1.8% 4.28 0.796 because of the quality of our products Customers buy from us 14.9% 53.5% 21.1% 7.0% 3.5% 3.69 0.932 because of the promotions on products Customers buy from us 22.8% 51.8% 16.7% 7.1% 1.8% 3.89 0.870 because of they prefer our brands

4.3.3. Customer Satisfaction On customer satisfaction, retail outlets perceived satisfaction with quality of service to be high, with 32.5% strongly agreeing and 44.7% agreeing (M=4.07, SD=0.846). Similar findings were reported for perceived satisfaction with staff responsiveness to customer inquiries (strongly agree, 36.8%; agree, 43.9%, M=4.18, SD=0.774), perceived level of customer loyalty with findings indicating that a majority were repeat customers (M=4.15, SD=0.742) as well as customers spreading information about retail outlets and products through word of mouth (strongly agree, 26%; agree, 62.3%, M=4.15, SD=0.715).

Table 4.3: Customer Satisfaction

SA A N D SD Means Std. Deviation

Customer Satisfaction Customers are satisfied with 32.5% 44.7% 18.4% 2.7% 1.8% 4.07 0.846 the quality of service Customers are satisfied with 36.8% 43.9% 16.7% 1.8% 0.9% 4.18 0.774 the amount of help they receive from our staff Customers are satisfied with 14.9% 51.8% 27.2% 4.4% 1.8% 3.74 0.831 the pricing of goods in our stores Most of our customers are 31.6% 53.5% 10.5% 3.5% 0.9% 4.14 0.742 repeat customers Customers recommend our 26.3% 62.3% 5.3% 4.4% 1.8% 4.15 0.715 store to friends and colleagues

4.3.4. Inferential Statistics

The study sought to establish the effect of customers on marketing mix strategy. Multiple regression was run to establish the effect of customer-related dimensions on the marketing mix strategy. The model summary indicates an R Square value of 0.523 meaning that 52.3% change in marketing mix strategies are influenced by customer behaviors, customer preferences, and customer satisfaction. The results are presented in Table 4.4.

Table 4.4: Model Summary for Customer

Model R R Square Adjusted R Std. Error of the Square Estimate 1 .723a .523 .510 .4599 a. Predictors: (Constant), Customer satisfaction, Consumer behavior, Consumer preferences

The regression model was tested for significance using ANOVA. The findings indicate that the model is significant, F (3,110) =40.133, p = 0.000, implying that the independent variables are significant predictors of the dependent variable at 95% Confidence level. The findings are reported in Table 4.5.

Table 4.5: ANOVA for Customer Model Model Sum of Df Mean F Sig. Squares Square 1 Regression 25.469 3 8.490 40.133 .000b Residual 23.269 110 .212 Total 48.737 113 a. Dependent Variable: Marketing mix strategies b. Predictors: (Constant), Customer satisfaction, Consumer behavior, Consumer preferences

The results show that customer-related factors have a significant effect on marketing mix strategies. Customer behavior had a positive and statistically significant effect on marketing mix strategies (p=0.000). Customer preferences had a positive and statistically significant effect on marketing mix strategies (p=0.004). Finally, customer satisfaction also had a positive and statistically significant effect on marketing mix strategies. The regression coefficients are reported in Table 4.6.

Table 4.6: Regression Coefficients for Customer Model Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Beta Error 1 (Constant) .332 .330 1.006 .317 Consumer .409 .097 .344 4.225 .000 behavior Consumer .306 .103 .292 2.968 .004 preferences Customer .211 .091 .214 2.313 .023 satisfaction a. Dependent Variable: Marketing mix strategies

4.4. The Influence of Competition on Marketing Mix Strategy

4.4.1. Threat of Entry

With regard to the threat of entry, the level of agreement with most statements was average and not highly rated. When asked whether other retail outlets in the mall held patents for goods that they sale, only 5.3% strongly agreed and 33.3% agreed, with more than a quarter, 28.1% stating neutrality and 26.3% disagreeing with the statement (M=3.04, SD=1.1047). In the same vein, only 5.3% strongly agreed and 39.5% agreed with the position that competitors in the mall were big and enjoyed economies of scale (M=3.14, SD=1.072). A moderate number of respondents agreed that retail outlets in the mall required high capital levels to enter the market, as indicated by 20.2% strongly agreed and 44.7% agreed (SD=3.75, SD=0.910). Slightly similar results were obtained for the level of regulation of the market segment (strongly agreed, 8.8%; agreed, 48.2%, M=3.51, SD=0.865) and levels of profitability (strongly agreed, 10.5%; agreed, 50.0%, M=3.62, SD=0.841).

Table 4.7: Threat of Entry

SA A N D SD Means Std. Deviation

Threat of Entry Our competitors hold the patents 5.3% 33.3% 28.1% 26.3% 7.0% 3.04 1.047 for the goods they sell Our competitors are big and enjoy 5.3% 39.5% 28.9% 16.7% 9.6% 3.14 1.072 economies of scale (they can sell more volumes at low prices) You need very high capital 20.2% 44.7% 25.4% 8.8% 0.9% 3.75 0.910 requirements to enter into our retail segment There are government policies 8.8% 48.2% 28.9% 13.2% 0.9% 3.51 0.865 that regulate entry to our market segment We enjoy very high levels of 10.5% 50.0% 28.9% 7.0% 3.6% 3.62 0.841 profitability in the industry

4.4.2. Competitive Rivalry

Competitive rivalry was one of the dimensions of competition investigated in the study. In general, the level of agreement with statements on the competitive dimensions was moderate. From the findings, 16.7% strongly agreed and 37.7% agreed with the statement that there are very many small competitors in the mall (M=3.49, SD=1.053). Comparatively fewer respondents strongly agreed (7.0%) and agreed (37.7%) with the statement that competitors were bigger than retail outlets (M=3.21, MD=1.041). There was also moderate level of agreement with the statement that many retail outlets were offering the same products (strongly agreed, 9.6%; 51.8% agreed, M=3.47, SD=1.018). Comparative levels of agreement were recorded for retail outlets offering the same products and same prices (M=3.32, SD=1.083) and retail outlet growth and profitability being hindered by competitors in the mall (M=3.19, SD=1.146).

Table 4.8: Competitive Rivalry

SA A N D SD Means Std. Deviation

Competitive Rivalry We have very many 16.7% 37.7% 24.6% 17.5% 3.5% 3.49 1.053 competitors in the mall Our competitors are bigger 7.0% 37.7% 28.1% 19.3% 7.7% 3.21 1.041 than us in terms of market share There are many retail 9.6% 51.8% 17.5% 15.8% 4.4% 3.47 1.018 outlets that offer the same products that we offer. There are many retail 7.9% 46.5% 23.7% 13.2% 8.8% 3.32 1.083 outlets that offer the same products we offer at the same prices Our growth and 8.8% 40.4% 19.3% 21.9% 8.8% 3.19 1.146 profitability are hindered by competitors

4.4.3. Substitutes

With regard to substitutes, 14.9% strongly agreed and 45.6% agreed that there were many substitutes to the products offered by retail outlets (M=3.53, SD=1.032). Further, 8.8% of the respondents strongly agreed and 38.5% agreed that the retail outlets do not offer unique products (M=3.09, SD=1.245), while 4.4% strongly agreed and 52.6% agreed that retailers are selling at nearly the same price (M=3.35, 1.057). Slightly over half of the respondents indicated that they source products from the same suppliers (M=3.19, 1.120), and that the products they sell were better priced and had better performance features (M=3.19, SD=1.120).

Table 4.9: Substitutes

SA A N D SD Means Std. Deviation

Substitutes There are many 14.9% 45.6% 19.3% 17.5% 2.6% 3.53 1.032 substitutes to the products we offer We do not offer unique 8.8% 38.5% 21.9% 14.0% 16.7% 3.09 1.245 products. Customers can either buy from us or buy from many other stores in the mall We sell at nearly the 4.4% 52.6% 21.9% 15.8% 5.3% 3.35 0.977 same price as other retail outlets offering the same products in the mall We source the products 10.5% 39.5% 25.4% 16.7% 8.0% 3.34 1.057 we sell from nearly the same suppliers Substitutes to the 8.8% 36.0% 32.5% 11.4% 11.4% 3.19 1.120 products we sell are better priced and have better performance features

4.4.4. Inferential Statistics

Multiple regression analysis was used to establish the relationship between competition, measured in terms of the three competitive forces captured in Michael Porter’s five forces theory. The forces were threat of entry, competitive rivalry, and substitutes.

The model summary statistics indicate an R Square value of 0.026, implying that only a 2.6% change in the dependent variable can be attributed to the independent variable. The results show a low predictor value of competition among retail outlets and how it is affecting the choice of marketing mix strategies.

Table 4.10: Model Summary for Competition Model

Model R R Square Adjusted R Std. Error of the Square Estimate 1 .160a .026 -.001 .6571 a. Predictors: (Constant), Substitutes, Threat of entry, Competitive rivalry

Before running regression analysis, the model was tested for significance. The findings show that the model is not statistically significant at 0.05 significance level. The results, F (3,110) = 0.961, p=0.414 imply that competition factors are not a significant predictor of changes in market mix strategies among retail outlets at the Village Market Mall.

Table 4.11: ANOVA for the Competition Model Model Sum of Df Mean F Sig. Squares Square 1 Regression 1.244 3 .415 .961 .414b Residual 47.493 110 .432 Total 48.737 113 a. Dependent Variable: Market mix strategies b. Predictors: (Constant), Substitutes, Threat of entry, Competitive rivalry

Regression coefficients note that there was a positive relationship between threats of entry and the choice of market mix strategies, but the relationship was not statistically significant at 0.05 significance level (p=0.276). There was a positive but not statistically significant relationship between competitive rivalry and marketing mix strategies (p=0.436). On the contrary, the

50 presence of substitutes had a negative effect on the choice of marketing mix strategies even though the effect was not statistically significant (p=0.464).

Table 4.12: Regression Coefficients for the Competition Model Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta 1 (Constant) 3.389 .343 9.872 .000 Threat of entry .159 .145 .150 1.096 .276 Competitive rivalry .094 .120 .132 .783 .436 Substitutes -.105 .143 -.135 -.735 .464 a. Dependent Variable: Market mix strategies 4.5. The Influence of Distribution Channels on Marketing Mix Strategy

4.5.1. Direct Distribution

The researcher was interested in examining the level of agreement with a set of questions on the retail outlet’s use of direct distribution. The respondents strongly agreed (24.6%) and agreed (46.5%) that they adopted a distribution strategy that allowed them to deliver products to customers faster (M=3.84, SD=0.987). The firms also had considerable control over how the products were marketed and sold on their premises, with 15.8% citing a strong agreement, 53.6% agreeing, 15.8% neither agreeing or disagreeing, 11.4% disagreeing and 4.4% strongly disagreeing (M=3.69, SD=0.968). A moderate number of retailers directly responded to customer feedback on product performance (M=3.88, SD=0.914), while building direct relationships with customers (M=3.97, SD=0.875). A comparatively smaller number of responded noted that products could only be bought from the retailer’s fixed locations, with findings indicating that 9.6% expressed strong agreement and 44.7% expressed agreement that the products they sold could only be bought from fixed retail locations (M=3.35, SD=1.052).

Table 4.13: Direct Distribution

SA A N D SD Means Std. Deviation

Direct distribution Our strategy is to deliver 24.6% 46.5% 20.2% 3.5% 5.3% 3.84 0.987 products to customers faster than any other retail outlet We have total control of 15.8% 52.6% 15.8% 11.4% 4.4% 3.69 0.968 how the product is marketed and sold We directly respond to 24.6% 47.4% 21.1% 3.5% 3.5% 3.88 0.914 customer feedback on product performance Our products can only be 9.6% 44.7% 20.2% 20.2% 5.3% 3.35 1.052 bought from our fixed retail locations We build direct 23.7% 57.0% 12.3% 3.5% 3.5% 3.97 0.875 relationships with our customers We do not market or 3.5% 39.5% 10.5% 21.9% 24.6% 2.77 1.296 create awareness for any of the products we sell Our products are low-cost 5.3% 39.5% 24.6% 14.0% 16.5% 3.06 1.172 and are not highly priced

4.5.2. Indirect Distribution

The use of indirect distribution channels was examined based on a set of items. The results indicate that 8.8% strongly agreed and 53.3% agreed that the firm distributed products through distribution agents (M=3.41, SD=1.111). Less than half of the respondents expressly agreed (3.5% strongly agreed and 43.9% agreed) that they focused on building relationships with distributors more than customers (M=3.08, SD=1.111). The proportion that leveraged on existing brand recognition was moderately high (M=3.80, SD=0.857) when compared with

52 those who stated that they get their products from local partners (M=3.49, SD=1.017). When asked whether the retailers interacted directly with end-users of products, 5.3% strongly agreed, 38.6% agreed, 16.7% were neutral, 21.9% disagreed and 17.6% strongly disagreed with the position (M=2.96, SD=1.218).

Table 4.14: Indirect Distribution

SA A N D SD Means Std. Deviation

Indirect distribution We distribute our 8.8% 53.5% 14.0% 13.2% 10.5% 3.41 1.111 products through distribution agents or retailers Our strongest 3.5% 43.9% 19.3% 21.9% 11.4% 3.08 1.111 relationships are with wholesalers and retailers, and not with customers (e.g. our customers are the retailers and wholesalers) We leverage on existing 14.9% 61.4% 11.4% 10.5% 1.6% 3.80 .857 brand recognition for the products we sell Customers can get our 10.5% 50.9% 14.0% 19.3% 5.2% 3.49 1.017 products from other local partners outside the mall We do not interact 5.3% 38.6% 16.7% 21.9% 17.6% 2.96 1.218 directly with the end- users of our products

4.5.3. Intensive Distribution

Intensive distribution is one of the micro-environmental factors that can affect the choice of marketing mix strategies. Findings indicate that 14.9% strongly agreed and 58.8% strongly agreed that the products sold at the retail outlets are not restricted to a single brand (M=3.74,

SD=0.992). Similarly, 13.2% strongly agreed and 57.0% agreed that the products sold at the outlets are interchangeable (M=3.72, SD=0.881). When asked whether the products sold at the outlet are also sold elsewhere in places supermarkets, 7.9% strongly agreed, 48.2% agreed, 20.2% were neutral, 11.4% disagreed and 12.3% disagreed strongly (M=3.30, SD=1.141). Only 3.5% strongly agreed and 39.5% agreed that the outlets are not invested in creating market awareness for the products (M=2.77, SD=1.296). The products sold by retailers were relatively inexpensive (M=3.06, SD=1.172).

Table 4.15: Intensive Distribution

SA A N D SD Means Std. Deviation

Intensive distribution We sell different products 14.9% 58.8% 10.5% 7.0% 9.0% 3.74 0.992 at our stores and are not restricted to brands from a single or few industry The products we sell are 13.2% 57.0% 19.3% 7.0% 3.5% 3.72 0.881 interchangeable. If a customer finds that one brand is unavailable from our shelf, they can pick another brand rather than going to another store The products we sell are 7.9% 48.2% 20.2% 11.4% 12.3% 3.30 1.141 also sold anywhere outside the mall, including in supermarkets and small retail outlets We do not market or 3.5% 39.5% 10.5% 21.9% 24.6% 2.77 1.296 create awareness for any of the products we sell Our products are low-cost 5.3% 39.5% 24.6% 14.0% 16.5% 3.06 1.172 and are not highly priced

4.5.4. Inferential Statistics

Multiple regression analysis was used to establish the relationship between distribution channel and marketing mix strategies. The dimensions of the distribution channel included in the model were direct distribution, indirect distribution, and intensive distribution.

The findings indicate that the R Square value for the model was 0.300. This means that independent variables were responsible for the 30.0% variance in marketing mix strategies. The model summary is presented in Table 4.16.

Table 4.16: Mode Summary for the Distribution Channel Model

Model R R Square Adjusted R Std. Error of the Square Estimate 1 .548a .300 .281 .5567 a. Predictors: (Constant), Intensive distribution, Direct distribution, Indirect distribution

The regression model was tested for statistical significance. The results found out that the model is statistically significant at 0.05, F (3,110) =15.750, p=0.000. This implies that the distribution channel factors are statistically significant predictors of marketing mix strategies at 95% confidence level. The results are presented in Table 4.17.

Table 4.17: ANOVA for Distribution Channel Model Model Sum of Df Mean F Sig. Squares Square 1 Regression 14.644 3 4.881 15.750 .000b Residual 34.093 110 .310 Total 48.737 113 a. Dependent Variable: Market mix strategies b. Predictors: (Constant), Intensive distribution, Direct distribution, Indirect distribution

The regression coefficients showed the level of significance for each distribution channel factor. Direct distribution had a positive and statistically significant effect on marketing mix strategies at 0.05 significance level (p=0.000). Indirect distribution had a positive effect on marketing mix strategies, but the effect was not statistically significant at 0.05 significance level (p=0.702). There was a negative relationship between intensive distribution and

55 marketing mix strategies, however, the relationship was not statistically significant (p=0.317). The findings are presented in Table 4.18.

Table 4.18: Regression Coefficients for Distribution Channel Model Model Unstandardized Standardized t Sig. Coefficients Coeff8cients B Std. Beta Error 1 (Constant) 2.306 .292 7.894 .000 Direct .488 .076 .571 6.454 .000 distribution Indirect .039 .102 .048 .384 .702 distribution Intensive -.106 .105 -.124 -1.006 .317 distribution a. Dependent Variable: Market mix strategies

4.6. Chapter Summary

The chapter presents a detailed description of the results and findings obtained in the study. The results encompass descriptive and inferential statistics on demographic information, customer related factors, competition related factors and distribution related factors and how they relate to marketing mix strategies. The study finds very high level of agreement with customer related factors and moderate level of agreement with competition and distribution factors. Customer and distribution related factors had a significant association with market mix strategies, while competition related factors did not have a significant effect on marketing mix strategies adopted by retail outlets operating at the Village Market Mall. The next chapter presents the discussion of the findings, conclusions drawn from the findings, and recommendations for practice and further studies.

CHAPTER FIVE

5.0. DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS

5.1. Introduction

The chapter is the final section of the research project. It summarizes the study, discusses the findings based on the research objectives, draws conclusions for each objective, and presents recommendations drawn from the results and findings to inform practice and stimulate further research on the link between micro-environment factors and marketing strategies.

5.2. Summary

The study sought to investigate the influence of micro-environment factors on marketing mix strategy. The micro-environment factors in the study were customers, competition, and distribution. The specific objectives were to investigate the influence of customers on marketing mix strategy, determine the influence of competitive forces on marketing mix strategy, and establish the influence of distribution on marketing mix strategy among retail business in shopping malls in Nairobi.

The study adopted a descriptive research design. The population was drawn from retailers operating in Village Market Mall. A total of 239 retailers were operating in the mall. A simple random sampling technique was used to generate a sample size of 150 retailers for the study. Data was collected using a validated and standardized questionnaire. The questionnaire was self-administered to the respondents at their place of work. Collected data was cleaned and analyzed using SPSS 23 for descriptive and inferential statistics. The descriptive measures included frequencies, percentages, means and standard deviations. To establish the influence of micro environment factors on market mix strategy, the study used multiple regressions. The results were presented using charts, graphs, and tables, accompanied by narrative descriptions.

The first objective of the study was to investigate the influence of customers on marketing mix strategy. Customers were examined on the basis of customer behavior, customer preferences, and customer satisfaction dimensions. Findings on customer behavior show that customers were concentrated around where the outlet was operating. Customers were also attracted to the stores due to the outlet’s design aesthetics and display. The store was situated in a

57 neighborhood where customers had disposable income that could allow them to access products and services at the prices offered at the mall. Findings on customer preferences indicated that customers made decisions based on the prices offered, and that the preference of one retailer to the other was dependent on the prices of the products. Customers also preferred the malls due to high perception of product quality and benefits of effective product promotions, since they were mainly drawn to recognizable brands. Customer satisfaction levels were comparatively high and driven by product quality, staff responsiveness, and customer loyalty. Multiple regressions demonstrated that all the dimensions of customers, notably, customer satisfaction, customer preferences, and customer satisfaction had a positive and statistically significant influence on marketing mix strategy.

The second objective was to investigate the influence of competitive forces on marketing mix strategy. Three competitive forces: threat of entry, competitive rivalry, and substitutes, were examined. In terms of the threat of entry, retailers moderately agreed that goods they sold were from patented innovations and that competitors enjoyed economies of scale. A significant amount of capital was also needed to enter the market, and government regulation and levels of profitability influenced competition among retailers. On competitive rivalry, retailers noted that there were many small competitors in the mall, rather than big competitors. The prices were comparable with retailers dealing in similar products. Most products had substitutes drawn from the same group of suppliers. The retailers contended that the price and performance attributes were competitive. However, the competitiveness of the retailers was greatly dependent on the competitiveness of the mall. As a result, even though the study reported a positive relationship between the threat of entry and competitive rivalry, these did not have a statistically significant influence on marketing strategy. The abundance of substitutes had a negative but not statistically significant influence on the retail outlet’s marketing strategy.

The third objective investigated the influence of distribution on marketing strategy decisions. The researcher looked at the different types of distribution channels: direct, indirect and intensive, and how they influenced marketing strategy decisions. Direct distribution channels were characterized by delivering products faster to customers, possessing considerable control over product marketing and selling, building direct relationships with customers and accessing goods only in fixed positions. The level of agreement with these characteristics was slightly

58 above average. Indirect distribution was characterized by distributing products through agents, building relationships primarily with distributors, leveraging existing brand recognition, and interacting more with end-users. Findings indicated comparatively low levels of agreement when compared to direct distribution. Extensive distribution, characterized by characteristics from the two channel strategies, reported moderate level of agreement among respondents. Overall, multiple regression demonstrated that direct distribution was the main predictor of marketing mix strategy, as opposed to indirect or extensive distribution.

5.3. Discussions

5.3.1. The Influence of Customers on Marketing Mix Strategy

Consumer behaviors influence how customers choose, purchase, use, and dispose of products or services. The study established that retail outlets. The present study has established that consumers are shopping at the retail outlets because of proximity. These consumers do not only live near the shopping mall but also have adequate disposable income to access products and services provided at the mall. The selection of one retail outlet, among competitors, is influenced by the store’s design and product display. In addition, they also take the extra step to examine what retail stores offer through information searches before making a purchasing decision. Customer behaviors were found to exert a significant influence on the strategies adopted by the retailers to market themselves and their products.

Other scholars have also observed the phenomenon reported in this study. Bakator et al. (2016) noted that when companies use pricing strategies as part of the marketing mix strategy, they must take into account the perceptions of customers about pricing. This is important because if a company sets a higher price that is above customer expectations, the likelihood of low sales and low profitability increases. As a result, setting the right price, as a marketing strategy, must be aligned with price perceptions in the market for the overall goal of higher sales volumes and higher profit margins to be realized. It is for this reason that Bakator et al. (2016) argued that companies must understand consumer behavior in order to respond to their needs and desires.

Lin et al. (2012) noted that creating a marketing strategy demands that firms must perform problem recognition, information search, alternative evaluation, purchasing and post-purchase evaluation. Nugroho and Irena (2017) added that understanding customer behavior means

59 examining psychological factors that relate to the purchase intention. Such behaviors can be personal, social or cultural influences and understanding them enables a company to develop an appropriate marketing strategy.

Other characteristics of consumer behavior that gave been identified in research are price, interior, promotional tool, location, range of products, experiential zone, quality and availability. Arbaina and Suresh (2018) found out that these attributes have a statistically significant influence on both purchase intention and marketing strategy. Mehrizi and Zahedi (2013) also found a significant link between marketing strategies and consumer behavior.

The study also established that customer preferences play a central role in not only influencing purchasing decisions but also exert influence on what marketing strategies are deemed effective by the outlets. The study found out that customers made purchasing decisions based on prices, and preferred making purchases in the mall due to perceived high-quality products. Customers also followed product promotions and were influenced by how the retail outlets did their product placement. Customer preferences had a positive and statistically significant effect on marketing mix strategies.

Sulaiman and Masri (2017) noted that customer preferences, defined as feelings of pleasure of disappointment after consuming a product, has a significant effect on whether a customer will purchase and consume a product again or whether they will opt for products from competitors. Sulaiman and Masri (2017) reiterate that higher levels of consumer preference not only increase the likelihood of purchases but are also important indicators that companies use to develop marketing strategies.

A study by Getzner and Grabner-Krauter (2015) investigated the relationship between consumer preferences and marketing strategies, and established that personal factors such as the education level of a customer can influence their willingness to purchase a product. As such, such personal characteristics must be incorporated in developing models for marketing strategies. Egboro (2015) demonstrated that customer preferences can also be influenced by technology, economy, intelligence responsiveness, competition and management competency. Miriti (2016) found a statistically significant relationship between marketing strategy on consumer preference among retail brands in Nairobi.

Satisfied customers are an indicator of how well the retail outlet is managing customer-related dimensions. The study established that customer satisfaction was primarily driven by the perception of product quality and staff responsiveness. Satisfied customers were more likely to make repeat purchases, were loyal, and marketed the retail outlet through word-of-mouth recommendations to family and friends. Customer satisfaction also had a positive and statistically significant effect on marketing mix strategies.

Consumer satisfaction can also be achieved through effective marketing strategies (Shaw, 2012). To be effective, marketing strategies must identify expectations of consumers in terms of product, price, promotion and place, which are the 4Ps of the marketing mix strategy. Ebitu (2014) adds that when marketers understand that adequately satisfying the demands of consumers, then it is possible to execute strategies that are aligned with the overall goal of improving the financial performance of the company. Marketing strategy can be long term or short term, however, irrespective of the duration, the organization, formulation, evaluation and selection of market-oriented strategies as well as the successful implementation of these strategies is determined by the level of customer satisfaction (Youjae, 2010). Azizi et al. (2015) concluded that the idea of relationship marketing holds that companies should identify, anticipate and satisfy customer requirements.

5.3.2. The Influence of Competition on Marketing Mix Strategy

Companies compete with other companies in the market for customers. There are various factors that influence a company’s competitive position. Michael Porter’s five forces theory is one model for conceptualizing these relationships. In this study, three out of the five elements in the theory were incorporated in this study. The researcher looked at the threat of entry, competitive rivalry, and substitutes, and how these influence decisions on marketing strategies. The study established that the barriers to market entry were moderately influential, as demonstrated by patenting, economies of scale, capital outlay, and industry regulation.

According to Lawrence (2011), it is easy for competitors to enter the market when the barriers of entry are low, however, this increases competition in the absence of increased consumer demand. Therefore, firms that are not able to thrive in a heightened competitive environment are likely to suffer from reduced profits. Marketing strategies can help firms to identify and

61 exploit opportunities and stay ahead of competition. Chiteli (2013) adds that having access to adequate capital is important because forms with substantial financial resources can increase investments in marketing, adopt pricing strategies that can force bigger competitors to reduce their prices, and execute strategies that allow it to tap into the market share of competitors.

Results on competitive rivalry showed that there were many small competitors in the market and fewer big competitors. Kaunyangi (2014) noted that the relative position of a firm in the market is influenced by its ability to withstand, survive and over-compete other firms in the same market. With the current study showing that most retail outlets were selling similar products, this shows that there is little differentiation in the market and customers are more likely to make their purchasing decisions based on brand loyalty and price comparisons. Kaunyangi (2014) reiterates that A highly competitive business environment results in competitiveness in prices, which subsequently affects the profitability and performance of firms.

In a study by Ogaga (2017) the researchers found out that there is a link between competition and corporate strategy. The study, which focused on firms listed at the Nairobi Securities Exchange, revealed that industry competition has a moderating effect on the association between corporate strategy and organizational performance. O’Cass and Weerawardena (2017) reported that an industry’s competitive intensity has a positive impact on marketing capability. On the other hand, Takata (2016) found out that marketing capabilities is the strongest driver of business performance, followed by competitive rivalry and the power of suppliers. Another study also reported that adopting a certain marketing strategy can have a significant effect on firm competitiveness. The study was a review of empirical literature and therefore did not present statistical analysis of primary data (Githaiga, Namusonge, & Kihoro, 2016).

Findings on substitutes revealed that most retail outlets stocked substitutes and that they did not offer unique products. These products also retailed at nearly same prices. Substitutes were found to exert a negative effect on the development of marketing strategies. Azzam (2018) noted that firms cannot depend on the same products forever, as such, they must invest in marketing strategies so as to identify new areas of growth. Camison and Lopez (2010) added that competitive pressures force firms to establish strategies that can help in increasing competitive advantage. One of those strategies is the introduction of new products or

62 modification of existing products. Retailers must innovate by increasing the diversity of their product offerings or the abundance of substitutes in the mall can reduce their competitive advantage.

5.3.3. The Influence of Distribution Channels on Marketing Mix Strategy

Distribution channels differ from firm to firm. The choice of a distribution channel is determined by a multitude of factors, however, there are three main topologies of distribution: direct, indirect and intensive. In the study, the level of agreement shows that direct distribution was the most dominant. Retailers noted that they have adopted a distribution strategy that allowed faster delivery of products. The retailers also had considerable had considerable control over how the products were marketed and sold on their premises and directly responded to customer feedback on product performance. The products were mainly being sold at retailer’s branded stores and locations. The findings further demonstrated a positive effect of this choice of distribution on the marketing strategy.

According to Mwanza and Ingari (2015), firms that use direct distribution sell directly to consumers without passing through intermediaries. They engage in face-selling or sell over the internet via e-commerce sites. Since the overall goal of distribution is to improve customer experiences, direct distribution channels allow the outlet to build relationships with the customer. It is through this phenomenon that distribution positively affects marketing strategy because consumer experiences can be enhanced through a set of marketing strategies, including design and branding of the physical stores and offering value-add services. A study by Koster (2018) looked at the direct distribution strategies for online retailers and revealed that they enhance delivery lead times.

The presence of indirect distribution channels was also examined among retail outlets at Village Market. Compared to direct distribution, the level of agreement with characteristic features of indirect distribution was lower. Nonetheless, there are those who used distribution agents to get the products to the consumer, focused on retailer-distributor relationship rather than retailer-customer relationship, leveraged on brand recognition, and interacted to a small extent with end-users of the products. Regression analyses reported a positive effect on marketing mix strategies, but the effect was not statistically significant.

The indirect distribution channel applies to distributors that outlets that sell through other retailers. A study by Kafaerpour (2015), focusing on Samsung Company, showed that the success of the channel is dependent on stock (in terms of stock availability, supervision of distribution agents, supervision on product delivery time), and distribution channels (in terms of sales offices of the company, distribution agents of the company, supervision of products delivery companies). Aleksandra, Nada, and Marija (2017) reported that the performance of indirect distribution is dependent on the size of the sales network and the number of sales facilities. In an analysis of the source of competitive advantage among certain FMCG firms in Kenya, Mwanza and Ingari (2015) demonstrated that direct distribution, indirect distribution, and intensive distribution had a positive effect on creating competitive advantage. Similar findings were reported by Adimo and Osodo (2017).

On the other hand, findings on intensive distribution showed comparatively lower level of agreement with whether the retailers sold different products without restriction to a few brands, whether what they sold was interchangeable, and whether the products they sold were found elsewhere outside the mall, such as in supermarkets.

When firms use an intensive distribution channel, their primary objective is to utilize all possible outlets to distribute their products. Marketing strategy comes into play when determining not only the kind of product but also the characteristics of potential customers being targeted. Most firms that adopt intensive distribution have the long-term goal of being dominant in the industry and controlling the supply chain and customer experiences. This level of control comes into play when making marketing decisions.

Aila, Ondiek, Mise, and Odera (2015) studied distribution channels in a soft drinks company in Kenya to determine the effect on delivery cycle time, stock availability and customer value. Findings indicated that there was a strong correlation between delivery time and stock availability, and subsequently, customer value. This means that marketing strategies built around delivery time are more likely to be effective. Marmullaku and Ahmeti (2015) found out that distribution strategies had a significant effect on marketing strategies such as pricing and advertising.

5.4. Conclusion

5.4.1. The Influence of Customers on Marketing Mix Strategy

Customer related micro-environment factors have a positive and statistically significant influence on market mix strategy among retail outlets in Kenya. Customer behavior was expressed in terms of personal, cultural, and social attributes. A majority of customers lived in the neighborhood of the mall and had disposable incomes allowing them to access products from the mall. Other behavioral attributes included attraction to store designs and product displays and shopping at specific time of the day or seasons. Consumer preferences were based on prices of products, stores, product quality, product promotion and brand identity. Customer satisfaction showed high levels of satisfaction with the quality of products or services, pricing of products or services, staff responsiveness, and customer loyalty. Overall, customer behaviors, customer preferences, and customer satisfaction had a positive and statistically significant influence on market mix strategies.

5.4.2. The Influence of Competition on Marketing Mix Strategy

Competition related micro-environment factors have a positive but not significant effect on marketing strategy among retail outlets in Kenya. Competition was conceptualized based on Michael Porter’s five forces theory. There was a moderate level of agreement with items relating to threat of entry, competitive rivalry, and substitutes. The threat of entry is determined by the extent to which firms hold patents as an indicator of innovativeness, exploitation of economies of scale, capital resources, government policies and industry profitability. Competitive rivalry was influenced by the number of competitors in the mall, relative sizes of competitors, products offered by competitors, prices offered by competitors, and profitability of competitors. Finally, substitutes related to the number of substitutes available to customers in the mall, level of product differentiation, pricing of substitutes, supplier structure, and performance features of substitutes. Multiple regressions revealed a positive but not significant relationship between threats of entry and the choice of market mix strategies, a positive but not statistically significant relationship between competitive rivalry and marketing mix strategies, and a negative non-significant effect on the choice of marketing mix strategies.

5.4.3. The Influence of Distribution Channels on Marketing Mix Strategy

Distribution channels, as micro-environment factors, have a positive and statistically significant influence on the marketing mix strategy of retail outlets in Kenya. Distribution channels are varied and range from direct to indirect to intensive. With respect to direct distribution, the findings revealed that the firms had adopted a distribution strategy that allowed them to deliver products to customers faster, and the firms had considerable control over how the products were marketed and sold on their premises. A moderate number of retailers directly responded to customer feedback on product performance, while building direct relationships with customers. The outlets sold from specific branded stores and locations. In terms of indirect distribution, the results indicated that some firms distributed products through distribution agents, with even lower numbers focusing on building relationships with distributors more than customers, leveraging on existing brand recognition, interacting directly with end-users of products. Intensive distribution is one of the micro-environmental factors that can affect the choice of marketing mix strategies. Findings indicate that products sold at the retail outlets are not restricted to a single brand, and they were also sold in outside the mall by retailers such as supermarkets. The regression results showed that direct distribution had a positive and statistically significant effect on marketing mix strategies. Indirect distribution had a positive effect on marketing mix strategies, but the effect was not statistically significant, while there was a negative relationship between intensive distribution and marketing mix strategies.

5.5. Recommendations

5.5.1. Recommendations for Improvement

5.5.1.1. The Influence of Customers on Marketing Mix Strategy

In terms of customer behavior, retail outlets should upgrade store designs and product display formats, increase the availability of store information online to aid information searches, and align operational hours according to customers shopping habits such as time of the day, weather, or season. In terms of customer satisfaction, the retail outlets should establish competitive prices, increase the quality of products offered, increase promotions, and stock highly established brands. Finally, with regard to customer satisfaction, the firm’s marketing

66 strategies should focus on improving the quality of service, staff responsiveness, and product quality.

5.5.1.2. The Influence of Competition on Marketing Mix Strategy

To improve the competitive position of the firms, the retail outlets should innovate, exploit economies of scale, and build capital reserves in anticipation of changing market conditions and to respond to market opportunities before other competitors. There is highly competitive rivalry at the mall, as characterized by many small outlets selling similar products and similar prices in the market. Finally, to overcome the abundance of substitutes offered within the mall, the firms should adopt a differentiation strategy to enhance the variety of product offerings available to customers.

5.5.1.3. The Influence of Distribution Channels on Marketing Mix Strategy

Direct selling is the most prominent strategy adopted by retail outlets at the mall. To exert positive impacts on marketing strategies, focus should be on improving the efficiency of product delivery to customers, investing additional resources in marketing of stores and products. Retailers should also build enhance experiential satisfaction with customers, while also establishing more locations where customers can access products.

5.5.2. Recommendations for Further Studies

The scope of the study was limited to investigating the effect of three micro-environment factors: customers, competition, and distribution, on market mix strategies. Further studies can examine other micro-environment factors not captured in the study. While competition is conceptualized under Michael Porter’s theory to comprise of five elements or forces, this study only investigated three forces. Future studies can incorporate other competitive forces in the regression models to determine whether there are variances in the relationship with market mix strategy.

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APPENDICES

APPENDIX I: INTRODUCTION LETTER

Dear Respondent,

My name is Maureen Wanjiku Gichiri. I’m a student at USIU pursuing a Masters in Management and Organizational Development. As part of the program, I’m required to do field research work. My research is focused on “The Influence of Micro Environment Factors on Marketing Mix Strategy: A Case of Retail Businesses Within Shopping Malls in Nairobi.”

The objective of the study is to investigate how three micro environment factors: customers, competition, and distribution, and how they affect your marketing strategy. To do this, I must collect data from retail businesses at the Village Market.

This email is a request that you help me complete the questionnaire. It will only take 10 minutes of your time.

The questionnaire will not collect personal information like your name or the name of your business.

Please click on this link and complete the questionnaire https://forms.gle/qyS5N86chBp9YVok6

Thank you for the assistance.

APPENDIX 2: QUESTIONNAIRE

PART A: BACKROUND INFORMATION 1. What is your age in years? 18-24 years old ( ) 25-34 years old ( ) 35-44 years old ( ) 45-54 years old ( ) Over 55 years old ( ) 2. What is your gender? Male ( ) Female ( )

3. What is your level of education? Primary school certificate ( ) Secondary school certificate ( ) Diploma ( ) Bachelor degree ( ) Masters degree ( ) PhD ( )

PART B: CUSTOMER FACTORS 4. To what extent do you agree with the following statements about customer-related factors? (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5= Strongly Agree) 1 2 3 4 5 Customer Behavior a) Our customers are highly concentrated where we operate our retail outlet b) Our customers are attracted to the store design and how we display our products c) Our customers have adequate disposable income to afford the prices we offer d) Our customers’ shopping habits are dependent on the time of day or weather of the season

e) Our customers go the extra step to search for information about us and the products we offer Consumer Preferences a) Customers buy from us because of the prices of our products b) Customers buy from us because they prefer our stores c) Customers buy from us because of the quality of our products d) Customers buy from us because of the promotions on products e) Customers buy from us because of they prefer our brands Customer Satisfaction a) Customers are satisfied with the quality of service b) Customers are satisfied with the amount of help they receive from our staff c) Customers are satisfied with the pricing of goods in our stores d) Most of our customers are repeat customers e) Customers recommend our store to friends and colleagues

PART B: COMPETITION FACTORS 5. To what extent do you agree with the following statements about competition-related factors? (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5= Strongly Agree) 1 2 3 4 5 Threat of Entry a) Our competitors hold the patents for the goods they sell b) Our competitors are big and enjoy economies of scale (they can sell more volumes at low prices) c) You need very high capital requirements to enter into our retail segment d) There are government policies that regulate entry to our market segment e) We enjoy very high levels of profitability in the industry Competitive Rivalry a) We have very many competitors in the mall b) Our competitors are bigger than us in terms of market share c) There are many retail outlets that offer the same products that we offer. d) There are many retail outlets that offer the same products we offer at the same prices e) Our growth and profitability are hindered by competitors Substitutes a) There are many substitutes to the products we offer b) We do not offer unique products. Customers can either buy from us or buy from many other stores in the mall

c) We sell at nearly the same price as other retail outlets offering the same products in the mall d) We source the products we sell from nearly the same suppliers e) Substitutes to the products we sell are better priced and have better performance features

PART B: DISTRIBUTION CHANNEL FACTORS 6. To what extent do you agree with the following statements about distribution channel-related factors? (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5= Strongly Agree) 1 2 3 4 5 Direct distribution a) Our strategy is to deliver products to customers faster than any other retail outlet b) We have total control of how the product is marketed and sold c) We directly respond to customer feedback on product performance d) Our products can only be bought from our fixed retail locations e) We build direct relationships with our customers Indirect distribution a) We distribute our products through distribution agents or retailers b) Our strongest relationships are with wholesalers and retailers, and not with customers (e.g. our customers are the retailers and wholesalers) c) We leverage on existing brand recognition for the products we sell d) Customers can get our products from other local partners outside the mall e) We do not interact directly with the end-users of our products Intensive distribution a) We sell different products at our stores and are not restricted to brands from a single or few industry b) The products we sell are interchangeable. If a customer finds that one brand is unavailable from our shelf, they can pick another brand rather than going to another store c) The products we sell are also sold anywhere outside the mall, including in supermarkets and small retail outlets d) We do not market or create awareness for any of the products we sell e) Our products are low-cost and are not highly priced

PART B: MARKET MIX STRATEGY 7. To what extent do you agree with the following statements on market-mix strategy? (1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5= Strongly Agree) 1 2 3 4 5 Product strategies a) Our marketing strategy presents reliable and accurate information about goods sold at our stores b) Our retail outlet stocks a wide variety of products c) Our products have a broad market appeal Price strategies a) Our retail outlet routinely monitors the prices and price changes implemented by our competitors and respond effectively b) Our retail outlet clearly communicates our prices to customers c) Our retail outlet offers discounts on products Place strategies a) Our retail outlet is located in an accessible and convenient location close to our customers b) Our retail outlet has is a comfortable and clean with clear signs showing customers directions c) Our retail outlet is designed to achieve a specific brand and image Promotion strategy a) Our retail outlet carries out many promotion campaigns on products and services b) Our retail outlet offers a lot of discounts such as cash, sale, and trade discounts to customers c) Our promotional strategy successfully elicits attention and enhances purchase intention

APPENDIX 3: LIST OF RETAIL OUTLETS

Shop/Trading Name Ground Floor Phase 7 1 Pizza Hut 2 Afta Eats 3 Alexandre's Chocolatier 4 Lorenzo 5 Rocco Mama 6 Erita Jewels 7 MAC instore 8 Goodlife Pharmacy 9 Baby shop 10 Bossini 11 Markham 12 Text Book Centre 13 Adidas 14 Nairobi Sports House 15 Artz 16 Optica Limited 17 Sterns 18 Rodeo Drive 19 Safaricom 20 Rupas 21 Techmart 22 Sunny Forex Bureau 23 Healthy U 24 Joo & Co 25 Village Supermarket 26 Village Cellar 27 Pasta Republic 28 Enoteca 29 Hi Kitchen 30 Off the Rocks 31 Taco 32 Zucchini-Ice Cream 33 Sina Shaka 34 Milola 35 Santorini 36 Souk 37 Tiramisu

38 Anise 39 Milola 40 Absolute Chocolate 41 Brown Cheese 42 Activation Kitchen 43 Spring Valley Coffee 44 Maru Bhajia 45 East Pocha 254 46 Zeeshan 47 Han Ji's Corner 48 Keventers First Floor Phase 7 49 Elias 50 SK Collection 51 OdaOmo 52 100years 53 Kshmr 54 DreamNails 55 Vacant 56 Equity Bank 57 Foschini 58 Fiona Kay 59 Woolworths 60 El Baul 61 Trevor Collections 62 Accessorize 63 Designing Africa Collective 64 Safebox 65 HanifabyHanifa 66 Moksh 67 Coco Lili 68 Vacant 69 Vivo Activewear 70 Hotpoint 71 I&M Bank 72 Vacant 73 Rose Jewellery Second Floor Phase 7 74 Vacant Kiosk 75 Vacant (Ferrari) 76 MP SHAH

77 Versatile Photographers 78 Refinery Grooming Third Floor Phase 7 79 Ballpoint 80 Ignite Fourth Floor Phase 7 81 Virtual Reality 82 Under the sea Children's Play area 83 Trampoline Park Link Area 84 Credible Sounds 85 Zeytoon 86 Lintons 87 Zinj 88 CJ's 89 Power Innovations 90 Kitengela Hot Glass Ltd 91 Kikoy 92 Invu (tuk tuk) Ground Floor -Old Phase 93 City Walk Ltd 94 Art Café Coffee & Bakery Ltd 95 Zucchini Greengrocers 96 Vacant 97 Chemichemi 98 Prime Cuts Butchery 99 Prime Cuts Deli 100 Tiramisu 101 Vacant 102 Nyama Mama 103 EAST 104 Sofra 105 VAcant 106 Orchid 107 Khazana 108 Thai Village 109 Pomodoro 110 Sensations 111 Toyworld 112 Past & Present 113 Yves Rocher

114 Mille Collines 115 Elias 116 Sweet Street 117 Wynton House of Music 118 HandCraft Place 119 Technology House Kenya 120 Technology House Kenya 121 Mocca 122 Fashion& Accessories 123 Kashmir Arts 124 Jit Gems 125 Telkom Kenya Limited 126 Pop-up 127 Village Photoshop 128 One Way 129 Samsonite 130 Bata 131 Rossetti 132 Blue Rhino 133 Artz 134 Kingsway Tyres Ltd Ex-Nakumatt Ground Floor 135 Homebox +Max 136 Clarks 137 Skechers 138 ANta 139 Gamechangers 140 Bottego 141 Airtel 142 Kenya Valuers 143 Aryana 144 Pop-Up 145 ABSA 146 Bbrood Kiosk 147 Coldstone 148 Vacant Unit 149 JIT Craft 150 Party Shop 151 Maasai Treads 152 Chapa Copy 153 Jaffs

154 Garnet Pharmacy 155 Barton collection 156 Beauty Point 157 Haute Perfumerie 158 Blue Lily Flower Crafts 159 All Times 160 Miniso First Level -Old Phase 161 AA Kenya 162 Tintoria 163 Densey Travel 164 KCB Bank 165 Kalabash 166 Elixir Health 167 Pinkopallino Gallery 168 Trevor Collections 169 Sandstorm Africa 170 Persian Bazaar 171 Salon Natali 172 Nikon 173 Fabric Gallery 174 Grassroots Salon 175 Trevor Collections 176 Osteria 177 Design Living 178 Ella Anatomic 179 Vacant (Lintons) 180 Phoenix Safaris 181 JPR Safari Camps 182 Kazuri Beads 183 Coco Chic 184 Made In Africa 185 Patrick Mavros 186 Nobri| Home 187 Enanai & Ikwetta 188 Exhibition Hall 189 Afrika handmade 190 Pop -Up 1 191 Highport Merchants Ltd -Office 192 VFS International Ltd 193 Ikono Investment Ltd

194 Athens 195 JPR offices 196 Wynton House of Music 197 Big unit -Former Athens 198 FAPCL 199 Salvatore 200 Non-Solo Gelato 201 Art Café Coffee & Bakery 3rd Level 202 Dr Kassiri Essajee & Associates 203 Blossom Aesthetics 204 Desert Rose 205 Salon Malibu 206 Vacant 207 TRevor Collections offices 208 Mugg & Bean 209 Local Grill 210 Karel Lounge 211 SBM Bank 212 Commercial Bank of Africa Ltd First Floor (Ex Nakumatt ) 213 Carrefour 214 Diamond Trust Bank (K) Ltd 215 NIC Bank Limited 216 Between The Lines 217 Mac Store 218 New Pop-up 219 Zuku 220 Samsung 221 Rus Interiors 222 Prime Bank 223 KFC Rooftop 224 Shifaz Veterinary Clinic 225 Mobile Klinik 226 Josh Designer -Service Centre 227 Tropical promoters Limited - 228 Village Sacco -Office 229 Post Office 230 DHL Worldwide Express Ltd 231 AA -Classroom

232 N/A 233 Safaricom Limited - Micro Cell Unit 234 CFC Bank Ltd - ATM 235 Tropical promoters Limited-Kiwi Stand 236 Liquid Telecommunications (K) Ltd 237 Jamii Telecommunications Ltd 238 Co-operative Bank of Kenya Ltd 239 Standard Chartered Bank Ltd

APPENDIX 4: IRB APPROVAL

APPENDIX 5: NACOSTI PERMISSION

APPENDIX 6: NACOSTI RESEARCH LICENSE