The influence of Entrepreneurial and Customer
Orientation at a retailer’s performance, and the
moderating role of the retailer’s size
Jan Jacob van der Zee S2582368
Supervisor: dr. A.J. Rauch Co-assessor: dr. F. Noseleit
University of Groningen Faculty of Economics and Business Programme: MSc Business Administration Specialization: Small Business and Entrepreneurship
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Abstract
Retailers are influencing the customer every day, and therefore they are a big player in our market. There are approximately 100.000 retailers with physical stores in the Netherlands, but this number is decreasing. Nevertheless, the number of webshops is increasing. In 2006, the Netherlands counted 12.500 webshops. In 2014 it already reached 50.000 webshops. This changing world makes it necessary for retailers to be entrepreneurial and customer oriented, in order to gain a competitive advantage. Therefore we will look at the Entrepreneurial Orientation (EO) and the Customer Orientation (CO) of retailers. Next to that, it seems interesting to see whether the size of a retailer matters (micro-sized retailers versus larger retailers).
This study focuses on the EO-performance and the CO-performance relationship. Does a high EO and CO relate to a high performance at retailers? Next to that, this study wants to find out whether a micro-sized retailer strengthens the EO-performance and CO-performance relationship. To find out, 89 retailers filled in a questionnaire. These questionnaires have been analyzed in SPSS. The results state that EO is positively related to performance at retailers. Unfortunately there was not enough evidence to conclude that CO is positively related to
performance. Next to that, moderating influence of the micro-sized retailer was not significant at both relationships.
2 Table of contents Introduction ... 4 Research Framework ... 7 Entrepreneurial Orientation ... 7 Innovativeness... 7 Risk-taking ... 8 Proactiveness... 8 Competitive Aggressiveness ... 9 Autonomy ... 9
The EO-Performance relationship at retailers ... 10
Innovation and performance ... 10
Risk-taking and performance ...11
Proactiveness and performance... 12
Competitive Aggressiveness and performance ... 12
Autonomy and performance ... 13
Customer Orientation ... 13
Customer Orientation and performance ... 15
The moderating influence of the retailer’s size at the EO-Performance relationship ... 15
The moderating influence of the retailer’s size at the CO-Performance relationship ... 16
Conceptual model ... 17
Research Design... 19
Research approach ... 19
Development of the questionnaire ... 19
Content of the questionnaire ... 19
Sample and data collection ... 20
Research measures, reliability, and validity ... 22
Entrepreneurial Orientation ... 22
Customer Orientation ... 23
Performance ... 24
Retailer’s size: the interaction variable ... 25
Data collection, analysis and findings ... 26
Correlation analysis ... 26
Regression analysis of EO ... 27
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Discussion and conclusion ... 30
Discussion ... 30
The EO-performance relationship... 30
The CO-performance relationship ... 30
The influence of the retailer’s size at the EO/CO-performance relationship ... 31
Theoretical and managerial implications ... 32
Limitations of this study ... 33
Suggestions for future research ... 34
References ... 36
Appendices ... 42
Appendix I: Questionnaire ... 42
Appendix II: The EO-scales ... 50
Appendix III: Validity EO ... 52
Appendix IV: Reliability EO ... 54
Appendix V: The CO-scales ... 55
Appendix VI: Validity CO without exclusion CO8 ... 56
Appendix VII: Validity CO with exclusion CO8 ... 57
Appendix VIII: Reliability CO ... 58
Appendix IX: The performance-scales ... 59
Appendix X: Validity Performance ... 60
Appendix XI: Reliability Performance ... 61
Appendix XII: Correlations ... 62
Appendix XIII: Regression Analysis of EO ... 63
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Introduction
Retailers are trying to get in contact with the customer every day, and they probably succeed most of the time. Look around when you walk down the street: retailers are trying to get you into their stores by using various marketing tools (e.g. promotions, scent, or their store presentation) (van Herpen, van Nierop, & Sloot, 2012). Or pay attention to the online
advertisements when you are visiting a random website: many retailers are trying to lure you to their own website. Retailers are influencing the customer every day, and therefore they are a big player in our market. This becomes clear when we look at the numbers: nowadays, retailers are accountable for ⅓ of the total household spending (i.e. 90 billion euros). Next to that, 10% of the Dutch population works at a retailer (Sloot & Voerman, 2014).
A retailer is a business that sells products and/or services to consumers for their personal use or family use (Levy & Weitz, 2011). Dutta (2011) defines a retailer as “a business which sells goods to the consumer, as opposed to a wholesaler or supplier which normally sell their goods to another business’’ (p. 33). There are approximately 100.000 brick-and-mortar retailers, -retailers who possess physical stores-, in the Netherlands. However, this number is decreasing. Store vacancies are increasing, and retail sales are decreasing , which results into many bankrupt retailers. The growing number of webshops is one of the reasons for the rising store vacancies: in 2006, the Netherlands counted 12.500 webshops. This number increased to approximately
50.000 in 2014 (Sloot & Voerman, 2014).
The shift towards digital retailers can be considered as seismic. According to Sorescu, Frambach, Singh, Rangaswamy, and Bridges (2011), the growth of the internet has created “mountains in the retail landscape that are revolutionary in scope, and unprecedented in nature’’ (p. 4). Retailers need to interact with consumers through countless channels: websites, physical stores, direct mail, catalogs, social media, mobile devices, gaming consoles, televisions, and more. Retailers who do not integrate these channels into their business models are likely to be swept away. Rigby (2011) states that retailers need to be entrepreneurial, and additionally need to create a great customer experience. Therefore, especially in this changing world, we think it can be interesting to look at the Entrepreneurial Orientation (EO) and the Customer Orientation (CO) at retailers.
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Mintzberg (1973), and further developed by authors like Lumpkin and Dess (1996), Covin and Slevin (1989), and Miller (1983). The relationship between EO and performance has been intensively studied during the last decade, in which researchers mostly agree that “firms benefit from highlighting newness, responsiveness, and a degree of boldness’’ (Rauch, Wiklund,
Lumpkin, & Frese, 2009: 764). This means that the literature generally agrees that EO positively influences performance (e.g. Wales, Gupta, & Moussa, 2013; Wiklund & Shepherd, 2003; Lee, Lee, & Pennings, 2001).
CO is about bringing value to the customer, to identify and anticipate its needs, and to feel enjoyment during that process (Lindblom, Kajalo, & Mitronen, 2015). The level of CO is considered an important leverage for the firm’s economic success. This CO-performance relationship has been studied during the last decade (e.g. Goad & Jaramillo, 2014; Brown, Mowen, Donavan, & Licita, 2002; Bitner, Booms, & Tetreault, 1990; Bove & Johnson, 2000; Sergeant & Frenkel, 2000). The main result of these studies includes the conclusion that CO positively relates to performance.
So according to the previous information, it can be stated that EO and CO are both important to the firm’s performance. But would this also be the case at retailers? Most studies focus at small and medium firms, but they rarely aim at retailers specifically. There are some exceptions: Home (2011) focused at the influence of EO at grocery retailers, and Tajeddini, Elg, and Trueman (2013) looked at retailers by studying the influence of EO and CO. Retailers could provide very interesting information, since the retail-market is changing so rapidly (Sorescu et al., 2011). Retailers need to distinguish themselves in order to stay alive (Rigby, 2011). A high entrepreneurial attitude and a strive to serve customers perfectly could just be the strategy which improves their performance. Therefore we believe a study about EO and CO in the retail-setting is a welcome contribution to the existing literature.
But there is another contribution we would like to make. Most researches about EO and CO mostly focus at small and medium-sized firms (e.g. Sorescu et al., 2011; Muchiri &
McMurray, 2015; Brettel, Chomik, & Flatten, 2015; Covin & Covin, 1990). Only some of them focus at large firms (e.g. Ambad & Wahab, 2013; Gupta & Gupta, 2014). We want to include the difference of size into this study, since large firms are so different from small firms. For
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influence of EO and CO at performance is being moderated by the size of the retailer. Therefore we think it is a contribution to the existing literature to compare micro-sized retailers with larger retailers.
The research question can be formulated as follows:
‘‘Do Entrepreneurial Orientation and Customer Orientation relate to performance, and do these relationships differ between micro-sized retailers and larger retailers?’’
Sub-questions:
- Does Entrepreneurial Orientation relate to performance? - Does Customer Orientation relate to performance?
- Does the size of a retailer have an influence at the relationship between Entrepreneurial Orientation and performance?
- Does the size of a retailer have an influence at the relationship between Customer Orientation and performance?
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Research Framework
This section contains the elaboration of the concepts EO, the EO-Performance
relationship, the concept CO, the CO-Performance relationship, followed by the influence of the retailer’s size at the EO-performance relationship and the CO-performance relationship, and finally the conceptual model.
Entrepreneurial Orientation
According to Rauch et al. (2009), the roots of EO lay in strategy-making process literature like Mintzberg (1973). Rauch et al. (2009) link these two areas by stating that ‘‘EO represents the policies and practices that provide a basis for entrepreneurial decisions and
actions’’, for which it can be viewed as an ‘‘entrepreneurial strategy-making process’’ (p. 763). Hughes and Morgan (2006) state that the most widely used dimensions of EO can be found in the research of Miller (1983). Miller (1983) investigated the entrepreneurial firm and defined it as ‘‘an entrepreneurial firm that engages in product-market innovation, undertakes somewhat risky ventures, and is first to come up with ‘proactive’ innovations, beating
competitors to the punch’’(p. 771). These conceptualizations result into the three dimensions of EO, namely: innovativeness, risk-taking, and proactiveness. Next to that, two more dimensions need to be added in order to create a complete view of EO: competitive aggressiveness, and autonomy (Lumpkin & Dess, 1996).
Innovativeness
The role of innovation in the entrepreneurial process was first emphasized by Schumpeter (1934). Schumpeter (1934) states that innovativeness is an important factor when characterizing entrepreneurship, for which it has been extensively elaborated since then. Rauch et al. (2009) define innovativeness as ‘‘the predisposition to engage in creativity and experimentation through the introduction of new products/services as well as technological leadership via Research & Development (R&D) in new processes’’ (p. 763). Taylor and Greve (2006) state that
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As you can see, innovativeness focuses on (new) products and processes. But does this include all the aspects of innovativeness? It is necessary to include the introduction of a new product/service in the definition of innovativeness, though it is not sufficient. The uniqueness (being the only one of its kind) of that product/service in the market is also important (Holbrook & Hughes, 1998). Therefore the definition of innovativeness that is being used in this research is: the way in which a firm engages in creativity and experimentation through the introduction of new unique products/services/processes, which offer the potential of extreme profits or extreme losses, which result in a competitive advantage.
Risk-taking
In the early literature, Cantillon (1734) stated that the characteristic factor that separated entrepreneurs from hired employees was the uncertainty and riskiness of self-employment. Since then, risk became an important aspect of entrepreneurship, which resulted into Miller’s (1983) EO-construct: risk-taking .
According to Rauch et al. (2009), ”risk-taking involves taking bold actions by venturing into the unknown, borrowing heavily, and/or committing significant resources to ventures in uncertain environments’’ (p. 763). The definition of Lumpkin and Dess (1996) is similar, since it refers to the propensity of managers to make large and risky resource commitments to ventures in uncertain environments.
Lumpkin and Dess (1996) mention that every firm experiences some degree of risk though, which makes it necessary to make a distinction between the nominal ‘‘safe’’ level (e.g. deposit money at another bank) and the highly risky actions (e.g. creating new resource-intensive products). This is covered in the definition of Rauch et al. (2009), and therefore their definition is being used to describe the concept ‘risk-taking’.
Proactiveness
forward-9
looking perspective characterized by the introduction of new products and services of the
competition and acting in anticipation of future demand’’ (p. 763). Next to that, Kreiser, Marino, Davis, Tang, and Lee (2010) define proactiveness as initiating actions which competitors respond to, having a strong tendency to be ahead of those competitors, and being the first business to introduce new products/services/processes/technologies. To conclude: proactivity is an opportunity-seeking, forward-looking perspective, with a strong tendency to be ahead of competitors, and a strong attitude to be the one who introduces new
products/services/processes/technologies earlier than their competitors.
Competitive Aggressiveness
Especially new firms need to be aggressive in order to survive at the market, since ‘‘new firms are much more likely to fail than established firms’’ (Lumpkin & Dess, 1996: 148). Therefore competitive aggressiveness is a well-used concept in the EO literature. Rauch et al. (2009) define competitive aggressiveness as ‘‘the intensity of a firm’s effort to outperform rivals, and is characterized by a strong offensive posture or aggressive responses to competitive threats’’ (p. 764). Covin and Covin (1990) state that a competitive aggressive firm is characterized by its very aggressive and intensely competitive attitude, and its ‘undo-the-competitors’ posture. Kreiser et al. (2010) also names this posture as characteristic of competitive aggressive firms, in contrast to the firms that have a ‘live-and-let-live’ posture. To conclude, we define competitive aggressiveness as: the intensity of a firm’s effort to outperform its rivals, its aggressive and intensely competitive attitude, and its ‘undo-the-competitors’ posture.
Autonomy
The concept of entrepreneurship took a giant step forward because lots of independent minded people decided to leave their paid job and secure positions. These people took a leap of faith by introducing new ideas and products into new markets, instead of playing by the rules of superiors. This is why autonomy became such an important concept in EO (Lumpkin & Dess, 1996).
Lumpkin, Cogliser, and Schneider (2009) stress that autonomy is related to EO.
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entrepreneurial ventures (Brock, 2003), and “increases competitiveness and effectiveness of firms’’ (Lumpkin et al., 2009: 49).
Rauch et al. (2009) define autonomy as ‘‘the independent action undertaken by entrepreneurial leaders or teams directed at bringing about a new venture and seeing it to fruition’’ (p. 764). Lumpkin and Dess (1996) state that autonomy refers to ‘‘bringing forth an idea or a vision and carrying it through to completion’’ (p.140). This definition, together with the definition of Rauch et al. (2009), is being merged into one, in order to create a complete
definition of autonomy. Therefore the definition that is being used in this paper is: the
independent action undertaken by entrepreneurial leaders or teams directed at bringing about a new venture, idea, or vision, and seeing it to fruition.
The EO-Performance relationship at retailers
The five components of EO (innovativeness, proactiveness, risk-taking, competitive aggressiveness, and autonomy ) have been extensively studied during the last decade, especially the EO-performance relationship. Lumpkin and Dess (1996) state EO is very imporant for organizational success.
Some studies (e.g. Rauch et al., 2009) discuss about the dimensionality of EO. Most studies collapse the different EO-constructs into one single dimension (e.g. Lee et al., 2001; Wiklund & Shepherd, 2003). The meta-analysis of Rauch et al. (2009) also states that most of the EO-studies use a single EO-variable. They also suggest that all of the EO-constructs are just as important in relation to a firm’s performance. Next to that, the face validity and predictive validity of the EO-scale are well established (Hughes & Morgan, 2006). Therefore this paper uses EO in a single dimensional way. Although, the paragraphs below describe the relationships between the different EO-constructs and performance separately. At the end of these paragraphs only one hypothesis will be formulated in which EO will be treated as one dimension.
Innovation and performance
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which influences performance positively (Avlonitis & Salavou, 2007). This is confirmed by Hughes and Morgan (2006), who state that a strong emphasis on innovativeness provides entry to new markets, strengthens the firm’s presence in existing markets, and makes it possible to explore opportunities. Also Wiklund and Shepherd (2003) agree by saying innovative companies perform better than their non-innovative counterparts, since the introduction of new products can generate extraordinary performance. Next to that, innovativeness contributes to competitive advantage by facilitating creative thinking (Calantone, Çavuşgil, & Zhao, 2002). Competitive advantage helps a firm better create value for the consumers, so therefore it improves the firm’s performance (Hao, 2000).
Being innovative could potentially include high costs, but prior researches (e.g. Wiklund & Shepherd , 2003; Hughes & Morgan, 2006; Avlonitis & Salavou, 2007) are clear that
innovativeness is a major contributor to business performance, and that there is a chance at high rewards. Therefore it is expected that innovation positively relates to performance.
Risk-taking and performance
Risk-taking has long been associated with performance (Le Roux & Bengesi, 2014). A firm that takes risks, orients itself towards action (Hughes & Morgan, 2006). These firms usually take opportunities and use their resources, before fully understanding what action should be taken (Covin & Slevin, 1991). Hughes and Morgan (2006) state that risk-taking pushes firms towards action and encloses uncertainty. It has been found that risk-taking is associated with strategic decision speed , which in its turn is positively related to performance (Eisenhardt, 1989). This risk-taking tendency could involve losses of resources, but there is also a chance at high rewards. In contrary, a firm with a lower risk-taking posture seems to undertake less exploitative activities, and is reactive to market changes, resulting into a weaker performance (Hughes & Morgan, 2006).
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(Eisenhardt, 1989). It can therefore be assumed that risk-taking is positively related to performance.
Proactiveness and performance
The uprising digital market asks retailers to be proactive and seize digital opportunities (e.g. social media, websites, online advertising), otherwise they will be swept away eventually (Rigby, 2011). Previous studies have often found a strong positive relationship between proactiveness and performance (e.g. Miller, 1983; Miller & Friesen, 1983). Proactive firms identify gaps in the market and want to be the first to respond to it. These firms have the urge to be the first to seize these unattended opportunities, which results in first mover’s advantage (Li, Zhao, Tan, & Liu, 2008). By doing so, they build the firm’s reputation, and they attract and retain customers to buy products from their store (Le Roux & Bengesi, 2014). This is in line with the study of Kreiser et al. (2010), who state that firms who enter new markets are able to benefit from higher demands, higher customer loyalty and become a more profitable firm. Covin and Miles (1999) add that being proactive ables firms to bring the competition to a new area, in which the first mover’s advantage could result in competitive advantage. Since competitive advantage leads to improved performance (Hao, 2000), it is expected that proactiveness positively relates to performance.
Competitive Aggressiveness and performance
The increasing store vacancies proof that retailers are operating in a competitive market (Sloot & Voerman, 2014). More and more retailers are being swept away when the digital capabilities are no strategic priority for them. Focusing on digital tools, and creating a customer experience give retailers a competitive advantage (Rigby, 2011). According to Hao (2000), competitive advantage leads to a better performance, so therefore it can be assumed that being competitive has a positive influence at performance.
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competitive market position, when customers are being exposed to a wide range of products. By beating your competitors you create a substantial advantage, resulting in a higher market share and profitability (Gupta & Gupta, 2015). Therefore it can be assumed that competitive
aggressiveness is positively related to performance.
Autonomy and performance
Autonomy is important to exploit the strengths of a company, and to identify the opportunities that are beyond the companies’ current capabilities (Kanter, North, Bernstein, & Williams, 1990). But autonomy can only be created by having a manager that encourages autonomy. According to Lumpkin et al. (2009), the role of the manager is so important, since he is the one to ‘‘encourage innovation by facilitating experimentation and risk taking through organizational systems and informal processes at both individual and team levels’’ (p. 50). Since the retail market is so sensible for new trends (Rigby, 2011), it is important to have employees that come up with new ideas. Having autonomous employees encourages innovation, increases competitiveness, and makes a firm more effective in its operations (Brock, 2003). This can be explained due to the fact that high autonomy implies a high level of freedom, which gives employees the possibility to identify opportunities that are beyond the firm’s current capabilities (Kanter et al., 1990), giving the firm a competitive advantage (Brock, 2003), which in its turn leads to a higher performance (Hao, 2000). Therefore, autonomy may be as important to the retailer’s performance as the other dimensions of EO (Lumpkin et al., 2009). It can be assumed that autonomy positively influences performance.
Every concept of EO is assumed to be positively related to the performance of a retailer, so therefore the following hypothesis can be formulated:
H1: Entrepreneurial Orientation is positively related to the performance of a retailer
Customer Orientation
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Weitz (1982) made the first attempt to measure CO. Since then it became the central construct in the marketing and sales literature (Goad & Jaramillo, 2014).
This paper studies the manager’s CO-level. The CO of a manager is projected by on-the-job perceptions, attitudes and behaviors (Brown et al., 2002). A customer oriented manager will try to motivate and coach employees on how they can best satisfy the needs of the customers, but he will also act as role model for his employees (Liaw, Chi, & Chuang, 2010). So the manager’s CO-level represents the firm’s CO as well, and therefore it makes sense to look at the manager’s level of CO.
According to Brown et al. (2002), CO is ‘‘the firm’s tendency to meet customer needs’’ (p. 111). This is elaborated by the service-oriented definition of Sousa and Coelho (2014), who state that ‘‘a customer oriented manager helps customers to identify their needs, offers services that fulfil those needs, accurately describes those services, delivers the service that matches customers’ needs, and adapts the communication to customers’ interests, whilst avoiding the use of high pressure and deceptive or manipulative influence tactics’’ (p. 1654).
Lindblom et al. (2015) and Donavan, Brown, and Mowen (2004) use the same definition for CO. They state that someone with a high CO has the need to pamper customers. This is about getting enjoyment when nurturing the customers. A customer oriented person tries to make every customer feel like he is the only customer. Next to that, it is about giving individual attention to each customer, and feeling that every customer’s problem is just as important.
CO also includes the tendency to read the customer and to identify his needs. People with a high CO get satisfaction when they anticipate to the needs of customers. Next to that, they read the customers’ body language in order to determine how much interaction they need (Lindblom et al., 2015; Donavan et al., 2004)
Customer oriented people also have a need for personal relationships. This is about enjoying the fact that you remember names and faces of customers. They also like to know the customers personally and get a bond with these customers. Next to that, they deliver the intended services on time, they take pleasure in completing tasks precisely for customers, and are very convinced that they deliver the greatest service to customers (Lindblom et al., 2015; Donavan et al., 2004).
To summarize: CO can be defined as the need to pamper customers, to deliver the
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for a personal relationship with the customer. The construct CO will be treated as single dimensional.
Customer Orientation and performance
It is widely accepted that CO is a very important part of the firm’s success and survival (e.g. Sousa & Coelho, 2013). The attitude and behavior towards consumers influences customer satisfaction, which affects the firm’s performance (Karatepe, Yavas, & Babakus, 2007).
Lindblom et al. (2015) and Donavan et al. (2004) agree: firms are noting the importance of CO, since it positively relates to performance.
It can even be stated that CO is crucial to the success of retailers (Ifie, 2014). Retailers need to understand the wishes of their customers (Donavan et al. (2004). The traditional brick-and-mortar stores cope with huge challenges, since customers are more likely to do their shopping online (Rigby, 2011). At these retailers, a high level of CO can make the difference between the success and failure. This is being confirmed by Saxe and Weitz (1982), who state that CO positively influence performance. This makes sense, because when the customers feel that the retailer is trying to fulfill all their needs, it allows the retailer to compete against the online retailers, giving the retailer a competitive advantage (Lindblom et al., 2015). Since a competitive advantage leads to a better performance (Hao, 2000), it can be assumed that:
H2: Customer Orientation is positively related to the performance of a retailer
The moderating influence of the retailer’s size at the EO-Performance relationship
The level of EO differs between micro-sized firms and large firms. For example at innovativeness: according to Jennings and Beaver (1997), micro-sized firms are more innovative since they are more flexible, caused by the fact that they are less formalized (Lechner &
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competition. Covin and Covin (1990) also state that micro-sized firms need to be at a certain size before they can benefit from the competitive aggressiveness strategy . And finally, micro-sized firms normally are less formalized and have less sophisticated control systems, which leads to a higher autonomy (Lechner & Leyronas, 2009).
But the question we need to discuss is whether micro-sized retailers benefit more from EO than the larger retailers. Compared to micro-sized retailers, larger retailers have more resources that enable them to operate more efficiently (Thornhill & Amit, 2003), they invest more heavily in R&D, and they have more aggregate knowledge. Next to that, larger retailers have the financial strength, asset base, and people to undertake activities which smaller firms cannot (Barrett, Balloun, & Weinstein, 2000). On the other hand, large retailers are more complex than their smaller counterparts. This complexity obstructs the information flows, lengthens the decision making process, and could kill initiative (Burns, 2005). So larger retailers do have more resources to be entrepreneurial, but their structure makes it more difficult to be entrepreneurial. Next to that, large retailers do not have to be very entrepreneurial in order to have a good performance, since they are more likely to have economies of scale (Storey & Greene, 2010). Large retailers already have a relatively high revenue compared to micro-sized retailers, so a higher EO has a relatively smaller impact at the performance. But a high EO at a micro-sized retailer would probably have a greater effect at the performance. Therefore we argue that micro-sized retailers benefit more from EO than large retailers.
H3: The positive relationship between EO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers.
The moderating influence of the retailer’s size at the CO-Performance relationship
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Large retailers mostly have some kind of hierarchy in their business model, which includes the presence of a middle-manager or an operational manager. The influence of the manager ‘waters-down’ through his employees (Curran & Blackburn, 2001). This means that the manager’s CO could be high, but the customer does not notice it as much compared with a small retailer. So it is expected that a large retailer has less benefit of its CO than a micro-sized retailer, since the micro-sized retailer has more face-to-face contact with its customers, and therefore provides a great customer experience (Rigby, 2011). This customer experience increases the chance that the customer becomes loyal to the retailer. It is expected that the charismatic leader of a micro-sized retailer makes the relationship between CO and performance stronger than at the larger retailers, where it is more difficult to bond with your customers. The hypothesis can be defined as follows:
H4: The positive relationship between CO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers
Conceptual model
Figure 1 shows the conceptual model. The arrows show the relationships between different constructs, in which the dashed arrows represent the moderating influence of the retailer’s size. Figure 2 shows an overview of the hypotheses.
Figure 1: Conceptual model
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H1: Entrepreneurial Orientation is positively related to the performance of a retailer
H2: Customer Orientation is positively related to the performance of a retailer
H3: The positive relationship between EO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers.
H4: The positive relationship between CO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers
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Research Design
This chapter discusses the research methodology. First an explanation of the research approach is being given, then the sample, response and data collection process is being
elaborated, and the chapter finishes with information about the research measures, validity, and reliability.
Research approach
This study uses the theory-testing approach, since it provides the opportunity to test the relationships of the conceptual model statistically (Bacharach, 1989). To do so, a survey research has been used to collect data about the concepts of EO, CO, and performance at retailers.
Development of the questionnaire
A literature review was conducted in order to develop the questionnaire. Since EO, CO, and performance are well-developed concepts, well validated measurement scales could be found. These measurement scales have been used in the questionnaire, since Hyman, Lamb, and Bulmer (2006) state this is a good way to achieve the most accurate responses. The great
advantage of pre-existing measurement scales is that they do not have to be tested and developed anymore, which saves a lot of time and effort. The measurement scales are being elaborated later on in this chapter.
Content of the questionnaire
The first draft of the questionnaire was written in English. This draft has been translated into Dutch and was published at Qualtrics, which gave the respondents the possibility to
participate online. The draft was tested by two retailers and one student. The experiences of the test panel were used to improve the questionnaire one last time. After that the final questionnaire went online at November 19, 2015. Appendix I includes the final questionnaire.
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about proactiveness. The fourth part asked three questions about risk-taking, followed by two questions about competitive aggressiveness in part five. The sixth part contained four questions about the last concept of EO: autonomy. The seventh part consisted of 13 questions regarding CO. The eighth part contained ten questions in which the respondents could compare their performance with their competitors, followed by three questions in which they were asked to fill in some numbers about their performance. The questionnaire ended with the ninth part in which the respondents were asked whether they wanted to receive the results in their mailbox.
To measure the five dimensions of EO, a 7-point Likert scale has been used. The 13 questions about CO also used a 7-point Likert scale, in contrary to the questions about
performance: a 5-point Likert scale has been used there. The reason why these Likert-scale vary, is because this study uses the same scales as in the existing literature.
Sample and data collection
This research compares micro-sized retailers with its larger counterparts. A retailer is a business that sells products and/or services to consumers for their personal use or family use (Levy & Weitz, 2011), or according to Dutta (2011): ‘‘a business which sells goods to the consumer, as opposed to a wholesaler or supplier which normally sell their goods to another business’’ (p. 33). This means that almost every shop in a city center can be seen as a retailer. Retailers are frequently part of a larger enterprise (e.g. franchisees as Plus, Albert Heijn, Blokker, WE, V&D, Primera etc.). This raises the question whether we look at the number of employees at a local establishment or at the whole chain. A chain’s idea about EO and CO need to be executed by the store managers, but every manager has a different level of EO and CO. By studying EO and CO at a firm-level, it gives us the highest probability to measure the influence of the manager’s attitude and ideas at that particular establishment.
248 retailers were approached by entering the store and ask for the manager. The manager then would be informed about the study, the questions, the anonymity, and the
possibility of online participation. When agreeing to participate, the manager received an email with a link to the Qualtrics-website.
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in Drachten (population 44.605), 37 questionnaires were handed out in Burgum (population 10.000), and a small number of 5 questionnaires were handed out to acquaintances in different sized cities.108 out of 208 questionnaires were returned, and 89 questionnaires were filled in completely. Therefore the response rate is 35,9%1.
A sample with different sized retailers is important, since this paper studies the influence of different sizes of retailers at the EO/CO-Performance relationship. According to the Eurostat (2008), micro-sized businesses have less than 10 employees. Its counterparts therefore have 10 or more employees. This definition, which can be seen in table 1, is also being used in this paper.
Table 1: EU business size definition
Company category Employees Medium-sized <250
Small <50
Micro <10
The sample of 89 respondents can be divided into 59 micro-sized retailers and 30 larger retailers. Table 2 presents some descriptive statistics.
Table 2: Descriptive statistics sample, micro is <10 employees, larger is ≥10 employees.
Category Total sample (%) Micro retailers sample (%) Larger retailers sample (%) Age 20-29 30-39 40-49 >50 15,7 24,7 32,6 27 18,6 27,2 25,4 28,8 26,7 6,7 50 16,6 Gender Male Female 62,9 37,1 66,1 33,9 56,7 43,3 Education Primary school
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Research measures, reliability, and validity
This paragraph describes the research measures of the three concepts EO, CO, and performance. The reliability and validity of these constructs is also being elaborated.
Entrepreneurial Orientation
Lots of studies have been scanned during the literature review in order to find existing measurement scales of EO. Covin and Slevin (1989) are very important authors in the EO-area, and therefore their measurement scales have been chosen to test two of their three EO-constructs, namely Innovativeness and Risk-taking. These two construct of EO were tested by three
questions, using a 7-point Likert scale. These questions included two opposite statements, both at one edge of the scale, in which the retailer had to position itself.
Covin and Slevin (1989) also treat a third EO-measurement scale, namely Proactiveness. However, Lumpkin and Dess (2001) state that Covin and Slevin’s approach minimizes the
important differences between Proactiveness and the fourth construct of EO, namely Competitive Aggressiveness. Therefore Proactiveness and Competitive Aggressiveness have been measured by the measurement scales of Lumpkin and Dess (2001). Proactiveness contained three
questions, and Competitive Aggressiveness two. Both constructs used a 7-point Likert scale, including two opposite statements, whereby the retailer had to position itself.
Autonomy is the fifth measurement scale, intensively studied by Lumpkin and Dess (1996). The measurement scale which has been used in this study was found in the literature of Lumpkin et al. (2009). They believe that none of the existing autonomy scales test autonomy from an EO-view. This is the reason why their measurement scales for autonomy have been used in this study. It consists out of four questions at a 7-point Likert scale, again including two opposite statements, in which the retailer needed to position itself. The used scales of EO can be found in appendix II.
A validity test has been done in order to test the scale’s construct validity. Although this study uses the EO-scale as one dimension, a validity test has been done in order to check the robustness of the scale, and see whether the EO-constructs could have been measured separately. The factor analysis (eigenvalue greater than 1, varimax rotation) shows us there are three
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0,466), which can be seen in appendix III. Therefore it can be stated that this EO-scale lacks construct validity, and therefore it is a good decision to view EO as a single dimensional construct.
A reliability test was performed as well. The Cronbach’s alpha was calculated, which resulted in a α = 0,865 reliability factor. An acceptable range for the Cronbach’s alpha is between the 0,70 and 0,95, so therefore this scale is reliable (Bland & Altman, 1997). All questions but one have a lower Cronbach’s alpha when the question would be deleted. Only one question (IN2) had a higher Cronbach’s alpha (α = 0,866). This is a miniscule difference, so therefore no
questions were excluded from this scale. An overview of every Cronbach’s alpha at the EO-scales can be found in appendix IV.
After these tests were performed, the different EO-constructs have been computed into one EO-measurement scale. All of the items were summed up and divided by 15 (the number of items). This resulted into a new variable which showed the mean EO of the respondent.
Customer Orientation
CO is a construct that has been intensively studied (e.g. Brown et al., 2002; Sousa & Coelho, 2013; Lindblom et al., 2015; Donavan et al., 2004). Therefore it is not very hard to find pre-exising measurement scales. During a literature review, lots of CO-literature has been scanned in order to find a reliable measurement scale. There were a lot of similarities in the research methodology of CO, but Donovan et al. (2004) presented a well validated measurement scale. Therefore this measurement scale has been chosen to measure CO.
The measurement scale contains 13 items about CO. The level of CO has been measured by using a 7-point Likert scale, ranging from ‘strongly disagree’ to ‘strongly agree’. The
measurement scale uses four different dimensions, namely ‘the need to pamper’, ‘the need to read cusomer’s needs’, ‘the need to deliver’, and ‘the need for personal relationship’. All of the 13 items can be found in appendix V.
A validity test has been done in order to test the scale’s construct validity. Although this study uses the CO-scale as one dimension, a validity test has been done in order to check the robustness of the scale, and see whether the CO-constructs could have been measured separately. The factor analysis (eigenvalue greater than 1, varimax rotation) shows us there are four
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to have a low rotated factor (namely 0,493), which can be seen in appendix VI. This item has been excluded from the CO-measurement scale. The factor analysis without CO8 can be found in appendix VII. CO will be used as a single dimensional construct, with item CO8 excluded.
The Cronbach’s alpha was calculated at α = 0,753. Therefore the CO-scale is reliable, since it lays within the range of 0,70 and 0,95. Next to that, the Cronbach’s alpha of every separate dimension has been calculated to see whether separate questions need to be excluded. Only one question (CO12) resulted in a higher Cronbach’s alpha when it would be excluded. Although no questions were excluded from the measurement scale, since this difference is diminishable (α = 0,764). An overview of the reliability test can be found in appendix VIII.
After performing these tests, the different CO-dimensions have been computed into one CO-measurement scale. All of the items but one (CO8) were summed up and divided by 12 (the number of items after the exclusion of CO8). This resulted into a new variable which showed the mean CO of the respondent.
Performance
Since performance is a multidimensional concept (Cameron, 1978), both objective and subjective measurement scales should be included to study performance. The subjective performance scale gives important information by comparing performance with competitors (Birley & Westhead, 1990). Therefore the measurement scale of Wiklund and Shepherd (2003) has been used to measure the subjective performance. This scale contains ten different
dimensions of performance, in which the respondent answers by filling in a 5-point Likert scale, ranging from ‘much lower’ to ‘much higher’. The complete scale can be found in appendix IX. The objective performance of a retailer was measured by using three questions in which respondents should elaborate in numbers about sales, revenue, and net profit. These three
concepts were picked out of the subjective measurement scale of Wiklund and Shepherd (2003). The respondents needed to fill in these numbers over the last three years.
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the data file, it appeared only one respondent answered these three questions completely.
Therefore the objective measurement scale was excluded from the study, and only the subjective measurement scale was used to measure performance.
The factor analysis of the subjective measurement scale showed there are three components that explain 69,1% of the variances of performance. The results can be found in appendix X. Still, this study treats performance as a single dimensional construct. This has been done since Wiklund and Shepherd (2003) do this as well.
The Cronbach’s alpha of the subjective measurement scale could be calculated at α = 0,845. It can be concluded that this measurement scale is reliable, since it falls between the range of 0,70 and 0,95. Next to that, every separate question was checked to see whether the
Cronbach’s alpha would have been higher by excluding that same question. It appears that none of the ten subjective questions result in a higher Cronbach’s alpha when excluded. Therefore no questions will be excluded from the subjective measurement scale. Appendix XI presents detailed information of the reliability tests.
After performing these tests, the different performance items have been computed into one performance measurement scale. All 10 items summed up and were divided by 10 in order to create the mean performance of a respondent.
Retailer’s size: the interaction variable
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Data collection, analysis and findings
This chapter contains the analysis of the collected data. First a correlation matrix is being presented, which shows us whether there are relationships between the constructs. After that the regression analysis of the EO-performance relationship is being elaborated, including the moderator size. This is being followed by the regression analysis of the CO-performance relationship, also including the moderator size.
Correlation analysis
To see whether the different constructs are related to each other, a bivariate correlation analysis was conducted. The four constructs which are leading in this paper are Performance, EO, CO, and Size. The control variables age and gender are also included in this correlation analysis. Table 3 presents the Pearson’s correlation-coefficients, but also the means and the standard deviations.
Table 3: Means, Standard Deviations, and Correlations. N=89, *Correlation is significant since p<0,05
Variables Mean S.D. 1 2 3 4 5 6 1 Performance 3,3966 0,46330 1,000 2 EO 4,0255 0,89355 0,299* 1,000 3 CO 6,0918 0,46348 -0,048 -0,016 1,000 4 Size 14,1112 28,56370 0.111 0,044 0,034 1,000 5 Age 41,52 10,434 -0,177 -0,234* 0,209* -0,147 1,000 6 Gender 1,37 0,486 -0,146 0,044 0,070 0,223* -0,242* 1,000
Keller (2008) states that the correlation analysis gives us information about the
relationships between two variables. The correlation coefficient can range from -1 to 1, whereby -1 indicates a perfect negative linear relationship, and 1 indicates a perfect positive linear
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Table 3 has been used to see whether there are relationships between the variables, and whether these relationships were significant. First of all, EO has a positive relationship with Performance, with a correlation coefficient of 0,299. This indicates that a higher level of EO results into a higher Performance. Second, there is a negative relationship between the control variable Age and EO, indicating the higher the age, the lower the level of EO (r = -0,234). Third, there is a positive relationship between the control variable Age and the retailer’s size. This means the higher the age, the larger the retailer’s size (r = 0,209). Fourth, there is a positive relationship between the control variable Gender and the retailer’s size (r = 0,223). Fifth, there is a negative relationship between the control variables Gender and Age. This indicates that women are younger than the men (r = -0,242).The generated SPSS-output can be found in appendix XII. Although these correlations are significant, according to Keller (2008) they are very weak correlations, except for the EO-Performance correlation, which can be considered as weak.
Regression analysis of EO
A linear regression analysis was conducted in order to investigate the relationship
between EO and Performance, and the moderating influence of the retailer’s size. The results can be found in table 4. The complete SPSS-output can be found in appendix XIII.
Table 4: Regression and Moderation analysis EO. *p<0,05
Model 1 Model 2 Model 3
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EO*Size -0,002 (0,002)
R Square 0,069 0,144 0,155
∆ R Square 0,075* 0,011
First we have to look whether this model fits. This can be done by looking at the ∆ R Square. This change in R Square needs to be significant in order analyze the results. The ∆ R Square between block 1 and block 2 is 0,075. This change is significant, so we can interpret the EO-Performance relationship stated in block 2.
Hypothesis 1 expected that EO and Performance were positively related. The regression analysis shows us there was a positive relationship between EO and Performance, with B = 0,148, and p < 0,05. This means that when EO increases by 1 unit, Performance increases with 0,148 unit. It can be stated that H1 is accepted.
The ∆ R Square between block 2 and 3 is not significant. Therefore we cannot interpret the moderating influence of the retailer’s size. Even when the ∆ R Square between block 2 and 3 would have been significant, it can be concluded that there is no significant interaction between EO and the retailer’s size, on the Performance of the retailer (p>0,05). This means that the retailer’s size does not have an moderating effect at the EO-Performance relationship. Therefore hypothesis H3 can be rejected due to lack of evidence and because the model does not fit.
.
Regression analysis of CO
The relationship between CO and Performance, and the moderating influence of the retailer’s size were also tested by doing a linear regression analysis. These results can be found in table 5. The generated SPSS-output can be found in appendix XIV.
Table 5: Regression and Moderation analysis CO. *p<0,05
Model 1 Model 2 Model 3
Step and variables
B SE B SE B SE
29 Control Gender -0,191 (0,102) -0,190 (0,105) -0,204 (0,104) Age 0,010 (0,005) -0,010 (0,005) 0,010 (0,005) Main effects CO 0,010 (0,109) 0,037 (0,109) Size -0,029 (0,104) -0,043 (0,103) Interaction CO*Size 0,006 (0,004) R Square 0,069 0,070 0,098 ∆ R Square 0,001 0,028
When we analyze whether the model fits, it can be concluded that there is no significant ∆ R Square. This change in R Square needs to be significant in order analyze the results, so therefore it the model cannot be used. Both the hypotheses (H2 and H4) associated with CO can
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Discussion and conclusion
This chapter discusses the most important findings of this research, and relates them to the literature. After that the theoretical and managerial implications are being reported, followed by the limitations of this study, and the chapter ends with the suggestions for future research.
Discussion
This paper studies whether EO and CO relate to performance, and whether these
relationships differ between micro-sized retailers and larger retailers. The four hypotheses were tested based on the findings of a questionnaire, filled in by 89 retailers. These 89 retailers were divided into 59 micro-sized retailers ( < 10 FTE’s in 2015) and 30 larger retailers ( ≥ 10 FTE’s in 2015). This study was built upon the prior EO-literature of Miller (1983), and Lumpkin and Dess (1996), and the prior CO-literature of Saxe and Weitz (1982).
The EO-performance relationship
The first hypothesis states that EO positively relates to a retailer’s performance (H1). The
results of the regression analysis result into the acceptation of this hypothesis. The results indicate there is a significant relationship between the retailer’s EO and performance, and that this relationship is positive. This means that when the EO of a retailer is higher, the performance of the retailer is also higher. This can be argued by the conclusions of Covin and Slevin (1986), and Wiklund and Shepherd (2003), who state that firms with a high EO perform better than firms that do not have an EO. Griffith, Noble, and Chen (2006) state that an entrepreneurial oriented retailer has a positive influence at the firm’s ability to create a competitive advantage, which leads to a better performance (Hao, 2000). So the results are in line with prior researches (e.g. Wiklund & Shepherd, 2003; Covin & Slevin, 1986).
The CO-performance relationship
The second hypothesis states that CO positively relates to a retailer’s performance (H2).
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rejected. This result was surprising, since prior research assumed CO and performance is positively related. Karatepe et al. (2007) argue that CO influences how consumers perceive the service quality of a retailer, which in turn influences the firm’s performance. Next to that, Brown et al. (2002) argue that CO positively affects the performance outcomes. Unfortunately, there is not enough evidence to assume that CO relates to performance. However, there are some authors who also have troubles when measuring the CO-performance relationship. Brockman, Jones, and Becherer (2012) found that firms with lower levels of risk-taking do not receive such a strong benefit from CO as firms with high levels of risk-taking. These firms cannot enter the areas of CO “because of their aversion to risk’’ (p. 439). This is also the case with innovativeness. When firms have a lower attitude to innovativeness, they also receive less performance benefits from CO, since they do not implement the new processes. This could be the case at this sample as well. Innovativeness and risk-taking are dimensions of EO, so when retailers have lower levels of innovativeness and risk-taking, it could influence the CO-performance relationship. This is something that could be studied further.
Next to that, it could be the case that a high CO is a natural attitude for every retailer. This could mean it is hard for a respondent to differentiate itself, since every other respondent finds that CO is high in his firm. This may have confounded the results.
The influence of the retailer’s size at the EO/CO-performance relationship
The third hypothesis states that the positive relationship between EO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers (H3). In the research
framework we stated that micro-sized retailers have more benefits from EO than larger retailers, since large retailers have more chances at economies of scale (Storey & Greene, 2010), and therefore do not need EO that much as micro-sized retailers. However, the moderating influence of the retailer’s size at the EO-performance relationship was insignificant. So therefore this hypothesis can be rejected. There is not enough evidence to assume that a micro-sized retailer strengthens the EO-performance relationship. It could be the case that separation of micro-sized retailers and larger retailers should have been different. Maybe the moderator would have been significant when we used small retailers (<50 employees2) compared to large retailers.
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This is also the case with the fourth hypothesis. It assumes that the positive relationship between CO and the retailer’s performance is stronger at micro-sized retailers than at larger retailers (H4). Unfortunately, this model was insignificant as well, so the moderating influence of
the retailer’s size at the CO-performance relationship is not valid. Therefore we can reject
hypothesis four. In the literature review we stated that the micro-sized retailer mostly has face-to-face contact with its customers, in contrast to its larger counterparts with more hierarchical layers (Curran & Blackburn, 2001; Rigby, 2011). It was assumed that the presence of a charismatic leader at micro-sized retailers would strengthen the CO-performance relationship. Unfortunately there was not enough evidence to assume a micro-sized retailer strengthens the CO-performance relationship. The same can be stated here: maybe this study should have used small retailers in instead of using micro-sized retailers.
Theoretical and managerial implications
Unfortunately, only one hypothesis in this study was accepted. This means that only the EO-performance relationship could have some value for theoretical and managerial implications.
The EO-performance relationship has been studied intensively (e.g. Covin & Slevin, 1986; Wiklund & Shepherd, 2003; Griffith et al., 2006). Although the relationship was
considered to be weak in this study, it still has the same assumption that a higher EO positively relates to a higher performance. This study shows that this relationship is not only generally considered to be true, but also specifically in a retail-setting. This study therefore has some theoretical contribution, together with the studies of Home (2011) and Tajeddini et al. (2013), who also focus at EO and the retail-setting.
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competitive advantage, which in turn leads to better performances. Gupta and Gupta (2015) state that a firm creates a substantial advantage when it is being competitive aggressive. Lumpkin et al. (2009) say having autonomous employees makes a firm more effective in its operations. So retailers can really distinguish themselves by being entrepreneurial oriented, which leads to competitive advantages, which in turn leads to increased performance (Hao, 2000).
The literature review assumes that also CO is positively related to performance. This relationship is probably common sense for most retailers. Nevertheless, we cannot confirm this relationship according to this study, and therefore we cannot suggest it for the theoretical and managerial implications.
Limitations of this study
There are several limitations in this study. The first limitation is the size of the research. Due to the limited time it was not possible to have a larger sample. The study would be more generalizable if the sample would have been bigger. The number of large retailers in this sample is also relatively low compared to the micro-sized retailers. This could have had an influence at the results.
The second limitation is the selection method of respondents in this study. Retailers were not chosen randomly. This means that this sample contains several retailers who are part of the same chain. This could have an influence at the results, for example if they would be obliged to have a very high EO. Next to that, the respondents are established close to each other, since the sample especially represents Leeuwarden, Drachten and Burgum. This makes the results less generalizable to other provinces or other countries.
The third limitation is about the respondents. The respondents in this study are managers of a retail-store. No employees were asked to fill in a questionnaire. This means that not all departments of the retailer were involved in the research topic. This could result into respondent biases and subjectivity.
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dimensions, since it is a well-known limitation. But it needs to be kept in mind while interpreting the results of this study.
The fifth limitation is about the measurement scale of the construct Performance. This study only measures the subjective performance of a retailer. The objective measurement scale was only filled in by one respondent, so therefore it was not possible to analyze it. The subjective performance measurement scale is widely used as well, but one needs to keep in mind there was no objective data used in this study.
The sixth limitation is about dividing the retailers in two groups: micro-sized retailers and larger retailers. Most literature (e.g. Sorescu et al., 2011; Muchiri & McMurray, 2015; Brettel et al., 2015; Covin & Covin, 1990) use small and medium-sized firms in their research. Maybe it would have been better to compare small retailers to larger retailers, instead of using micro-sized retailers, since it could improve the moderating influence of the retailer’s size.
These limitations could have caused the insignificant CO-performance relationship, and the moderating influence of the retailer’s size. This limitations were unforeseen, but it needs to be prevented in future research.
Suggestions for future research
This study already elaborated why CO seems to be important to retailers, but the CO-performance relationship was not significant at this study. However, prior studies (e.g. Karatepe et al., 2007; Brown et al., 2002) suggest there is a positive relationship between CO and
performance. Since this study did not find a significant relation, it could be interesting to look at this relationship again, and take the limitations of this study into account.
It is also very interesting to see whether micro-sized retailers strengthen the EO-performance and the CO-EO-performance relationship. These relationships could have a great contribution to the existing literature, since the literature review of this study suggests there are big differences between micro-sized retailers and larger retailers. Unfortunately these moderating influences were not significant, so further research should study this phenomenon better.
EO-35
dimensions at the CO-performance relationship? Further research could study this assumptions, which in its turn could be a reason for the weak CO-performance relationship in this study.
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