The effect of entrepreneurial behavioral
processes on firm performance of
franchises and independent businesses
MSc Business Administration Small Business &
Entrepreneurship
Jorn (J.E.) van Eck Student number: S2586509
Date: 21-06-2015
Master Thesis Business Administration Small Business & Entrepreneurship First supervisor: Dr. Ir. J. Kraaijenbrink
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Abstract
The question how entrepreneurs create new businesses and how to manage those businesses on a daily basis is related to entrepreneurial behavior. Prior research stated that entrepreneurial behavioral processes have been receiving increasingly more attention within the field of entrepreneurship. In this study, a comparison between causation and effectuation is made. Causation can be seen as a planned entrepreneurial behavioral approach based on prediction, as opposed to effectuation, which can be seen as an emergent approach based on non-predictive control. The purpose of this study is to discover if and how entrepreneurial behavioral processes in franchises and independent businesses differ, if this leads to differences in firm performance and if this relationship is affected by managerial discretion and the perception of the environment.
Based on prior academic research, it is proposed that franchisees would prefer a causation approach and independent business owners would prefer an effectuation approach. A high level of managerial discretion could make causal reasoning more preferable for both business contexts, while a high level of perceived environmental dynamism could make effectual reasoning more preferable for both business contexts. A strategy based on causation, a high level of managerial discretion and a low level of perceived environmental dynamism would be positively associated with firm performance in franchises. While a strategy based on effectuation, a high level of managerial discretion and a high level of perceived environmental dynamism would be positively associated with firm performance in independent businesses.
Through survey research, 21 franchisees and 21 independent business owners of Dutch liquid stores are questioned regarding their entrepreneurial behavioral processes. Using statistical analysis the results were analyzed which resulted in the following main findings. Causation is more favorable among franchisees, while effectuation is more favorable among independent business owners. A high level of managerial discretion does have a positive effect on the preference for the causation approach. The relationship between the chosen entrepreneurial behavioral process, firm performance and the two moderating variables are not significant, which seems to be in line with Sarasvathy’s (2001a)
thoughts; she stated that it’s hard to predict firm performance based on causation or effectuation. Despite the limitations of this study, the findings have practical relevance and give implications for (potential) entrepreneurs, policy makers and scholars.
Acknowledgements
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Table of Content
1. Introduction ... 5 1.1 Background ... 5 1.2 Research objective ... 7 1.3 Research questions ... 81.4 Outline of the Thesis ... 8
2. Literature Review ... 9
2.1 Entrepreneurial Behavioral Processes: Causation and Effectuation ... 9
2.2 Business Context: Franchises vs. Independent businesses ... 12
2.3 Probability of Causation and Effectuation in Franchises and Independent Businesses ... 13
2.4 Firm Performance ... 16
2.4.1 Causation and Effectuation in relation to Firm Performance... 16
2.4.2 Moderating effects of Managerial Discretion in relation to the two business contexts ... 17
2.4.3 Moderating effects of (perceived) Environmental Dynamism in relation to the two business contexts ... 18
2.5 Conceptual Model ... 19
3. Methodology ... 20
3.1 Research approach ... 20
3.1.1 Development of the questionnaire ... 20
3.1.2 Pilot & Final questionnaire ... 20
3.2 Research measures ... 21
3.2.1 Causation and Effectuation ... 21
3.2.2 Managerial Discretion ... 22
3.2.3 (Perceived) Environmental Dynamism ... 22
3.2.4 Performance ... 23
3.3 Sample and data collection ... 24
3.3.1 Data collection ... 24
4. Results... 26
4.1 Correlation Analysis ... 26
4.2 Probability of choosing Causation or Effectuation... 28
4.3 The effect of Managerial Discretion and Perceived Environmental Dynamism on the probability of choosing Causation or Effectuation ... 28
4.4 Causation and Effectuation in relation to Firm Performance ... 29
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5. Discussion & Conclusion ... 38
5.1 Discussion ... 38
5.2 Implications for theory, practice and policy makers ... 39
5.3 Research limitations ... 41
5.4 Suggestions for future research ... 41
5.5 Main conclusion ... 42
References ... 43
Appendix 1 – Final questionnaire (in Dutch) ... 48
Appendix 2 – Measurement scales causation and effectuation ... 56
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1. Introduction 1.1 Background
Entrepreneurial activity is one of the primary drivers of industrial dynamism, economic development and growth. According to Carlsson et al. (2013) those entrepreneurial activities have developed enormously in the last couple of years and research on entrepreneurship is rapidly evolving. That entrepreneurship is a useful field of social science, was also the conclusion of a study by Shane & Venkataraman (2000). They provided other researchers with a new conceptual framework in which they explained how the field of entrepreneurship could explain a set of empirical phenomena and predict a set of outcomes.
According to Spencer and Gomez (2004), the concept of entrepreneurship is multidimensional. In the existing literature, this concept consists of various facets, some related to creating or
discovering opportunities, some related to self-employment and other related to the concept of innovation. Those several facets could also lead to different ‘types of entrepreneurship’. According to Storey & Greene (2010), entrepreneurship could lead to being self-employed (e.g. having an
independent business), being an franchisee (e.g. having a business agreement with a franchisor) or being a social entrepreneur.
Entrepreneurial behavior is an important topic within this field of entrepreneurship (Fisher, 2012) and over the past decades, several different theoretical perspectives have emerged to describe and explain the logic and behavior underlying the entrepreneurial decision-making process. According to Gabrielsson & Politis (2011), decision making lies at the very heart of the entrepreneurial process. Entrepreneurship is about making several kinds of different decisions on a daily basis, for example recruiting and motivating key personnel, making daily adjustments to the product or service and making use of marketing to get your product of service on the market. Every entrepreneur has his/her own way to solve problems and make decisions in entrepreneurial processes, and this behavior will also be an important part of the strategy of the company. Although every entrepreneur has his/her own decision making style, those decisions can have long lasting consequences and it may has
unforeseeable impacts upon the entire future success and performance of the company (Reuber and Fischer, 1999; Vohora, Wright and Lockett, 2004). Therefore, studying entrepreneurial decision making is important for a better understanding of the process how entrepreneurs create and exploit new venture opportunities.
In order to understand how entrepreneurs perceive, process and use market information, or information relating to the creation of new markets, a baseline of the entrepreneurial decision making approaches needs to be studied. Sarasvathy’s (2001a) theory of causation and effectuation has been the first attempt to develop such theoretical framework. In this theoretical framework, two distinct
6 | P a g e ‘entrepreneurial bricolage’, which is defined as “applying combinations of resources at hand to handle new problems and opportunities”. Fisher (2012) and Hindle & Senderovitz (2012) argued that the theory of entrepreneurial bricolage have similarities with the theory of effectuation, e.g. both processes use existing resources as a source of entrepreneurial opportunity and have a planning averse. Because effectuation and causation are seen as more obvious counterparts, and differences between those approaches are more observable, those two distinct approaches are chosen in my study.
An entrepreneur makes use of causal reasoning when a particular effect/outcome is given and when this entrepreneur is focused on the selection of several means to reach that outcome. When an entrepreneur makes use of effectual reasoning, the set of means is already given and this entrepreneur could select between the possible effects/outcomes that can be created with those means. According to Chandler et al. (2011) the most important factors of effectuation are experimentation, affordable loss and flexibility. The most important factors of causation are ‘envision the end from the beginning’, maximizing expected returns, business planning and competitive analyses to predict an uncertain future.
Besides the several factors associated with the two entrepreneurial behavioral processes, some entrepreneurs could also have a certain preference for a specific entrepreneurial behavioral approach. For example, regarding the career motive of the entrepreneur, Gabrielsson and Politis (2011)
concluded that an entrepreneur with a linear career motive (progressive series of steps upward the hierarchy) has a strong preference for a causal decision-making process, and an entrepreneur with a transitory career motive (when a person moves from one field or job to a very different and unrelated field or job) has a strong preference for an effectual decision-making process. Also the years of entrepreneurial experience could explain whether an entrepreneur would make use of causal reasoning or effectual reasoning. Dew et al. (2009) concluded that entrepreneurial experts (with more years of entrepreneurial experience) prefer the effectual reasoning logic, while novice entrepreneurs (with relatively less entrepreneurial experience) prefer the causal reasoning logic.
Sarasvathy (2001a) suggests that causation and effectuation do not predict firm performance. However, according to the study of Chandler et al. (2011), it would be reasonable to expect a greater variance in firm performance under certain circumstances, e.g. when entrepreneurs use effectual reasoning under high levels of uncertainty. Brettel et al. (2012) studied the differences in firm performance in innovative vs. non-innovative markets; they found that effectuation is positively related to success in highly innovative markets, where causal approaches are more beneficial in markets with low levels of innovativeness.
Consequently, quite a lot effort has been given to the explanation of the several entrepreneurial approaches that exist nowadays. However, maybe as a result of the suggestion of Sarasvathy (2001a), less attention has been given to the relationship between entrepreneurial behavior and firm
performance. According to Sarasvathy (2001a), there is no specific prescription of which
7 | P a g e business context. Only future empirical studies could resolve the issue under what circumstances which particular entrepreneurial behavioral process would lead to certain advantages and
disadvantages. Based on the conclusion of Chandler et al. (2011), that it was reasonable to expect a greater variance in firm performance under certain circumstances, it would be reasonable to expect those differences in several different entrepreneurship types and business contexts. Therefore, I propose that ‘the effects of the entrepreneurial behavioral processes on firm performance will be
moderated by the context of the business‘, and this general hypothesis will be studied in this research.
1.2 Research objective
Based on the conclusions of Sarasvathy (2001a) and Chandler et al. (2011), it motivated me to study this issue and to figure out whether certain circumstances associated with a specific business context are associated with a specific entrepreneurial behavioral approach, and if this approach has effects on firm performance.
In order to study this issue correctly, two distinct business contexts need to be chosen. According to Knight (1984), independent business owners are more self-reliant, motivated and independent-minded than franchisees. Bronson & Morgan (1998) stated that franchisees can benefit more from economies of scale than independent business owners. Those two differences are probably just two out of many differences, and therefore these two business contexts are interesting to study, because of their distinct characteristics. Furthermore, their associated entrepreneurial behavior
processes may differ, and therefore those two business contexts are chosen as research samples. To the best of my knowledge, the concepts of effectuation and causation have never been compared between franchises and independent businesses.
8 | P a g e 1.3 Research questions
To be able to achieve the research objective, the following research question for this study is formulated:
To what extent do independent businesses and franchises differ in their entrepreneurial behavioral processes and to what extent does this affect their firm performance?
Sub-questions are established to acquire enough information in order to be able to understand and justify this research. The sub-questions for this research are as following:
- To what extent do independent businesses and franchises differ in the extent and way they adopt an effectuation approach to entrepreneurship?
- To what extent do independent businesses and franchises differ in the extent and way they adopt a causation approach to entrepreneurship?
- To what extent do these differences explain firm performance differences between independent businesses and franchises?
- To what extent does the level of managerial discretion have effect on the causation/effectuation – firm performance relationship?
- To what extent does the level of perceived environmental dynamism have effect on the causation/effectuation – firm performance relationship?
1.4 Outline of the Thesis
In the first chapter of this thesis, the background is described, which gives a preview of this research and formulates the research objective and research questions. In chapter 2 the literature review is conducted and the most important concepts of this study (causation, effectuation, firm performance, managerial discretion and perceived environmental dynamism) are defined. Hypothesis are drawn based on the literature review and are visualized in the conceptual model. In chapter 3 the ‘Methodology’ section is described. It consists of the research approach, the research measures and the associated reliability and validity results, and it will be ended with the data collection process. Chapter 4 contains the data analysis and will show if the hypothesis are confirmed or rejected. This thesis will be concluded with chapter 5, which consists of a discussion of the practical findings with the
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2. Literature Review
In this chapter a literature review will be conducted, which describes the main concepts of this study. The first section explains the entrepreneurial behavioral processes (causation and effectuation). The second section describes the business contexts, franchises and independent businesses, while the third section describes the probability a specific entrepreneurial behavioral process in franchises or independent businesses. The fourth section explains the relationship between causation/effectuation and firm performance and the moderating role of managerial discretion and perceived environmental dynamism on this relationship. The last section provides a conceptual model of this study.
2.1 Entrepreneurial Behavioral Processes: Causation and Effectuation
Entrepreneurial behavior is a key construct in understanding how entrepreneurs create new businesses and how they manage those businesses on a daily basis. According to Bird, Schjoedt & Baum (2012), entrepreneurial behavior can be seen as the concrete and observable actions of individuals (as solo entrepreneurs or as part of a team of entrepreneurs). These observable behaviors are the outcome of traits, knowledge, skills, abilities, cognition (e.g., perceptions, thoughts, mental models, and scripts), motivation, and emotion. Research on entrepreneurial behavior became more important the last couple of years, because it could explain, predict, and control behavior at individual and team level.
Prior literature stated that there are several theories to explain the existing entrepreneurial behavioral processes. Moroz and Hindle (2012) found that there are a total of 32 entrepreneurial process models existing in the literature, e.g. bricolage (Baker & Nelson, 1995), opportunity discovery (Kirzner, 1997) and effectuation (Sarasvathy, 2001a). They studied all the different theories in order to find a single harmonized model of entrepreneurial processes. The 32 models were tested on
distinctness, generality, accuracy and simplicity. The results of this study showed that the thoughts of the entrepreneurial processes are very fragmented, and that it was not possible to extract a single harmonized model of entrepreneurial processes. But an interesting conclusion was found; except the effectuation theory of Sarasvathy (2001a), most of the models were built on a causation-based theory. This indicates that there could be a difference in thinking about entrepreneurial processes among entrepreneurs and this could be very relevant for entrepreneurship research and education.
In 2001, a groundbreaking academic article of Sarasvathy has been published within the field of entrepreneurial behavior processes. In this article, she described two distinct approaches: causation and effectuation. She came up with the following definitions:
‘Causation: A process which takes a particular effect as given and is focused on selecting between means to create that effect.’
10 | P a g e Sarasvathy (2008) stated that causal or predictive reasoning begins with a pre-determined goal and a person who uses causation seeks to identify the optimal (fastest, cheapest, most efficient etc.) alternative to achieve that goal by selecting the most appropriate means. People who are using causal reasoning frame the future as a continuation of the past, but accurate prediction is necessary. They are focused on the expected return, are excellent at exploiting knowledge and they are focused on the predictable aspects of an uncertain future. People using causal reasoning are driven by competitive analyses and desire to limit the dilution of ownership as far as possible. Contingencies and
unpredictable circumstances are seen as obstacles to be avoided (Sarasvathy, 2001a). Individuals who make use of causal reasoning make rational choices based on all the available information relevant to a specific decision and this results in an expected utility of each option (Viale, 1992). Examples of those situations can be the ‘make-vs.-buy’ decision in production, choosing a specific target market with the highest potential return or hiring the best person on the job in human resources management.
Contrary to causal reasoning, effectual reasoning does not begin with a specific goal; it is means-orientated. Entrepreneurs begin with three categories of means: Who they are (their traits, tastes and abilities); What they know (their education, training, expertise, and experience); and, Whom they know (their social and professional networks). With those means, entrepreneurs begin to imagine possible outcomes and goals that can be created. Individuals using effectual reasoning frame problems as one of pursuing opportunities without investing more resources than the stakeholders can afford to lose; their focus is on limiting downside potential. To limit downside potential, partnerships could help them to create new markets. Effectual entrepreneurs are excellent at exploiting contingencies and are focused on the controllable aspects of an unpredictable future. An effectual entrepreneur maintains flexibility, utilizes experimentation and seeks to exert control over the future by making alliances with, and getting pre-commitments from potential suppliers, competitors and customers (Sarasvathy,
2001a).
11 | P a g e Table 1. Summary characteristics Causal- & Effectual Reasoning. Sources: Sarasvathy (2001a, 2008), Sarasvathy and Dew (2005) and Chandler et al. (2011)
Causation Effectuation
Goals are.. Pre-defined Emerging
Decisions are based on.. Maximization of expected return Affordable loss
Relation to uncertainty..
Avoiding uncertain situations as much as possible
Seeking uncertain situations for opportunities
Dealing with uncertainty through.. Business planning & competitive- and market analysis Pre-commitment & alliances
Focus on..
Predictable aspects of an uncertain future
Controllable aspects of an unpredictable future
12 | P a g e Although causation and effectuation are both distinct types of processes, suggesting that those two approaches are dichotomous ends of a continuum, both processes are integral parts of human reasoning that can occur simultaneously, are overlapping and may occur in different contexts of decisions and actions. According to Sarasvathy (2008), empirically the two approaches can go together, but conceptually these approaches should be considered as inverses.
The core characteristics of causation and effectuation are summarized in table 1 and figure 1 on page 11.
2.2 Business Context: Franchises vs. Independent businesses
The first business context in this study is the franchise business. Franchising is a popular and multifaceted business arrangement that has attracted considerable research attention (Combs et al., 2010). Franchising is a business arrangement wherein a firm (the franchisor) collects up-front and ongoing fees in exchange for allowing other firms (the franchise) to offer products and services under its brand name and using its processes. In this study, a franchise will be defined as ‘A business that makes use of a license from the owner (franchisor) of a trade or service mark, permitting the user (franchisee) to market a product or service under that name in accordance with the franchisor’s system within a specified region and time period (Norback and Norback, 1982; Justis & Judd, 1998).
According to Webber (2012) there are several advantages for franchisees compared to other entrepreneurs, like company-owned managers of independent business owners. First, franchisees are able to operate under a well-known brand name. Second, they can used a tried-and-tested format, which reduces the business risks. And third, franchisees can benefit from the several economies of scale and know-how of the franchisor, e.g. lower costs in purchasing, marketing and the availability of resources. However, according to Webber (2012), there are also some disadvantages for franchises compared to other business contexts. First, a franchisee needs to follow the franchisor’s procedures. In most cases there is a certain level/percentage of freedom, but it is clear that franchisees have a
restricted level of entrepreneurial autonomy. Second, franchisees have to pay fees (one-time) and royalties (variable and ongoing). Third, there could be restrictions in selling the business unit. And fourth, a franchisee is dependent on the franchisor and on the reputation of the system.
The second business context in this study is the independent business. An independent firm is a firm created from almost nothing and where the business idea and operations flow directly from the entrepreneur. This is in contrast to the franchise, where the product area, patterns of business and operating procedures are provided by the franchisor (Mescon & Montanari, 1981).
13 | P a g e Regarding the differences between the companies in this business context, Seawright et al. (2011) started their research with the assumption that there is still no baseline in the literature which fully addressed the differences between franchisee-entrepreneurs and non-franchisee-entrepreneurs. However, in the late twentieth century more attention has been given to this comparison and researchers concluded that franchisees may be less skilled (Williams, 1999) or may be less familiar with their businesses (Kaufmann, 1999) than non-franchisee-entrepreneurs. An important conclusion of the study of Seawright et al. (2011) is that franchisee-entrepreneurs look less like non-entrepreneurs than previously was thought. For example; it appears more likely that franchisee-entrepreneurs rely on the contractual agreement with the franchisor, where non-franchisee-entrepreneurs give more attention to opportunity recognition.
Méndez et al. (2014) studied the determinants of those factors that could encourage individuals to choose to start a franchise rather than an independent business. They concluded that the decision to become an independent business owner or a franchisee is mainly based on personal characteristics. In the case of the franchise choice, tolerance for ambiguity (having difficulty facing unstable and unpredictable situations) and inner control (when someone is convinced that their decision can
moderate external influences) are the main personal characteristics to become an franchisee. The study of Withane (1991) revealed that relatively many respondents choose to join franchises over starting independent businesses in order to take advantage of the established business format, goodwill and on-going support.
Another study regarding the differences between franchisees and independent business owners is done by Knight (1984). This study revealed that franchisees more often have no managerial experience (72 % of the franchisees) compared to independent business owners (18% of the
independent business owners). Also, independent business owners do have more prior management experience (64 % of the independent business owners reported such prior experience versus 11 % of the franchisees), thus independent business owners seem to have been better prepared to operate a business on their own. Regarding the process of consulting for information before starting a
franchise/independent business; independents tended not to consult any other people, while franchise-entrepreneurs tended to talk to as many people as possible. This could be argued that franchisees need more external sources (e.g. lawyers) because of the difficult franchisee-franchisor agreement, but it could also be a form of risk-aversion.
14 | P a g e self-interest, this will lead to trademark erosion and quality deterioration’. Franchisees give more attention to possess an ordered knowledge structure regarding their funding and financial resources, their asset and idea reduction and regarding their contacts/network necessary for new value-creating economic relationships (Seawright et al., 2001). Due to the fact they can easily rely on the contractual agreement with the franchisor, they indirectly prefer more certain circumstances. Therefore, H1 is hypothesized as following:
H1a: The probability of choosing a causation approach is higher among franchises than among independent businesses.
Sarasvathy (2001b) stated that (independent) entrepreneurs prefer to use effectual logic for their daily activities. With their effectual logic, entrepreneurs could shape the unpredictable markets through their own decisions in conjunction with pre-committed stakeholders, customers or partners. According to Knight (1984), independent entrepreneurs tended not to consult other people before starting a business, while franchisees tended to talk to as many people as possible. Independent business owners prefer using their imagination in their entrepreneurial processes. Another point is about the knowledge structures of independent entrepreneurs, they give more attention to knowledge structures that underlie the readiness or receptivity to exploring economic possibilities, urgency, risk-taking motivation and opportunity recognition (Seawright et al., 2001). They prefer indirectly more uncertain circumstances. Based on the argumentation above, H1b is hypothesized as following:
H1b: The probability of choosing an effectuation approach is higher among independent businesses than among franchises.
Previous empirical literature on the antecedents of causation and effectuation in
entrepreneurship is relatively rare. For example, Harms and Schiele (2012) studied the antecedents and consequences of effectuation and causation in an international new venture process and Johansson and McKelvie (2012) tried to unpack the antecedents of causation and effectuation in a corporate context.
Managerial discretion is one of those antecedents and is therefore the first moderating variable in this study. Managerial discretion is defined by Hambrick and Finkelstein (1987) as the latitude to take action and reflects a manager’s influence on strategic decision making and consequent
organizational outcomes. According to Wangrow et al. (2015) there are three forces that determine an executive’s latitude of action: task environment, internal organizational factors and managerial characteristics. Where the task environment is characterized by factors in the organization’s domain (industry), internal organizational factors and managerial characteristics are probably more suitable for this study, because single firms within the same industry are studied. The last important characteristic of managerial discretion is internal locus of control, which is defined by Carpenter & Golden (1997) as ‘the extent to which the entrepreneurs perceive the degree to what extent they control the
15 | P a g e Less prior research has studied the relationship between managerial discretion and
entrepreneurial behavioral processes. One of the few studies that studied those two variables was a study done by Da Costa and Brettel (2011). They found that entrepreneurs with a strong internal locus of control, would avoid unexpected events (causation), because they simply don’t appreciate them. Another finding is that when entrepreneurs do have a higher time availability, thus a higher latitude of action, the higher the goals-orientation (causation) is. Therefore, hypothesis H2a is hypothesized as following:
H2a: The probability of choosing a causation approach is higher among both franchises and independent businesses, if there is a high level of managerial discretion.
Another antecedent which could influence the preference for causation or effectuation is
(perceived) environmental dynamism. Environmental dynamism could be defined by two fundamental characteristics; volatility (rate and amount of change) and unpredictability (uncertainty) (Miller and Friesen, 1983). Environments with a low level of dynamism are characterized by infrequent changes and market participants usually anticipate to those changes that occur. In contrast, highly dynamic environments are those where rapid and discontinuous changes are common. In the middle lie moderately dynamic environments with regular changes that occur along roughly predictable and linear paths (Schilke, 2013).
Because the sample of this study consists of 1 industry, the moderating construct will be
perceived environmental dynamism. According to Miller and Dröge (1986), this could be defined as
‘the extent to which the respondent perceive the predictability of the changes in the various components of their industry/environment’.
According to Chandler et al. (2011), causation measures are negatively related to measures of uncertainty and the experimentation sub-dimension of effectuation is positively related to measures of uncertainty. Another finding regarding this relationship is by Wiltbank et al. (2009). They concluded that the theory of effectuation, specifically the efforts related to the use of existing means and pre-committed partnerships, can provide useful benefits under uncertainty. Therefore, hypothesis H2b is hypothesized as following:
16 | P a g e 2.4 Firm Performance
In a case study done by Tan & Smyrnios (2011), they stated that academic research on firm performance measurement is derived from a wide spectrum of disciplines, including accounting, human resource management, psychology and economics. Firm performance measures are defined as the metrics employed to quantify the efficiency and/or effectiveness of actions (Tangen, 2003).
According to Walker & Brown (2004), firm performance can be measured by financial and non-financial criteria. Although non-financial criteria are usually considered as the most appropriate
measurement, more small business owners are motivated to start a business based on non-financial goals. The most important financial criteria which can be used for the measurement of firm performance are profit margin/return on sales (which determine a firm’s ability to withstand competition, adverse rising costs, falling prices, and future declining sales), turnover, return on investment and return on assets (which determines the ability to utilize assets) (Barkham et al., 1996; Kelmar, 1991; Tan & Smyrnios, 2011). Those measurements have generally been popular, because it’s quite easy to administer those results, since those are very ‘hard’ and objective measures.
However, especially in the small and medium sized (SME) businesses, more attention in the literature has been given to the non-financial criteria of firm performance. The ‘soft’ non-financial measures like autonomy, job satisfaction or the ability to balance work and family responsibilities are just a few of the many non-financial criteria which are more important for some entrepreneurs than the ‘hard’ financial criteria (Kuratko et al., 1997; Parasuraman et al., 1996).
As you can see, the measurement of firm performance in small firms could be very complex and there is no ‘best prescription’ for what is the best method of measuring the performance within an SME (Jennings & Beaver, 1997). By adopting a stakeholder perspective, multiple ways in which success and/or failure are defined and measured can be expected to change over time based on the specific stakeholder’s orientation towards that specific SME.
2.4.1 Causation and Effectuation in relation to Firm Performance
As stated in the introduction, according to Sarasvathy (2001a), causation and effectuation do not predict firm performance. However, according to Chandler et al. (2011), it would be reasonable to expect a better firm performance based on their chosen entrepreneurial processes under certain circumstances in a certain business context. Despite this conclusion, there is relatively less attention given to the relationship between the concepts causation and effectuation and firm performance. Instead, the ‘planning (associated with causation) vs. emergence (associated with effectuation)’ dichotomy in strategy has got much attention to establish a relationship between entrepreneurial behavioral processes and firm performance (Kraaijenbrink et al., 2011).
17 | P a g e uncertainty and effectuation offers better ways to deal with projects with a high level of innovativeness and uncertainty. In section 2.3 was stated that franchisees prefer more certain circumstances, so
causation would be more beneficial for firm performance than effectuation.
Instead of using Sarasvathy’s developed terminology of causation, several studies were conducted to establish a relationship between planning and firm performance (Kraaijenbrink et al., 2011). To get insight in the several studies researching this relationship, Schwenk and Schrader (1993) conducted a meta-analysis on the relationship between strategic planning and financial performance in small firms; they concluded that strategic planning does have a significant, positive relation with performance. However, there are also situations in which planning is not or less beneficial. Brinckmann et al. (2010) concluded that firms that need to deal with contingencies, such as
uncertainty limited prior information and an absence of business planning structures and procedures could be limited by the use of business planning (causation). Those contingencies are more common for independent businesses. Another conclusion by Wiltbank et al. (2009) was that predictive strategies (causation) were less beneficial during times of high uncertainty, and therefore they provided empirical evidence in support of the arguments in the theory of effectuation during times of high uncertainty. Because of the fact that the abovementioned contingencies are more common for independent businesses, H3a and H3b are hypothesized as following:
H3a: An entrepreneurial behavioral process based on causation is positively associated to firm performance in a franchise-owned company.
H3b: An entrepreneurial behavioral process based on effectuation is positively associated to firm performance in an independent business.
2.4.2 Moderating effects of Managerial Discretion in relation to the two business contexts
In a study done by Sahaym et al. (2012) the relationship between managerial discretion, innovation and uncertainty on export intensity was investigated. They found that in the presence of uncertainty in the domestic market, high levels of managerial discretion were required, which gave the managers freedom and authority to seek opportunities for sharing investments. When uncertainty is low, managers do not face significant pressure to distribute risks and they will continue allocate resources in their home market.
18 | P a g e execution of managerial discretion does have a positive impact to firm performance, e.g. a firm will have greater performance consequences if managers have managerial power over critical
organizational developments. Therefore, H4a and H4b are hypothesized as following:
H4a: The positive relationship of using a causation approach and the firm performance of franchises is moderated by managerial discretion; the relationship is strengthened when there is a high level of managerial discretion.
H4b: The positive relationship of using an effectuation approach and firm performance of independent businesses is moderated by managerial discretion; the relationship is strengthened when there is a high level of managerial discretion.
2.4.3 Moderating effects of (perceived) Environmental Dynamism in relation to the two business contexts
According to Dew et al. (2008), the state of the environment could provide a possible explanation for the chosen entrepreneurial behavior process. In unpredictable and uncertain environments, entrepreneurs could achieve control through non-predictive strategies (e.g.
accumulating stakeholder commitments under goal ambiguity), in order to focus on what they can control by deploying the means they have to transform the environment. Thus, by using effectuation.
Wiltbank et al. (2009) concluded that the use of non-predictive strategy (effectuation) can be beneficial for entrepreneurial firms when they operate in hostile environments. Hostile environments are characterized by precarious industry settings, intense competition and the relative lack of
exploitable opportunities. The level of environmental dynamism tends to by high in hostile environments.
The role of causation and effectuation in opportunity creation and recognition during times of high uncertainty were studied by Maine et al. (2015). They found that entrepreneurs can shift from effectuation to causation, remain in one particular mode or adopt a combination of both when
responding to the evolving environment. Another important result of their study was that entrepreneurs face low constraints when using effectual reasoning in highly uncertain environments and
entrepreneurs face high constraints when using causal reasoning in highly uncertain environments. Therefore, H5a and H5b are hypothesized as following:
H5a: The positive relationship of using a causation approach and firm performance in franchises is moderated by market dynamism; the relationship is strengthened when there is a low level of market dynamism.
19 | P a g e 2.5 Conceptual Model
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3. Methodology
In this chapter the research methodology which is used to study the several hypothesis is described. This chapter consists of an explanation of the research approach (3.1), an explanation of the research measures (3.2) and information about the sample, response and data collection process (3.3).
3.1 Research approach
To be able to study the relationship between entrepreneurial behavioral processes and its effect on performance of franchises and independent businesses, a survey research has been applied. The theory-testing process will be used in this research, because it provides the opportunity to test the several relationships from the conceptual model statistically (Bacharach, 1989). The theoretical field of ‘Entrepreneurial Behavioral Processes’ will be studied in this master thesis project, especially focused on the differences between causation and effectuation processes between franchises and independent businesses.
3.1.1 Development of the questionnaire
The first step in the development process of the questionnaire was scanning academic articles to find pre-existing scales of the variables causation, effectuation, managerial discretion, (perceived) environmental dynamism and firm performance. According to Hyman, Lamb and Bulmer (2006) this is an appropriate strategy to find the most useful questions. Hyman et al. (2006) stated that pre-existing questions provide the researcher the correct manner in gaining information from respondents which are designed to generate the most accurate responses possible. Besides that, this process saves time, because the questions do not need to be tested and developed anymore. Based on the pre-existing questions from the academic articles, the first version of the questionnaire was developed.
3.1.2 Pilot & Final questionnaire
After the development of the first version of the questionnaire, the questionnaire was translated into Dutch and was tested in a pilot of two entrepreneurs and two students. During this pilot, feedback on the first version and possibilities for improvement were discussed. Based on this pilot session, the final version of the questionnaire was constructed.
21 | P a g e perceived certain developments within the market. The sixth and final part of this questionnaire was focused on the performance of the firm. The questionnaire ended with two (optional) questions; if the entrepreneur was interested in the results of this study, the entrepreneur could fill in contact
information and the entrepreneur could write down the name of the firm.
The questionnaire consisted mostly of closed questions using a 7-point Likert scale and
according to Dawes (2008) this scale can be seen as one of the most common scales used in academic research. For certain questions, especially regarding the entrepreneurial processes and (perceived) environmental dynamism, respondents were forced to choose the most appropriate answer out of two answers. These questions were constructed after the pilot session, because it would save time and effort for the respondents. The questions regarding performance consisted mainly of 5-point Likert scales. The final questionnaire, in Dutch, is included in appendix 1.
3.2 Research measures
3.2.1 Causation and Effectuation
Several academic articles were scanned to find existing measurement scales of causation and effectuation. In order to correctly measure those elements, the measurement scales should attain a high level of reliability and validity. After a thorough literature study, the measurement scale of Brettel et al. (2011) was chosen. In appendix 2 the original scale can be found. The four dimensions which are used in the scale of Brettel et al. (2011) consist of relatively many items. During the pilot session, the several items were pre-tested and totally 22 items of the Brettel et al. (2011) scale were chosen. Five items regarding the dimension ‘means vs. goals’, five items regarding the dimension ‘affordable loss vs. expected returns’, six items regarding the dimension ‘partnerships vs. competitive market analysis’ and six items regarding the dimension ‘acknowledge vs. overcome the unexpected’. The questions in this survey consisted of a mix of questions with a 7-point Likert scale ranging from strongly disagree to strongly agree (to what extent do the respondents agree or disagree with the statement) and two-choices questions (in which the respondent was ‘forced’ to choose a process which was more
favorable). Although the original Brettel et al. (2011) consisted of a 6-point Likert scale, in this study the option ‘Neutral/No Opinion’ was added based on the findings of the pilot.
To determine if all the pre-selected items could be included in the scales, a factor analysis of the separate item scales of causation was performed. The component matrix showed that relatively many items loaded most heavily on the same factor. According to Pallant (2000), it’s then warranted to include all the items in the scale. After that, the reliability of causation was assessed by calculating Cronbach’s alpha. The result was a reliable scale (α= .840) and according to Bland & Altman (1997) this score lies in the acceptable range between 0.70 and 0.95. This process was repeated for the
22 | P a g e alpha and all the items were included. The result was a reliable scale (α= .817), which lies in the acceptable range.
3.2.2 Managerial Discretion
In order to be able to measure managerial discretion correctly, literature was scanned to find pre-existing scales. No single article was found, which completely tested managerial discretion. However, the literature review showed that managerial discretion could be tested by the following dimensions: locus of control (Carpenter & Golden, 1997), standardization/formalization, resource availability (Wangrow et al., 2015) and task autonomy (Yan et al., 2010). The questions in this survey regarding managerial discretion consisted of statements with a 7-point Likert scale ranging from strongly
disagree to strongly agree, to find out to what extent the respondents agree or disagree with the several statements.
The six items of the managerial discretion scale were tested, whether they should be included in this study or not. Therefore, a factor analysis was performed and first of all it should be determined how many underlying components there are in the dataset. Kaiser’s criterion was used, which suggests that components with an eigenvalue of 1.0 or more should be retained in this study. In this study, three components explaining 71,69 % of the variance were extracted for the 6 items of managerial
discretion. Because there were no factor loadings below .45, no items were excluded. This is in line with Comrey and Lee (1979).
After that, the reliability of managerial discretion was assessed by calculating Cronbach’s Alpha. Unfortunately, the result was an unreliable scale (α= .413). Therefore, the method ‘descriptives for scale if item deleted’ in SPSS was used, which resulted to exclude the questions 30, 31 and 33 from the scale. This increased the reliability to α= .543. Although this result lies below the acceptable range, the questions 28, 29 and 32 were combined into the variable managerial discretion and the relatively low reliability score will be further elaborated in section 5.3.
3.2.3 (Perceived) Environmental Dynamism
In order to be able to measure environmental dynamism correctly, several academic articles were scanned to find pre-existing scales. Because this study is only focused on one industry, measurement scales regarding perceived environmental dynamism were studied. Otherwise, all the respondents would probably give the same answers because they are operating in the same market.
23 | P a g e Although these questions only consisted of two response options, a factor analysis was
conducted to assess whether all questions could be included in this scale. The component matrix showed that the questions 37 and 38 were loaded on the second component, and the other questions were loaded on the first component. Therefore, the reliability was assessed for all the items (questions 34-39) and for the items (34, 35, 36 and 39). The reliability for all the items was α= .550, and the reliability for the items 34, 35, 36 and 39 was α= .649. Although, this lies somewhat below the acceptable range, only these four items are included in the perceived environmental dynamism scale.
3.2.4 Performance
According to the literature review, it is hard to find the most appropriate measurement scale for firm performance. Especially for SME firms, more small business owners are motivated by both financial and non-financial goals (Walker & Brown, 2004). This is also in line with the thoughts of several scholars like Sarasvathy (2008) and Schwenk & Shrader (1993), who recommended to use multiple dimensions of firm performance consisting of both financial and non-financial measures. Therefore, the measurement scale of firm performance consists of five financial and non-financial measures. Employment growth, turnover growth and profit growth were used as financial performance measures and were derived from Murphy et al. (1999). Those items were measured with a 5-point Likert scale ranging from strong decrease (>20 %) to strong increase (>20%). Personal freedom of the entrepreneur and job satisfaction were used as non-financial performance measures and were derived from Kuratko et al. (1997). These items were measured with a 5-point Likert scale ranging from very low to very high for the personal freedom scale and very dissatisfied to very satisfied for the job satisfaction scale. After that, the respondents were asked to what extent the status of those dimensions changed in the past year. Those items were measured with a 5-point Likert scale ranging from strong decrease to strong increase.
A factor analysis was also conducted for the performance scale. The pattern matrix showed that the question regarding the change of amount of employees was the only item that was loaded on two different components. Therefore, this question was removed and this resulted in three components explaining 78,53 % of the variance that were extracted from the 6 items of performance. Because there were no factor loadings below .45, no items were excluded.
24 | P a g e Table 2. Reliability scores firm performance
Variable Questions Cronbach’s Alpha
Performance – Total 41, 43, 45-49 0.545
Performance – Total exc. 43, 45-49 0.531
Employees change
Performance – Total Change 43, 45, 47 & 49 0.673
Performance – Financial 43 & 45 0.808
Performance – Non Financial Change 47 & 49 0.694
Based on the results from the reliability analysis, the variables ‘Performance – Financial’ and ‘Performance – Non-Financial’ will be used in this study.
3.3 Sample and data collection
The entrepreneurs who were asked to participate in this research were entrepreneurs of both franchise-owned companies and independent businesses. To be able to make correct conclusions about the differences between those two study groups, one specific business context should be studied. Therefore, the market for liquid stores was chosen, because this market relatively consists of the most franchise-owned and independent businesses.
3.3.1 Data collection
In order to obtain as many respondents as possible, two different methods of data collection were used. Firstly, an online data collection tool, ThesisTools, was used. Entrepreneurs were invited personally through mail, or through a contact form on their website, and were asked to participate in this research. A clear explanation of the added value and the opportunity to receive the main results and conclusions was mentioned in the invitation email to increase the response rate. This invitation mail (in Dutch) can be found in appendix 3. Secondly, a printed version of the questionnaire was used, to hand out to the entrepreneur in the physical stores. After the pilot session and the first day of handing out the questionnaires, it was decided to invite the entrepreneurs only by mail. The time associated with this process, the absence of the entrepreneur and the unwillingness of the entrepreneur to participate were the most important reasons to only focus on the online process.
25 | P a g e In total 42 questionnaires were returned and 41 questionnaires were filled in completely. The incomplete questionnaire is used in the data analysis, because the respondent answered all the questions about the other five variables. The response rate is 6.4%. In table 3 the core characteristics of the data collection process are presented.
Table 3. Core characteristics data collection process
Which firms to approach? Dutch liquid stores.
How many firms are approached? 275 franchises and 383 independent businesses. How many firms responded? 21 franchises and 21 independent businesses.
Size of the firms? 1 – 5 employees; franchises does have more
employees on average compared to independent businesses.
Location of the firms? Proportionally divided in the Netherlands. Gender of the entrepreneur? Male, only 2 female franchisees.
Age of the entrepreneur? Mainly between 46 – 65 years. Less differences between the two business contexts.
Education of the entrepreneur? Mainly MBO or HBO. Less differences between the two business contexts.
26 | P a g e
4. Results
In this chapter the actual analysis of the collected data will be described. First, the correlation matrix will be presented and shows if there are relationships between the several constructs. In section 4.2 the probability of causation/effectuation in a specific business context will be tested and in section 4.3 the moderating effects of managerial discretion and perceived environmental dynamism on this probability will be tested. In section 4.4 the relation between causation/effectuation and firm performance will be tested and in section 4.5 the moderating effects of managerial discretion and perceived environmental dynamism on this relationship will be tested.
4.1 Correlation Analysis
In order to determine whether the variables are related to each other, a bivariate correlation analysis of all the key and control variables was conducted. This study consists of six key variables (causation, effectuation, financial performance, non-financial performance, managerial discretion and perceived environmental dynamism) and entrepreneurial experience as control variable. In table 4 the Pearson’s correlation-coefficients of the variables are presented. According to Keller (2009), these coefficients can say something about the degree of relationship between two variables. The value of this coefficient lies between -1 and 1 and can be represented by a straight line. If the correlation coefficient is (-)1, then there is a perfect linear relationship between two variables and when the correlation coefficient is 0, then there is no relationship between two variables. If the coefficient lies between 0 and 0.3, the relationship is very weak and if the coefficient lies between 0.3 and 0.5, the relationship is weak. If the coefficient lies between 0.5 and 0.7, there is a moderate relationship and all the values above 0.7 explain a strong relationship. Practically, a correlation coefficient of 0.5 means that if X increases with 1 unit, Y increases with 50 % of that unit.
27 | P a g e Table 4. Means, standard deviations, and correlations. Notes: N = 41, * Correlation is significant at the .05 level
Mean St. dev. (1) (2) (3) (4) (5) (6) (7)
(1) Causation 4.19 0.87 1.000
(2) Effectuation 4.36 0.82 .296 1.000
(3) Performance – Financial 3.26 0.85 .247 -.001 1.000
(4) Performance – Non Financial 3.12 0.35 -.362* -.180 .315* 1.000
(5) Managerial Discretion 4.69 1.06 .260 -.027 .347* .104 1.000
(6) Perceived Environmental Dynamism 0.46 0.32 .282 .054 -.216 -.208 -.235 1.000
28 | P a g e 4.2 Probability of choosing Causation or Effectuation
In order to investigate the differences between the probability of choosing a specific
entrepreneurial behavioral approach between franchises and independent businesses, an independent samples t-test was conducted. In table 5 and table 6 the results of this analysis are presented.
Regarding the probability of choosing a causation approach, the scores were for franchises (M=4.40, SD=.72) and independent businesses (M=4.01, SD=.97) conditions; t (40) = 1.46, p = .077. Although franchisees experience a higher level of causation than independent business owners, this difference is not significant on 5 % level, but it would be significant on a 10% significance level, and therefore H1a is weakly accepted.
Table 5. t-test Results comparing Franchises and Independent Business on Causation
Grade Level n Mean St. Dev. t-value df p (one-tailed)
Franchise 21 4.40 0.72 1.455 40 0.077
Independent Business 21 4.01 0.97
Regarding the probability of choosing an effectuation approach, there was a significant difference in the scores for franchises (M=4.15, SD=.87) and independent businesses (M=4.56,
SD=.72) conditions; t (40) = -.1688, p = .0495. Because the p-score is below the 0.05 level, it may be
concluded that this result is significant. H1b is therefore supported, which means that the probability of choosing an effectuation approach is higher among independent businesses than among franchises.
Table 6. t-test Results comparing Franchises and Independent Business on Effectuation
Grade Level n Mean St. Dev. t-value df p (one-tailed)
Franchise 21 4.15 0.87 -1.688 40 0.0495
Independent Business 21 4.56 0.71
4.3 The effect of Managerial Discretion and Perceived Environmental Dynamism on the probability of choosing Causation or Effectuation
In order to investigate the relationship between managerial discretion or perceived
29 | P a g e Hypothesis 2a expected that a high level of managerial discretion is positively associated with the probability of using a causation approach. The regression coefficient is .281. This implies that when managerial discretion increases by 1 unit, the level of causation increases by .281 unit. This is in line with the expectations based on the literature review. The p level is .071, which isn’t significant on a 5 % significance level, but it would be significant on a 10 % significance level. Therefore, H2a is weakly accepted.
Hypothesis 2b expected that a high level of perceived environmental dynamism is positively associated with the probability of using an effectuation approach. The regression coefficient is .054. This implies that when perceived environmental dynamism increases by 1 unit, the level of causation increases by .054 unit. This positive relation is in line with the expectations based on the literature review, but according to the fact that the p level is .740, this isn’t significant on a 5 or 10 % significance level. Therefore, H2b is rejected.
Table 7. Regression model regarding hypothesis 2. Note: *p<0.05, ( )= non-significant P-value
Dependent Variable Causation Effectuation
Managerial Discretion .281 (.071) .026 (.871)
Perceived Environmental Dynamism .282 (.075) .054 (.740)
N 41 41
4.4 Causation and Effectuation in relation to Firm Performance
In order to study the relationship between the two entrepreneurial behavioral processes and firm performance, a linear regression analysis was performed. The dependent variable firm performance is divided in financial performance and non-financial performance. The results for franchise-owned companies are presented in table 8, the results for independent businesses are presented in table 9.
30 | P a g e Table 8. Regression models performance in Franchises. Note: *p<0.05, ( )= non-significant P-value
Dependent Variable Financial Performance Non-Financial Performance
Causation -0.79 (0.722) -0.160 (0.070)
Effectuation -0.129 (0.480) -0.068 (0.369)
N 21 21
R^2 0.150 0.112
Hypothesis 3b expected that effectuation is positively associated to firm performance in an independent business. The regression coefficient on financial performance is 0.396 and -0.143 on non-financial performance. This would indicate that if effectuation increases by one unit the non-financial performance would increase by 0.396 units and non-financial performance would decrease by 0.143 units. The relation between effectuation and financial performance in independent businesses is in line with the expectations based on the literature. The relation between effectuation and non-financial performance isn’t. Unfortunately, the positive relationship between effectuation and financial performance isn’t significant (p = 0.175), and therefore H3b is rejected.
Table 9. Regression models performance in Independent Businesses. Note: *p<0.05, ( )=
non-significant P-value
Dependent Variable Financial Performance Non-Financial Performance
Causation 0.337 (0.112) -0.130 (0.163)
Effectuation 0.396 (0.175) -0.143 (0.265)
N 21 21
R^2 0.028 0.174
4.5 Interaction effect of Managerial Discretion (MD) and Perceived Environmental Dynamism (PED) on the Causation (CAU) & Effectuation (EFF) - Firm Performance relationship
In order to test hypothesis 4 and 5, a hierarchical multiple regression was used. It should be said, that it’s quite hard to do such a complex analysis with this relatively low amount of respondents. It is important to keep this in mind, while interpreting the results. In section 5.3, this issue will be further elaborated.
31 | P a g e Second, the relationship between the four constructs of this study (CAU, EFF, MD & PED) and the firm performance (financial and non-financial) were investigated. Third, by multiplying CAU and MD (H4a), EFF and MD (H4b), CAU and PED (H5a), EFF and PED (H5b) the moderating effect of MD and PED on the CAU/EFF – firm performance relationship was investigated. These multiplications resulted in interaction variables. Two models were included to test the hypothesis. Model 1 includes all the independent and moderating variables. Control variables were not added because of the relatively low amount of respondents. In Model 2 the interaction variables were added to the
independent and moderating variables. In order to test the hypothesis, the cases were selected in SPSS on target group (franchises or independent businesses). Table 11 and table 12 display the results of the hierarchical regression analyses of performance in franchises (hypothesis H4a and H5a). Table 13 and 14 display the results of the hierarchical regression analyses of performance in independent businesses (hypothesis H4b and H5b).
Regarding the independent variables in Model 1, none of those variables have a significant impact on firm performance of the franchises. According to Keller (2008), if the significance level is below the .05 level, the associated variables make a significant contribution in predicting the outcome. 7.8 % of the variance of financial performance in franchises and 30.1 % of the variance of
non-financial performance in franchises can be explained by only the independent variables. By adding the interaction variables, those percentages increased to respectively 21.5% and 47.9 %. Regarding the independent businesses, 37.4 % of the variance of financial performance can be explained by the independent variables and by adding the interaction variables, this percentage increased to 39.5 %. Looking at the non-financial performance in independent businesses, 21.4 % can be explained by the independent variables and by adding the interaction variables, this percentage increased to 35.2 %. All the above-mentioned explained variance percentages and changes within those variances weren’t significant (Sig. F Change > .05).
Looking at hypothesis 4a, the positive relationship between causation and financial performance (β = .508, p = .163) and non-financial performance (β = .530, p = .081) in franchises isn’t significant strengthened by managerial discretion. This means that although a high level of managerial discretion (Beta score of above zero) does strengthen the causation and performance relationship, the interaction isn’t of a significant value when the significance level is 5 %. When the significance level would be 10 %, hypothesis H4a regarding non-financial performance would be accepted. Therefore, H4a is rejected for financial performance and weakly accepted for non-financial performance.
Looking at hypothesis 4b, the positive relationship between effectuation and financial
32 | P a g e Looking at hypothesis 5a, a negative relationship between causation and financial performance (β = -.173, p = .626) and non-financial performance (β = -.500, p = .100) in franchises exists when it’s moderated by perceived environmental dynamism. This implies that when the perceived
environmental dynamism will become higher, the relation between causation and firm performance will become weaker. Although this is in line with the expectations, H5a is rejected for financial performance and weakly accepted for non-financial performance (p =.10).
Looking at hypothesis 5b, a weak positive relationship between effectuation and financial performance (β = .222, p = .571) and a weak negative relationship between effectuation and non-financial performance (β = -.042, p = .917) exists regarding the effects of perceived environmental dynamism on this relationship within independent businesses. This implies that when the perceived environmental dynamism will become higher, the relation between effectuation and financial performance will become stronger and the relation between effectuation and non-financial performance will become weaker. The last conclusion is contrary to the expectations, and the first conclusion isn’t significant. Therefore, H5b is rejected.
33 | P a g e Table 10. Summary tested hypotheses
Hypothesis Description Accepted/Rejected
H1a The probability of choosing a causation approach is higher among franchises than among independent businesses. Weakly Accepted H1b The probability of choosing an effectuation approach is higher among independent businesses than among franchises. Accepted
H2a The probability of choosing a causation approach is higher among both franchises and independent businesses,
if there is a high level of managerial discretion. Weakly Accepted
H2b The probability of choosing an effectuation approach is higher among both franchises and independent businesses,
if there is a high level of perceived market dynamism. Rejected
H3a An entrepreneurial behavioral process based on causation is positively associated to firm performance in a franchise. Rejected H3b An entrepreneurial behavioral process based on effectuation is positively associated to firm performance in an IB. Rejected H4a The positive relationship of using a causation approach and the firm performance of franchises is moderated by
managerial discretion; the relationship is strengthened when there is a high level of managerial discretion. Rejected (Finan.) / Weakly Accepted H4b The positive relationship of using an effectuation approach and firm performance of independent businesses is
moderated by managerial discretion; the relationship is strengthened when there is a high level of managerial discretion. Rejected H5a The positive relationship of using a causation approach and firm performance in franchises is moderated by
market dynamism; the relationship is strengthened when there is a low level of market dynamism. Rejected (Finan.) / Weakly Accepted H5b The positive relationship of using an effectuation approach and firm performance in independent businesses
34 | P a g e Table 11. Hierarchical regression analysis financial performance in franchises. Note: *p<0.05, ( )=
non-significant P-value
Model 1 Model 2
Dependent Variable Financial Performance Financial Performance
Causation (CAU) -.006 (.986) -.184 (.646)
Effectuation (EFF) -.165 (.541) -.329 (.325)
Managerial Discretion (MD) .071 (.823) .296 (.409)
Perceived Environmental Dynamism (PED) -.224 (.416) -.192 (.486)
Interaction CAU * MD .508 (.163)
Interaction CAU * PED -.173 (.626)
N 20 20
R^2 .078 .215
R^2 Change .078 .137
35 | P a g e Table 12. Hierarchical regression analysis non-financial performance in franchises. Note: *p<0.05, (
)= non-significant P-value
Model 1 Model 2
Dependent Variable Non- Financial Performance Non- Financial Performance
Causation (CAU) -.313 (.340) -.316 (.340)
Effectuation (EFF) -.133 (.571) -.442 (.116)
Managerial Discretion (MD) .123 (.659) .284 (.335)
Perceived Environmental Dynamism (PED) -.359 (.145) -.302 (.190)
Interaction CAU * MD .530 (.081)
Interaction CAU * PED -.500 (.100)
N 20 20
R^2 .301 .479
R^2 change .301 .178
36 | P a g e Table 13. Hierarchical regression analysis financial performance in independent businesses. Note:
*p<0.05, ( )= non-significant P-value
Model 1 Model 2
Dependent Variable Financial Performance Financial Performance
Causation (CAU) .308 (.223) .322 (.244)
Effectuation (EFF) .102 (.666) .197 (.603)
Managerial Discretion (MD) .440 (.074) .434 (.094)
Perceived Environmental Dynamism (PED) -.072 (.767) -.067 (.802)
Interaction EFF * MD .138 (.620)
Interaction EFF * PED .222 (.571)
N 21 21
R^2 .374 .395
R^2 Change .374 .021
37 | P a g e Table 14. Hierarchical regression analysis non-financial performance in independent businesses. Note:
*p<0.05, ( )= non-significant P-value
Model 1 Model 2
Dependent Variable Non-Financial Performance Non-Financial Performance
Causation (CAU) -.306 (.277) -.394 (.172)
Effectuation (EFF) -.162 (.540) -.422 (.291)
Managerial Discretion (MD) .371 (.169) .374 (.157)
Perceived Environmental Dynamism (PED) .183 (.504) .308 (.277)
Interaction EFF * MD .463 (.123)
Interaction EFF * PED -.042 (.917)
N 21 21
R^2 .214 .352
R^2 Change .214 .138
