University of Amsterdam
Exploration, Exploitation and Firm Performance
The Moderating effect of sales growth
Master Thesis
Surname Bakker
First name John
Student ID 10682392
MSc EPMS Executive Programme in Management Studies – Strategy Track Institution Amsterdam Business School, University of Amsterdam
Date 30 January 2017
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Statement of Originality
This document is written by John Bakker who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Abstract
In strategic management, it has long been questioned why some firms perform better than others. In this respect, exploration and exploitation effects on firm performance has increasingly captured the attention of researchers. Results, however, remain inconclusive. This study tries to add to the current body of literature by investigating whether the favorable or unfavorable situation the manager is in - captured by sales growth/decline as a moderating variable - influences his decisions with regard to investments in exploration and exploitation and how this, in turn, affects both long-term and short-long-term firm financial performance. When sales revenue is lagging, does a self-interested manager still focus on return on investments in investment decisions or would job security become the main incentive. By using a dataset of the Eurostoxx 600 during the course of 3 years from 2010 until 2012, this study finds evidence for a moderating effect of sales growth on the relationship between exploration and long-term firm financial performance. More specifically, it appears that in situation of high sales growth, this relationship will be stronger, whereas this relationship decreases in a situation of low sales growth. The results do not show a moderating effect for the relationship between exploitation investments and short-term financial performance. By providing new insights into the effects of sales growth on the exploration-performance relationship this research provides managers more thorough information with regards to the effectiveness of the investments in exploration. From a scholarly point off view, findings contribute to principal-agent theory by stressing the importance for principals (owners) to monitor their managers and make goal alignment priority in times of low or even declining sales growth.
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1.
Introduction ... 5
2.
Literature Review ... 9
2.1
Exploration versus exploitation ... 9
2.2
Exploration and exploitation: Ambidexterity. ... 10
2.3
Moderators on impact of exploration, exploitation and firm performance ... 12
3.
Hypothesis development and conceptual model ... 16
3.1
Exploration and firm performance ... 16
3.2
The moderating effect of sales growth on the exploration impact on firm performance ... 16
3.3
Exploitation and firm performance ... 18
3.4
The moderating effect of sales growth on the exploitation impact on firm performance .... 19
3.5
Conceptual model ... 20
4.
Methodology ... 21
4.1
Research sample ... 21
4.2
Measures ... 22
4.2.1
Independent variables ... 22
4.2.2
Dependent variable ... 23
4.2.3
Control variables ... 23
4.3
Reliability and validity ... 24
4.4
Data analysis ... 24
5.
Results ... 26
5.1
Univariate analyses ... 26
5.2
Bivariate analyses ... 26
5.3
Impact of exploration on firm performance and the moderating role of sales growth ... 27
5.4
Impact of exploitation on firm performance and the moderating role of sales growth ... 29
6.
Discussion and conclusion ... 31
6.1
Discussion of findings ... 31
6.2
Contributions ... 34
6.3
Limitations and future research ... 35
6.4
Conclusion ... 36
References ... 37
Appendices ... 48
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1. Introduction
Explaining performance differences between firms is still a present day topic and at the core of strategic management. The environment is constantly changing due to for example (de)regulation, disruptive innovations, new entrants and changing customers preferences. Companies have struggled to try sustaining their advantages; in fact, no organization can build a competitive advantage that is sustainable. In a hypercompetitive environment, companies are on the one hand advised to disrupt their own advantages and the advantages of competitors (D’Aveni, 1995). On the other hand there are short-term competitive forces demanding stability, such as the need to exploit the organizations assets and avoid risky unproven projects (Volberda et al., 2001a). Rivalry amongst firms forces companies to participate in continuous and escalating actions and developments. All firms end up racing as fast as they can to stay on par with competitors (Derfus et al., 2008). Derfus (2008, p. 61) calls it “the red queen effect” based on the conversation between the red queen and Alice in Lewis Carroll’s Through the looking Glass, where the queen lets Alice know that only in “a slow sort of country” you can get ahead by just running. “Now, here, you see, it takes all the running you can do to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” (Lewis Carroll; Through the Looking Glass, 1946, p. 178- 179). As most companies tend to adopt similar renewal responses as their competitors, others choose an alternative more risky renewal path to try to get ahead (Flier et al., 2003; Volberda et al., 2001b).
If “it takes all the running you can do to keep in the same place”, as said by the red queen to Alice, what will happen when you lag behind the competition? Does it make sense to use resources to try to get back into the game? Population ecology (Carroll and Hannan, 2000; Hannan and Freeman, 1977, 1984) states that due to build up inertia large organizations are better suited to exploit today’s markets than adapting to fast changing environments. We have seen companies like Blackberry, Nokia, Chrysler and many retail chains desperately trying to win back their advantages, spending resources in the process, but ultimately failing in their attempts to recover their position. In times of radical change the organizational population will probably change, as compared to relative stable times when it is easier to adapt to the environment. No strategy will bring sustainable competitive advantage (Barnett and Burgelman, 1996; Baum and Singh, 1994).
6 In his book, The Innovators Solution, Clayton Christensen tells of how, during the 1990s, AT&T lost more than $50 billion trying to get into new businesses that all proved disastrous. He concludes: “We could cite many cases of companies’ similar attempts to create new growth platforms after the core business had matured”.
Organizational learning is a necessary resource and capability to keep up with competitors or when seeking for a competitive advantage (Barney, 1991). According to resource-based theory, resources include all the “assets, capabilities, organizational processes, firm attributes, information, knowledge, etc., controlled by a firm that enable the firm to conceive of and implement strategies that are efficient and effective” (Barney, 1991, p. 101). In this light, organizational learning, defined as the capability for organizations to create, disseminate, and act upon generated knowledge, can be regarded as a resource (Auh and Menguc, 2005). Auh and Menguc (2005) asserted that exploration and exploitation are different modes of organizational learning. March (1991) tells us that it is not only the intensity of investments that matters but also the balance between exploration and exploitation. The ability of an organization to simultaneously pursue both exploration and exploitation is known as organizational ambidexterity (O’Reilly and Tushman, 2004). There is a trade-off between exploration and exploitation and organizations need to find the optimal balance (Benner and Tushman, 2002, 2003; Ghemawat et al., 1993; Gupta et al., 2006; McGrath, 2001). Firms that overemphasize exploration, risk spending scarce resources with very little payback (March, 1991). Conversely, firms that overemphasize exploitation reduce learning of new skills and might become captive of outdated practices, knowledge and resources, possibly depressing their long-term performance.
According to the meta-analysis of Capon et al. (1990) both advertising intensity and R&D spending, being proxies for respectively exploitation and exploration, are positively related to financial performance at the firm level. Empirical evidence on the effects of Organizational Ambidexterity on performance is mixed; some studies have found a positive relationship (e.g., Gibson and Birkinshaw, 2004; Lubatkin et al., 2006), whereas others have found a negative association (e.g., Athuahene-Gima, 2005), contingent effect (e.g., Lin et al., 2007), or no relationship at all (Venkatraman et al., 2007).
7 The optimal balance between exploration and exploitation can be moderated by environmental conditions (Uotila et al. 2009). Uotila et al. (2009) also state that large companies tend to systematically overemphasize exploitation. The literature also found moderators that influence the impact of exploration and exploitation on firm performance. Auh and Menguc (2005) find empirical evidence for the moderating role of competitive intensity on the impact of exploration and exploitation on firm performance. Jansen et al. (2006) empirically determined that exploration is more effective in dynamic environments, whereas exploitation is more beneficial in a competitive environment. Firm-specific moderators found by Raisch and Birkinshaw (2008) in their meta-analysis include market orientation (Kyriakopoulos and Moorman, 2004), resource endowment (Kyriakopoulos and Moorman, 2004; Venkatraman et al., 2007) and firm scope (Lubatkin et al., 2006). Bierly and Daly (2007) find that exploitation has a stronger impact on performance in stable and high-tech environments than in dynamic and low-tech environments. Exploration also has a stronger impact on performance in high-tech environments than in low-tech environments.
“The strategic choice approach (Child, 1972, 1997; Miles et al., 1978) endows organizations with a capacity to change their destiny by adapting themselves and reshaping their environments. This approach emphasizes the importance of managerial intentionality of decision makers being the intermediary between organizations and their environments” (Flier et al., 2003, p. 2166). The observations of Flier et al. (2003) indicate managerial intentionality at firm level and suggest evidence regarding firm-specific patterns of the temporal dimension of strategic renewal behavior. With regard to motivation of managers, assuming, as agency theory does (Eisenhardt, 1989), that humans are self-interested, all individuals are only motivated by their personal monetary payoffs, the agents (working within the firm) are interested in using resources to create new opportunities for positions they can fill or profit from. Applying agency theory, it is also important to consider the issue of risk sharing (Eisenhardt, 1989). Agents, who are unable to diversify their employment, should be risk averse and interested in keeping their job. When investing in exploration or exploitation managers could be influenced by their job security. In unfavorable situations, like declining sales growth, mangers’ decisions with regard to investments in exploration and exploitation could be influenced by their self-interest.
8 This study draws from March (1991) organizational learning and Child’s (1972, 1997) strategic choice together with agency theory (Eisenhardt, 1989) and investigates the managerial influence on the exploration and exploitation relationship with firm performance. Could agency theory explain performance differences in the investments in exploration and exploitation? Managers make investment decisions regarding exploration and exploitation and are self-interested (Eisenhardt, 1989). This could lead to different considerations in different situations. If a company’s sales is growing the managers goals are also to grow sales or make more profit at better margins from this sales, as his job is not at risk. He can optimize his benefit as in most companies the managers will be financially rewarded for his contributions. When a company’s sales growth is stagnating or even declining the manager’s job could be at risk, this changes the manager’s goal in keeping his job and this could influence his decisions on investments in exploration and exploitation. This could lead to investments done with the incentive to create job security more than a financial income.
This paper attempts to add to the current literature by examining the moderating effect of sales growth on the relationship between exploration, exploitation and firm performance. The central argument put forward in this research is that the exploration/exploitation-performance relationship is moderated by the sales growth during the investment. Therefore, the research question of this study is:
To what extent does sales growth impact the relationship between exploration, exploitation and firm performance?
By providing the knowledge of these effects managers are made more responsive to these issues when spending recourses on exploitation or exploration. Also (stock) owners can better monitor their managers. This will result in better managerial capabilities that in turn will lead to higher performance of the firm.
The remainder of this study proceeds as follows. Prior literature is discussed in chapter 2. The hypothesis of this research and the conceptual model are described in Chapter 3. Chapter 4 explains the methodology of this research. In Chapter 5 the results are presented. Finally in chapter 6 these results are discussed and conclude this research.
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2. Literature Review
In this section the literature is discussed related to the exploration, exploitation to firm performance relationship and the moderators on this relationship.
2.1 Exploration versus exploitation
As it comes to defining exploration and exploitation there are roughly two groups in the literature that are divided by differences in the type of learning or by the presence versus the absence of learning (Gupta et al., 2006). Baum et al. (2000), Benner and Tushman (2002), and He and Wong (2004) state that both exploration and exploitation are associated with learning and innovation. Baum et al. (2000, p. 768) refer to “exploitation as learning gained via local search, experiential refinement, and selection and reuse of existing routines. Exploration refers to learning gained through processes of concerted variation, planned experimentation, and play”. On the other hand Vermeulen and Barkema (2001, p. 459) defined exploration as the “search for new knowledge” and exploitation as the “ongoing use of the firm’s knowledge base.” Rosenkopf and Nerkar (2001) treat all activities associated with learning and innovation as exploration and exploitation as using past knowledge. This study will follow the conclusion also made by Gupta et al. (2006) and build on March's (1991) logic to argue that all activity includes at least some learning. Even when an organization is attempting to do nothing more than replicate past actions, it accumulates experience and goes down the learning curve, albeit in an incremental manner (Yelle, 1979). As March (1991, p. 85) noted, "The essence of exploitation is the refinement and extension of existing competencies, technologies, and paradigms and the essence of exploration is experimentation with new alternatives".
These two types of learning activities are based on different competencies and organizational capabilities (Benner and Tushman, 2003) finding the right balance is a constant challenge. The ease or difficulty in finding a balance will depend on whether these two tasks are seen as competing or complementary aspects of organizational decisions and actions (Gupta et al., 2006).
10 When exploration and exploitation are seen as competing activities, organizations need to emphasize one over the other (Ghemawat and Costa, 1993; Bierly and Chakrabarti, 1996). Short-term efficiency is positively related to exploitation activities as reducing variety and adapting to current environments (Uotila, 2009). But these activities might become liabilities as environments change over time and firms that focus on exploitation might lack the capabilities to adapt to these changing environments. On the other hand the explorative activities that increase variety to develop new knowledge to adapt to changing environments for long-term survival are uncertain in their performance effects. Other empirical studies (He and Wong, 2004; Tushman and O’Reily, 1996; Lubatkin et al., 2006) found support for the complementary view on exploration and exploitation and the need to balance the two. This simultaneous pursuit of both exploration and exploitation is known in the literature as the concept of organizational ambidexterity.
2.2 Exploration and exploitation: Ambidexterity.
Within the firm there is a continuous consideration to find an optimal balance between resources used for exploration and exploitation. In the literature this phenomenon is addressed as “organizational ambidexterity” originally introduced by Robert B. Duncan in 1976 in his book chapter, The Ambidextrous Organization: Designing Dual Structures for Innovation. Organizational ambidexterity is defined as the ability of an organization to simultaneously pursue both explorative (discontinuous) and exploitative (incremental) innovation (O'Reilly and Tushman, 2004). As Gibson and Birkinshaw (2004) state among others that engaging in both explorative and exploitative processes is crucial for the long-term survival and success of organizations. However we can learn from the meta-analysis of Junni et al. (2013) that the empirical evidence on the effects of organizational ambidexterity on performance is mixed; some studies have found a positive relationship (e.g., Gibson and Birkinshaw, 2004; Lubatkin et al., 2006), whereas others have found a negative association (e.g., Athuahene-Gima, 2005), contingent effect (e.g., Lin et al., 2007), or no relationship at all (Venkatraman et al., 2007).
11 March (1991) started with arguing that achieving and maintaining a proper balance between exploration and exploitation is essential for organizational survival. Cao et al. (2009) state that it are only managers in resource-constrained contexts that benefit from a trade-off between exploration and exploitation. When a firm has sufficient resources they are better off simultaneously pursuing both high levels of exploration and exploitation, which will yield synergistic benefits.
Junni et al. (2013) show that most studies agree that firms involved in both exploration and exploitation whether through balanced or combined Organizational ambidexterity will perform better than firms emphasizing one over the other (Raisch and Birkinshaw, 2008; Tushman and O'Reilly, 1996). Finding the right balance is of great importance as by emphasizing managers become vulnerable for either one the “success trap” or the “failure trap” (Levinthal and March, 1993). The success trap refers to business managers that focus on the exploitation of their historically successful current business activities and as such neglect the need to explore new territory. This will lead to organizational inertia that prevents the organization from properly adapting to changing environmental conditions, which will cause poor performance outcomes in the long run (Levinthal and March, 1993; Smith and Tushman, 2005). Levinthal and March (1993) introduced the failure trap, sometimes exploration drives out exploitation: “Organizations are turned into frenzies of experimentation, change, and innovation by a dynamic of failure. Failure leads to search and change, which leads to failure, which leads to more search, and so on. New ideas and technologies fail and are replaced by other new ideas and technologies, which fail in turn”( Levinthal and March 1993, p. 105-6). Managers fall into the trap because aspirations adjust downward more slowly than they adjust upward and exhibit a consistent optimistic bias (Lant, 1992). Furthermore Levinthal and March (1993, p. 106) state that “Most new ideas are bad ones, so most innovations are unrewarding”.
This study is trying to add to the literature by giving more insight in the efficiency of both exploitation and exploration. This will add to the discussion on both exploration and exploitation by creating a better support for the relationship with firm performance. To give managers a tool to
12 find a proper balance between exploration and exploitation, giving them a better chance to avoid the traps.
2.3 Moderators on impact of exploration, exploitation and firm performance
Previous studies have investigated several moderators both environmental and firm specific to explain the effect differences in the exploration, exploitation and firm performance relationship. Researchers have argued that local environmental aspects such as dynamism and competitiveness can require firms to become ambidextrous (Floyd and Lane, 2000; Levinthal and March, 1993; March, 1991).
Both Levinthal and March (1993) and Lewin et al. (1999) expected environmental dynamism and competitiveness to moderate the relationship between exploitation, exploration, and firm performance. Firm-specific factors found by the meta-analysis of Raisch and Birkinshaw (2008) include market orientation, resource endowment and firm scope. Market orientation has been defined as the firm’s capability to generate, disseminate, and respond to intelligence pertaining to current and future customers (Kohli and Jaworski, 1990; Narver and Slater, 1990). Kyriakopoulos and Moorman (2004) find that market orientation positively moderates the impact of pursuing high levels of exploitative and exploratory marketing strategies on new product performance. Kyriakopoulos and Moorman (2004) also argue that rich firms with resources to exploit and explore simultaneous compared to firms with less resources have a moderating effect on ambidexterity’s effect on firm performance.
What follows next is an overview of some of the most important studies regarding moderators on the impact of exploration and exploitation on firm performance. Table 1 gives an overview of all Independent variables and the moderators. With all the studies the dependent variable is firm performance. The table is followed by a summary per study and the different coefficients.
13 Table 1 0verview of moderators on impact of exploration, exploitation and firm performance.
Studies / Year Independent Variable Moderator
Auh and menguc (2005) Exploration Exploitation
Competitive Intensity
Jansen et al. (2006) Exploration Exploitation
Environmental dynamism Environmental competitiveness Kyriakopoulos and
Moorman (2004)
Marketing exploitation strategies Marketing exploration strategies
Market orientation
Uotila et al. (2009) Relative amount of exploration vs exploitation
Environmental conditions
Ho and Lu (2015) Marketing exploitation Marketing exploration
Supplier collaboration
Lubatkin et al. (2006) Top Management Team, Behavioral Integration
Mediator: Ambidextrous orientation
Bierly and Daly (2007) Exploration Exploitation
Environmental Dynamism Industry Technology
Auh and Menguc (2005) argue that for defenders as competitive intensity increases exploration will be positively related to firm performance while exploitation will be negatively related to firm performance. Conversely, for prospectors, exploration will be negatively related to firm performance and exploitation will be positively related to firm performance as competitive intensity increases. Their research finds that with high levels of competitive intensity for defenders and for prospectors there is no significant support for the moderating effect of competitive intension on the exploration and firm performance impact. For exploitation they found a negative and significant relation to firm performance at high levels of competitive intension for defenders (t=-5.27; p<0.001) and for prospectors a positive relation to firm performance (t=3.14; p<0.01).
14 Jansen et al. (2006) examine among other things how environmental dynamism and competitiveness moderate the effect of exploratory and exploitative innovation on firm performance. They found support for their hypothesis that, environmental dynamism positively moderates the relationship between exploratory innovation and financial performance (β=0.15, p<0.01), and negatively moderates the relationship between exploitative innovation and financial performance (β=-0.23, p<0.001). They also found support for their hypothesis that, environmental competitiveness positively moderates the relationship between exploitative innovation and financial performance (β=0.19, p<0.001).
Kyriakopoulos and Moorman (2004) argue that market orientation on a firm level creates the context within which project level marketing exploitation and exploration strategies improve new product financial performance. They found support for their hypothesis that, when market orientation is high, firms engaging in high levels of both marketing exploitation and marketing exploration strategies will have strong new product financial performance (b=1.21, p<0.05). However, as predicted by the tradeoff, they also found support for the hypothesis that, when market orientation is low, firms engaging in high levels of both marketing exploitation and marketing exploration strategies will have weak new product financial performance (b=-2.66, p>0.01).
Uotila et al. (2009) show with their study that the optimal balance between exploration and exploitation depends upon environmental conditions. They found support for their hypothesis that industry technological dynamism positively moderates the relationship between relative exploration orientation and the future financial performance of the firm (β=0.601, p<0.01).
Ho and Lu (2015) propose and test the conjecture that firms' collaborations with suppliers would moderate the impact of marketing exploitation and exploration on firm performance. Their hypothesis that a firm’s collaboration with suppliers positively moderates the effect of marketing exploration on market performance is supported (b=0.12, p<0.05). They also found support for their hypothesis that a firm’s collaboration with suppliers negatively moderates the effect of marketing exploitation on market performance (b=-0.14, p<0.01).
15 Lubatkin et al. (2006) focus their research on small- to medium-sized firms. They found support for their hypothesis that the level of behavioral integration of top management teams in small- to medium sized firms is positively associated with the extent to which they pursue an ambidextrous orientation (b=0.45, p<0.001) and an ambidextrous orientation is positively associated with subsequent firm performance (b=0.27, p<0.01).
Bierly and daly (2007) find that the competitive environment moderates the relationship between exploitation and performance and partly with exploration and firm performance. The interaction term of exploitation and dynamism is statistically significant (B=-1.635, p<0.10) and the interaction term with exploitation and technology is also significant (B=2.128, p<0.05). Exploitation in a stable, high-technology environment is associated with higher performance. For exploration Bierly and Daly (2007) only found support for moderation of high-technology environment (B=1.66, p<0.05).
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3. Hypothesis development and conceptual model
3.1 Exploration and firm performance
March (1991) defines exploration activities as including ‘things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation’ (March, 1991, p.71). Previous studies have reported a positive relationship between firms with a strong exploration focus and firm performance (e.g. Hufbauer, 1970; Mansfield, 1981; Kotabe 1990b). According to Kotabe (1990a) firm performance increases when an organization focuses on product development and improve product quality relative to its competitors. This results in advantages by differentiating products from competitors, and consequently achieving greater returns. March (1991) posits that exploration is often uncertain and the realization of returns takes generally more time than learning from exploitation. The outcome of exploration can be difficult to measure in the short-term but might be effective in the long-term.
Hypothesis 1: There is a positive relationship between a firm’s exploration focus and a firm’s long-term financial performance.
3.2 The moderating effect of sales growth on the exploration impact on firm
performance
Watts and Zimmerman (1978) proclaim that managers (agents) are self-interested and therefore make choices to maximize their own wealth. Agents have their income and their reputation tied to the firm they are relatively under diversified and stand to lose a great deal if their firm stumble or fail (Milgrom and Roberts, 1992). Shareholders (principals) are generally more diversified they are more risk neutral and seek to maximize returns on investments. In order for the principal to provide itself with some degree of assurance that the agent will act in the principal’s best interest, incentives are set into practice for the agent. In their article, Hall and Liebman (1998, p656) state that: “The most direct solution to (the) agency problem is to align the incentives of executives with the interests of shareholders by granting (or selling) stock and stock options to the CEO”. This statement proclaims that by means of stocks and stock options, managers will tend to act more in
17 the best interest of the shareholders. But as a side effect it also influences the behavior of the agent. According to the prospect theory (Tversky et al., 1992), agents are loss aversion rather than risk aversion. As the firms performance well the options will become valuable and the success trap becomes a risk as agents want to protect their wealth. When the firm’s sales growth is lagging the agent may be persuaded to invest financial assets in uncertain categories, such as research and development (R&D), capital expenditures, and acquisitions as he has no downside with regards to the value of his options but these uncertain investments will give a small chance of success and no downside. Sanders and Hambrick (2007) find statistical support for their hypothesis, which states that the heavy use of CEO stock options brings about more big losses than big wins.
When a firm’s sales are declining managers who are unable to diversify their employment should be risk averse (Eisenhardt, 1989). The risk for the manager of losing his job could increase, this could influence the manager in his decisions regarding investments. For example when Nokia lost its market share because they had no smartphone, managers within Nokia could spend free cash flow in R&D with the intention to create job security instead of investing only in projects with a financial healthy return on the investment. This study will investigate if sales growth, in a way of managerial intentionality, has a moderating affect on the exploration and firm performance relationship. In formal terms,
Hypothesis 2: Sales growth positively moderates the relationship between exploration and a firm’s long-term financial performance. In a situation of high sales growth this relationship will be stronger whereas in a situation of low sales growth this
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3.3 Exploitation and firm performance
Exploitation activities include; such things as refinement, choice, production, efficiency, selection, implementation, execution’ (March, 1991, p71). Barnett et al. (1994) argue that an awareness of changing market conditions provides opportunities for the firm to refine existing resources. Because of these arguments this study argues that marketing can be seen as exploitation.
In the literature evidence can be found that marketing capabilities contribute to better firm performance (Day, 1994; O’Driscoll et al., 2000; Dutta et al., 1999). Kotabe et al. (2002, p. 82) state that the “marketing capability of a firm “is reflected in its ability to differentiate products and services from competitors and build successful brands”. Kotabe et al. (2002) also state that spending money on advertising and promotion can increase sales both by expanding the sales as also by getting customers to switch to their product. This will result in more efficiency because of a better fit and targeting to the customer needs of their products and services. Because of the globalization of markets and the presence of intermarket segments across countries Helsen et al. (1993) state that those firms that inject substantial advertising and marketing investment emphasizing differentiation are more likely to succeed in different markets than those that do not. Firms can become more efficient by creating a standardized marketing program and herewith strengthening bargaining power with both distributors and customers (Levitt, 1983; Takeuchi and Porter, 1986). March (1991) states that the outcome of exploitation is less uncertain than exploration and the realization of the returns are generally nearer in time than exploration.
Hypothesis 3: There is a positive relationship between a firm’s exploitation focus and firm’s short-term financial performance.
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3.4 The moderating effect of sales growth on the exploitation impact on firm
performance
As discussed in paragraph 3.2 the goals of the self-interested agent can differ when sales growth is changing. Exploitation investments can have an effect on short-term firm performance (March, 1991). When agents are looking for job security they could be incentivized to create performance by investing in exploitation. Exploitation is primarily a top-down process whereby managers have the lead in refining competencies to adjust them to changing environments (Lubatkin, 2006). Managers could be tempted to conceal the fact that sales are declining by investing in exploitation to ratchet performance unsustainably. A marketing campaign though financially not appealing at the return on investment level, can create performance and postpone the realization that the environment changed away from the firm. These investments in exploitation could be far less efficient.
This study attempts to add to the current literature by examining if managers decisions with regards to exploitation are influenced by the less or more unfavorable situation they are in which will influence the efficiency of the investments made in exploitation. Within the firm unfavorable situations can occur when sales growth is lagging.
Hypothesis 4: Sales growth positively moderates the relationship between exploitation and a firm’s short-term financial performance. In a situation of high sales growth this relationship will be stronger whereas in a situation of low sales growth this
relationship decreases.
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3.5 Conceptual model
The actual design of this study can be captured as follows:
Hypothesis 2
Hypothesis 1
Hypothesis 4
Hypothesis 3
This paper will test both exploration and exploitation individually because as stated by Gupta et al., (2006) no universal argument can be made in favor of either exploitation and exploration as two ends of a continuum or as orthogonal. Only that “across different and loosely coupled domains (i.e., individuals or subsystems), exploration and exploitation will generally be orthogonal, in that high levels of exploration or exploitation in one domain may coexist with high levels of exploration or exploitation in the other domain” (Gupta et al., 2006, p. 697).
This paper assumes as the agency theory does, that people are self-interested (Eisenhardt, 1989). People make decisions based on the best outcome for themselves.
Exploration performance Firm
Sales growth
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4. Methodology
In this section a description is provided concerning the data sources used and an explanation of the operationalizations of the constructs. In addition, the analysis strategy is explained.
4.1 Research sample
The data used in this study are retrieved from the Bloomberg database. Bloomberg is a computer software system that enables professionals mainly in the financial sector to monitor and analyze financial market data as well as data from companies’ financial statements. The sample group consists of companies that are part of the STOXX Europe 600. The STOXX Europe 600 Index represents large, medium and small capitalization companies across 17 countries of the European region and across 10 sectors as shown in Table 2. The variables included in this study change across companies and over time, therefore in order to capture both of these variations simultaneously this study took measurements over a period of 3 years from 2010, 2011 and 2012. These were years of slow recovery after the 2008 financial crises.
In the dataset used for this study cross-sectional data was collected for the Independent variables and the dependent variables all measured over the same year. This was done for 3 years and this made up the dataset.
Table 2 0verview of sectors in dataset
sector frequency percent
Consumer Discretionary 104 11.5 Consumer staples 96 10.6 Energy 38 4.2 Financials 18 2.0 Health Care 109 12.1 Industrials 234 25.9 Information Technology 78 8.6 Materials 131 14.5 Telecommunication Services 40 4.4 Utilities 55 6.1 Total 903 100
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4.2 Measures
The variables included in this study to test the hypotheses are operationalized as follows.
4.2.1 Independent variables
This study uses March’s (1991) classification of exploration and exploitation allowing for a detailed examination of the way the sales growth of a company influences the effects of exploration and exploitation on firm performance.
Exploration
March (1991) defines exploration activities as including ‘things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation’ (March, 1991 p. 71). Because of these associations this study argues that exploration capabilities are primarily driven by R&D resources. Supported by earlier studies (Hufbauer, 1970; Mansfield, 1981), R&D capabilities are measured by the ratio of annual expenditure on R&D divided by sales revenue(R&D Intensity).
Exploitation
In contrast, exploitation activities include, ‘such things as refinement, choice, production, efficiency, selection, implementation, execution’ (March, 1991 p71). Barnett et al. (1994) argue that an awareness of changing market conditions provides opportunities for the firm to refine existing resources. Because of these arguments this study argues that marketing expenses can be seen as exploitation costs. The marketing efforts of a multinational firm are routinely operationalized by their advertising intensity (Capon et al., 1990), as firms are reluctant to disclose their total marketing expenditures. Advertising intensity is measured by the annual advertising expenditures divided by sales revenue.
Sales growth
This study calculated the sales growth in a year-on-year percentage change of the sales revenue in the year of the exploration and exploitation investments.
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4.2.2 Dependent variable
Researchers continue to measure firm performance using a wide array of operationalizations in their hunt for assessing the implications of different business decisions on firm performance (Venkatraman and Ramanujam, 1986). Exploration and exploitation as stated by March (1991) influence performance in different ways and time periods. Exploitation has a more direct effect where the effects of exploration are usually more distant in time (Uotila et al., 2009). Market value based measures as Tobin’s Q have the advantage of capturing short-term performance and long-term prospects simultaneously (Lubatkin and Shrieves, 1986; Allen 1993). Tobin’s Q allows using a single performance variable and test both short- and long-term performance effects.
𝑇𝑜𝑏𝑖𝑛!𝑠 𝑄 =(𝐸𝑞𝑢𝑖𝑡𝑦 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒 + 𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑀𝑎𝑟𝑘𝑒𝑡 𝑉𝑎𝑙𝑢𝑒) (𝐸𝑞𝑢𝑖𝑡𝑦 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒 + 𝐿𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐵𝑜𝑜𝑘 𝑉𝑎𝑙𝑢𝑒)
Market value based measures are used to research performance effects over varying time horizons by more empirical research (e.g. Uotila et al., 2009). The Tobin’s Q of the same year as the independent variables was used.
4.2.3 Control variables
This study uses firm size as a control variable to avoid biased results. Previous research has indicated that the size of the firm partly explains the difference in firm performance (DeCarolis and Deeds, 1999). Prior research also shows that firm size may influence the innovation and learning processes necessary for exploration and exploitation (Bierly and Daly, 2007; Damanpour, 1991; Hitt et al., 1990;). “Larger organizations usually have more control over their environment, stronger marketing skills, more bargaining power with suppliers, distributors, and regulatory agencies, more product development experience, and more resources to develop technological capabilities; but their disadvantages usually include being more bureaucratic, less flexible, stronger inertia along established paths, and lower managerial commitment to innovation”, Bierly and Daly (2007, p. 503).
24 To measure the size of the firm this study uses market capitalization and number of employees. Year dummies are included in the models to control for unobserved time effects.
4.3 Reliability and validity
The variables included in this study change across companies and over time, therefore in order to capture both of these variations simultaneously, multiple years of data is used. If the changes across time are not taken into account it could be that outcomes are specific to a given period of time making any inferences drawn based on this data to be unreliable (Kotabe et al., 2002).
To increase reliability robustness checks were done by also researching different timeframes. The regressions were run with a one and three year lag on firm performance. So for every line in the database besides Tobin’s Q in the same year this study also included for robustness checks Tobin’s Q after 1 en after 3 years. All the models were statistically significant with the time lags. The
moderator sales growth on the exploration and firm performance relationship is still statistically significant with a 1 year time lag in Tobin’s Q but no longer significant with a 3 years time lag on Tobin’s Q. (see Appendix for the tables with the 1 and 3 years lagging firm performance for both exploration and exploitation).
4.4 Data analysis
Statistical analysis was performed with the IBM SPSS Statistics Version 23 statistical package.
We dealt with missing values by excluding companies that do not report R&D budgets or advertisement budget separately. This means that only companies that had no missing data were analyzed.
The independent variables have high readings on both skewness and kurtosis, but “with large samples, skewness will not make a substantive difference in the analysis”(Tabachnick and Fidell, 2001, p. 74). “Kurtosis can result in an underestimate of the variance, but this risk is also reduced
25 with a large sample” (200+ cases: Tabachnick and Fidell, 2001, p. 75) This dataset has a N of more than 800, therefore the risk is reduced and skewness would not make a substantive difference in the analysis. The dependent variable firm performance has normally distributed items.
This study chose hierarchical regressions to measure the relative contributions of variables to the total model. The effects of the control variables were measured first and thereafter the explanatory variables and the joint effect terms. If the addition of our independent variables and the interaction term shows a change in R2 that is significant the model is determent to be
significant. In the coefficient table this study uses the unstandardized B to determine if the independent variables and the interaction is statistically significant.
26
5. Results
In this chapter the results are presented concerning the impact of exploration and exploitation on firm performance, as well as the moderating effect of sales growth.
5.1 Univariate analyses
Table 3 presents descriptive statistics and bivariate correlations. From the total 1800 observations 891 have records of R&D expenses and 403 have records of advertising expenses. All variables are measured at the ratio level. On average companies tend to focus more on exploitation than on exploration. Table 3 shows that on average 15.43% of sales revenue is reinvested in exploitation as only 4.11% is reinvested in exploration. Exploration measured by R&D expenditures as a percentile of sales revenue has a mean of 4.11% with a Standard Deviation of 8.27% indicating strongly different R&D investment behavior by companies in the sample.
Table 3 Descriptive statistics and correlation matrix
Variable Mean Std. Dev. N 1 2 3 4 5 6
1 Firm performance 1.7264 0.9214 885 1 2 Sales Growth 0.1113 0.1502 903 0.181** 1 3 Exploration 0.0411 0.0827 891 0.106** -0.080* 1 4 Exploitation 0.1543 0.1020 403 0.192** -0.121* 0.168** 1 5 Market Cap 15,419 25,813 879 -0.002 -0.034 -0.016 0.107* 1 6 Employees 52,098 83,449 877 -0.232** -0.088** -0.099** -0.132** 0.362** 1
* is significant at 0.05;**is significant at 0.01.
5.2 Bivariate analyses
For the calculations of the correlations this study used Pearson’s correlation coefficient. Exploration and firm performance have a statistically significant positive correlation. The correlation between exploitation and firm performance is also statistically significant and of a higher level than exploration. Both correlate with firm performance measured in Tobin’s Q which measures both short-term and long-term performance.
Exploitation correlates positive and statistically significant with exploration, which indicates that when companies tend to focus on learning they focus on both exploration and exploitation. The
27 control variable total number of employees has a statistically negative effect on Firm performance in line with findings of Ho And Lu (2015) that firm size is negatively associated with firm performance.
5.3 Impact of exploration on firm performance and the moderating role of sales
growth
A Hierarchical multiple regression is used to test for a positive relationship of exploration and firm performance and the moderating role of sales growth on this relationship. A Mahalanobis’ distance test is performed to locate outliers. The test measures the distances from the mean of the predictor variables. These distances have a chi-square distribution, with degrees of freedom equal to the number of predictors (Tabachnick and Fidell, 2012). Assessed using p<0.001 for this regression the cases with a greater distance are removed as outliers. As suggested by Aiken and West (1991), the variables of exploration and sales growth were mean-centered in equations where we created interaction terms, to minimize the threat of multicollinearity.
The first model in Table 4 shows the impact of the control variables on firm performance. Model 1 explains 11.6% of variances for firm performance and this is a statistically significant contribution (Sig. F change <0.01). In the second model exploration intensity is added together with sales growth and the mean centered interaction of the 2 variables. Model 2 explains another 4.4% of variances in firm performance. This is also a statistically significant contribution (Sig F change < 0.01).
Model 2 in table 4 shows significant results for a positive associating of exploration with firm performance (B = 2.738; p<0.01), finding support for Hypothesis 1. For this dataset the prediction of increase in our dependent variable Tobin’s Q is 2.738 as our independent variable R&D intensity increases with 1, which in this case is 100% of sales reinvested in R&D. For every 1% of sales invested in R&D the dependent variable Tobin’s Q increases with 0.02738.
28 The moderating effect of the mean-centered interaction between exploration and sales growth on the firm performance relationship is positive and significant (B = 15.204; p<0.01) as shown in model 2 in table 4, Finding support for Hypothesis 2.
Table 4 Hierarchical multiple regression on the relationship between exploration and firm performance
Variable Model 1 2 B B Constant 1.916 1.716 (0.057) (0.65) 2010 0.006 -0.056 (0.073) (0.073) 2011 -0.126 -0.131 (0.073) (0.071) Marketcap 7.16E-6 ** 6.90E-6 ** (0.000) (0.000) Employees -5.60E-6 ** -5.17E-6 ** (0.000) (0.000) Exploration 2.738 ** (0.544) Sales Growth 0.973 ** (0.245)
Interaction Exploration * Sales Growth 15.204
(4.368) **
Adjusted R Square 11.6% ** 16.0% **
Number of observations 745 745
29
5.4 Impact of exploitation on firm performance and the moderating role of sales
growth
A Hierarchical multiple regression is used to test for a positive relationship of exploitation and firm performance and the moderating role of sales growth on this relationship. A Mahalanobis’ distance test is performed to locate outliers (Tabachnick and Fidell, 2012). Assessed using p<0.001 for this regression the cases with a greater distance are removed as outliers. As suggested by Aiken and West (1991), the variables of exploitation and sales growth were mean-centered in equations where we created interaction terms, to minimize the threat of multicollinearity.
In table 5 in model 1, the control variables explain 9% of the variance in Tobin’s Q and is statistically significant (Sig F change <0.01). When the Independent variables exploitation and sales growth and their mean centered interaction are added in model 2, another 6.4% of variances in Tobin’s Q is explained and is a statistically significant contribution (Sig F change <0.01).
Model 2 shows that exploitation is significant positive associated with firm performance (B = 1.739; p<0.01), finding support for hypothesis 3. For this dataset the prediction of increase in our dependent variable Tobin’s Q is 1.739 as our independent variable advertising intensity increases with 1, which in this case is 100% of sales reinvested in advertising. For every 1% of sales invested in R&D the dependent variable Tobin’s Q increases with 0.01739.
The interaction effect of exploitation and sales growth on firm performance is not significant (B = 1.975; p>0.10), finding no support for hypothesis 4.
30 Table 5 Hierarchical multiple regression on the relationship between exploitation and firm performance
Variable Model 1 2 B B Constant 2.007 1.492 (0.099) (0.14) 2010 -0.017 -0.110 (0.127) (0.124) 2011 -0.086 -0.080 (0.126) (0.121) Marketcap 8.25E-6 * 7.20E-6 * (0.000) (0.000) Employees -5.09E-6 ** -4.01E-6 ** (0.000) (0.000) Exploitation 1.739 ** (0.513) Sales Growth 2.037 ** (0.477)
Interaction Exploitation * Sales Growth 1.975
(4.742)
Adjusted R Square 9% ** 15.4% **
Number of observations 363 363
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6. Discussion and conclusion
6.1 Discussion of findings
Uotila et al. (2009) state that large companies tend to systematically overemphasize exploitation. This study finds similar results as companies in this dataset focus more on exploitation than on exploration, the results also show a stronger correlation between exploitation and firm performance than between exploration and firm performance.
There is a statistically positive correlation between exploration and exploitation. When investments in exploration increase, companies tend to simultaneously invest more in exploitation. Companies that acknowledge the importance of learning tend to see the importance of both learning competences. Bierly and Daly (2007) found a strong correlation between exploration and exploitation and concluded that “firms can simultaneously pursue exploration and exploitation and the organizational barriers discussed in the literature appear to be exaggerated” (Bierly and Daly, 2007, p. 508). Gibson and Birkinshaw (2004) also respond to the simultaneous pursue, stating that both exploitation and exploration are crucial for the long-term survival and success of organizations. The results of this study are in line with the insights of these papers.
In line with hypothesis 1 this study finds that there is a positive relationship between a firm’s exploration focus and a firm’s long-term performance. Previous studies have also reported a positive relationship between a firm’s exploration focus and firm performance (e.g. Hufbauer, 1970; Mansfield, 1981; Kotabe, 1990b). This study also confirms March’ (1991) statement that the outcome of exploration though difficult to measure in the short-term, might be effective in the long-term. This study found a statistically significant positive effect on firm performance of exploration focus measured by Tobin’s Q which measures both short- and long-term performance.
The findings of this study support hypothesis 2 and find a positive moderating effect of sales growth on the exploration and firm performance relationship. More specifically, investments in exploration become more efficient when managers within the firm are in favorable situations, like high sales growth. In this situation the goals of principals and agents are more likely aligned as with the right incentives both parties prosper by maximizing firm performance. This study results also show that in unfavorable situations, like low sales growth or even declining sales, the relationship between exploration and long-term firm financial performance decreases, investments in exploration have
32 less of an impact on firm performance. The outcome of the investments are becoming less certain when the manager is in an unfavorable situation. This could make investments in exploration in unfavorable situations riskier without the coherent possibility of more performance. Agency theory assumes a linear and positive link between risk and performance (Jensen and Meckling, 1976). But literature is by far conclusive about the relationship between risks and return. Bowman (1980) found a negative relationship between risk and return, which developed a whole research stream known as “Bowman’s paradox” (Nickel et al., 2002). Later on Bowman (1982) finds through an experiment, that individuals who are placed in an unfavorable situation make choices that are consistent with risk seeking rather than with risk aversion. In this article Bowman (1982) referred to three different industry studies that suggest that this is not only the case for individuals but also implies to troubled companies that take lager risks and could be one of the explanations for the paradox of the negative association between risk and return within industries as measured in his earlier work. Bromiley (1991) verified this in his research, which states that low performance drives risk taking. This could be the underlying effect this study captured, together with managers changing their objectives in unfavorable situations. In agency theory problems arise when agents and principals have different interests and both are trying to maximize their own utility (Jensen and Meckling, 1976). This could be what happens in unfavorable situations like low sales growth, managers no longer are interested in maximizing firm performance, but in job security. Managers’ decisions concerning exploration investments could be influenced by self-interest. Managers could decide to invest in riskier and less efficient projects that could create job security instead of a financial return on investment. This could result in a less positive or even negative relationship between risk and financial return and subsequently in decreasing relationship between exploration and firm performance in unfavorable situations.
In line with hypothesis 3, findings show a positive relationship between exploitation and short-term firm performance. This is in line with literature about the relationship between marketing capabilities and firm performance (Kotabe et al., 2002; Helsen et al., 1993; Takeuchi and Porter, 1986; Levitt, 1983). This research confirms that investments in marketing will have a positive effect on firm performance in the short-term.
33 That this study captures both explorations and exploitations positive effect on firm performance is also in line with the literature, Uotila et al. (2009) found that exploitation activities lead to positive short-term performance effects and exploration oriented activities performance effects usually occur in the long run. Firm performance operationalized by Tobin’s Q measures both time frames.
The strength of the effect of exploration and exploitation on firm performance in this study deviates from some empirical studies. For example Bierly and Daly’s (2007) findings, that exploitation is a stronger driver of performance than exploration. Furthermore population ecology (Carroll and Hannan, 2000; Hannan and Freeman, 1977, 1984) states that due to build up inertia large organizations are better suited to exploit today’s markets than adapting to fast changing environments. This study reveals that for exploration and exploitation the significant unstandardized coefficients (B) are 2.738 and 1.739 respectively. Exploration and exploitation are both measured as a percentage of sales revenue, 1 being 100 % of sales. Deriving from this every 1 percent of sales revenue invested in exploration increases Tobin’s Q by (0.01(R&D intensity)*2.738(B)) 0.02738 and every 1% of sales invested in exploitation increases Tobin’s Q by (0.01(advertising intensity)*1.739(B)) 0.01739. This study shows in contrast with Bierly and Daly (2007) that exploration is a stronger driver for performance than exploitation.
The means of exploration and exploitation in the dataset show that on average 15.43% of sales revenue is invested in exploitation and only 4.11% in exploration. March (1991) states that firms that overemphasize exploitation reduce learning of new skills and might become captive of outdated practices, knowledge and resources, possibly depressing their long-term performance. According to the dataset used for this study it seems that on average firms tend to be subject to the “success trap” (Levinthal and March, 1993). The success trap refers to managers that focus on the exploitation of their historically successful current business activities and as such neglect the need to explore new territory. This will lead to organizational inertia that prevents the organization from properly adapting to changing environmental conditions, which will cause poor performance outcomes in the long run (Levinthal and March, 1993; Smith and Tushman, 2005). According to the results of this study it would be more efficient to find a better balance between the two learning competences and invest more in exploration and less in exploitation.
34 Hypothesis 4 predicts that when sales growth is high the effect exploitation has on firm performance will be stronger and when sales growth is low the effect on the relationship decreases. The findings of this study do not support hypothesis 4. Contrary to the findings for exploration it seems that managers in unfavorable situations are not negatively influenced in their decision making with regard to investments in exploitation. Considering March (1991), that the outcome of exploitation is less uncertain than exploration, one can also argue that investments in exploitation although made for the wrong reason does still positively contribute to firm performance.
6.2 Contributions
This research contributes by adding empirical evidence to previous studies that investigated and found a positive relationship between exploration focus and firm performance (e.g. Hufbauer, 1970; Mansfield, 1981; Kotabe 1990b). Adding to the empirical evidence regarding exploitation and its positive effect on firm performance (Day, 1994; O’Driscoll et al. 2000; Dutta et al. 1999) is another contribution of this study.
This study adds to the current body of literature by investigating whether the favorable or unfavorable situation the manager is in - captured by sales growth/decline as a moderating variable - influences his decisions with regard to investments in exploration and exploitation and how this, in turn, affects both long-term and short-term firm financial performance. The results of this study show evidence for a moderating effect of sales growth on the relationship between exploration and long-term firm financial performance. This study argues that agency theory can be an explanation for the moderating effect. These results have implications for managerial understanding of the efficiency of investing in exploration. From a principal point of view the contribution can be valuable especially in circumstances of relative low sales growth. In these circumstances normal alignment of goals procedures like stockownership for managers seems to be less effective and it could be better to investigate other means accomplishing the alignment of goals. Furthermore principals could implement standardized thresholds for investments in exploration like minimum expected returns on investments to take more control over the allocation of resources.
35 The findings of this study in combination with the agency theory and the self-interested manager could be an explanation to the “Bowman’s Paradox” where Bowman (1980) found a negative relationship between risk and reward in unfavorable situations.
Another contribution comes from the fact that the results of this study show a stronger impact of exploration than of exploitation on firm performance. This challenges the current literature which seems to agree upon firms being better suited for exploitation than for exploration (Bierly and Daly, 2007; Carroll and Hannan, 2000; Hannan and Freeman, 1977, 1984)
6.3 Limitations and future research
This study has limitations which, in turn, could provide opportunities for future research.
A first limitation is regarding the data. This study used the Eurostoxx600 index and subtracted data for the period from 2009 until 2015. Doubts may emerge concerning possible survivor bias. The longer the period, the greater survivorship bias (Elton et al., 1996). One could argue that as the sample only includes firms that were capable of surviving the time period that was studied and could still make the requirements for the index may not properly represent the population.
This study measured exploration, exploitation and the impact on firm performance separately. As shown by earlier research (e.g. March, 1991; junni et al., 2013; lubatkin et al., 2006) the balance between exploration and exploitation can also influence performance and could be considered in future research.
This study measured exploration by using the R&D expenditures of the firm. This study does not allow examining the isolated effect of research activities and development activities separately (Kotabe, et al., 2002). Future research could focus on these details and investigate their impact on firm performance.
36 This study uses advertising intensity as a operationalizing of exploitation one must realize that this does not fully reflect a firm’s investments in exploitation activities. Future research could add to the literature by investigating other proxies and replicate this study. To operationalize the favorable or unfavorable situation the firm is in, this study used sales growth. Future research could replicate this study using other operationalizations. Firm performance has been measured in the literature using a wide array of operationalizations. This study used Tobin’s Q to capture both short-term performance and long-short-term prospects (Lubatkin and Shrieves, 1986; Allen, 1993). Future research could use financial or operational performance measures and replicate this study for more empirical evidence.
6.4 Conclusion
This study adds to the current body of literature by contributing sales growth/decline as a moderator for the exploration relationship with firm performance; the results did not show this effect for exploitation. This study argues a new understanding of how the favorable or unfavorable situation the manager is in influences his decisions with regard to investments in exploration and exploitation and how this, in turn, affects both long-term and short-term firm financial performance. For the dataset the EUROSTOXX 600 index from 2010-2012 results show that sales growth positively moderates the exploration and firm performance relationship. This study suggests that alignment of goals between agents and principals differ in unfavorable circumstances, which could explain this effect. The self-interested agent with no option to diversify can become risk averse in achieving his goal and will undertake risky investments within the firm to try to create job security, without considering the principals’ interest to maximize the financial return on the investment. This potentially can start a vicious circle, once a firm starts to perform poorly, matters will keep getting worse and worse.
Instead of “just” running twice as fast (exploitation), as the red queen told Alice to do, to get somewhere it might be more important to find an alternative route (exploration) to get somewhere, as this study shows a stronger impact of exploration than of exploitation on firm performance. Certainly just as important is that within the firm there is agreement about that route to take and especially where the finish is located.
