Absorptive capacity: Important, essential or
detrimental for performance in organizational and
sequential ambidexterity?
M.A van der Vaart
S3275876
Supervisor: prof. dr. J.D.R. (Jana) Oehmichen
Co-assessor: dr. J.D. (Hans) van der Bij
Groningen, 21
stJanuary 2019
Word count: 11.730
Master thesis
MSc. BA Strategic Innovation Management
Faculty of Economics and Business
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ABSTRACT
This paper builds on the dynamic capability theory, where the effects of organizational and sequential ambidexterity on firm performance and the moderating role of absorptive capacity are examined. Hypothesized is that organizational and sequential ambidexterity are positively related to firm performance, while absorptive capacity will strengthen this relationship. This relationship is expected since absorptive capacity is a crucial component of the dynamic capability that explains a firm’s internal resource and external marketplace-based competitive advantage. Without having one, firms will have diminishing returns. Through an empirical analysis examining 242 companies within a timeframe of 16 years, the findings show contradicting results to the built hypotheses. Although sequential ambidexterity found a strong significant positive relationship with firm performance, organizational ambidexterity did not. The main contribution of the study is the result with regards to absorptive capacity. A negative relationship with firm performance is found. Additionally, absorptive capacity moderates the relationship between sequential ambidexterity and firm performance negatively. The main reason for this relationship is the way of measuring absorptive capacity, which is measured as the R&D intensity. This can be explained in multiple ways. First, the measurement is rather static, while the process of absorptive capacity is cumulative. Second, the measurement lacks the focus of the absorptive capacity of firms. It does not distinguish between internally developed and externally sourced technologies. Lastly, environmental differences need to be considered when measuring absorptive capacity since this affects the willingness to invest in R&D.
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INTRODUCTION
It is critical for companies to keep innovating in order to sustain a competitive advantage (Schumpeter, 1942). When companies achieve to become an ambidextrous organization, it permits them to increase their short- and long-term innovations. In turn, it enables them to sustain a competitive advantage and perform on a high financial level (e.g Gibson & Birkinshaw, 2004; He & Wong, 2004; O’Reilly & Tushman, 2013; Tushman & O’Reilly, 1996). The concept of absorptive capacity is claimed to be a crucial element in achieving ambidexterity by acquiring, assimilating, transforming and exploiting knowledge (Cohen & Levinthal, 1990; Rothaermel & Alexandre, 2009; Zahra & George, 2002).
Ambidexterity, the ability to use both hands with equal skills, is used in literature as a metaphor for pursuing exploration and exploitation at equally high levels (Halevi, Carmeli, & Brueller, 2015; Simsek, 2009; Tushman & O’Reilly, 1996). Many conceptualizations of ambidexterity are offered by the literature. Two of the most important are organizational and sequential ambidexterity. While these concepts both claim to achieve ambidexterity, their characteristics differ significantly (Lavie, Stettner, & Tushman, 2010; O’Reilly & Tushman, 2013). Organizational ambidexterity is the process of performing explorative and exploitative innovation simultaneously (Jansen, George, Van Den Bosch, & Volberda, 2008; Tushman & O’Reilly, 1996). On the other hand, sequential ambidexterity is achieved in a sequential fashion by either pursuing exploration or exploitation at one point in time (Duncan, 1976; O’Reilly & Tushman, 2013; Raisch, Birkinshaw, Probst, & Tushman, 2009). Achieving either organizational ambidexterity (Gibson & Birkinshaw, 2004; Levinthal & March, 1993; March, 1991) or sequential ambidexterity (Chou, Yang, & Chiu, 2018; Mudambi & Swift, 2014; Swift, 2016) is claimed to increase firm’s success and survival.
The underlying theory of this paper, the dynamic capability theory, explains this success of ambidextrous firms in the way that successful firms are characterized by the ability to timely respond to changes (Eisenhardt & Martin, 2000; Teece, Pisano, & Shuen, 1997). Ambidexterity can be seen as such a dynamic capability since they reflect under the same conditions under which they are valuable. The combination of exploration and exploitation gives firms the ability to adapt over time (Benner & Tushman, 2003; O’Reilly & Tushman, 2008). Ever since the ambidexterity research has gained attention, the concepts were associated with dynamic capabilities (Danneels, 2011; Harreld, O’Reilly, & Tushman, 2007; Leonard-Barton, 1992; O’Reilly & Tushman, 2008).
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knowledge into usable knowledge and exploits it in order to build other organizational competencies. In organizational ambidexterity, absorptive capacity helps to overcome the tensions of exploration and exploitation to avoid that the one, or the other becomes too dominant (e.g. Cohen & Levinthal, 1990; Rothaermel & Alexandre, 2009; Zahra & George, 2002). Furthermore, considering sequential ambidexterity, it helps to make the leap between exploitation towards exploration when moving from periods of stability to periods of intense change (and vice versa) (e.g. Chou, Yang, & Chiu, 2018; O’Reilly & Tushman, 2013). In both forms of ambidexterity, absorptive capacity can help to sustain a competitive advantage for firms. Yet, the importance is claimed to differ in the relevant literature. While absorptive capacity is an important part of organizational ambidexterity, the literature with regards to sequential ambidexterity claims that it is essential and firms are doomed to fail without it (Chou et al., 2018; Swift, 2016).
However, this assumption has never been empirically tested. It is important to fill this research gap for literature on organizational and sequential ambidexterity to better understand what their drivers of the positive relationship with firm performance are. Furthermore, for managers in companies with a high level of absorptive capacity, it is important to fill this gap to make them be able to determine whether to pursue exploration and exploitation simultaneously or in sequences to achieve the highest firm performance. Thus, the question remains whether a difference in importance of absorptive capacity between organizational and sequential ambidexterity exists in their relationship with firm performance. Therefore, the following research question is going to be investigated:
How does absorptive capacity influence performance of firms that perform organizational and sequential ambidexterity?
In order to answer the research question, the following sub-question needs to be answered first: What is the influence of organizational and sequential ambidexterity on firm performance?
The research is conducted on the firm-level perspective with a sample of 241 firms in the manufacturing and services industry. In contrast to the discussed findings derived from relevant literature, the results show that absorptive capacity is not beneficial and even negative for firm performance in general. Also, it moderates the relation of sequential ambidexterity and firm performance negatively, while no significant moderation effect is found for the relation between organizational ambidexterity and firm performance.
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study. Prior scholars developed the proxy of the R&D intensity as the measurement of absorptive capacity (Cohen & Levinthal, 1989, 1990; Rothaermel & Alexandre, 2009; Swift, 2016; Tsai, 2001). However, this measurement is rather static (Cohen & Levinthal, 1990), while the absorptive capacity of firms is cumulative (Escribano, Fosfuri, & Tribó, 2009). The measurement also lacks the focus of the absorptive capacity of firms. It does not distinguish between internally developed and externally sourced technologies. Furthermore, R&D intensity could be influenced by environmental differences, since this affects the willingness to invest in R&D. To conclude, the method of measuring the absorptive capacity of previous studies to use R&D intensity is not reliable.
The following sections of this paper are structured as follows: the first paragraph will outline the relevant theory, including all important concepts which will subsequently lead to the hypotheses development. Second, the applied methods will be described. After which the findings of the conducted study are assessed and discussed. Last, the conclusion, limitations and future research, as well as theoretical and managerial implications, are presented.
THEORY
The underlying theory used in the paper is the dynamic capability theory. This theory is heavily connected with ambidexterity since exploration and exploitation are present in both, which helps firms to sustain a competitive advantage and ultimately brings firms success. The theory explains this relation and built up hypothesis with regard to ambidexterity and firm performance. Ambidexterity can be put in to three groups: contextual (De Clercq, Thongpapanl, & Dimov, 2014; Gibson & Birkinshaw, 2004), simultaneous or organizational (Jansen et al., 2008; Tushman & O’Reilly, 1996) and sequential ambidexterity (Mudambi & Swift, 2014; O’Reilly & Tushman, 2013). However, this paper will only focus on organizational/simultaneous and sequential ambidexterity. Lastly, the moderation effect of absorptive capacity, which is a critical component of a dynamic capability, on the relation between ambidexterity and firm performance is investigated.
Dynamic capability: Underlying theory
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with many rapid changes while others do not (Barreto, 2010; Eisenhardt & Martin, 2000; Teece et al., 1997; Wang & Ahmed, 2007; Wu, 2010). The dynamic capability theory extends the RBV by explaining this phenomenon. The dynamic capability theory states that successful firms are characterized by the ability to timely respond to changes, to continuously renew their knowledge bases and to rapid and flexible product innovations (Lewin & Volberda, 1999; Teece et al., 1997; Wu, 2010). Besides, those firms are able to redeploy external and internal competencies due to a managerial capability (Teece et al., 1997; Wu, 2010).
The dynamic capability theory originates from the paper of Teece et al. (1997) who define it as the firm’s ability to integrate, build and reconfigure internal and external competencies to address rapidly changing environments. However, this implies that a rapidly changing environment is needed for the existence of dynamic capabilities, but in moderate dynamic or stable industries firms do also integrate, build and reconfigure internal and external competencies (Barreto, 2010; Eisenhardt & Martin, 2000; Zahra, Sapienza, & Davidsson, 2006) Therefore, this paper will define dynamic capabilities according to Zullo & Winter (2002) who state that dynamic capabilities are a learned stable pattern of collective activity through which the organization systematically generates and modifies its operating routines in pursuit of improved effectiveness (Zollo & Winter, 2002).
Additionally, Teece (2007) adds to this definition by disaggregating dynamic capabilities into “the capacity to (1) sense and shape opportunities and threats, to (2) seize opportunities, and to maintain competitiveness through enhancing, combining, protecting, and, when necessary, (3) reconfiguring the business enterprise’s intangible and tangible assets” (Teece, 2007: 1319). Many authors explain firm-level success with dynamic capabilities and find direct links between dynamic capabilities and performance of firms (Barreto, 2010; Jantunen, Tarkiainen, Chari, & Oghazi, 2018; Teece et al., 1997; Wu, 2010; Zollo & Winter, 2002).
Ambidexterity and dynamic capability
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mean to simply achieve both exploration and exploitation at the same level, but maximizing the attainment of both (Simsek, 2009).
After Teece et al. (1997) and Eisenhardt & Martin (2001), many authors conceptualized dynamic capabilities in their study. For example, Luo (2002) conceptualized dynamic capabilities as the exploitation and upgrading capability, while Shamsie, Martin, & Miller (2009) conceptualized the dynamic capability as replication and renewal. Both consist of two categories, which can be related to exploration and exploitation, instead of the traditional three introduced by Teece et al. (1997) and Teece (2007). However, these conceptualizations could also be merged from three into two categories. The integration/seizing and reconfiguration could be merged towards the exploitation capability since both are associated with replication of external resources for internal use. Besides, the creation of new resources/sensing is similar to the exploration capability since they both focus on the creation of new resources (Zhan & Chen, 2013). Therefore, dynamic capabilities are present in both exploration and exploitation. Furthermore, Benner & Tushman and O’Reilly & Tushman (2008) found that ambidexterity and dynamic capabilities reflect the same condition under which they are valuable. Additionally, they stated that the ambidexterity can be seen as a dynamic capability since firms who simultaneously explore and exploit give them the ability to adapt over time. Many research papers have associated the concept of ambidexterity with dynamic capabilities (e.g. Danneels, 2002, 2011; Harreld et al., 2007; Leonard-Barton, 1992; O’Reilly & Tushman, 2008; Vahlne & Jonsson, 2017). Therefore, this paper will treat ambidexterity as a firm’s dynamic capability as well.
Organizational ambidexterity
Organizational ambidexterity is the process of simultaneously performing explorative and exploitative innovation within the organization (Jansen et al., 2008; Tushman & O’Reilly, 1996). As stated above, exploration is characterized by new and radical activities for long-term profits in emerging markets (Abernathy & Clark, 1985; Benner & Tushman, 2003; Piao, 2010). Besides, exploitation is characterized by incremental activities focused on short-term profit for current customer needs on the market (Abernathy & Clark, 1985; Benner & Tushman, 2003; March, 1991).
Previous studies revealed that the balance between exploration and exploitation is necessary for survival and lead to greater firm success (Gibson & Birkinshaw, 2004; Levinthal & March, 1993; March, 1991). According to the dynamic capability theory, organizational ambidexterity, as dynamic capability, can offer a competitive advantage. However, itself is not a source of competitive advantage, but it facilitates new resource configurations that might offer a competitive advantage (Eisenhardt & Martin, 2000; O’Reilly & Tushman, 2008).
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Hughes, & Hotho, 2011; Halevi et al., 2015; Jansen, Van Den Bosch, & Volberda, 2006). On the one hand, the balance withholds firms to fall an over-exploration trap, also called the failure trap. Here, instead of focusing only on the long-term profit, without gaining benefits in the short run, the balance allows firms to additionally focus on short-term profit (Levinthal & March, 1993; O’Reilly & Tushman, 2008; Volberda & Lewin, 2003). On the other hand, the balance withholds firms from over-exploitation. This process is characterized by the inability to respond to environmental changes due to the competence trap. In this trap, people might believe that the same practice may lead to more success in the future and do not see reasons to change. This leads to structural inertia. Ambidexterity helps to overcome tensions to focus on both short- and long-term profit. Firms who only focus on short-term profit can easily overlook new technologies and might miss out on new innovations (Ahuja & Lampert, 2001; Levinthal & March, 1993; O’Reilly & Tushman, 2008; Volberda & Lewin, 2003). Furthermore, firms that only focus on long-term profit do not gain profit in the short run (Levinthal & March, 1993; Volberda & Lewin, 2003). Therefore, the following hypothesis can be derived:
Hypothesis 1: Organizational ambidexterity has a positive impact on firm performance.
Sequential ambidexterity
In contrast to organizational ambidexterity, sequential ambidexterity is achieved in a sequential fashion by either pursuing exploitation or exploration at one point in time (Duncan, 1976; O’Reilly & Tushman, 2013; Raisch et al., 2009). Firms pursue exploitative R&D in periods of stability and move to explorative R&D in periods of intense change (Mudambi & Swift, 2014; Swift, 2016). The perspective originates from the punctuated equilibrium theory in which firms adapt to environmental shifts by redefining their processes and structures (Levinthal & March, 1993; March, 1991; O’Reilly & Tushman, 2013; Swift, 2016).
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Boumgarden et al. (2012) argue that firms using a structure which promotes either exploration, via decentralization and autonomy, or exploitation, via centralization and integration, increases the organization’s commutation pattern, knowledge flow and decision-making routines. They can make use of the advantages of an organic structure when performing explorative projects, but also from the advantages of a mechanistic structure when performing exploitative projects (Chou et al., 2018). In doing so, firms can make the most efficient use of the structure in combination with their innovation processes (Boumgarden, Nickerson, & Zenger, 2012; Nickerson & Zenger, 2002). However, firms need to effectively make the leap between exploration and exploitation. This transition between explorative and exploitative projects can be highly disruptive when jumping between the two multiple times in a short period (O’Reilly & Tushman, 2013). In order to handle the constant change, firms need to timely respond to changes in the market (Eisenhardt & Martin, 2000; Teece, 2007). As the dynamic capability theory states, firms who are able to timely respond to changes are successful. The dynamic capability of firms give managers the ability to rapidly and efficiently allocate their resources and allows the firm to be flexible in handling transition uncertainties (Chou et al., 2018; Teece et al., 1997; Wu, 2010).
To conclude, when firms successfully make the leap between exploration and exploitation they can gain a competitive advantage and thereby increasing their firm performance. Therefore, the following hypothesis can be derived:
Hypothesis 2: Sequential ambidexterity has a positive impact on firm performance.
Ambidexterity and absorptive capacity
Absorptive capacity is widely defined as the firm’s ability to value, assimilate and apply new knowledge to commercial ends (Cohen & Levinthal, 1990; Datta, 2011; Todorova & Durisin, 2007). The concept is similar to an information processing capacity but is applied to firm level rather than an individual level perspective (Datta, 2011). When possessing an absorptive capability, the firms’ awareness of new opportunities increases. This can lead to developing a competitive advantage and to a significant increase in innovation performance (Swift, 2016). Furthermore, it can enhance the firm’s interaction with the external environment (Rosenkopf & Nerkar, 2001) and increases learning among business units within the organization (Lavie et al., 2010). In the dynamic capability theory, absorptive capacity is one of the three critical components of the dynamic capabilities, besides the adaptive and innovation capability, that explains the firm’s internal resource and external marketplace-based competitive advantage. Without having one, firms will have diminishing returns (Grant, 1996; Wang & Ahmed, 2007).
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brings the knowledge acquisition in-house and assimilates it through the organization. In contrast, the realized absorptive capacity transforms this knowledge into useable information and exploits it to build other organizational capabilities (Zahra & George, 2002). Both can add to each other in the way that the potential absorptive capacity obtains more knowledge and solutions, while the realized absorptive capacity determines the importance and usage (Chou et al., 2018). Moreover, these two processes can bring tensions in the organization when one of the two is too dominant within the organization. This will cause that the other will be dysfunctional (Cohen & Levinthal, 1990; Rothaermel & Alexandre, 2009). Thus, both factors need to be balanced in order to successfully make use of the absorptive capacity.
Furthermore, absorptive capacity helps firms to overcome the tensions of organizational ambidexterity. First, firms that acquire and assimilate new knowledge (potential absorptive capacity) may suffer from the costs of acquiring new knowledge without gaining benefits (Zahra & George, 2002). Ambidexterity literature outlines this fact as the failure trap or over-exploration (Levinthal & March, 1993; Volberda & Lewin, 2003). The chances of over-exploration are decreased by absorptive capacity since it helps firms to better predict the potential of their innovations (Cohen & Levinthal, 1990; Rothaermel & Alexandre, 2009; Zahra & George, 2002). When firms see that the potential of their innovation is too low, they are able to cut them off.
Second, firms that transform and exploit their knowledge (realized absorptive capacity) may only achieve short-term profits and fall into a competence trap (over-exploitation) (Datta, 2011; Rothaermel & Alexandre, 2009; Zahra & George, 2002). The trap causes that people might believe that the same practice may lead to more success in the future and don’t see reasons to change. This can lead to structural inertia, which makes them unable to respond to environmental changes. Absorptive capacity can help overcome this problem in two ways. First, it can provide firms with the ability to make novel linkages among different types of existing knowledge. Second, it can help to link newly acquired external knowledge with existing internal knowledge. In this way, firms can overcome the competency trap and pursue exploratory innovations (Cohen & Levinthal, 1990; Datta, 2011; Grant, 1996; Raisch et al., 2009; Rothaermel & Alexandre, 2009; Zahra & George, 2002). In line with this reasoning, absorptive capacity helps overcome the tensions of exploration and exploitation in order to gain a competitive advantage and ultimately achieve higher firm performance. Consequently, the following hypothesis can be derived:
Hypothesis 3: Absorptive capacity moderates the relationship between organizational ambidexterity and firm performance that the relationship becomes more positive.
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exploration and exploitation. They argue that the leap between explorative and exploitative projects (and vice versa) in sequential ambidexterity can be highly disruptive when changing multiple times in a short time period. Absorptive capacity can help to make this transition in two ways.
In the transition from an exploitative project towards an explorative project, a firm which can apply external knowledge for internal use can make this leap more effectively and can contribute to their exploratory projects (Chou et al., 2018). The potential absorptive capacity can contribute to this in the sense that the firm has more knowledge available to apply. Furthermore, in the transition from an explorative towards an exploitative project, the realized absorptive capacity can heavily contribute by applying and distribute knowledge within the organization (Chou et al., 2018). Overall, absorptive capacity determines how much knowledge can be obtained and how effectively it can be applied. So, if a firm makes the leap and can employ more resources, it can gain a competitive advantage. Firms having many resources can better fluctuate between exploration and exploitation since they have sufficient knowledge for exploration in-house and have enough time to exploit this available knowledge at a later point in time (Goossen & Bazazzian, 2012).
Hypothesis 4: Absorptive capacity moderates the relationship between sequential ambidexterity and firm performance so that the relationship becomes more positive.
As described, the organizational ambidexterity literature stresses the importance of absorptive capacity. They argue that it contributes to an increase in firm performance by helping to overcome the danger of over-exploration and exploitation. However, it just contributes and is not an essential part of performing organizational ambidexterity. This is different in sequential ambidexterity; the underlying dynamic capability theory explains this by stating that successful firms are characterized by the ability to timely respond to changes (Eisenhardt & Martin, 2000; Teece et al., 1997). This is harder for sequential ambidexterity to achieve without having the absorptive capacity capability since they have to make the leap between exploration and exploitation when responding to changes. When firms do not have the capability of absorptive capacity and therefore failing to make the transition, they are doomed to fail since knowledge will be lost quickly (Chou et al., 2018; Swift, 2016). Therefore, expected is that absorptive capacity is more important in the relationship of sequential ambidexterity and firm performance than in the relationship of organizational ambidexterity and firm performance.
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Conceptual model
All the above-mentioned hypothesis leads to the following conceptual model:
Figure 1: Conceptual model
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METHODS
Sample and data collection
The data is retrieved from the Ambidexterity Financials dataset provided by the Department of Innovation and Strategy of the University of Groningen. The data display 242 companies from the service and manufacturing industry with data from the year 2000 until 2016. Additional data is gathered via the Thomson Reuters DataStream database which is merged with the Ambidexterity Financial dataset. After accounting for missing values, the final dataset consists of 2.064 observations of 242 companies. The dataset consists of panel data as the observations are grouped per company and per year.
Measurement
Dependent variable
Firm performance is measured by the Tobin’s Q, which is defined as the ratio of the market value of a firm to the replacement cost of its assets. The Tobin’s Q is calculated as the market capitalization plus the total assets minus the total shareholder equity divided by the total assets. Firms with a value greater than zero create economic value since they can be sold for more than it costs to obtain their assets (Mudambi & Swift, 2014). The advantages of the Tobin’s Q above the return on assets or return on equity as firm performance measurements are that the Tobin’s Q is a forward-looking measurement, while the return on assets and return on equity only look at current results (Goossen & Bazazzian, 2012; Wang & Li, 2008). The market capitalization includes all future cash flows of the company. Thus, it looks at short-term performance as well as at its long-term profitability (Goossen & Bazazzian, 2012; Uotila, Maula, Keil, & Zahra, 2009).
Independent variables
Sequential ambidexterity
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reason for this difference is that the studentized residual is calculated for every company by dividing the forecasted residual at that point by the standard deviation of all residuals for the entire year-frame (Hutcheson & Sofroniou, 1999).
Organizational ambidexterity
Following the papers of Heyden et al. (2015) and Uotila et al. (2009), organizational ambidexterity is measured as the relative amount of exploration and exploitation on firm-level obtained in the firm’s annual reports. For this measurement, the CATA (computer-aided text analysis) method is used. The specific words of exploration, exploitation and ambidexterity that are counted are retrieved from the study of Uotila et al. (2009) which made use of the studies of March (1991) and Volberda et al. (2001). Examples of exploration words that are used are “search variation”, “risk-taking”, “experimentation”, “play”, “flexibility”, “discovery” and “innovation” (March, 1991), whereas for exploitation “refinement”, “choice”, “production”, “efficiency”, “selection” “implementation, and “execution” are examples (March, 1991). Other measurements for organizational ambidexterity mostly only capture financial returns of exploration and exploitation for firms (Heyden, Oehmichen, Nichting, & Volberda, 2015). In contrast, the advantage of using annual reports as measurement is that the strategies of firms can be compared over time (Oehmichen, Heyden, Georgakakis, & Volberda, 2017). Additionally, for this measurement, the data is available for a broad number of firms including a wide time-frame. Furthermore, it can be used for a large scale of industries.
Moderator
Absorptive capacity
The study follows the papers of Cohen & Levinthal (1990), Swift (2016) and Tsai (2001) by using the proxy of R&D intensity to measure the absorptive capacity as a moderation effect. Specifically, it is measured as the R&D expenditures divided by firm sales. Other studies, like Rothermael & Alexandre (2009), state that the usage of R&D expenditures of firms can be seen as a reflection of the willingness of firms to invest in their absorptive capacity via R&D expenditures.
Control variables
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Company size. Company size is measured as the number of employees per firm. The natural logarithm is included to reduce the impact of big outliers and therefore it normalizes the data. Firm size is controlled for as large firms might have more resources, but suffer from structural inertia (Jansen et al., 2006).
Return on equity. When assessing the effect of firm performance, it is critical to control for prior firm performance (Rothaermel & Alexandre, 2009). Differences in firm performance might affect the strategic orientation of firms (Heyden et al., 2015). The control variable is calculated as the net income preferred divisions minus preferred dividend requirement divided by the last year's common equity times 100.
R&D expenses. R&D expenses have to be controlled for because they affect the firm’s innovation level. R&D expenditures help absorb, transform and exploit knowledge (Cohen & Levinthal, 1990; Uotila et al., 2009). The natural logarithm is included to reduce the impact of big outliers and therefore it normalizes the data.
Industry. The study controls for a difference between the services and manufacturing industry using a dummy variable. The study of Geerts, Blindenbach-Driessen & Gemmel (2010) hypothesized that the services industry has less radical and technological innovations, which means that there is no need to continuously innovate on the explorative level. For this reason, organizational ambidexterity might be less successful in service industries then sequential ambidexterity is (Geerts, Blindenbach-Driessen, & Gemmel, 2010). In more dynamic markets, such as the manufacturing industry, a simultaneous approach of doing exploration and exploitation might be more suitable (O’Reilly & Tushman, 2013; Raisch & Birkinshaw, 2008).
Year. There is also controlled for year effects by including year dummies to account for time effects (Yanadori & Marler, 2006).
Analysis method
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avoid big outliners in the data. Moreover, the OLS makes the observations random components for the response variable. In order to avoid this, the data is set as panel data per company and year.
An additional multiple OLS analysis is conducted to check for industry differences. The significant difference is tested in a two-sample t-test using groups with equal variances since it is assumed that data is normally distributed.
Lastly, a robustness check is conducted to improve the reliability of the regression models. The performance indicator, which is used as a dependent variable (Tobin’s Q), is replaced by another Tobin’s Q variable and a return on assets performance variable in order to check for consistency in the results. The robustness variables are measured as follows:
Tobin’s Q
Return on Assets
RESULTS
At first, the mean, standard deviation and correlations between the variables are measured and shown in table 1. In total, 2.064 observations for all variables are included. Most correlations found are low and very low. The most surprising very low correlation is found between the two sorts of ambidexterity. The two were expected to find a high correlation, since both measure ambidexterity in a different way. The correlation coefficient is r = -0,06, which means that both have a negative correlation with a very small coefficient.
Furthermore, the moderating effect of absorptive capacity is measured through R&D expenses divided by firm sales, whereas sequential ambidexterity is measured by using R&D expenses as well. One would expect the two variables to be highly correlated, but the opposite is found. The both have a correlation coefficient of r = 0,00. A moderate correlation coefficient is found between organizational ambidexterity and company size, which are correlated with a coefficient of r = 0,39. Moreover, sequential ambidexterity and company size are correlated with r = 0,06. Lastly, sequential and organizational ambidexterity are correlated with industry with a coefficient of
Market Capitalization + Preferred Stock + Long Term Debt Total Assets - Short Term Debt & Current Portion of Long Term Debt
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r = -0,07 and r = 0,04. The only high correlation coefficient is company size with R&D expenses (r = 0,82). A possible reason might be the logarithmic transformation of the variables.
Table 1: Descriptive statistics and correlation table
Since there are no high correlation coefficients in general, no problems regarding multicollinearity are expected. To fully exclude the presence of multicollinearity, a variation inflation model is tested since a high degree of multicollinearity might be a serious problem for the interpretation of the results (Hutcheson & Sofroniou, 1999). The results are shown in table 2. The average of the variation inflation factors (VIF) for all variables is 1,75 with the highest values for company size (3,49) and R&D expenses (3,42). The relatively high VIF values can be explained by the reason that both are logarithmic transformations of their variable. The values are below the maximum threshold of 10 (Robinson & Schumacker, 2009). Therefore, there is no multicollinearity found in the data.
Table 2: Variation inflation model
Regression results
In order to test the hypotheses, a random-effects generalized linear model modelling technique: a multiple regression analysis is conducted. The results are shown in table 3. The results show a R-square within groups of 0,188, between groups of R = 0,01 and the overall R-square = 0,07. In model 1,
Variables Mean S.D. (1) (2) (3) (4) (5) (6) (7) (8) 1 Firm performance 3,00 2,04 1,00 2 Organizational ambidexterity 2,73 2,15 0,02 1,00 3 Sequential ambidexterity 0,11 2,49 0,08 -0,06 1,00 4 Absorptive capacity 0,22 1,43 0,02 -0,01 0,00 1,00 5 Company size * 7,73 1,69 -0,07 0,39 0,06 -0,11 1,00 6 Return on equity -0,88 331,74 0,03 0,06 0,00 -0,04 0,05 1,00 7 R&D expenses * 11,09 1,89 0,02 0,33 0,15 -0,02 0,82 0,02 1,00 8 Industry 0,68 0,46 -0,07 0,04 -0,07 -0,02 -0,04 -0,03 -0,15 1,00
N = 2,064. Variables with an anstrisk * are logarithmic transformations
Variable VIF 1/VIF
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hypothesis 1 is tested. Hypothesized is a positive effect of organizational ambidexterity on firm performance. The results are show a positive relationship (b = 0,0436, p= < 0.1). For every increase in organizational ambidexterity, firm performance increases as well. However, since the result is only significant on p < 0.1, hypothesis 1 is only weakly supported. Additionally, in model 1, hypothesis 2 is tested. Hypothesized is that sequential ambidexterity has a positive effect on firm performance. The results show a b = 0,111 slope with a significance of p < 0,01. This indicates the result is highly significant, therefore hypothesis 2 is supported. In model 2, hypothesis 3 expected a positive moderation effect of absorptive capacity on the relationship between organizational ambidexterity and firm performance, which would make the relationship more positive. However, the results show an insignificant effect, thus hypothesis 3 is not supported. In model 4, also a positive moderation effect of absorptive capacity on firm performance and sequential ambidexterity is expected. The results show a negatively moderated relationship (b = -0,388, p < 0,05). The opposite of what was hypothesized is found. Therefore, hypothesis 4 is not supported. The interaction graph of this moderation effect is shown in figure 2. It shows that with low absorptive capacity, high sequential
Table 3: Regression results
Model 1 Model 2 Model 3 Model 4
Firm performance Firm performance Firm performance Firm performance
Organizational ambidexterity 0.0436* 0.0502* 0.0453* 0.0518* (0.0262) (0.0269) (0.0262) (0.0269) Sequential ambidexterity 0.111*** 0.111*** 0.158*** 0.156*** (0.0411) (0.0402) (0.0465) (0.0457) Absorptive capacity -0.114*** -0.0370 -0.145*** -0.0682 (0.0282) (0.0837) (0.0315) (0.0850) Company size -0.416*** -0.414*** -0.421*** -0.418*** (0.0763) (0.0754) (0.0765) (0.0756) Return on equity 0.000292*** 0.000293*** 0.000291*** 0.000292*** (0.000107) (0.000108) (0.000107) (0.000107) R&D expenses 0.0916 0.0966 0.0952 0.100 (0.0685) (0.0677) (0.0687) (0.0679) Industry -0.178 -0.179 -0.181 -0.182 (0.191) (0.187) (0.191) (0.188) Organizational ambidexterity * -0.0331 -0.0323 Absorptive capacity (0.0343) (0.0343) Sequential ambidexterity * -0.388** -0.376** Absorptive capacity (0.182) (0.181) Constant 6.684*** 6.592*** 6.684*** 6.590*** (0.519) (0.513) (0.520) (0.514) Observations 2,064 2,064 2,064 2,064 Number of companies 242 242 242 242
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ambidexterity gives the highest firm performance, whereas with high absorptive capacity, low sequential ambidexterity brings the highest firm performance. Furthermore, the base effect of absorptive capacity with the firm performance was expected to be positive, but is found to be negative as well (b = -0,114, p < 0,01).
Hypothesis 5 expects a stronger moderated relationship between sequential ambidexterity and firm performance by absorptive capacity so that it becomes more positive than it becomes between organizational ambidexterity and firm performance. The results show that the relationship with regards to sequential ambidexterity gives a negative moderation effect, while a positive effect was expected. Besides, the moderation effect with respect to organizational ambidexterity shows an insignificant result. However, looking at the slopes of the two relations only provide a first indication that the relationship between sequential ambidexterity and firm performance is more negatively moderated by absorptive capacity compared to the relationship between organizational ambidexterity and firm performance. No full conclusion can be drawn since there is not tested for a significant difference between the two slopes. Overall, this means that there is no support found for hypothesis 5. Furthermore, there are also some results found in the regression concerning the control variables. Company size shows a highly significant negative effect (b = -0,416, p < 0,01) on firm performance. This means that the larger the size of the company, the lower the relative performance of the firm. Return on assets is highly significant (b = 0,00, p < 0.01), however, since the slope is almost zero, the positive effect on firm performance is rather low. Lastly, R&D expenses and industry show an insignificant effect on firm performance, which means that no effect is found between the variables.
Figure 2: Interaction graph
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At first, the Tobin’s Q performance indicator which is used as the dependent variable in this study is replaced by another Tobin’s Q performance indicator to check for robustness of the results. The two indicators are correlated with a coefficient of r = 0,946 and show almost similar results in the regression. Only hypothesis 2 shows different results since this hypothesis was weakly supported (p < 0.1) with the used performance indicator, but would not have been supported with the use of the second Tobin’s Q performance indicator.
Furthermore, the second robustness check is conducted with the return on assets (ROA) performance indicator. The used Tobin’s Q performance indicator and the return on assets are correlated with a coefficient of r = 0,1934, which indicates that the two are not highly correlated. The possible explanation for this low correlation is the Tobin’s Q bases the results on the market perspective which includes future cash flows of the company, while return on assets is based on the current results. Moreover, the robustness test shows that only hypothesis 2 would be rejected instead of being weakly supported. All other results are consistent with the aforementioned findings; therefore, the two robustness tests indicate that the study is robust. The complete correlation and regression models can be found in Appendix B.
Additional analyses
Additional tests are conducted adding to the hypothesis testing. Surprisingly, organizational and sequential ambidexterity are very low correlated (r = -0,06), while the ambidexterity literature claims that both achieve ambidexterity, but in a different fashion. Therefore, an additional correlation between the components of organizational and sequential ambidexterity is tested (for the complete tables, see Appendix C). Exploration in organizational ambidexterity is related to the compact significant increase of the R&D expenditures in sequential ambidexterity. Oppositely, exploitation in organizational ambidexterity is related to a compact significant decrease in R&D expenditures in sequential ambidexterity. The results show that the compact significant increase and exploration are correlated with r = 0,4788 and a compact significant decrease is correlated with exploitation with a coefficient of r = -0,2238. These findings indicate moderate correlation coefficients instead of the very low correlation between the two main variables.
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capacity. To check for significant differences between the services and manufacturing industry, a two-sample t-test using groups with equal variances is conducted (for complete tables, see Appendix C). The test revealed no evidence in order to reject the H0. This implies that the difference between the two variables is 0. Therefore, a difference in outcomes exists in the regression between the services and manufacturing industry, however, this difference is not significant.
DISCUSSION
Since Duncan (1976) and March (1991) introduced the topic of ambidexterity, the amount of literature on the subject grew substantially. Many articles are written about ambidexterity and much of the unknown is discovered. Nevertheless, no research is found that compared organizational and sequential ambidexterity in relation to firm performance while investigating the influence of absorptive capacity between these relationships. The literature claims that absorptive capacity is more important for firm performance in sequential ambidexterity than it is in organizational ambidexterity. However, this has never been empirically tested. This paper first provides insights into these relationships.
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Nerkar, 2001; Simsek, 2009). In this study, 170 of the 242 companies are companies in the services industry, which might influence the relationship of sequential ambidexterity with firm performance.
In addition, the correlation between organizational and sequential ambidexterity was expected to be highly correlated since both achieve ambidexterity, but in a different fashion (Goossen & Bazazzian, 2012; Gupta, Smith, & Shalley, 2006; Lavie et al., 2010; O’Reilly & Tushman, 2013). Although the two differ significantly in how to achieve an ambidextrous organization, performing exploration and exploitation simultaneously or in sequences, the both can lead to it. However, the results show a very low correlation between the two concepts. Lavie et al. (2010) state that sequential ambidexterity does not need to be conceptualized as a form of ambidexterity. In their view, sequential ambidexterity is, as it originates from the punctuated equilibrium approach, shifting and balancing between exploration and exploitation in sequences and not ambidexterity since they cannot achieve exploration and exploitation at equally high level. This statement might be an explanation for the low correlation coefficient. To further examine the aspects of organizational and sequential ambidexterity an additional correlation test is conducted. The correlation shows instead of a very weak, a moderate correlation between components of exploration and exploitation of organizational and sequential ambidexterity. These results are more in line with the statements in the current literature (O’Reilly & Tushman, 2013; Raisch & Birkinshaw, 2008).
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technologies. They argue that it requires a balance between the two to increases firm performance. Both processes need different routines, processes and skills in-house to achieve ambidexterity. Lastly, environmental differences might affect the R&D intensity of firms heavily. Previous studies on absorptive capacity that used the proxy of R&D intensity as well, found a positive relationship with firm performance (Swift, 2016; Tsai, 2001). However, these studies are conducted in dynamic industries, while this study is partly conducted in a less dynamic industry (services). An explanation for the difference in results might be that firms in less dynamic industries have lower levels of technological opportunities present and therefore fewer incentives to increase their R&D expenditure (Cohen & Levinthal, 1990; Geerts et al., 2010). These firms will involve in more late-stage R&D, exploitative, projects which need fewer R&D costs (Mudambi & Swift, 2014). On the other side, dynamic industries, like manufacturing, have more radical and technological opportunities present and are more likely to involve in early-stage, explorative, R&D projects. These projects cost more R&D expenses to develop (Mudambi & Swift, 2014). So, the willingness to invest in R&D intensity might be affected by environmental differences. This could influence the variable of absorptive capacity heavily. To check this assumption, an additional regression analysis has been conducted. In services industries, absorptive capacity has a highly significant negative relationship with firm performance (b = - 0.129, p < 0,01), while in the manufacturing industry there is no significant relationship found between firm performance and absorptive capacity. To test for significant differences in the relation of absorptive capacity with the services and manufacturing industry, a two-sample t-test with equal variances is conducted, but no evidenced for a difference between the two variables is found. This indicates that there is a difference in outcome in the regression between services and manufacturing, but that the difference is not significant. However, it gives a first indication that part of the negative relationship might be explained by environmental differences.
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CONCLUSION
The paper concludes that the found relationships of ambidexterity on firm performance are consistent with current literature. The relation between organizational ambidexterity and firm performance is found to be weakly significant, while the robustness check even shows an insignificant effect. This is consistent with the current literature because most studies find a positive relationship, while in some conditions no relationship is found. Furthermore, the relationship between sequential ambidexterity and firm performance is found to be positive and highly significant. This is in line with current literature. However, the effect can be influenced by the environment the study is conducted in. The dynamic capability theory states that the more dynamic the environment, the more firms will drive to become ambidextrous. Nevertheless, the sequential ambidexterity literature argues that the effect of sequential ambidexterity is stronger in more stable and slower moving environments.
Absorptive capacity, measured as R&D intensity, is found to be negative for firm performance and moderates the relationship of sequential ambidexterity and firm performance negatively, while no moderation effect of absorptive capacity is found in the relation between organizational ambidexterity and firm performance. Looking at the slopes of the two relationships, a first indication can be made that the relationship between sequential ambidexterity and firm performance is more negatively moderated by absorptive capacity. However, there is not tested for a significant difference between the slopes, that’s why a full conclusion cannot be drawn. The study is the first who find a negative relationship of absorptive capacity to firm performance. The main reason for this negative relationship found is the way of measuring absorptive capacity. Measuring absorptive capacity as R&D intensity is not sufficient. First, the measurement of R&D intensity is a rather static model, while the process of absorptive capacity is cumulative. Furthermore, an additional survey is suggested to collect data in order to be able to distinguish the R&D expenses between internally developed and externally found sources of technologies. Lastly, environmental differences need to be considered when measuring absorptive capacity since this affects the willingness to invest in R&D.
MANAGERIAL IMPLICATIONS
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ambidexterity. Although in most studies organizational ambidexterity is found to be positively related to firm performance, managers in the services and manufacturing industries should take a more in-depth look when pursuing organizational ambidexterity. This because under some conditions organizational ambidexterity may not only have no effect on firm performance but can also be counterproductive or inefficient (Ebben & Johnson, 2005; March, 1991; O’Reilly & Tushman, 2013). Second, managers should be careful in increasing their R&D intensity since a negative relationship with firm performance is found. In this study, R&D intensity is used as a proxy for absorptive capacity. However, treating them as the same is not the right approach. This measurement is rather static, while the process of absorptive capacity is cumulative. Second, the measurement does not take environmental differences into account and lastly, the measurement lacks the focus of the absorptive capacity of firms. It does not make the distinction between internally developed and externally sourced technologies. So, managers should take a look at their current level of R&D before increasing their R&D expenses, should keep in mind what industry they are operating in and what opportunities are present in this industry, and should know what the focus is of their R&D activities before investing in R&D.
THEORETICAL IMPLICATIONS
This paper also has some theoretical implications for research with regards to organizational and sequential ambidexterity and their relationship with firm performance and the measurement of absorptive capacity, the moderator, as R&D intensity.
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Second, the relationship between ambidexterity and performance is hypothesized to be moderated by absorptive capacity, which is measured as the R&D intensity in the study. However, R&D intensity is a rather static model of measuring absorptive capacity while the process is rather cumulative (Escribano et al., 2009). Additionally, the measurement lacks the focus of the absorptive capacity of firms. It does not distinguish between internally developed and externally sourced technologies. Furthermore, R&D intensity could be influenced by environmental differences, since this affects the willingness to invest in R&D. Therefore, the implication for research is that when measuring absorptive capacity, the usage of R&D intensity itself is not reliable. There has to be looked at the current level of R&D intensity of firms. Besides, a more detailed look at the focus of the absorptive capacity is needed and environmental differences have to be considered since it affects the willingness to increase the R&D expenditures.
Lastly, hypothesized is that absorptive capacity would have a stronger positive moderation effect on the relationship between organizational ambidexterity and firm performance than it would have on the relationship between sequential ambidexterity and firm performance. Found is a negatively moderated relationship between sequential ambidexterity and firm performance, while there is no moderation effect found in the relation between organizational ambidexterity and firm performance. Looking at the slopes in the regression analysis, a first indication can be made that the relationship between sequential ambidexterity and firm performance is more negative moderated. However, researchers should be careful in interpreting this result. The conducted test is not statistically significant, therefore it is impossible to draw a full conclusion.
LIMITATIONS AND FUTURE RESEARCH
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Second, the results regarding absorptive capacity might be influenced by the unreliable measurement. However, the study gives a first indication in the moderation effect of absorptive capacity on the relationship between organizational and sequential ambidexterity and firm performance. Sequential ambidexterity is found to be negatively moderated by the relationship, while no effect is found for organizational ambidexterity. Even though there is not measured if there is a significant difference between the two relationships, the slopes of the two effects give the first indication of their relationship. Future research could take a look at the same relationship while using a test that measures a significant difference between the two relationships.
Third, sequential ambidexterity is characterized by switching between explorative and exploitative projects over time. Nevertheless, the variable is not measured on project-level, but on firm-level instead. In the study, the absolute highest R&D increase or decrease of the year per firm is taken to measure sequential ambidexterity. Therefore, even though firms could have more than one peak of project switching’s in a year, this is not observed in the study. Future research could contribute to the study to measure sequential ambidexterity on project-level, instead of firm-level. Fourth, organizational ambidexterity is measured via computer-aided text analysis. This method counts the words for exploration and exploitation from annual reports for every firm. Although the method is widely used in research (Heyden et al., 2015; March, 1991; Uotila et al., 2009), the method doesn’t work hundred present error-free (McKenny, Aguinis, Short, & Anglin, 2018). Therefore, future research could extend the research by adding survey data on organizational ambidexterity to improve the reliability in the method of measuring organizational ambidexterity. Lastly, this study is conducted in the services and manufacturing industry where of which 170 of the 242 companies are services companies. The literature on sequential ambidexterity claims that in stable and slow-moving environments, like the service industry sequential ambidexterity is more useful (Goossen & Bazazzian, 2012; O’Reilly & Tushman, 2013; Rosenkopf & Nerkar, 2001). Only 70 companies in this study are from a more dynamic industry (manufacturing), which might influence the results with regards to the relationship of sequential ambidexterity with firm performance. Future research might look at the relationship of sequential ambidexterity in completely stable industry setting to see if the assumption of the current literature holds.
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