We conducted our research in the German engineering industry. This industry is particularly suitable as it is typically characterized by a high level of innovation and competitive intensity and as it was recently affected by new technologies that enable substantial changes of established business models (e.g. Internet of Things, robot process automation, predictive maintenance etc.). Additionally, high innovativeness and increasingly faster innovation cycles that are facilitated by intelligent, interconnected systems determine the industry environment (Kaiser, 2016). On the other hand, international competitors (e.g. from China) put considerable pressure on firms to increase their quality and performance.

We collected the data via a mail survey which was send to 800 randomly selected firms that are members of the VDMA, the German association for the mechanical engineering industry. We received 157 responses (19.6% response rate). After the elimination of seven cases with incomplete responses in key variables, our final sample comprised 150 firms. Of these firms, 47.4% employed 50 or less people, 37% had 51–500 employees, and 15.6% employed 500 people or more. Key informants for the survey were 23.7% upper level managers (such as CEOs), 25% middle-level divisional or area managers, and 43.2% functional managers, and 8.1% others.

The measurement items applied in this survey are listed in Appendix A, which entail constructs and scales derived from previous studies. Strategic agility was measured as a type II second-order reflective-formative construct. The scales to measure strategic agility and its three underlying dimensions stem from Hock et al. (2016). Items for the measurement of exploration and exploitation are based on Sirén et al. (2012). To assess competitive advantage, seven pre-validated self-evaluation criteria to analyze a firm’s position relative to its competitors were used (Durand, 2003; Hooley, Greenley, Fahy, & Cadogan, 2001; Venkatraman & Ramanujam, 1986).

In addition to the key constructs used in our hypothesis model, we control for several variables that were previously shown to be related with firms’ competitive advantages: firm size as measured by the number of employees, industry, and the competitive intensity (measured by four items from Jaworski & Kohli, 1993).

Reliability of the items was assessed by observing the respective factor loadings, which range from 0.46–0.92. We deleted three items that achieved factor loadings below the common threshold of 0.6. In order to assess the internal consistency of the constructs, composite reliability was calculated, which showed satisfactory values ranging from 0.82–0.93 (Hair et al., 2011). To assess the convergent validity of the measurement model, which analyzes whether the constructs measure what they ought to (Fornell & Larcker, 1981), average variance extracted (AVE) was calculated with values ranging from 0.48–0.83. AVE values, except the construct of competitive advantage (AVE: 0.47), were above the significance level of 0.5, indicating that 50% or more of the indicator’s variance are explained by the latent variables. Discriminant validity measures whether the constructs within the measurement model differ from each other and whether the items load on the constructs they ought to. As can be seen in Appendix B, each AVE is higher than its highest squared correlation with the remaining latent variables, which indicates discriminant validity (Hair et al., 2011), fulfilling the Fornell and Larcker (1981) criterion. In order to analyze potential redundancy between the first order constructs in the formative measurement model the variance inflation factors (VIF) were calculated. They all show values below 2, ranging from 1.41 to 1.72, which implies that there are no redundancy problems within the constructs (Hair et al., 2011). The weights of the first order measures on strategic agility range between 0.37 and 0.51 and are all significant (p < 0.001).

We compare three models in a successive way (Table 1). In Model 1 only the control variables were considered. This model achieves only an R2 of 0.1 and yields few significant effects. We then integrated the main effects in Model 2. This model shows that an exploration orientation has a significant effect on the competitive advantage of firms. The R2 in this model increases substantially to 0.45. Model 3 shows the highest R2 value of 0.49 and has been used as a basis for the hypothesis test.

The positive hypothesized relationship between exploration orientation and competitive advantage was significant with a standardized β = 0.577 (p < 0.001), supporting H1. In contrast to our hypothesis, an exploitation orientation does not affect the competitive advantage (β = 0.145, p > 0.05), leading to a rejection of H2. The hypothesized negative effect of ambidexterity on a firm’s competitive advantage (H3) could be supported with a significant coefficient of β = −0.360 (p < 0.01). Eventually, as proposed by H4, we find a positive and significant interaction term of exploitation orientation and strategic agility on competitive advantage (β = 0.194, p < 0.05). Hence, H4 is supported. The results of the structural model are summarized in Table 1.

Our study provides results to the largely unexplored research streams of ambidexterity, exploration and exploitation, and their influence on the competitive advantage (Jurksiene & Pundziene, 2016) of firms operating in the German engineering industry. It has further analyzed how the established exploitation-exploration model is influenced by a firms’ strategic agility. The combination with exploitation as an innovation strategy in order to increase the competitive advantage of a firm is a unique insight into how firms can strategically position themselves to attain a competitive advantage. Our study therefore contributes to the literature on firms’ strategic orientations and ambidexterity theory (e.g., O’Reilly & Tushman, 2013) by providing an extended model for the context of the German engineering industry. Furthermore, we contribute to the literature on strategic agility (e.g., Doz & Kosonen, 2010) by demonstrating that strategic agility will be particularly beneficial for firms that follow an exploitation orientation.

The results show a significant positive effect of exploration orientation on the competitive advantage of a firm. Especially considering that exploration’s impact on performance is difficult to analyze, as it often is the preliminary stage of exploitation (Ojha et al., 2018), the results of this study is interesting. Our result supports previous research that show positive effects of exploration orientation such as innovation success (Matzler et al., 2013), the innovativeness of new products (Molina-Castillo et al., 2011) as well as the acquisition of valuable information and knowledge (Lisboa et al., 2011). However, our study strengthens the argument that exploration even increases the competitive advantage of a firm which is remarkably impressive new information. It is indeed the case that firms in the engineering industry have the potential to position themselves ahead of their competition with excessive, new technological knowledge, innovative products and services, entry into new market segments as well as new ways to acquire novel customers and increase the satisfaction of existing ones (Sirén et al., 2012), even though the exploration oriented activities take considerable amounts of time (Lin & Si, 2019).

Our results did not show a positive effect of exploitation on competitive advantage. This might be explained as intense competition, R&D intensity, and the requirement to create new knowledge and radical innovations to stay competitive, are typical of the German engineering industry (Kaiser, 2016). In light of these industry characteristics, it is possible that exploitation and the resulting efficiency increase are primarily hygiene factors that need to be in place to keep the market position but are not strategically suited to increase competitive advantage. Even though Molina-Castillo et al. (2011) argue that competition requires increased exploitation to reach more efficiency, Jansen, Van Den Bosch, and Volberda (2006) provide evidence that within such dynamic industry environments, exploration positively influences performance while exploitation does not. Even though exploitation allows firms to cut down on prices (Molina-Castillo et al., 2011; Yamakawa et al., 2011) and is associated with high performance in family businesses (Hughes et al., 2018), it is apparently not enough to increase the competitive advantage of a firm that operates in an industry that is driven by innovations and excessive R&D (Kaiser, 2016).

Ambidexterity was found to negatively affect the competitive advantage of a firm. This finding is in contrast to research that has found positive impacts of ambidexterity on performance (e.g., Hsu et al., 2013; Severgnini et al., 2018). Here, the results contrast with the findings of March (1991) who outlined that firms need to strive for both exploration and exploitation in a balanced manner in order to secure success and continuity. Even though firms might benefit from an ambidextrous strategy (Birkinshaw & Gibson, 2004; Lee & Huang, 2012), it is not the right strategic orientation for establishing a competitive advantage. Consistent with Boumgarden et al. (2012) and Parida et al. (2016), ambidexterity is not the strategy that yields superior firm benefits. One reason for these antithetic results may indeed be the issue that successfully pursuing an ambidextrous strategy demands considerable amounts of resources (Parida et al., 2016) and poses increased tensions and contradictions within organizations (Hu & Chen, 2016; Van Looy, Martens, & Debackere, 2005) which firms potentially are not able to resolve. Firms are likely to have their difficulties in coping with the considerable tensions that are inherent to an ambidextrous strategy (Hu & Chen, 2016; Ireland & Webb, 2009). In addition to that, increased environmental dynamics in the engineering industry might impair ambidexterity’s influence on performance (Luger et al., 2018). In line with O’Reilly and Tushman (2013) who suggested that the influence of ambidexterity depends on contextual factors, we therefore believe that structural ambidexterity, i.e. the simultaneous pursuit of the two orientations, should be avoided in rather turbulent environments, as the external conditions might be more favorable to exploratory organizations.

The current study’s most significant contribution is that exploitation together with strategic agility has a positive influence on competitive advantage. Various factors within an organizational environment influence the ecosystem in which businesses operate, thus making it necessary to stay responsive to changes (Weber & Tarba, 2014). The combination of strategic agility and exploitation allows firms to stay competitive in the short run through incremental innovations and increasing financial returns from efficiency (O’Cass et al., 2014), as well as seize emerging opportunities in the organizational environment through an increased responsiveness from strategic agility (Shin et al., 2015), and thus stay competitive also in the long-run. The combination of strategic agility with exploitation offers a unique solution to overcome the tensions and contradictions that are inherent to this paradigm. The reason for a greater compatibility of exploitation and strategic agility is that strategic agility bases on certain meta capabilities (i.e. strategic sensitivity, collective commitment and leadership unity) that can be utilized to innovate the business model in times of external changes (Clauss et al., 2019; Doz & Kosonen, 2010). As these capabilities enable firms to conduct significant changes to the organization if needed, based on strategic observations, specific decisions and dedicated resource allocations, it is not inherently conflicting with an exploitation orientation. Therefore, inherent tensions between radical innovation and continuous improvement may be overcome. As strategic agility as such does not show a direct effect on firms’ competitive advantage and does also not interact with exploration, these capabilities will particularly improve the competitive position of rather traditional, exploitative firms such as family firms (Hughes et al., 2018).

Our study provides some important implications for managers of firms in rather turbulent markets (e.g. engineering firms) who want to strategically manage short-term efficiency and long-term change. First, we find that an exploration orientation is beneficial to the firms’ competitive advantage. Therefore, managers may assess their exploratory capacity. In case they are primarily exploratory, this orientation may ensure competitive advantages without further strategic changes. If however a firm is primarily exploitation-oriented, considerations may be different. As it has been shown that changing a strategic orientation is difficult and time-consuming, as these are deeply rooted in the organizational mission and culture (Sidhu, Volberda, & Commandeur, 2004), changing to an exploration orientation might be difficult or even impossible. Therefore, those firms may be advised to build the necessary capabilities for achieving strategic agility (Doz & Kosonen, 2008, 2010), such as investing in market screening, utilizing experiments, intensive end empathic leadership dialogues and designing more modular and decoupled organizational structures. The achieved strategic agility together with the exploitation strategy will help to achieve a new form of strategic ambidexterity.

This study is not without limitations that may be addressed when conducting future studies on the topic. First, our study bases on data from one industrial and cultural context, namely the German engineering industry. Although, this context is relevant from a managerial perspective and has been used for many other studies (e.g., Clauss & Tangpong, 2019), it may not be generalizable to other more or less dynamic industries. Therefore, future studies might replicate our analysis with data from other contexts. Second, we focus only on one particular form of ambidexterity―the simultaneous utilization of both exploration and exploitation at the same time. However, the literature has discussed that there might also be other forms of ambidexterity such as temporal or special ambidexterity (e.g., O’Reilly & Tushman, 2013). From our perspective, we gain no understanding how strategic agility may interact with these other – less paradoxical – types of ambidexterity. Finally, our study is based on cross-sectional data. We can therefore not draw any conclusions on how the effects of exploitation, exploration, ambidexterity and strategic agility may influence competitive advantages on a long-term base. Such an analysis may provide further insights into the intertemporal dynamics of these strategic constructs.