Abstract
This study discusses how the perceived entrepreneurial orientation (EO) of individuals, and in particular that of the work group leader impacts the perceived EO of the work group, which in turn improves the work group’s performance. Using a sample of 356 individual employees of five companies operating globally in diverse industries, the results of our structural equation model and multiple linear regression analyses indicate that both the group members and work group leader’s EO decisively encourage the EO of the work group, with a significantly positively effect on its performance. Furthermore, while work group heterogeneity shows a small but significant positive influence, a shared vision in the work group is found to have a clearly positive impact on work group EO. Accordingly, this study has crucial practical implications for work groups and their leaders aspiring to ameliorate work group performance through EO increasing measures with reference to the specific individual and group characteristics. From a theoretical perspective, this research contributes to the academic debate on the EO concept at individual and work group levels.
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Introduction
Representing a comparatively fast growing knowledge pool in entrepreneurship research, the body of empirical and theoretical cumulative literature on entrepreneurial orientation (EO) is receiving increasing scholarly attention (e.g., Rauch et al. 2009; Slevin and Terjesen 2011; Gupta and Pandit 2012; Filser and Eggers 2014; Covin and Miller 2014; Rigtering et al. 2014). While on the one hand light has successfully been shed on the discussion associated with the three main dimensions of the EO construct – namely, risk taking, innovativeness, and proactiveness – (Poon et al. 2006; Zhang et al. 2013; Jalali et al. 2014), on the other hand international researchers have been extensively exploring the relationship between EO and performance (e.g., Lumpkin and Dess 1996; Wiklund 1999; Todorovic and Schlosser 2007; Rauch et al. 2009; Schepers et al. 2014). However, despite this increasing concentration on EO research and proliferation of the literature, the debate has revealed research gaps related to EO at the individual and work group levels of analysis, i.e. how EO is manifested within organizations (Wales et al. 2011; Joardar and Wu 2011; Bolton 2012; Covin and Miller 2013).
Only few efforts dedicated to the EO construct have taken account of individuals (e.g., Joardar and Wu 2011; Bolton 2012; Langkamp Bolton and Lane 2012; André 2013; Goktan and Gupta 2013) or work groups (e.g., Bruining and Wright 2002; Van Doorn and Volberda 2009; Li and Liao 2010; Van Doorn et al. 2013; Brettel and Rottenberger 2013). However, while Weaver et al. (2002) and Van Doorn et al. (2013) considered certain features of working groups at the top level or key managers to increase EO, the impact at subordinate levels or on other work groups has been largely neglected, even though primary EO work hypothesized that as an organizational construct, EO is visible at all levels within an organization (Covin and Slevin 1991). Consequently, drawing attention to an individual such as the work group leader in the EO concept is an important step in building upon the research in this academic debate to raise the awareness of the EO construct at different organizational levels such as that of the work group. The following research question will therefore be discussed as an essential foundation of this research framework:
What are the antecedents and performance implications of EO in work groups?
To answer this research question, various independent effects in connection with the work group are paid more detailed attention in the next section on theoretical background and hypothesis development. After the presentation of the research hypotheses and model, the methods are discussed. The results are presented in the subsequent section. Finally, after discussing the results including limitations and implications for both the research and the business community, this study closes with final remarks and recommendations for future research.
Theoretical background and hypothesis development
Although the original construct of EO was not intended for the individual level (Kreiser and Davis 2010; Covin and Lumpkin 2011; Wales et al. 2013), recently emerging investigations conducted on the EO domain focus on the founding entrepreneur or the founding entrepreneurial group viewing EO as an individual-level phenomenon (e.g., Covin and Miller 2013, 2014; Kollmann and Christofor 2014). In particular, Wales et al. (2011) observed theoretically that EO embodies a pervasive manifestation across levels within an organization. Even if this manifestation is perceived heterogeneously, the indicators of the firm’s EO construct appear to be appropriate for the individual level due to the fact that individuals represent the reasons why a company acts entrepreneurially (Lee and Peterson 2000; Poon et al. 2006; Joardar and Wu 2011; Bolton 2012; Langkamp Bolton and Lane 2012). However, Wales et al. (2011) expected differences in perceived EO at different levels from different employees with different roles and positions. In this context, the perception regarding the EO of leading employees and EO of the working group members is expected to affect the EO of the working group itself. Individuals in working groups perform entrepreneurial activities autonomously or as a group, drive and lead themselves or the whole group through daily tasks to an anticipated result and performance (Covin and Miller 2013). Because the working group is formed by individuals working together led by a working group leader, the perceptions of the individuals of their own EO as well as their perception of their working group leader’s EO are expected to be reflected in the working group’s EO. In particular, the impact of the work group leader’s EO on the work group’s EO is expected to be even stronger because it is the leaders who direct the work groups and so also the firm towards success.
Fundamentally, at the heart of EO, and given that a company unifies the outcomes of individuals’ behaviours and capabilities, Weaver et al. (2002) and Zhang et al. (2013) applied the EO scale of Miller/Covin and Slevin (1989a) to key managers. From the perspective of a working group the engagement of the individual is reflected in the working group. This is based on the work of Wales et al. (2013) regarding the pervasive manifestation of the EO construct throughout the organization. With respect to further required support, the individual-level construct is appropriate for implementation at different organizational levels (Covin and Miller 2013) such as the working group level when measuring the EO of the working group. However, only few studies dedicated to the individual-level EO have identified working group leaders as the value-creating potential of EO (e.g., Weaver et al. 2002; Van Doorn et al. 2013). With a sample of 800 managers in three countries Weaver et al. (2002) found support for the way in which these key individuals perceive their environment to have significant implications for decisions in the sphere of organizational structures, procedures and finally performance. Moreover, Van Doorn et al. (2013) measured how characteristics of the working groups moderate the EO-performance relationship. In general, working groups have the potential to enrich the value-creation of EO. This first evidence offers proof positive that not only leading individuals of working groups at the top level management but also individuals of working groups at different hierarchical levels are expected to show an impact on EO and performance when taking their perceptions into account. To the best of our knowledge, no study has investigated the EO of work group leaders at different levels within an organization. Even though the involvement of subordinate levels has not so far been taken into sufficient consideration empirically, descriptive models have already been proposed by Wales et al. (2011). These require further refined empirical testing for an organizational homogeneous EO construct that manifests in and pervades all hierarchical levels within a company. Consequently, linking the EO dimensions to an individual level such as the work group leaders and work groups appears to be appropriate and important in showing evidence of antecedents across firm levels as an alternate model applying well-cited dimensions of the EO scale (Lumpkin and Dess 1996; Hughes et al. 2007a). While the perceived EO of the work group leader is supposed to play a key role in leveraging the perceived work group’s EO, the perceived EO of the underlying group of individuals working together is expected also to add significant value to the work group’s EO construct at the same time. Thus, we hypothesize the following:
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Hypothesis 1: An individual’s perception of her group leader’s EO is positively related to her perception of the group’s EO.
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Hypothesis 2: An individual’s perception of her own EO is positively related to her perception of the group’s EO.
When assessing the work group level, its characteristics play an important role. In the last decade EO antecedents such as culture (e.g., Runyan et al. 2012; Engelen et al. 2014, 2015), firm structure (e.g., Jogaratnam and Tse 2006; Green et al. 2008; Molokwu et al. 2013), and also environmental attributes (e.g., Wiklund and Shepherd 2005; Wong 2014; Shehu and Mahmood 2014; Milovanovic and Wittine 2014) have attracted researchers’ attention. Within the group environment heterogeneity has already been taken into careful consideration in prior research work at the work group level (Van Doorn et al. 2013), stressing that working group heterogeneity leverages EO which, in turn, will improve performance. In other words, the more different individuals are working together, the greater is the likelihood that the EO of the whole group will be enhanced. This assumes that the contrasts between individuals contributes positively to the entrepreneurial initiatives of the working group. Through the differences of the working group members risk attitudes, proactiveness, innovativeness, and autonomous behaviour are strengthened in a working group. Entrepreneurial activities will be facilitated. The working group members do enrich each other, which in turn contributes to the working group’s EO. Moreover, working group heterogeneity permits individuals and the group to accumulate comprehensive information with reference to exploring and exploiting entrepreneurial opportunities (Heavey et al. 2009). However, this may not be true for all sectors, work group sizes or working groups. In addition, other characteristics such as ownership or vertical dyads differences between individuals may influence this relationship (Yang and Wang 2014). Nevertheless, our study affiliates itself with the scholars finding support for the positive impact of heterogeneity of a group on the working group’s EO, and thus, we predict the following:
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Hypothesis 3: The heterogeneity of the group has a positive effect on the group’s EO.
Furthermore, scrutinizing working group characteristics, according to Li and Liao (2010), and sharing equal thoughts among work group members is positively linked to EO. However, the direct moderating effect of a shared vision of the EO-performance relationship was not significant in an earlier investigation (Van Doorn et al. 2013), we concur with these studies, arguing that shared values foster entrepreneurial thinking (e.g., Gupta et al. 2004; Wang 2008). In other words, the more strongly individuals in a group share a common vision that builds a basis within the group, the greater is the likelihood that the EO of the whole group will be enhanced. Thus, we anticipate the following:
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Hypothesis 4: Shared goals have a positive effect on the group’s EO.
The positive EO-performance relationship represents the heart of the original EO construct (e.g., Lumpkin and Dess 2001; Covin et al. 2006; Rauch et al. 2009; Soininen et al. 2012a, 2012b;), and is therefore also proposed as the fundamental basis at the work group level. To proceed further, a whole body of recent literature argues that EO explains (firm) performance (e.g., Filser and Eggers 2014; Spillecke and Brettel 2014; Sciascia et al. 2014; Lindsay et al. 2014; Le Roux and Bengesi 2014). However, the unique role of work groups has so far been insufficiently addressed in the academic EO discourse (Van Doorn and Volberda 2009; Van Doorn et al. 2013; Sciascia et al. 2013). As a solid multi-level construct this argumentation has also to be proven for the perceived work group level. As outlined by colleagues (e.g., Covin and Miller 2013; Wales et al. 2011) important efforts are required to stretch the EO concept to the subsequent levels of an organization to add value to theoretical constructs. We build on the work of Wales et al. (2011), who explain the organizational heterogeneity and pervasiveness of EO across firm levels. Entrepreneurial activities in organizations are driven by working groups and are reflected in individuals’ behaviours within the firm (Burgelman 1983). Work group members develop their entrepreneurial group activities, communicate these within their groups and work towards performance indicators. In a firm with freedom for autonomy, variation in EO attitudes and behaviours across levels occurs at lower levels. Consequently, individuals at different organizational levels may autonomously display entrepreneurial initiatives with the potential to guide the whole group and firm towards success (Stopford and Baden-Fuller 1994). Thus, this work assumes that the perceived work group’s EO has a significant and positive effect on work group performance. Based on this line of argumentation, the following hypothesis is proposed:
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Hypothesis 5: An individual’s perception of her group’s EO is positively related to her perception of the group’s performance.
As noted by Wales et al. (2011), a key aspect may be environmental dynamism, which encourages the firm to change and adapt fast in order to stay competitive. With respect to the assumed pervasiveness within an organization, this has to hold true for the work group performance as well. Findings by Van Doorn et al. (2013) point out that the effect of working groups on the relationship between EO and performance is reliant on environmental dynamism. Overall, EO is crucial in dynamic environments due to the fact that it boosts innovations (Zahra and Covin 1995), which in turn promotes performance and this also applies to the group level. Based on this line of argumentation, we propose:
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Hypothesis 6: The environmental dynamism moderates the group’s EO-performance relationship in a positive way.
Finally, taken as the research framework, the hypotheses and the proposed directions of the effects are summarized in Fig. 1.
Proposed research model
Methods
Research settings and sample characteristics
The data set consists of five companies of different sizes including one very small firm, two medium-sized firms, and also two large organizations, which are all globally active in a diverse set of industries – namely, construction, ICT, transportation, the aircraft parts business and the banking sector. All companies have their headquarters in Austria. Table 1 presents the sample characteristics for our questionnaire-based survey collected from June 2015 to November 2015. Data from 27 different groups were collected. For companies with fewer than 300 employees (firms A, B, C and firm D), the whole entire personnel was divided into working groups by the human resource department based on the organigram. All employees were invited to participate in the research project via email. For firm E only 300 out of more than 1200 employees were clustered into working groups and invited to join the survey via email. These working groups were chosen randomly by the human resource department. Overall, a response rate of 47.34 % was achieved. The total sample includes 356 individuals.
Because of the use of single informants the propositions of Podsakoff et al. (2003) were followed to avoid common-method bias. Firstly, a number of different scale types was employed. While confidentiality and anonymity of the responses were ensured (Reio 2010), a study report was also offered. Furthermore, intra-class correlations within work groups were applied for all variables which were highly significant. Therefore a good level of interrater reliability was achieved (Jones et al. 1983; James et al. 1984). Finally, common-method bias does not appear to be a crucial problem within this research project. Table 13 in the Appendix presents the bivariate correlation analysis. Because all correlations are below 0.70 (Tabachnick and Fidell, 1996) our results are valid although the significant correlations stress multi-collinearity (Bartlett 1937).
Measurement
The measures applied in this study are adapted from previously validated scales published in a variety of studies. The individual EO is measured based on a 17-item scale initially elaborated by Covin and Slevin (1989b) and dedicated to the firm level, and later modified by Langkamp Bolton and Lane (2012) and Bolton (2012) to the individual level (see Table 6 in the Appendix). The EO construct at work group level is measured through a slightly modified fourteen-item scale (see Table 7 in the Appendix) proposed by Hughes et al. (2007a). The EO from the work group leader is computed on a thirteen-item scale (see Table 8 in the Appendix) adapted from Covin and Slevin (1989b) and Hughes et al. (2007b). All the scales applied at the individual and work group level measure EO as an average mean of the items proactiveness, risk-taking, innovation, and autonomy. Tables 14a and b in the Appendix present the mean and standard deviation (SD) of each implemented variable in this study.
As in earlier investigations, this contribution also uses eight self-reported items related to performance (e.g., Wiklund and Shepherd 2005). As suggested by Hoegl and Gemuenden (2001), we slightly modified the scale indicators for estimating performance at the work group level on a five-point scale ranging from “much worse than other teams in my firm” to “much better than other teams in my firm” (see Table 9 in the Appendix).
Work group heterogeneity was measured on a four-item scale (see Table 10 in the Appendix) adapted from Campion et al. (1993). While for measuring work group shared vision we used an adapted four-item scale proposed by Jansen et al. (2008) (see Table 11 in the Appendix), for environmental dynamism we adapted a five-item scale from Jansen et al. (2008) which was initially introduced by Dill (1958) (see Table 12 in the Appendix).
As suggested by Letz and Gerr (1995) a variety of analyses was run to confirm the reliability of this study. A Confirmatory Factor Analysis (CFA) ensures an acceptable model fit (see Table 15 in the Appendix). Firstly, in the internal consistency method Cronbach’s alpha was performed (Cronbach 1951) as in other EO studies (Wiklund and Shepherd 2005). All the Cronbach’s alpha values for the scales developed were higher than .70, thus showing an acceptable internal consistency according to Nunnally (1978). To achieve these results no item could be omitted. As depicted in the CFA in Table 15 in the Appendix, the construct validity of the variables and also the standardized factor loadings are all significant (p < 0.001). As suggested by Hair et al. (2010), all these are above the 0.5 threshold. Moreover, indicator reliability also stresses adequacy according to Bagozzi and Baumgartner (1994) with most values above 0.4. Only the items I_IP1 and I_IR3 from the individual EO and the item T_TI3 from the work group EO reflect a value of 0.3, which can be accepted with respect to the values of the Average Variance Extracted (AVE). These are equal or higher than 0.5 for all variables except for the variable individual EO. However, we are able to accept a value of 0.4 because Fornell and Larcker (1981) suggest that if AVE is less than 0.5, but composite reliability is higher than 0.6, which is appropriate according to Bagozzi and Yi (1988), the convergent validity of the construct is still satisfactory. In addition, the Durbin-Watson statistics were between 1.5 and 2.5, indicating that there is no first-order auto-correlation. These results indicate the sufficient reliability of this research.
Analysis methods
For this cross-sectional study we applied a structural equation model (SEM) to test all our hypotheses related to the research question and used statistical software SPSS 23 to analyse our collected data. These results are in line with a preceding multiple linear regression analysis (see Appendix Table 16). The residual patterns of the regression models were examined and no evidence of heteroscedasticity or non-linearity was detected. Furthermore, the preceding multiple linear regression analysis included controlling variables such as work group position, work group size, and industry type. Because the initial regression results illustrated in Table 16 in the Appendix highlight that these controlling variables show no significant effects on the depending variables, it has been decided to exclude them in the SEM. Accordingly, we removed it as it is superfluous. However, including them might improve the results. In particular, it can reduce the residual variance and potentially improve power to detect an effect of independent variables.
First of all, with respect to reduce potential bias previous investigations pointed out that multiple informant will decrease the degree of subjectivity (e.g., Jalali et al. 2014). As a consequence, we followed this suggestion while taking account of the individual’s position in an organization. We included work group position as a control variable. In particular at the work group level, the size of the group has to be taken into careful consideration as suggested by a contribution dedicated to work groups (e.g., Van Doorn et al. 2013). Furthermore, the entrepreneurial approach appears to be dependent on the industry type and also the sector (Lumpkin and Dess 2001; Dess and Lumpkin 2005b; Tajeddini 2010) which represents our final control variable.
As depicted in the following Table 2, our model is adequate because the subsequent conditions are met. The goodness-of-fit indices comprise the chi-square (X2), Goodness of Fit Index (GFI), comparative fit index (CFI), Tucker-Lewis coefficient (TLI), Incremental Fit Index (IFI), and root mean square error of approximation (RMSEA). The X2 value is 32.575. Accordingly, the X2/df reaches 4.072 in the model (N = 356, degree of freedom =8, p-value =0.00). Based on Hair et al. (2010) a value between 2.0 and 5.0 can be accepted as a moderately satisfactory fit level. Furthermore, GFI is above 0.8 — to be precise 0.975 — which also specifies a proper fit. Then CFI reaches 0.974, which is higher than 0.90, indicating a good model fit according to Hu and Bentler (1999) and also to Byrne (1994). Additionally, the TLI value is 0.933 and the IFI value is 0.975 characterizing the essential thresholds for a suitable fit (Bentler and Bonett 1980; Mulaik et al. 1989). Finally, RMSEA reaches 0.093, which is above the most commonly recommended value 0.07 (Browne and Cudeck 1993; Rigdon 1996) but still below the acceptable value of 0.1. An RMSEA between 0.05 to 0.10 is considered an indication of fair or mediocre fit (MacCallum et al. 1996). Generally, Table 2 indicates the goodness of fit indices for the model applied.
Analysis and results
Descriptive statistics
Table 3 shows the descriptive statistics of the key constructs by sector, and the corresponding descriptives for all 27 working groups are illustrated in Tables 14a and b in the Appendix. All variables with the exception of performance (which was measured on a scale from one to five) were calculated on a scale from one to seven. The average values of respondents’ individual EO ranged from 4.79 in the bank sector to 5.18 in the ICT sector. The differences between sectors were not statistically significant according to an ANOVA test. However, a significant difference between the working groups in the variable “group shared goals” was detected. Overall, the range of working group averages was from 4.00 to 6.29 (see Table 14a). The construction sector scored highest on both group leader’s and group’s EO, although the differences in sector means were not statistically significant. On average, the group’s EO is evaluated as somewhat lower (4.81) than the individual EO of the group leader (5.04) or members (4.98).
While the sector’s mean of environmental dynamism reaches 4.60 in the aircraft parts supplier business, it reaches 4.99 in transportation. The mean ranges from 4.00 to 6.60 between the work groups (see Table 14a). In line with the analyses run regarding the different EO levels, according to an ANOVA F-test the mean values of environmental dynamism were not statistically different across the 27 groups (F = 1.215. p = .219). While the mean of a group’s heterogeneity ranged between 5.13 for the transportation sector and 5.48 for ICT, again, according to an ANOVA F-test the mean values of group’s heterogeneity were not statistically different across the 27 groups (F = 1.045. p = .407). Interestingly, the mean of the group’s shared goals varies between 4.96 for the aircraft parts supplier and 6.11 for the construction business. In contrast to all other ANOVA F-tests, the mean values of group’s shared goals were statistically significantly different across the working groups (F = 2.564. p = .000). This difference across different groups may explain an expected strong impact of shared values on group’s EO. However, this may also be explained through the banking sector, in which several work groups were represented by only one survey participant. Finally, the mean of group performance reflects values between 3.63 and 3.75 for the sectors and values between 3.00 and 5.00 for the work groups. As a consequence, according to an ANOVA F-test the mean values of group performance were not statistically different across the 27 groups (F = 0.903. p = .605).
Hypothesis testing
The hypothesized effects of individual-level EO, group heterogeneity and shared goals on the group-level EO were tested with a SEM, see Table 4. A similar method has commonly been applied in studies related to EO at the individual and firm levels (e.g., Sharma and Dave 2011; Zhang and Chin 2014; Sciascia et al. 2014; Filser and Eggers 2014).
As shown in Table 4, the perceived work group’s EO is impacted significantly positively by the individual EO (b = .198) and work group leader’s EO (b = .328). In addition, work group heterogeneity (b = .083) and work group shared goals (b = .325) also show positive significant effects. Overall, this analysis provides support for hypotheses 1, 2, 3 and 4. As proposed in hypothesis 1, an individual’s perception of her group leader’s EO is positively related to her perception of the group’s EO. Next, as anticipated in hypothesis 2, an individual’s perception of her own EO is positively related to her perception of the group’s EO. Furthermore, as assumed in hypothesis 3, the heterogeneity of the group has a positive effect on the group’s EO. Finally, we found evidence supporting hypothesis 4 that shared goals have a significant positive effect on the group’s EO.B87
Subsequently the perceived EO of the work group impacts work group’s performance significantly positively (b = .278). As hypothesized in hypothesis 5, an individual’s perception of her group’s EO is positively related to her perception of the group’s performance. However, while strong evidence was found to support all the other hypotheses, no support was found for hypothesis 6, namely that environmental dynamism moderates the work group EO-performance relationship (b = .020).
Discussion and conclusions
The purpose of this study is to draw attention to the direct perceived individual’s and work group leader’s EO impact on the work group’s EO, which in turn is expected to influence the work group’s performance. In addition, group characteristics such as group heterogeneity, shared goals, and environmental dynamism have been taken into consideration at the work group level. For an empirical test of the hypotheses, 356 individuals evaluated their perceived individual EO, their work group leaders’ EO, the work group’s EO, their group heterogeneity, their group’s shared goals, the group’s environmental dynamism, and the work group’s performance based on validated EO items adapted from prior research. Both multiple linear regression analyses as well as a SEM were implemented to test and compare the hypotheses developed with respect to the effects of the different perceptions at the work group level.
Figure 2 summarizes the results of the research model. The data collected provides support for all hypotheses with one exception – environmental dynamism does not moderate the group’s EO-performance relationship. Interestingly, the impact of the work group leader’s EO is stronger, would explain why these are the ones that direct the work groups towards success. However, the effect of the individual EO on the work group’s EO is also significant. Furthermore, the heterogeneity of the working group and shared goals show also a significant positive impact on work group’s EO. At this point, it is worth mentioning that the effect of shared vision is much stronger than the effect of group heterogeneity. Finally, work group’s EO shows a significant influence on the work group’s performance, while this relationship is not significantly moderated by environment dynamism.
SEM model results - unstandardized coefficients B for hypotheses 1 to 6 (N = 356). Notes: Unstandardized Coefficients B, Significance codes: *** = p < .01, ** = p < .05, * = p < .1. The goodness of fit indices: χ2 = 32.575; χ2/df = 4.072; GFI = 0.975; CFI = 0.974; TLI = 0.933; IFI = 0.975; RMSEA =0.093
Overall it can be concluded that both individuals and more notably work group leaders facilitate the work group’s EO, which in turn promotes work group’s performance. In addition, the work group’s heterogeneity and shared vision also play a significant role in enhancing the group’s EO, which has to be taken into consideration especially in the following theoretical and practical implications.
Theoretical and practical implications
This study provides both essential theoretical and vital practical implications. First of all, from a theoretical perspective the demonstrated significant direct value-added potential of individuals and work group leaders to enhance the work group’s EO reinforces the construct of EO in the course of disseminating it to underlying levels within a firm, which has been theorized but not so far empirically proven in the primary groundwork of EO (e.g., Covin and Slevin 1991; Wales et al. 2011). Furthermore, these outcomes explain the contribution of individual’s EO at the work group level in more detail. In particular, work group leader’s EO and the shared goals within a group require full attention to foster a work group’s EO to direct them towards superior performance. These detailed findings embody an interpolation of studies examining the impact of working groups on the relationship between EO and performance (e.g., Bruining and Wright 2002; Weaver et al. 2002; Cruz and Nordqvist 2012; Van Doorn et al. 2013; Sciascia et al. 2013). This work strengthens the existing theory stating that the EO construct is also an appropriate individual construct (e.g., Joardar and Wu 2011; Bolton 2012; Langkamp Bolton and Lane 2012; Goktan and Gupta 2013; Backhaus 2014).
The theoretical implications stimulate practical deduction. The results allow human resource departments to capture the additional potential value-creation of EO by using the EO construct in their selection processes for upgrading the companies’ entrepreneurial portfolio and increasing work group’s performance in the long run. Special attention should be paid to the work group leaders and shared goals. Individuals should be aware of and follow the vision of their group to strengthen the group’s EO. In addition, team heterogeneity also constitutes an essential working group characteristic, which should be taken into consideration when shaping entrepreneurial oriented and successful work groups. In other words, the greater the heterogeneity and the more the individuals share their goals, the higher is the EO of the work group, which, in turn, improves work group performance.
Limitations
These insights include a few limitations. First of all, due to empirical valid data generation with more particularized information, this study includes only five globally operating companies. This sample needs to be extended for greater generalizability. In particular, a multi-country approach as implemented in earlier EO studies (e.g., Lee et al. 2011; Goktan and Gupta 2013; Mueller and Conway Dato-on 2013; Gunawan et al. 2015) will enhance and enrich this work. However, Miller (2011) argued that context-specific studies are of immense importance to researchers in terms of focusing. In particular, for this groundwork this focus was essential as a first step in the right direction.
Next, another limitation of this contribution lies in the examination of the items, which require more detailed scrutiny within a SEM. Such an examination would yield more information about the moderating and mediating effects to enhance the comprehension of the interplay within the EO construct. In particular, because the initial regression results illustrated in Table 16 in the Appendix highlight that our controlling variables show no significant effects on the depending variables, it has been decided to exclude them in the SEM. However, including them might reduce the residual variance and potentially improve power to detect an effect of independent variables. Furthermore, this study discusses only the perception of individual’s EO and work group’s performance. Similar to an enormous body of EO literature (e.g., Sciascia et al. 2006; Abebe and Angriawan 2011; Zortea-Johnston et al. 2012; Gupta and Pandit 2013; Kim et al. 2015) this study focuses on all different sizes of firms as well as on a wide spectrum of industries. While this diverse focus was on only totally disparate five companies, no observed significant difference across the groups emphasized the validity of this investigation. Nevertheless, future investigations, especially of particular firm size categories (e.g., small and medium-sized enterprises) or industries (e.g., service industries) will broaden the interplay of EO forces even more.
Although earlier research has reported study designs similar to that used here (e.g., Gunawan et al. 2015), the final limitation appears to be the current cross-sectional design with a sample size of only 356 employees. Without doubt, a longitudinal study with a bigger sample in terms of participating companies would definitely strengthen the results at the work group level. Finally, single respondents represent another limitation, likewise the fact that the model takes the individual as its unit of analysis. All in all, this research opens up recommended future research directions, which will be discussed next.
Directions for future research
While this work touched upon the manifestation of EO being pervasive throughout five organizations, several new interconnected avenues of research and novel research questions have been opened up within this context. While several research questions proposed in prior work (Wales et al. 2011) have been explored empirically in more detail, there is still some work to be done across organizational levels. In particular, are there any other actors at different levels that drive EO manifestation? Within this framework, analysing the differences in perceptions of EO at various levels by the same individual will enhance our contribution from the work group leader to an even wider view of the EO construct, and in a different light. Going even further, the contrast between the “single informant way of measuring EO and performance” with the “multiple informant way” within a longitudinal study and a bigger sample would also contribute significantly to the manifestation of EO across different levels within an organization. Moreover, the examination of the impact of the EO-performance relationship across different levels would explore different moderation and mediation effects that might provide valuable insights for further manifestation of the multi-level EO construct.
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Fellnhofer, K., Puumalainen, K. & Sjögrén, H. Entrepreneurial orientation in work groups – effects of individuals and group characteristics. Int Entrep Manag J 13, 427–463 (2017). https://doi.org/10.1007/s11365-016-0408-5
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DOI: https://doi.org/10.1007/s11365-016-0408-5