This study investigated the mediating role of Dynamic Capabilities (DC) in the relationship between Entrepreneurial Orientation (EO) and Business Process Performance (BPP). Moreover, it investigates the moderating role of strategy type in the EO-DC-BPP relationship. A quantitative paradigm was followed using SEM-PLS methodology to analyze data from 179 SMEs operating in food production in Egypt. The study found a strong and positive mediating effect of DC on the EO-BPP relationship.
Research
Entrepreneurial Orientation, Dynamic Capabilities, and Business Processes Performance: Evidence from Egyptian SMEs.
https://doi.org/10.21203/rs.3.rs-1557654/v1
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Entrepreneurial Orientation
Dynamic Capabilities
and Business Processes Performance
The performance of small and medium companies (SMEs) is often regarded as a crucial driving factor behind both developed and developing country economic growth. In developing countries, micro, small, and medium-sized firms (SMEs) have traditionally been seen as a driving force for long-term economic growth and employment creation (Zaazou & Salman Abdou, 2021). Around 2.5 million SMEs operate in Egypt, accounting for 75 percent of the total workforce and 99 percent of non-agricultural private sector companies (Abdelkareem, 2020; Anter & Elnagy, 2019). Despite their importance, they are still facing several problems related to poor performance, low entrepreneurial spirit, and, weak execution of firm strategy (AlQershi, 2021; Chakraborty et al., 2019; Isichei et al., 2020). SMEs performance at the domestic level is very poor in Egypt; Only 2% of total SMEs are achieving EGP 20 million and EGP 50 million sales (Accelerate consulting and development, 2014). Moreover, SMEs have gotten insufficient attention in Egypt, particularly when it comes to addressing their poor performance in comparison to other developing countries (Abdelkareem, 2020; Abu Hatab et al., 2021). As a result, the poor performance of Egypt's SMEs is a major issue that should concern practitioners and policymakers alike, as well as academic scholars who can undertake research that can help the case.
Small and medium sized businesses usually suffer from a prolonged problem of survival (Abdelkareem, 2020; Z. Li & Johansen, 2021). The lack of adequate resources hinders the ability of SMEs to secure higher level of flexibility which erode their ability to survive and grow (Okpara, 2011). Understanding the factors that could play a role in SMEs survival is a major issue that should be explored and investigated. One of the most prominent solution of this problem might be the adoption of Entrepreneurship orientation strategy. Entrepreneurial orientation is a strategic tool that could help SMEs to improve their performance (Abatecola & Uli, 2016; Al-Awlaqi et al., 2021). in Egypt, SMEs have gotten insufficient attention, particularly when it comes to addressing their Entrepreneurial orientation in comparison to other developing countries (central bank of Egypt, 2010). According to Accelerate Consulting Development (ACD) report (2014), SMEs in Egypt are hampered by a slew of issues related to the effort to keep their company afloat. Owners rarely have time to consider how new ideas or technology could improve their company' efficiency.
Due to the lack of resource abundance, EO is considered as the only strategic option available for SMEs to follow (Al-Awlaqi et al., 2021). Previous literature has investigated thoroughly the impact of EO on the performance and survival of firms. However, the empirical evidences related to EO-performance relationship was inconsistence (Alarape, 2013; Cannavale et al., 2020; Galbreath et al., 2020; Hughes & Morgan, 2007; Kollmann & Stöckmann, 2014; Y. H. Li et al., 2009; Monteiro et al., 2019; Semrau et al., 2016; Silahtaroğlu & Alayoglu, 2016; Wiklund & Shepherd, 2005; Shaker A Zahra & Garvis, 2000). The inconsistency of the magnitude and direction of the effect of EO on businesses performance shows clearly that previous literature could be missing the impact of some interfering variables. Although, the impact of these interfering variable could alternate the EO-performance relationship, previous literature has lacked the interest to investigate such important issue (Li et al., 2009; Sousa et al., 2008; Wiklund & Shepherd, 2005). There was a little effort has been done to examine the mediating impact of potential confounding variables on the EO-performance relationship. Therefore, this study comes to fill this and investigate the effect of an important interfering variable on the EO-performance relationship.
To secure more survival rate and higher performance, SMEs should be able to manoeuvre in order to deal with its surrounding environment. Dynamic capabilities reflect the way that the organization fellows to integrate its resources and competences to deal with the fast-changing environment. Thus, organizations need the DC to get the best of EO and utilise the new opportunities that in turn enhances performance. The literature emphasized that not all strategy types have the same influence in performance (Walker, 2013). In summary, Dynamic capabilities were selected as one of the most important potential mediating variables that could considerably affect the EO-performance relationship.
For SMEs in developing countries, EO is still a vital and worthwhile endeavour (Wales et al., 2021). However, the lack of understanding of the nature of EO and its results in terms of business performance in emerging economies must be taken into account further (Shan et al., 2016). While multiple studies have found favourable associations between EO and business success in the developed countries, the penchant for taking risks as a byproduct of EO has resulted in a number of exceptions to these findings, thereby contradicting the anticipated association between EO and performance (Galbreath et al., 2020; Escamilla-Fajardo et al., 2021). As a result, in order to have a better understanding of the problem, the purposes of this research are to study the relationship between entrepreneurial orientation and firm business performance in the Egyptian context, to investigate the mediating role of Dynamic Capabilities (DC) in EO-performance relationship, and to examine the moderating effect of firm strategy type in such relationship. This research enriches the literature by investigating the mediating role of DC in EO-performance relationship, particularly business process performance (BPP).
For the purpose of this research, the paper has divided into four parts. First, the introduction was followed by theoretical foundation and hypotheses development. Then, research methodology, methods, and data analyses were presented. Third, research findings have been discussed. Finally, the paper concluded with implication, limitations, and suggestions for further research.
2.1 Conceptualization of Entrepreneurial Orientation EO
Entrepreneurial Orientation (EO) is a universally usable and applicable concept which describes a firm strategic orientation regarding the strategy-making process (Al-Awlaqi et al., 2021). EO has been conceptualized to include five dimensions proactiveness, risk-taking, innovativeness, competitive aggressiveness, and autonomy (Lumpkin & Dess, 1996; Saha et al., 2017). They believe that EO is decision-making styles, processes, and methods. Since then, researches have frequently ought to manifest that EO is beneficial for firms' performance (Wahyuni & Sara, 2020; Wilson et al., 2020).
According to resource advantages theory, EO can be seen as a resource that encourage a firm to surpass its competitors and yield a competitive position (Anwar & Shah, 2021). The entrepreneurial oriented firms have the tendency to discover future opportunities (Donbesuur et al., 2020), and they are able to adapt with the challenging environment (Lumpkin & Dess, 1996). Therefore, By establishing a conceptual framework of EO–performance, studying potential moderators, and investigating the dimensions of the hypothesized relationship between EO and business processes performance, a cumulative body of information is forming to comprehend this relationship (Shan et al., 2016).
While many scholarly attempts have been done to describe the EO-performance relationship, the findings report inconsistent results. However, the literature can be divided into three streams. First, investigations that support a positive impact of EO on firm performance with respect to the different types of performance (Ireland et al., 2003; Kollmann & Stöckmann, 2014; Y. H. Li et al., 2009; Monteiro et al., 2019; Semrau et al., 2016; Wiklund & Shepherd, 2003, 2005; Zahra, 1991; Zahra & Covin, 1995; Zahra & Garvis, 2000). Second, studies the cut off the EO-performance relationship or even report a negative impact (Covin, J.G. and Slevin, 1991; Morgan & Strong, 2003; Smart & Conant, 1994). Third, researches that prove a positive relationship for some of the EO's dimensions and decline the positive effect for other dimensions; in other words, researches that partially emphasize the EO-performance relationship (Hughes & Morgan, 2007; Lumpkin & Dess, 1996).
2.2 The nature of Dynamic Capabilities (DC)
The term of Dynamic Capabilities (DC) is described as a firm ability to integrate, develop, and configure all organizational resources to cope with the external challenging environment. DC view has emerged in strategic management field mainly to help firms understand the need of adoption to cope with dynamic environment (Haim Faridian & Neubaum, 2021). However, the Resource Based View (RBV) theory highlighted that capabilities are substantial for the organizational success, sustainability, and survival (Freeman et al., 2021). According to RBV, creating distinctive pool of resources is the only way to build and maintain the competitive advantages (Campbell & Kubickova, 2020). However, having the resources would not contribute to the success without the capabilities that refer to the firm's competences to combine these resources whether tangible or intangible and make best use of it (Lu et al., 2010). While, RBV emphasized the importance of strategic resources that help companies to build their competitive advantages, recent studies put more emphasize on intangible resources which deemed more relevant and strategically important for the performance (Abu Bakar & Ahmad, 2010; Khan et al., 2019; Monteiro et al., 2017; O. Rua et al., 2018; O. L. Rua, 2018).
DC refer to a firm's ability to integrate the available resources with respect of the external environmental challenges to sustain future success (Haarhaus & Liening, 2020). Zahra et al., (2006), noted that the use of DC is fundamental to exploiting future opportunities. Thus, DC not only have direct effect of the organizational performance, but also have indirect effect on building more operational resources (Bocken & Geradts, 2020; Helfat & Peteraf, 2015; Mikalef et al., 2020). In a fragile and emerging context such as Egypt, this feature could be given DC a main role in helping small business to secure higher rate of business growth and survival (Weaven et al., 2021). Moreover, it can play a role on explaining the relationship between EO and business performance.
3.1 The mediating effect of dynamic capabilities
Previous literature showed inconsistency and discrepancy in the impact of EO on businesses performance. Although previous literature has examined EO-performance relationship, little attention has been given to the interfering variables that could affect this relationship. For instance, the mediating role of environment (Zahra & Garvis, 2000); technology (Knight, 2000); market and industry (Lohrke & Franklin, 2015); competitive strategy (Bell et al., 2004; Hernández-Perlines et al., 2016); societal culture (Semrau et al., 2016); knowledge creation process (Li et al., 2009) were investigated. However, none of the studies attempt to investigate the mediating role of dynamic capabilities on EO-performance relationship.
Dynamic capabilities are an essential factor that could affect businesses’ strategic orientation especially the small and medium sized businesses. Dynamic capabilities found to have positive and direct impact on EO and export performance of small businesses (Monteiro et al., 2017). Previous literature recommended further studies to explain anomalies in the EO-performance relationship (Hughes & Morgan, 2007). Dynamic capabilities is an important potential factor that could play a mediating role on the relationship between EO and business performance.
To demonstrate, Robb et al., (2020), found a positive impact of EO on export performance in a group of South African SMEs. A moderating role of three types of capabilities (market, institutional, and rational) was investigated. While market and institutional capabilities moderate such a relationship, the role of rational capabilities was insignificant. Furthermore, a study on small businesses in Portugal showed a positive direct effect of EO on DC as well as a significant effect of DC on a firm’s competitive advantages (Correia et al., 2021). Although some intention was given to the role of DC and its positive consequences, nothing has been done to understand this mediating role of DC particularly, in emerging market with a high level of SMEs failure rate such as the Egyptian economy.
Therefore, it is postulated that:
H 1: DC mediates the relationship between EO and BBP.
3.2 The Moderating Role of Firm Strategy
Firm strategy defines how the firm creates and sustains the competitive advantages. Miles et al. (1978), typology is one of the main frameworks that has be used to examine the impact of strategy on performance in a various domains (Lin et al., 2020; Setijadi Lumbantoruan et al., 2020).
The framework identified four strategy types. Prospectors who are seeking innovativeness and exploiting new opportunities whether in new markets or in current markets by introducing new products or services. Analysers tend to prefer waiting for better second opportunity (Hawrysz, 2020). Analysers seek to be innovative and opportunity driven but more cautiously and selectively than prospectors. According to Miles et al. (1978), analysers are “unique combination of the prospector and defender types” (p. 68). Defenders on the other hand focus more on market segment. They try to keep and maintain their niche secure and stable as much as they can (Hawrysz, 2020). Reactors are short-term driven. They maintain lowest entrepreneurial behaviour levels (Slater & Narver, 1995; Wang, 2008).
Miles and Snow strategy types are summarising the way in which busnesses deal with the environment and react to three critical problems and solutions namely: entrepreneurial, engineering, and administrative (Walker, 2013). The entrepreneurial problem seeks to use innovative solutions to close the gabs and exploit opportunities in a manner that help superior performance. Proactive firms have a more proactive way of dealing with the dynamic environment than other strategy types. They always scan and develop markets and products to explore and exploit new opportunities (Miles et al., 1978; Onwe et al., 2020). Moreover, prospectors demonstrate higher EO than other firms (Wang, 2008). However, not all types of strategy are associated with superior performance and effectiveness (Walker, 2013). In summary, firm strategy could play a moderating role that could strengthen EO-performance relationship (Shan et al., 2016).
From the previous discussion, it is postulated that:
H 2: strategy type moderates the EO–DC-BPP relationship; prospector firms are likely to enhance EO–DC-BPP relationship than other strategy types.
4.1 Sample and data collection
A survey questionnaire was used in the current study. The target population was small and medium-sized enterprises registered at industrial development authority in Egypt. 2024 SMEs were registered in the food industry in October 2020. We contacted the firms that clearly stated email addresses. 1615 emails were sent with two rounds following up emails during October, November, and December 2020. 179 usable responses were valid that yielding a response rate of 11%. A non-response bias was tested using the Kolmogorov-Smirnov test (Ryans, 1974) following (Côrte-Real et al., 2017; Ebrahim et al., 2021) comparing the potential deviation between the early survey respondents and late respondents. No statistical differences (p > 0.05) were found between the first wave respondents and the second wave respondents (see Table 2). The sample characteristics, however, is shown in Table 2.
| Constructs | Full sample N = 179 | Early respondents N = 97 | Late respondents N = 82 | Kolmogorov- Smirnov test | |||
|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | p- Value | |
| EO | 4.7 | 0.93 | 4.8 | 0.87 | 4.6 | 0.99 | 0.31 |
| DC | 5.8 | 0.85 | 5.7 | 0.90 | 5.9 | 0.79 | 0.67 |
| FS | 6.0 | 0.92 | 6.0 | 0.82 | 6.0 | 1.01 | 0.19 |
| BPP | 5.1 | 1.13 | 4.9 | 1.23 | 5.3 | 1.03 | 0.74 |
| Characteristics | n | % | |
|---|---|---|---|
| Respondent position | CEO Middle manager other | 113 49 17 | 63 27 10 |
| Gender | Male Female | 160 19 | 89 11 |
| Firm age | < 5 years 5–10 11–15 15–20 > 20 | 39 61 28 40 11 | 22 34 16 22 6 |
| Number of employees | < 10 11–50 51–100 101–150 > 150 | 9 88 72 6 4 | 5 49 40 4 2 |
| N = | 179 | 100 |
4.2 Measures
The research is composed of four main constructs and demographic variables. The constructs were measured using a 7-point Likert scale (1- strongly disagree to 7- strongly agree). The constructs' measures are shown in Table 2.
The independent variable is entrepreneurial orientation. the variable was coined to involve three dimensions: proactiveness (3 items), risk-taking (3 items), and innovation (3 items) (Covin & Miller, 2014; Miller, 1983; Naman & Slevin, 1993; Rostain, 2021). However, the study measures this variable using (Lumpkin & Dess, 1996) five-dimension scale. (Lumpkin & Dess, 1996) have added two more dimensions (aggressiveness (2 items) and autonomy (6 items)) to the seminal work of (Miller, 1983) to be more comprehensive scale. Therefore, the multidimensional construct used for this study consist of five dimensions and 17 items.
The dependent variable is business processes performance. The study measures this variable using a 5-items scale drawn from the literature (Aydiner et al., 2019; Elbashir et al., 2008; J. Luo et al., 2012; Mahmood & Soon, 1991; Mclaren et al., 2011; Mithas et al., 2011).
The mediator variable is dynamic capabilities. The study measures dynamic capabilities using (Sher & Lee, 2004) scale. The scale comprises 10 items and developed from previous studies (Bierly & Chakrabarti, 1996; Eisenhardt & Martin, 2000; Y. Luo, 2000; D.J Teece, 2007; David J. Teece et al., 2009).
The moderator variable is strategy type. Firms were asked to indicate their strategy typology following (Miles et al., 1978) and.(Snow & Hrebiniak, 1980) Surveyors were asked to choose only one of the strategy typologies (prospectors, analyzers, defenders, and reactors) that most closely describes their organization.
5.1 Measurement model
In order to assess the outer model, the parameters associated with the measurement model are calculated. The entrepreneurial orientation is a second-order hierarchal construct with 5 first-order constructs and 17 survey items. Therefore, internal consistency, indicator’s reliability, construct reliability, convergent validity, and discriminant validity are evaluated. As seen in table 3, Cronbach's alpha exceeds 0.70 for all constructs, which establishes the internal consistency. All items' loadings were above 0.701 which maintains good indicator’s reliability. Composite reliability (CR) was used to assess construct reliability where all constructs have composite reliability above 0.73. Regarding convergent validity, the average variance extracted (AVE) was computed. As the role of thumb indicates that AVEs should be higher than 0.50, the research constructs meet the criteria. To ensure discriminant validity, the Fornell-Larcker criterion was used and reported in Table 4. the square root of the AVEs in the diagonals should be greater than correlations with other constructs (Fornell & Larcker, 1981). Overall, the model has good internal consistency, indicator’s reliability, construct reliability, convergent validity, and discriminant validity.
|
Table 3: assessment of the measurement model |
|||
|
Constructs |
Loading |
Mean |
SD |
|
EO - Proactiveness (α = 0.90, CR = 0.89, AVE = 0.71) PR1 PR2 PR3 EO- Aggressiveness (α = 0.89, CR = 0.96, AVE = 0.79) AG1 AG2 EO- Risk-taking (α = 0.87, CR = 0.75, AVE = 0.59) RT1 RT2 RT3 EO- innovativeness (α = 0.76, CR = 0.88, AVE = 0.63) IN1 IN2 IN3 EO- autonomy (α = 0.92, CR = 0.98, AVE = 0.71) AU1 AU2 AU3 AU4 AU5 AU6
Dynamic capabilities (α = 0.87, CR = 0.88, AVE = 0.84) DC1 DC2 DC3 DC4 DC5 DC6 DC7 DC8 DC9 DC10
Business Process performance (α = 0.94, CR = 0.73, AVE = 0.79) BPP1 BPP2 BPP3 BPP4 BPP5 |
0.902 0.704 0.779
0.701 0.790
0.994 0.983 0.777
0.791 0.765 0.811
0.711 0.797 0.962 0.799 0.881 0.801
0.734 0.899 0.884 0.734 0.989 0.824 0.734 0.849 0.974 0.734
0.789 0.774 0.834 0.989 0.774 |
4.28
5.12
4.79
5.03
5.15
5.82
5.14 |
1.32
1.13
1.16
1.27
1.16
1.06
1.56 |
|
Table 4: Inter-correlations of the first-order latent constructs |
||||||||
|
|
Constructs |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
|
1 |
PR |
0.92 |
|
|
|
|
|
|
|
2 |
AG |
0.71 |
0.89 |
|
|
|
|
|
|
3 |
RT |
0.45 |
0.38 |
0.93 |
|
|
|
|
|
4 |
IN |
0.49 |
0.76 |
0.41 |
0.95 |
|
|
|
|
5 |
AU |
0.82 |
0.34 |
0.62 |
0.91 |
0.87 |
|
|
|
6 |
DC |
0.57 |
0.68 |
0.74 |
0.89 |
0.37 |
0.91 |
|
|
7 |
BPP |
0.69 |
0.57 |
0.39 |
0.82 |
0.54 |
0.79 |
0.98 |
5.2 Structural model
To test the inner model, Smart PLS 3.0 was used. PLS-SEM with nonparametric bootstrapping and 5000 re-sampling to obtain the standard errors of the estimates was applied (Hair et al., 2017). The structural model was assessed using a coefficient of determination (R2 value), predictive relevance Q2 value, effect size (f2 value), and the goodness of fit \(GoF= \sqrt{\left(\overline{{R}^{2}}+\overline{AVE}\right)}\). R2 for all independent variables (DC= 0.51 & BPP= 0.67) which is large enough to consider the model validity (Ebrahim et al., 2021). Similarly, the predictive relevance Q2 value of all independent variables (DC = 0.39 & BPP = 0.49) were above zero. Effect size (f2) values, however, are small. furthermore, the goodness of fit of the model was estimated, and it was above 0.36 as suggested by (Wetzels et al., 2009). Furthermore, GFI and CFI 0.914 and 0.937 respectively. Finally, the SRMR value for this model equals 0.038.
5.3 The Mediating Effect of DC
The first research hypothesis of this research postulates a mediating effect of Dynamic Capabilities (DC) in the impact of Entrepreneurial Orientation (EO) on Business Process Performance (BPP). EO has a positive impact on DC that, in turn, has a positive impact on BBP. In this research, the magnitude of the mediation effect between EO (independent variable) and BPP (dependent variable) mediated by DC (mediator) is the product of the standardized paths between independent and mediator, and between mediator and dependent. The statistical analysis results have supported H1 as shown in Table 5. The direct path of EO on BPP was significant (β = 0.141; t = 2.632; P ≤ 0.01). the path of DC on BPP was also significant. Furthermore, the indirect effect was also significant (β = 0.098; t = 3.918; P ˂ 0.01).
|
Table 5: Mediation analysis |
|||
|
EO |
Direct effect |
Indirect effect |
Total effect |
|
Path coefficient |
0.141 |
0.098 |
0.239 |
|
t- value |
2.632 |
3.918 |
5.041 |
|
p- value |
0.011 |
0.009 |
0.000 |
|
VAF |
54.91% |
||
|
Interpretation |
Partial mediation |
||
|
Conclusion |
H1 supported |
||
|
Note: 20% ≤ VAF ≥ 80% show partial mediation. |
|||
DC 5.4 The Moderating Effect of Strategy Type
The second research hypothesis of this research postulates a moderating effect of Firm Strategy (FS) in the impact of Entrepreneurial Orientation (EO) on Business Process Performance (BPP) through Dynamic Capabilities (DC). According to the survey results, the respondents' firms' strategy types were prospector (n = 66), analyzer (n = 60), defender (n = 36), and reactor (n = 17). To investigate the proposed hypothesis, the strength of the hypothesized EO–DC–BPP relationship was compared between the prospectors and the analyzers as well as between the defender and the reactor. According to (Doty et al., 1993), prospector firms and analyzer firms are very close strategies but distinct entrepreneurial strategies from each other. Similarly, defenders and reactors are very close strategies but distinct. However, the sample size of the defenders (n = 36) and reactors (n = 17) was insufficient to run the structural equation modelling. According to (Tabachnick and Fidell, 2001), the minimum number of observations to run the SEM is from 100 to150.
Therefore, using multigroup analysis, the hypothesized EO-DC-BPP relationship were submitted for the prospectors' type and the analyzers type. Paths of EO-DC and DC-BPP were permitted to variegate freely across groups. As is shown in table 6, there was a significant difference between prospectors and analyzers in the EO-DC-BPP relationship (∆X2 = 5.264; ∆df = 2; P ˂ 0.01). Hence, H2 has been supported confirming that strategy type moderates the EO-DC-BPP relationship. More specifically, the relationship between EO-DC and DC-BPP was stronger for the prospectors (β = 0.323.) and (β = 0.278) than analysers (β = 212) and (β = 0.190) (see table 7).
|
Table 6: Multigroup analysis |
|
|||
|
|
X2 |
df |
∆X2 |
p-value |
|
EO |
139.675 |
76 |
---- |
0.012 |
|
EO |
134.411 |
78 |
---- |
0.000 |
|
Difference between groups (∆X2 & ∆df) |
------ |
------- |
5.264 (2) |
0.003 |
|
Note: The total sample size is 126, (66) prospectors & (60) analyzers. |
|
|||
|
Table 7: Direct loading for prospectors and analyzers |
||
|
|
Prospectors |
Analyzers |
|
EO |
0.323 |
0.212 |
|
DC |
0.278 |
0.190 |
This study aims to investigate how dynamic capabilities act as a mediator in the EO-performance relationship and how the strength of the relationship differs according to different strategic typologies. A structural model has been built and validated before running a statistical test and examines the two pre-sited hypotheses to reveal the following:
The first hypothesis H1 has been supported. Dynamic capabilities play a mediating role in EO-performance relationship. In other words, firms adapt the EO not only need resources, competencies, or even normal capabilities but also need capabilities that are dynamic to contribute to the performance. This result, however, is consistent with operationalized functions of DC as it senses and shape opportunities as well as threats (Teece, 2007). Similarly, this research' outcome has been confirmed by (Wang, 2008; Zahra et al., 2006) as they emphasize DC as a key concept and central for EO; however, sustainability and superior performance are of the main consequences of adapting DC.
The empirical investigation has supported H2 as well. Firm strategy type moderates EO-performance relationship. Specifically, EO-DC-BPP relationship is stronger for prospector firms than analyzers. According to (Wang, 2008), the impact of EO in performance is stronger in firms that adapt prospector strategy than firms adapt analyser strategy. Our result is inconsistent with (Miles et al., 1978) theory of entrepreneurial problem as prospector firms adapt advanced level of environmental scanning and they are able to exploit new opportunities and develop new markets. Furthermore, prospectors are able to achieve most of the positive outcomes of the EO than other strategy typologies (Hambrick, 2003).
7.1 Theoretical implications
This study provides a set of theoretically based contributions. Firstly, it complements the EO literature by providing new insight to conceptualize EO as a composite construct consist of five first-order variables. according to (Hughes & Morgan, 2007), the tendency of the literature has conceptualized EO to be three dimensions commonly proactiveness, innovativeness, and risk-taking.
Secondly, this contribution puts emphasis on BPP as a dependent variable which has had lower interest by the entrepreneurial researchers. However, Business process performance is a more comprehensive and multi-disciplinary variable that reflects the effectiveness of all organizational resources, operations, and capabilities(Aydiner et al., 2019).
Thirdly, while the research not investigating the direct effects of EO-DC, DC-BPP, and EO-BPP, the research provides new insight by investigating the mediating role of DC in the EO-BPP relationship. Finally, the study explains the strength of the EO-DC-BPP relationship according to the different strategy prospectors.
7.2 Managerial implications
From a practical point of view, our insight is to directing managers to develop a managerial vision in thinking about the importance of entrepreneurial orientation. Moreover, the research findings emphasize the mediating role of dynamic capabilities in the EO-BPP relationship. Managers are advised not only to encourage the entrepreneurial orientation but also, they need to build capabilities that are dynamics. The use of DC is fundamental in exploiting future opportunities. Thus, DC not only have a direct effect on the organizational performance but also have an indirect effect on building more operational resources (Borch & Madsen, 2007; Helfat & Peteraf, 2015; Helfat & Winter, 2011)
This research does not exist without its limitations. This research, however, was examined the mediating effect of DC in the EO-BPP relationship. Further research could investigate the mediating effect of other related variables such as business analytics and big data capabilities. Furthermore, the research focus on the impact of EO in BPP, other research, however, could adapt other dependent variables such as sustainability, firm growth rate, and innovativeness. One of the methodological limitations of this study is using SEM-PLS methodology and collecting cross-sectional quantitative data. Future research could adopt qualitative data analysis techniques and collecting data through face-to-face interviews. Another limitation of this research is the empirical part as it has been applied in Egyptian SMEs using a self-reported questionnaire. Future research could duplicate the same study in other geographical domains.
Acknowledgements
First of all, all the praise is to Allah/the Almighty God for his support. All the bodies that directly or indirectly supported us when we develop this manuscript are acknowledged.
Authors’ contributions
Corresponding author (problem identification, arranging and collecting data, interpretation, analysis and writing) and the Co-authors (developing the manuscript). All authors read and approved the final manuscript.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Availability of data and materials
Data will be available on request.
Declarations Competing interests
The authors declare that they have no competing interests
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