The conceptualization and dimensionality of EO

Despite the ongoing debates on whether EO should be defined as a disposition or behavior construct or measured as a reflective or formative construct [17], most scholars agree with Miller’s [18] definition that EO as a firm’s strategic posture of specific processes, practices and activities is constituted by three idiosyncratic components—innovativeness, risk taking, and proactiveness—which enable firms to create value by engaging in product-market innovation, undertaking somewhat risky ventures, and acting on future demands [19–20]. Conceptually, innovativeness represents a firm's strong commitment to embrace creative ideas, novel technology and products; risk taking refers to a firm's willingness to make large resource commitments with a reasonable chance of costly failures; proactiveness embodies a firm's opportunity-seeking tendency such as entering new markets and introducing new products and services ahead of the competition in anticipation of the future market trends [1, 21].

Some scholars suggest that the above-mentioned three characteristics of EO should be viewed as a joint/ integral construct consisting of three sub-dimensions that must positively covary in order for an EO to be exhibited [3, 22]. This conceptualization posits that the three attributes of EO, acting as a unidimensional gestalt, should be aggregated together when measuring EO. However, a recent view seeks to uncover the unique roles played by each of the EO dimensions, clarifying the differential effects of individual EO factors on firm-level outcomes [19, 23]. This multi-dimensional standpoint underscores the potentially distinct nature of the three EO dimensions and their corresponding unique contributions to firm performance. Research has indicated the significance of assessing the impact of individual EO dimensions on outcome variables, especially about examining the performance of small-to-medium sized enterprises (SMEs) [16, 23]. Given the possession of constrained resources, each sub-dimension of EO may mirror a distinctive strategic posture by a SME in determining the level and distribution of resource commitment with its unique cost-benefit trade-offs. Whereas our focus on a specific type of SMEs here, we follow this logic and expect that the individual dimensions of EO may exhibit heterogeneous effects on a global startup OEM’s performance under the context of reverse internationalization.

EO-performance relationships in the context of “reverse internationalization”

The EO-performance relationships have been found to be very discordant, complex, and particularly context-sensitive [6,8,16]. By adopting a uni-dimensional EO construct, many studies suggest a positive, linear effect of EO on performance [3]; however, some research analyzing Chinese data shows that EO may not always translate into improved performance above a saturation point but rather has a curvilinear relationship with performance [22]. While taking the dimensionality of EO into consideration, research presents even more discrepant results. Kraus et al. [1] demonstrates that during the turbulent times, risk-taking is negatively related to performance, innovativeness has no impact, but proactiveness still contributes to performance; Kollmann and Stockmann [20] discover a negative association between risk-taking and performance despite innovative- and proactiveneess-performance relationships remain positive. In contrast, Rauch et al. [2] manifest a positive association between risk-taking and performance while some scholars even report the presence of non-linearity in EO-performance relationships [16]. Given the inconsistent findings, Dai et al. [23] claim that the EO-performance relationships may differ depending on whether the EO construct is presumed to be uni- or multi-dimensional. The evidence above corroborates the eminent contingent and somewhat emic nature of EO with its diversified impact on firm outcomes. Moreover, it implicitly sheds light on the imperative to further investigate the distinct influences of individual dimensions of EO on performance in a specific, representative entrepreneurial environment.

The reverse internationalization by Chinese global startup OEMs, as characterized by Chin et al. [9] is just a peculiar, entrepreneurial, and increasingly prevalent phenomenon in China that is very suitable for our research setting. In the past three decades, numerous FDIs have entered China for capitalizing on its low-cost production, which actually facilitate the emergence of Chinese global startup OEMs that embarked on their business by serving as contracting producers for international well-known brands (e.g., Nike, Gucci, & Apple) or large multinational manufacturers (e.g. Foxconn) [10–11]. The outsourcers that usually came from more developed economies might frequently transfer a certain level of technology know-how to the OEM suppliers, in order to ensure the quality of their end products. Hence, the acquisition of manufacturing, technological, and marketing knowledge has been widely recognized as the most valuable benefit obtained by Chinese OEMs through cooperating with foreign clients/buyers at home [9, 11].

However, the consecutive 2009 financial crisis and 2010 Europe debt crisis resulted in global recession and China’s export stagnation, which has further triggered the strategic trend of reverse internationalization by Chinese global startup OEMs. It is because many of such firms have been continuing to lose low-cost advantages in international competitions since then [24, 25], and thus have targeted China’s tremendous market to offset their loss in export. As a matter of fact, the strategic option of “reverse internationalization” by Chinese global startup OEMs is also partly encouraged by the Chinese government according to the China’s 12^th and 13^th Five-Year Economic Plans (2011–2015 & 2016–2020) [9]. This ‘reverse internationalization’, in this sense, characterizes a new growth strategy by Chinese OEMs to venture back to cultivate their domestic market, as a result of choosing between the escalating uncertainty and precipitous profit decline in mature markets and the growing demand at home.

One of the severest challenges China confronts is to incorporate two antagonistic ideologies-the socialist and the capitalist structures-into a unified institutional system. This could impose a variety of stress and confusion, and even generate unexpected institutional frictions and constraints that may diminish the value of EO for such global startup OEMs [10, 24]. In this vein, despite huge potential for growth, the Chinese market appears to be very dynamic and complex [24, 25]; the global startup OEMs, therefore, still have to change their learning strategies and patterns from learning from developed-country partners to learning from the incumbents in domestic markets. Viewed from this angle, this ‘reverse internationalization’ embodies the unique direction changes on the growth and learning trajectories of Chinese entrepreneurial OEMs in an attempt to survive a fast-changing and fiercely competitive situation. Taking the aforementioned discussions together, ‘reverse internationalization’ is particularly appropriate for assessing the impact of the broader conceptualization of EO on firm performance during China’s socio economic reform.

Innovativeness and performance

Innovativeness is often regarded as a critical factor in facilitating growth by introducing and investing in new products, services, and cutting-edge technologies with high profit potential or market value [17]. This EO dimension generally involves a higher level of R & D investment and a large prior expenditure of organizational resources, which tends to provide long-term rather than short-term returns [16, 23].

Chinese global startup OEMs used to confine their business activities to labor-intensive production, relying on China’s huge labor endowment and low-wage advantages to compete in export markets [25]. Compared with large and foreign-invested manufacturers, such entrepreneurial OEMs had been confronted more institution-based barriers in the area of innovation in China, such as limited access to financial support and weak abilities to protect their intellectual property rights [24, 26]. Research also indicates that it seems to be quite difficult for small-and medium- sized OEMs to harvest from innovations than they deserve in China [22, 26]. Hence, global startup OEMs, without a legacy of innovation, usually invest very little in R & D.

As noted earlier, the 2009 and 2010 global economic crises triggered the reverse internationalization phenomenon in China. Due to an appreciating currency, rising minimum wage, tighter environmental protection policy, and severer competitions from other developing countries, Chinese global startup OEMs that have been facing sharp drop in export volume are endeavoring to benefit from their domestic markets with more promising opportunities [9, 24]. At this critical time, the strategic priority for most of such OEMs is to meet short-term financial obligations by exerting their strength to pursue short-term or current gains, instead of increasing resource commitment to unleash their innovation potential for long-term returns in the Chinese market. More specifically, the substantial costs and up-front investment accompanying the innovative activities may outweigh the profits gained from innovativeness and thus deteriorate firm performance. Hence, although many studies show the positive effect of innovativeness on performance, we hypothesize:

Risk-taking and performance

Risk-taking that represents a willingness to commit resources to carry out strategies and business activities with significant chances of costly failure is believed to orient SMEs toward a direction of embracing uncertainty as opposed to a fear of it [27]. Despite a positive relationship between risk-taking and performance often found in literature [2], more recent studies have exhibited a negative effect of risk-taking on performance under fast-changing or uncertain circumstances, such as in turbulent times [1] and at the embryonic stage of firm development [20]. Evidence also indicated a concave (inverted U-shaped) relationship between risk-taking and international expansion [23] and a convex (U-shaped) association between risk-taking and SME performance [16], which reveal that lower or higher levels of risk-taking may both lead to the highest level of performance, according to different contexts.

Based on the contradictory findings above, risk-taking may not represent a worthwhile endeavor sometimes, particularly for smaller firms operating in turbulent markets, due to the risk-averse nature of such firms and the substantial resource commitment adhered to risk-taking. Following this logic, given the Chinese global startup OEMs are still striving to neutralize the loss of export revenue in reverse internationalization activities, we argue that these firms may bear a relatively low fault tolerance; high levels of risk taking are likely to be too hazardous and counterproductive.

Proactiveness and performance

Proactiveness orients firms towards taking the initiative to position themselves in anticipation of changes, being the first to introduce new offerings in the existing markets, or to enter and develop new markets [27]. Firms with a higher level of proactiveness are able to accommodate to and identify valuable opportunities more quickly than their rivals in a fast-changing context [19].

While carrying out the strategy of reverse internationalization, Chinese global startup OEMs are required to be more sensitive to market signals and better position themselves to obtain a more solid foundation for organizational legitimacy, since they are shifting from competing in well-regulated international arenas to China, an unpredictable, volatile and underdeveloped market [10,22]. As such, proactiveness is of greater importance to firms in reacting to “the rules of the games” of unprecedent and vigorous market competition situations.

Proactiveness per se indeed entails a certain levels of innovativeness and risk-taking [7,18]; however, acting proactively is far less risky because proactiveness primarily facilitates firms to competing in a more agile manner, and in general won’t result in as much up-front investment as do innovativeness and risk-taking. Hence, we hypothesize:

Social network relationships/Guanxi: The moderating effect

According to the literature [17, 20], the controversial and conflicting findings highlight the significance of identifying other factors influencing the EO-performance relationship. The EO-performance linkage has been found to be moderated by a variety of internal and external contingency factors, such as a firm’s capabilities and resources, internal social context, the technological level of the industry, and cultural variables [3, 16]. However, moderators have not yet been sufficiently articulated so far [21], while there remains a scarcity of knowledge about how an entrepreneurial organization’s social networks are leveraged and applied in a specific business circumstance such as reverse internationalization. Thus, we intend to examine the moderating effect of a key contingent factor—social networks/guanxi- on EO-performance relationships in the Chinese context of reverse internationalization here.

In China where legal and financial institutions are still immature, entrepreneurial firms, in order to achieve competitive advantages, may capitalize on establishing informal social networks with main stakeholders as a critical source of social capital to build legitimacy and credibility in economic exchanges [4, 12, 13, 28]. Such social network relationships may encompass personal and business relations such as buyer-supplier relationships or strategic alliances; nevertheless, here we chose to concentrate on the “social networking”/guanxi pertaining to informal structures of personal ties, as it mirrors one salient cultural propensity in China.

Built upon interpersonal trust and goodwill, Guangxi as an indigenous Chinese concept with Confucian origins is often characterized by informal interpersonal connections bonded with reciprocal expectations, and has been extended from the individual to the corporate levels [25, 29]. Evidence indicates that guanxi provides abundant information benefits and has significant value in enhancing firm performance and entrepreneurial success in the unique institutional environment of China [28]. In general, on the basis of building linkages involved in a business transaction, firms operating in China have to develop and exploit guanxi at the organizational level with two major groups of economic actors that provide crucial advantages: 1) Local business network ties: guanxi with managers of business stakeholders, e.g., suppliers, buyers, intermediaries and competitors; 2) local institutional network ties: guanxi with government officials, key members in trade or industry associations, bankers, and professionals, e.g., professors and scientists [30,31].

Guanxi seems to become more critical for Chinese global startup OEMS to harvest from reverse internationalization activities. While these firms are actually latecomers in Chinese market, the development of guanxi with local business and institutional partners can provide a buffer for their weak legitimacy, facilitating them to mobilize limited resources in China’s undeveloped, diversified and fragmented regional markets, so as to cope with constraints imposed by highly bureaucratic institutional structures [29]. We thus hypothesize:

Strategic flexibility: the mediating effect

Scholars point out the imperative to empirically identify more variables intervening in the causal chain between EO and outcomes [21], whereas previous research dealing with the mediation mechanisms of EO-performance relationships mostly focuses on knowledge-based variables, such as organizational learning and knowledge creation process. To fill this gap, here we will unearth the mediating effect of strategic flexibility on EO-performance relationships in China.

Strategic flexibility that refers to a firm’s intrinsic ability to leverage and flexibly use resources in reaction to substantial and rapidly occurring environmental changes seems to be a peculiarly effective approach for SMEs to handle institutional constraints embedded in underdeveloped countries. It can impel the entrepreneurial performance of SMEs in unstable and unpredictable emerging economies like China and India, by ushering firms to break down the institutional routines, make precipitate commitments, and undertake competitive actions when facing a variety of changes [32,33]. Strategic flexibility can be seen as an organizational trait as well as one type of complementary organizational capability that enables entrepreneurial firms to alter their business practices and strategic initiatives faster than their competitors in terms of grasping new opportunities and tackling treats. In this sense, proactive firms may be more inclined to exhibit strategic flexibility; research has implicitly suggested that proactiveness as one of the EO dimensions indeed synthesizes a certain level of such strategic flexibility [1]. Hence, we hypothesize:

Sample and data collection

Consistent with Chin and Liu [10], considering the prominent export-oriented nature, “Chinese global startup OEMs” are defined as small-and medium-sized firms in China with export sales accounting for at least 50% of their total sales within 3 years of inception (OEMs refer to the contract manufacturers that are not responsible for the overall value of R & D technology as well as the trademarks of the ultimate products, and anonymous in the final product market). Given that over 50% of FDI into China were found to be pumped into the OEM sector, the number of OEMs has been increasing since the late 90’s; there were more than 5,000 OEMs specializing in shoe production in Guangdong province [34]. As such, to generate a large and representative sample, we relied on the 113 Canton fair exhibitor list to select our sample firms. As a world well-known, comprehensive exhibition held biannually in Guangzhou, this fair has the longest history (55 years) and the largest scale (i.e., the most complete exhibit variety, the broadest distribution of foreign buyers, and the greatest business turnover) in China. More importantly, the participants of this trade fair must supply organizers with clear and accurate demographic and business information about the firm. Hence, in February 2013, we randomly chose firms from the list that fit the definition of Chinese global startup OEMs” above with annual sales of no more than 500 million Yuan (about USD 7.3 million) and fewer than 1,000 employees. To control for the extraneous factor’s influence, the firms with foreign or state-owned shareholders were excluded.

We first made a call to the 300 selected firms and then mailed or emailed a questionnaire to the firms that agreed to join our survey. 21 firms claimed that they have not undertaken reverse internationalization activities and would still focus on export, while 200 firms returned completed questionnaires, yielding a 67% response rate. The informants were chosen from key decision makers, e.g., managing director, chief executive officer, or general manager. To reduce the method bias, we assured the respondents that this is an anonymous survey and there are no right or wrong answers [35]. To validate data, we carried out follow-up telephone interviews shortly after the questionnaires were returned. During this process, we first requested the respondents to indicate their answers to a set of selected questions, and then asked them to recommend a second informant to further confirm the answer. The post survey responses were highly accordant with previous answers.

The final sample included a variety of business domains, e.g., gifts, home decorations, textile garments, electronics, and pharmaceutical products; 24% came from Guangdong province, 14.5% were from Fujian, 23.5% from Zhejian, 8.5% from Guangxi, and 29.5% from other provinces. Referring to the 2002 version of Chinese Standard Industrial Classification, 23.5% of these firms were from technology/capital-intensive industries while 76.5% from labor-intensive industries. The average number of employees per firm is 159 and the average age is 12.1 years. We also conducted a non-response bias test using a within-sample extrapolation method [9]. We compared the early response group (the first 129 responses) and the late response group on key firm characteristics such as firm age, firm size, and industry type. The results of mean comparison t-tests did not return any significant differences between the two groups (p>0.1 in all three characteristics).

Measures

All items except firms’ information were anchored on a five-point Likert scale (from 1 = “strong disagree” to 5 = “strong agree”; from 1 = a large decrease to 5 = a large increase).

Domestic performance

Given that entrepreneurs in China experience strong incentives to hide or distort their firms’ financial performance to avoid unwanted attention from corrupt government officials or criminal circles, performance in reverse internationalization was measured by three self-reported indicators (sales performance, market share and profitability performance) referring to previous studies [9,26] (Cronbach α = .942).

Entrepreneurial orientation

Referring to Covin and Wales [17], “innovativeness” was measured by asking respondents about their firm’s tendency to invest heavily in cutting-edge R & D activities, to be a technological leader, and to introduce innovative products and services during reverse internationalization (3 items, α = .906). Proactiveness was measured by the firm’s propensity to be proactive to change competitive approaches, reorganize operations processes, and to initiate new programs (3 items, α = .800). Risk taking was measured by the firm's preference for taking bold actions and engaging in high-risk projects such as diversifying into new products or service lines, acquiring companies in very different industries, and initiating unknown new business (3 items, α = .740).

Social network relationships/guanxi

Considering the inherent complexity of the definition of Chinese Guanxi and our commercial-oriented backdrop, we merely focused on studying the moderating effect of instrumental and utilitarian guanxi (i.e., business and institutional network ties) rather than that of affective, obligatory, or reciprocal guanxi (e.g., family, friend, and acquaintance’s relations) [36]. Hence, Referring to Kiss and Danis [31], we measured social networking relationships by asking the respondents to describe how close the links between their firms and the six parties (three on business network ties; three on institutional network ties): (1) key clients; (2) key suppliers; (3) key competitors; (4) governmental officials; (5) key members in trade association or industry policy committee, (6) professionals (e.g., professors, scientists, and bankers) (Cronbach α = .875).

Strategic flexibility

Consistent with Nadkarni and Herrmann [33], we measured strategic flexibility by asking the respondents to assess the extent to which their firms respond to environmental variations: Our firm (1) regularly shares information with all stakeholders, and (2) frequently changes strategies to derive benefits firm external changes; our strategy (3) emphasizes exploiting new opportunities arising from environmental variability, (4) reflects a high level of flexibility in managing financial and political risks, and (5) emphasizes versatility and empowerment in HR allocation (Cronbach α = .878).

Control variables

Whereas firm size, firm age, and industry type may influence SMEs’ success [3], we controlled for these variables. Firm size was measured as the number of full-time employees; firm age as the number of years since it was established. We used a dummy variable to classify the industry type into technology and capital-intensive industries (0) or labor-intensive industries (1). In addition, environmental dynamism has been found to significantly influence the EO-performance relationship, particularly in a highly dynamic environment riddled with dramatic and rapid changes [5, 12, 37]. Therefore, given the dynamic nature of reverse internationalization as noted above, we controlled for environmental dynamism using three indicators according to Wiklund and Shepherd [37]: (1) products have a short life; (2) customers’ demands are highly unpredictable; (3) competitors’ actions are highly unpredictable (Cronbach α = .777).

Reliability and validity of the measurement model

Cronbach α for all constructs was above 0.70, indicating adequate reliability. We then evaluated the construct validity of the proposed five-factor model by a confirmatory factor analysis (CFA). The CFA results provided a good model fit (χ²_{n = 200} = 233.613, df = 119, χ² /df = 1.963<2, p<0.001, CFI = 0.952>0.90, IFI = 0.954>0.90, RMSEA = 0.070<0.08). The assumed five-factor model displayed a good fit to the data, confirming its nomological validity. We further assessed the convergent and discriminant validities by checking for the values of construct reliability (CR) and average variance extracted (AVE). As shown in Table 1, except the second item of the risk-taking scale, all values of factor loadings are higher than 0.5; except risk-taking, all CR and AVE values are above the acceptable levels of 0.6 and 0.5, respectively [9]. One plausible explanation is that during reverse internationalization, global startup OEMs may be unable to bear excessive financial risks like company acquisition (i.e., the second item of the risk-taking scale). Overall, our key measures captured distinct constructs.

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Table 1. CFA results.

https://doi.org/10.1371/journal.pone.0162175.t001

Common method bias

Since information about the dependent and independent variables is given by the same respondent, we recognize the potential for common method variance (CMV). Given we had built a five-factor CFA model to examine the construct validity as shown above, we further created a first-order latent marker with all of the measures as indicators to the original CFA model to address the CMV issues. This latent variable approach that has been used in a large body of research allows us to control for the effects of a single unmeasured latent method factor [35]. In comparison with the original five-factor model (χ²_{n = 200} = 233.613, df = 119, χ² /df = 1.963, p<0.001, CFI = 0.952, IFI = 0.954, RMSEA = 0.070), the new model with the latent CMV factor still fit the data well (χ²_{n = 200} = 225.494, df = 108, χ² /df = 2.088, p<0.001, CFI = 0.951, IFI = 0.953, RMSEA = 0.074) and didn’t make any significant differences (△χ² = 8.119, p >.05). We believe that CMV is unlikely to be a major treat here.

Multiple regression analyses

Scholars have pointed out that examining moderation effects using SEM (i.e., multi-group model) remains extremely difficult [38] and comes with the obvious disadvantage of lower statistical power [39]. As a result, many scholars nowadays still choose to use a hierarchical linear modeling (HLM) to test moderation effects [39–40]. In view of this, we also chose the use of HLM rather than SME to test moderation effects in this paper.

Table 2 presents the means, standard deviations, and correlations of the variables included in our analysis, which confirms that there were no outliers or major violations of regression assumptions. We referred to Cohen et al.’s [41] recommendation to mean-center all independent and moderator variables for minimizing the probability of multicollinearity. The caluculated variance inflation fctors (VIF) were all lower than the cut-off point of 5 [41–42], indicating no apparent multicollinearity.

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Table 2. Mean, SD, correlations.

https://doi.org/10.1371/journal.pone.0162175.t002

To assess the explaining power of each set of variables, we followed prior research [1,22] using a HLM with SPSS 21.0 to test the direct influence of each EO dimension on performance and the moderating effect of guanxi on the EO-performance relationship. As per the sequential steps of HLM practices, we included all control variables in Model 1A, added independent variables in Model 1B, and added the assumed interation terms in Model 1C. Table 3 presents the summarized results.

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Table 3. Hierarchical regression analyses.

https://doi.org/10.1371/journal.pone.0162175.t003

Of the control variables, environmental dynamism and firm age had negative impact on firm perfrmance as shown in Model 1A(environmental dynamism: ß = -0.240, p < .001; firm age: ß = -0.042, p < .001). According to Model 1B and Model 1C, proactiveness had a significant direct positive contribution to firm performance (p < .001), while innovativeness showed a signifiacnt negative impact on performance, supporting Hypothesis 1a and 1c. Risk-taking did not have a direct effect on performance, leading to the rejection of Hypothesis 1b.

In Model 1C, the interaction of social networking relationships with proactiveness was significantly and positively related to firm performance (ß = 2.185, p < .01), supporting Hypothesis 2c. The estimated coefficients of the interactions between guanxi and innovativeness and between guanxi and risk-taking were not statistically significant, leading to the rejection of Hypothesis 2a and 2b.

Additionally, Model 1A showed that the control variables explained only 18.9% of the variance in domestic performance. After including three EO variables and guanxi, Model 1B explained 34.1% of the variance in performance (△R² = 15.3%, p < .001). In Model 1C, the inclusion of interaction terms explained 42.3% of the variance in performance, further adding another 8.2% (p < .001) in terms of the explanatory power.

In sum, full support was found for Hypotheses 1a, 1c, and 2c, while Hypotheses 1b, 2a, and 2b were rejected.

Mediation tests

To test the mediating role of strategic flexibility between proactiveness and reverse internationalization performance, we conducted the structural equation modeling (SEM) approach suggested by Mackinnon et al. [42] to build mediation models. Testing a series of nested models againt the presumed baseline model with sequential chi-sqaure tests enables researchers to better rule out alternative explanations, and so as to discern the model that best illustrates the results of the hypotheses [9, 43]. This approach advocated by Anderson and Gerbing [43] has been widely applied to examine the intervening effects in previous studies [25, 39, 44, 45]. The significance of mediation can be examined by comparing the fit for the direct effect model with that of the predictor-mediator-outcome model (with and without the direct path from the predictor and the outcome constrained to zero) [44, 45]. A full mediation would be identified if the model with the direct path between predictor and outcome displays a better fit.

Table 4 manifests the results of the mediation tests. Consistent with prior studies [25], we estimated a baseline model as the full mediation, which has no direct path from proactivenss to domestic performance. The results of this full mediation model (Model 2A) showed an unsatisfactory model fit (χ2_{n = 200} = 25.690, df = 11, χ²/df = 2.335>2, p<0.01; CFI = 0.934>0.90; NFI = 0.897<0.90; IFI = 0.939>0.90; RMSEA = 0.082>0.08). Then we tested a series of nested models against our baseline one via sequential chi-square tests with the parameter constraints of interest in our research. We comapred Model 2A with a partial mediation model (Model 2B) in which the path from proactiveness to performance was added. As seen in Table 4, the fit indices of Model 2B look more acceptable than that of the baseline model (χ2_{n = 200} = 9.345, df = 9, χ²/df = 1.038<2, p = 0.406>0.05; CFI = 0.998>0.90; NFI = 0.963>0.90; IFI = 0.999>0.90; RMSEA = 0.014<0.05), considering the significant chi-square difference between Model 2A and Model 2B (△ χ² = 16.345, df = 2, p<0.05).

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Table 4. Hypothesis test of alternative models.

https://doi.org/10.1371/journal.pone.0162175.t004

Model 2C is a direct effect model, where there is no causal relationship between the proactiveness and strategic flexibility, as proactiveness and strategic flexibilty were set to directly link performance. Model 2D is a non-mediation model assuming that the path from strategic flexibility to performance was constrained to zero. Model 2E represents a reverse causality model that treats strategic flexibility as an antecedent of proactiveness, whereby proactiveness conversely mediated the relationship between strategic flexibility and performance. According to Table 4, the fit indices of Model 2B are significantly superior to those of Models 2A, 2C, 2D, and 2E. Overall, the results suggest that the partial mediation model 2B best fit our data.

Assessment of hypotheses

Fig 1 delineates the parameter estimates of the final best fit model 2B for examining our hypotheses 3a and 3b. Hypothesis 3a states that proactiveness is positively related to strategic flexibility. As shown in Fig 1, the direct path from proactivenss to domestic strategic flexibility is significant (β = 1.280, p <0.001), supporting Hypothesis 3a. Hypothesis 3b assumes that strategic flexibility mediates the effect of proactiveness on domestic performance. According to Fig 1, the direct path from proactiveness to performance is still significant (β = 0.014, p<0.001) while the indirect path from proactiveness via strategic flexibility to performance is significant (from proactiveness to strategic flexibility: β = 0.1280, p <0.001; from strategic flexibility to performance: β = 0.1231, p <0.001). Hypothesis 3b is strongly supported as well.

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Fig 1. The Mediation Model.

https://doi.org/10.1371/journal.pone.0162175.g001