Abstract
Enterprise innovation (EI) has become an important means to promote the sustainable development of enterprises in the new era. This study aims to explore the multiple concurrent factors and causal complex mechanism of the configuration effect of five conditions in the environmental and organizational levels and their influence on the differences in EI activity. Taking 20 information technology enterprises as case samples, this study uses the qualitative comparative analysis method of fuzzy sets. The main conclusions are as follows: (1) The ability to identify opportunity is the necessary condition affecting the high innovation activity of enterprises; the lack of internal innovation culture, the low innovation activity. (2) The driving mechanism of high EI activity can be divided into three paths, and the different configurations of the five factors can produce many paths to achieve such activity. (3) The driving mechanism of low EI activity can be divided into two paths, and it has an asymmetric causal relationship with the driving mechanism of high EI activity. This study is helpful in expanding the innovation perspective of environment and organization matching. This study also provides enterprises with valuable enlightenment to effectively stimulate innovation vitality.
Introduction
The new normal of economy puts forward new requirements for Chinese enterprises to further implement the innovation-driven development strategy. In this context, dealing with the changes brought by new technology and business model, many industries are facing challenges and even subversion. Enterprises should welcome the concept of sustainable development to grasp the strategic initiative and win the sustainable competitive advantage in the complex external business environment. In January 2019, the State Council proposed promoting the deep integration of state-owned enterprises’ mixed ownership reform and enterprise innovation (EI), encouraging large and medium-sized enterprises to carry out innovation activities so as to realize the strategic rejuvenation of enterprises. EI has become an effective way for enterprises to resolve the growth crisis and obtain sustainable competitive advantage.
In recent years, EI has gradually become a research hotspot for scholars at home and abroad. Any enterprise contains a certain degree of innovation, the question is how much. Some enterprises often experience difficulties in business creation. They gradually fall into the “success trap” after reaping rewards and lose innovation vitality after a short period of innovation activity and finally are in danger of a merge or decline [1]. Other enterprises can continuously iterate their own value system and achieve and maintain outstanding innovation performance through continuous innovation [1]. The reason for this phenomenon is twofold. On the one hand, scholars built a relatively rich EI model in theory to explain the complexity of EI. Among them, Marianne’s innovation process model not only summarizes the key core elements in the innovation process but also emphasizes the dynamic interconnection between the elements in innovation activities [2]. Later, scholars further integrated the external environment and innovation culture into an overall model to further explain the driving process of innovation [3]. On the other hand, in the empirical study of EI, scholars tested the impact of single-level factors, such as organizational capacity or competitive environment, on EI, aiming to further explore the mechanism of organizational factors on EI [4]. Therefore, environmental and organizational factors become the basic logic in analyzing EI driving mechanism. However, given the heterogeneity of external environment, internal culture, and capability between real enterprises, the mechanism driving EI is inconsistent. Although existing studies have found that EI is affected by many factors, they have not explored the configuration effect of interdependence and the combination of factors inside and outside an organization on EI activity due to the limitations of regression research methods (assuming that variables are independent and do not interact). The differences in EI degree and the diversity of implementation paths among enterprises are difficult to explain.
To break through the aforementioned limitations, this study uses the qualitative comparative analysis of fuzzy sets (fsQCA) to conduct multi-condition interdependence analysis. From a configuration perspective, this study deeply excavates the antecedent complexity and causality asymmetry and fully excavates the influence mechanism of the collaborative configuration of multi-layer antecedent conditions on EI [5]. Using QCA to carry out EI research is helpful to reveal the causal complexity mechanism of multiple factors affecting EI. This method also makes up for previous ones such as factor regression and structural equation, which are mainly suitable for analyzing linear correlation. The previous methods cannot analyze how configuration formed by multiple factors depending on one another affects EI. Considering its advantages over other methods, QCA is applied to integrate the matching perspective of environment and organization [6]. This study examines the relationship between the environment composed of five antecedents and the different configurations of organizations and EI activities and excavate the path to enhance EI vitality. At the environmental level, environmental uncertainty and internal innovation culture are mainly considered [7, 8]. In terms of organizational factors, this study uses Marianne’s point of view as basis to analyze organizational factors from a competence perspective and examines the organizational level of opportunity recognition ability, resource integration ability, and employee engagement [2]. Five conditions are selected because QCA is suitable for analyzing the configuration of four–seven conditions. The purpose of QCA method is not to list all variables but to approach or find the cause of the phenomenon by analyzing the consistency of important variables in the case [9]. Specifically, this study intends to answer the following questions: what are the core and marginal conditions that affect EI? Why can some enterprises maintain a high level of EI activity, that is, which paths can activate EI efficiently? Which paths will restrict EI? What are the connections between these paths?
Literature review and model construction
Enterprises mainly develop new business opportunities through updates in strategy, technology, and product to realize the value added [1]. Following a psychological perspective, early scholars believed that organizational factors lead to the occurrence of innovation activities [10]. The constructed model reflects the identification and development of innovation opportunities under the influence of organizational subjective intention. However, the occurrence of innovation activities is not entirely determined by organizational factors. Enterprises also adopt innovation in response to changes in the external competitive environment [11]. In addition, organizations’ internal learning atmosphere and loose institutional culture, and their teams’ risk orientation have a positive impact on EI [12]. To address the shortcomings in the past measurements of organizations’ innovation culture, Jonatha [3] developed an assessment tool to measure the internal innovation atmosphere of organizations. Jonatha [3] also discussed the mechanism of cultural environment on the innovation action of organizations. Sambrook [6] found that the internal and external environment of an organization act on the EI together and then react on the internal and external environment through EI, finally contributing to the innovation cycle ecology of the organization. As evidenced by existing research, the driving factors of EI are not unique and independent. The multiple linkage between internal and external environment and organizational factors has become a theoretical fact that cannot be ignored in the analysis of EI’s driving mechanism. Marianne [2] put forward a representative innovation process model. She believed that the key of innovation activities is the proper combination of opportunities, resources, and teams. She emphasized that innovation activities are the result of multiple factors and later included uncertain competition environment. Thus far, scholars have constructed EI models with different emphases based on various theoretical perspectives, but most of these models extend or supplement a certain concept in Marianne’s classic model [2]. An integrated research covering all theoretical perspectives and organizational factors has not been carried out yet.
The consensus is that EI is the result of many factors. However, limited by research methods, most of the previous EI studies stay in the deduction and induction of complex theoretical models. Quantitatively exploring the impact of multiple factors on EI or empirically testing the linear relationship between some factors and EI, are impossible. Doing any of the two ignores the theoretical fact that the occurrence of EI is affected by many factors. Neither of them can fully explain the driving mechanism and activity difference of EI in real enterprises. Moreover, some studies blur the concept between the driving cause of EI and the process of maintaining EI. The factors supporting the occurrence of EI do not necessarily trigger the occurrence of EI. In view of these limitations, this study incorporates EI capabilities into configuration analysis to match organization and environment. According to Sambrook [6], environmental uncertainty is the external environmental condition, and the innovation culture as the internal environmental condition. With Marianne’s innovation process model as basis, this study constructs the organizational level of EI model from the perspective of opportunities, resources, and teams [2]. Specifically, this study explores the multiple concurrent causes and complex mechanisms that affect the differences in EI activity through the five antecedents of the two levels. They need to be further analyzed through QCA method combined with actual cases. Therefore, this study constructs the EI model shown in Fig. 1. The environment layer includes environmental uncertainty (EU) and internal innovation culture (IIC). The organization layer includes opportunity recognition capability (ORC), resource integration capability (RIC), and employee engagement (EE).
Enterprise innovation driving mechanism model.
EU is composed of two dimensions: environmental dynamics and complexity. Dynamics reflects the speed and extent of changes in external environment (knowledge, technology, culture, policy), whereas complexity reflects market factors and participants (e.g., competitors, suppliers, and customers) and the degree of government intervention [13]. EU causes the unpredictability of the probability of environmental results recognized by the organization. It also provides development opportunities for the birth of new enterprises and the innovation actions of mature enterprises. In particular, EU drives large enterprises to pay much attention to reshaping their own innovation mechanism, create new products and services constantly, and open up new markets to seek comparative advantage in the environment.
IIC refers to the environmental atmosphere that can improve the recognition of organizational members for internal innovation behavior [7]. For an organization to be committed to the development of innovation, it must have a cultural orientation to support innovation [8]. Jonatha [3] also paid attention to the innovation activities that commonly exist in large companies, identified the key factors that affect the internal innovation atmosphere. The internal innovation atmosphere is reflected through top management support, work autonomy, reward mechanism, time availability, and organizational boundary. When organizational members perceive management support, the more likely they are to participate in a new career, the more time, resources, and rewards they receive [4].
Organizational level
ORC refers to the capability to perceive and discover market demand and then create business concepts, that is, the process of perception, discovery, and creation [7]. Some scholars even conceptualized opportunity as the essence of innovation and regard it as the fundamental difference between innovation and management activities [11]. Innovation opportunities not only exist in the potential market objectively but can also be created by the innovation subject. As a leading factor in the entire EI process, opportunity identification helps enterprises find changes in market demand and customer preference, avoid excessively fierce market competition, and achieve innovation performance [12]. Enterprises with strong ORC can identify many possible sources of value and carry out EI activities such as creating new business units in existing enterprises.
RIC refers to the ability to identify, acquire, allocate, and utilize resources from within and outside an organization [13]. The school of innovative resources believes that the essence of EI is the reasonable allocation of resources to achieve value creation and gain competitive advantage. When the resources owned or likely to be acquired in the future can match the identified EI opportunities, enterprises are inclined to take practical innovation actions. On the contrary, even if organizations recognize the new opportunities that may create added value, they often give up due to resource constraints. Organizations cannot implement EI through the internal screening mechanism of the organization.
EE refers to the degree of recognition, commitment, and investment of employees in an organization by combining self with work role [14]. EE is a work emotional cognitive attitude characterized by vitality, contribution and concentration [13]. Vitality refers to the energy and resilience of employees at work, and their ability to continue working despite difficulties. Contribution refers to the sense of meaning and mission given by the work and the ability to perform additional tasks conducive to the development of the organization. Concentration refers to the state wherein employees can focus on their own work while neglecting working hours. The overall working state of organization members is one of the main aspects to measure the differences in enterprises’ ability. Employees with high engagement are committed to improving their careers and organizations and are likely to help enterprises create new value growth points [5].
Research methods
Data collection
Enterprises or organizations (including non-profit organizations) have different levels of EI activities. This study follows the QCA’s case selection principle for small and medium-sized samples (15–20), that is, “to ensure the full homogeneity of the overall case and the maximum heterogeneity within the overall case” [4]. The cases in this study are mainly selected from the information technology industry. To better explore the driving mechanism of EI activity among different enterprises, the differences in innovation activities among information technology enterprises are highlighted in the selection of case enterprises. Twenty enterprises that agreed to participate in the survey in six regions were randomly selected as the research objects. Five months from the beginning of March 2019, 503 questionnaires were distributed to managers of different levels in all the departments of the enterprises with the assistance of their human resources department. After eliminating the invalid questionnaires, 460 valid questionnaires were recovered, with an effective recovery rate of 91%. Among the 20 enterprises surveyed, 73.5% of the participants are male, 60.2% have been working for 10–15 years, 68.4% are department or deputy manager, 2.1% are chairman or general manager, 92.1% have a bachelor degree or above. Table 1 summarizes the information of each case.
Basic Information of Case Enterprises
Basic Information of Case Enterprises
The respondents completed the questionnaire independently, which may lead to common method variance (CMV). In this study, clear and concise items are used as much as possible, and anonymous filling is used in the questionnaire. The CMV of the first principal component is 38.1%, indicating that the first principal component only explains 38.1% of the variation (less than 50%). A variance of 0.005 is explained by the method factor, and the load of most method factors is insignificant. Therefore, the survey data have no serious common method variance (CMV).
Seven-point Likert method was used, and all the variables studied refer to the existing mature scale to ensure the reliability and validity of the scale. The questionnaire is translated into Chinese and English in the form of double blind, and the questions are properly corrected according to the interview situation in China. EI is measured from three dimensions, namely, strategic update, product update, and technology update [4], with a total of nine measurement items. One of the items is “often becoming the first company in the industry to launch new products or services to the market.” EU was measured with four items in total, such as “fierce product competition in the company’s industry” [5]. IIC was measured from the five dimensions of management support, work autonomy, reward, time availability, and organizational boundary [3]. A total of 15 measurement items were included in the questionnaire, such as “companies are willing to support small business experiments.” The scale of Ardichvili, Cardozo and Ray [9] has four items in total (e.g., “the company can search and identify opportunities according to customer needs and preference changes”), and it was used to measure ORC. The scale of Nayager [8] also has four items in total (e.g., “the company can make resource allocation decisions to maximize benefits”), and it was used to measure RIC. Schaufeli’s [12] scale reflects EE from the three dimensions of employee vitality, participation, and contribution. The scale includes nine items, such as “employees can always adhere to the goal of the plan, even if things are not smooth.”
Reliability and validity analysis
According to the reliability and validity analysis in Table 2, the Cronbach’s coefficients and combined reliability (CR) of EU, IIC, ORC, RIC, EE, and EI are all greater than 0.7. Such an outcome means the questionnaire has good reliability. Factor analysis method was used to test the structure validity. The KMO value is greater than 0.7, the minimum cumulative variance contribution rate is 56.42%, the factor load of each item is more than 0.60, and the AVE of all constructs is more than 0.5. Therefore, the validity of the questionnaire is good.
Reliability and Validity Analysis
Reliability and Validity Analysis
Note: EU = environment uncertainty, IIC = internal innovation culture, ORC = opportunity identification ability, RIC = resource integration ability, EE = employee engagement, EI = enterprise innovation.
During data collection and variable measurement, we evaluated the EU, IIC, ORC, RIC, EE, and EI of participating organizations through several managers in each enterprise. We aggregated and averaged the initial data after obtaining them at the individual level. Before analysis, data aggregation at the individual level needs to be raised to the organization level. In this study, the measurement of environmental and organizational factors is aggregated from individual responses to the organizational level, so the internal consistency of individual respondents to each variable must be confirmed. According to the test results in Table 3, RWG is greater than 0.7, ICC (1) is greater than 0.12, and ICC (2) is greater than 0.47. All variables meet or exceed the requirements of aggregation [14]. Table 4 presents the original data after aggregation.
Aggregated Data
Aggregated Data
Original data of case enterprises
Calibration involves transforming variables into sets and assigning membership degree to cases [15]. Through theoretical deduction and practical knowledge, variables are calibrated into sets and based on which three critical values are set (i.e., complete membership, intersection, and complete non membership). The transformed membership degree of the sets is between 0 and 1. Referring to Fiss [15] and Kraus [17], this study obtains relevant data through 7-point Likert scale and sets “7” as the full membership, “4” as the intersection, and “1” as the full non-membership. By setting these three thresholds, fsQCA converts these values into fuzzy scores of 0–1. Table 5 presents the calibration anchors for each variable.
Original Data of Case Enterprises
Original Data of Case Enterprises
Necessary condition analysis
A necessary condition can be regarded as a super set of the result. If the necessary conditions are included in the truth table analysis, then they may be simplified in the reduced solution included in the “logical remainder” [18]. Referring to Ragin [18] necessary condition analysis (NCA) is required before configuration analysis. And the results of the NCA (high/low EI activity) are shown in Table 6.
Necessary Condition Analysis of Innovation Activity of Case Enterprises
Necessary Condition Analysis of Innovation Activity of Case Enterprises
Note: “∼” means “not” of logical operation
The consistency of the necessary conditions in Table 6 shows that high ORC is the necessary condition for producing high EI activity (consistency 0.966 > 0.9), and the lack of high ICC (∼ IIC) is the necessary condition for low EI activity (consistency 0.910 > 0.9). These two conditions constitute the bottleneck of relevant results. On the basis of the NCA, these antecedent factors are included in the fsQCA to further explore the configuration of high and low EI activity.
Three kinds of solutions can be obtained by fsQCA: complex solution (without “logical remainder”), intermediate solution (with “logical remainder” conforming to theory and practice), and reduced solution (with all “logical remainder” that may help simplify configuration, but its rationality will not be evaluated). The intermediate solution does not reduce the necessary conditions, so it should be reported [18]. The core and edge conditions should be distinguished by combining the reduced solution [18]. If the antecedent condition appears in the reduced and intermediate solutions, then it is the core condition [7]. If this condition only appears in the intermediate solution, then it is recorded as the marginal condition [7].
FSQCA3.0 was used to analyze the data of 20 enterprises. The frequency of selection is 1, and the consistency is greater than 0.8, with PRI consistency greater than 0.75. Three configurations have high EI activity (as shown in Table 7), and the consistency indexes of the three configurations are 0.954, 0.945, and 0.949, indicating high consistency [18]. These three configurations are sufficient conditions for high EI activity. The coverage of the model solution is 0.899, which shows that three configurations explain the main reason for high EI activity. In addition, the fsQCA shows two configurations that lead to the low EI activity. The overall consistency is also high at 0.954, and the coverage is up to 0.77, which explain the main reason for low EI activity.
Configuration of High and Low Innovation Activity
Configuration of High and Low Innovation Activity
Note: •represents the existence of core causal condition, ○ represents the absence of core causal condition, □ represents the existence of edge causal condition, ⊙ represents the absence of edge causal condition, “blank” indicates that the condition can or cannot appear in the configuration.
Table 7 reveals that three configurations (H1, H2, H3) generate high EI activity. Among which, ORC is a necessary condition for each configuration. H1 shows that enterprises with high ORC (core condition), high RIC (core condition), and high EE (marginal condition) can generate high EI activity regardless of EU and ICC. H2 shows that with high EU and IIC, enterprises with high ORC (core condition) and high RIC (edge condition) can generate high EI activity. H3 shows that enterprises with high ICC (edge condition), high ORC (core condition), and high EE (core condition) can generate high EI activity in a highly uncertain environment. Two configurations (L1, L2) generate low EI activity, which are consistent with the NCA. Each configuration contains ∼ IIC. L1 shows that EI activity is low in enterprises lacking high EU (marginal conditions), high ICC (core conditions), and high EE (marginal conditions). L2 shows that the EI activity of enterprises with ∼ IIC (core condition) and high ORC (core condition) and RIC (marginal condition) is low. The findings provide new evidence and sheds light on the previous innovation theory. Demirdomen [4] found that ORC has the greatest impact on EI and is the key factor in the EI process. Enterprises first need to identify valuable opportunities and establish them as strategic objectives to carry out a series of creation activities.
The lack of ORC results in the inhibition of EI. Innovation opportunities are also not developed “overnight” as they need to match with innovation resources and personnel. The essence of implementing EI activity is the integration and utilization of existing and unknown resources. The initiative of innovation subjects can stimulate the creative potential and execution enthusiasm of innovative employees, and the willingness of employees to participate in innovation is closely related to the internal culture factors [13].
In the complex configuration of environment and organization, the following three configurations/paths activate high EI activities. To better understand these implementation paths, this study analyzes these three paths with the following cases.
Regardless whether the enterprise is in a highly uncertain environment or has high ICC, as long as the members of the organization are highly engaged and have the ability to identify opportunities, once they have the ability to integrate into relevant resources, EI will be carried out. According to the innovation process model built by Marianne [2], the dynamic interaction among opportunities, resources, and teams is the key factor to trigger EI. The “innovator” in the team, as the main body identifying opportunities and integrating resources, is the key to the successful implementation of EI. EE highlights the working state of the innovation team. Employees with high engagement can devote much time, energy, and enthusiasm to the long-term development of the organization [11]. Once valuable opportunities are identified and matched with the integrated resources, EI will be carried out. Typical cases of this configuration are Fenghuo Technology, Datang Telecom, Tencent, and Huawei, among others.
When an enterprise has the ability to identify opportunities and integrate resources and a team with high engagement, whether it is in a highly uncertain environment and has high ICC has no substantial impact on the high EI activity. The operating environment of large state-owned enterprises represented by Fenghuo Technology and Datang Telecom is stable. Influenced by past planned economic system, their innovation culture is still not active compared with private enterprises, and the internal organization continues to strictly follow traditional management procedures. However, due to technology accumulation and policy support, a unique competitive advantage has been created. In addition, the influence of employees in state-owned enterprises on the identity, honor, sense of belonging, and red culture of the large enterprises has enabled them to devote themselves to the long-term development of the organizations. With the implementation of the supply side reform under the new normal, the state-owned manufacturing enterprises are focused on R&D, constantly transforming China, and actively developing the international market under the Belt and Road Initiative. The technology-based enterprises represented by Tencent and Huawei also have an active innovation culture, which enables them to maintain their advanced technology, products, and market advantages in the uncertain domestic and foreign competitive environments under the organic allocation of opportunities and resources. This type of enterprise has a large scale of production and solid technical, talent, and capital strength. It is the leading enterprise in its industry field and enjoys a good brand reputation, showing the characteristics of initiative to launch EI.
Regardless whether EE exists or not, when an enterprise is in a highly uncertain environment, despite ∼ IIC, as long as it has the opportunity to identify the ability and can be integrated into the corresponding resources, it will produce high EI activities. Different from H1, this type of enterprise deals with uncertain market competition, always facing the strategic choice of life and death. Although the ICC is low, based on the urgent survival pressure of the enterprise, once the enterprise recognizes the new opportunity conducive to the realization of strategic rejuvenation and can integrate resources for implementation, it will take a series of EI activities. This EI behavior reflects passive innovation activities driven by the environment [16]. The typical case of this configuration is the Tianyu information. The enterprise is a solution provider of telecommunication access network. With the rise of Chinese telecommunication equipment manufacturers and the rapid change of telecommunication technology, the competition environment faced by the enterprise is becoming increasingly severe. Therefore, with the advantages of technology and cost in the field of optical fiber access, the enterprise continues to acquire similar competitors at home and abroad, expand its R&D team, guarantee the speed of product development, and use the global market network to expand its telecommunication business.
Highly uncertain competitive pressure gives enterprises urgent EI power. During crisis, whether to maintain high EE does not have a substantial impact on the high EI activity. The senior management of the organization will actively seek new development opportunities. Considering their career, the members of the organization will actively implement the senior management’s decision making and commit to the implementation of new business. The main form of this kind of enterprise EI is to apply the existing products to the new market or carry out related diversification.
Regardless whether the enterprise has strong RIC or not, when it is in a highly uncertain competitive environment, as long as the enterprise has high IIC, high EE, and strong ORC, the enterprise will carry out EI. Specifically, Kassa and Raju [19] believed that a series of support, authorization, and incentive systems under the IIC can improve EE based on social exchange theory. Once potential value growth opportunities are identified, all means will be taken to lead the EI. Although resources are a key factor in innovation, during the process, good innovation opportunities and competent management teams can attract investors and obtain the resources needed for development opportunities (Marianne, 1998). RIC is only necessary to maintain the successful operation of EI, not to trigger EI. The typical case of this configuration is Xiaomi, an Internet company that started with mobile phone business. Upon its establishment, Xiaomi formulated an employee stock ownership plan, and its IIC is active. With the focus on products and customers and the love for work of Xiaomi people, its business scale continues to expand, from the initial mobile phone business to the current construction of intelligent hardware and IOT platform. At the early stage of the development of new businesses (e.g., air purifier, smart bracelet, mobile power supply, etc.), Xiaomi has no ability to effectively integrate into the resources associated with its new business. However, it can always make up for the lack of resources by developing creative solutions (e.g., layouting of ecological chain enterprises).
By comparing the three configurations, configuration H1 is higher than configurations H2 and H3 according to the coverage index. H1 explains 73% of the result variables and covers seven cases, that is, most enterprises achieve high EI activity through the first path. This finding fully illustrates the role of opportunities, resources, and configuration between teams in EI. The coverage of configurations H2 and H3 is 38% and 60%, respectively, revealing the many ways to achieve high EI activity. EU and IIC also affect EI. This finding fully reflects the advantages of QCA in explaining the configuration effect among various factors. Traditional statistical methods of management research cannot explain this complex phenomenon [15].
Driving mechanism of low innovation activity
In view of the cause and effect asymmetry of QCA, that is, whether a result appears or does not need different “cause combinations” to be explained separately. In this study, the cause of high EI activity is not the negative condition of low EI activity (see Table 7). To comprehensively explore the driving mechanisms of EI, this study analyzes the configuration that leads to low EI activity with the following cases.
Regardless whether an enterprise has high ORC or RIC, when it does not suffer from high EU, as long as the organization does not have high IIC and high EE, EI activities will be inhibited. The main business of enterprises in a relatively stable business environment is better, but the path dependence is significant [7]. Coupled with ∼ IIC, organizational and structural inertia cannot be broken for a long time, and employees have no motivation, extra time, and resources to experiment their ideas [7]. EE is low as they only regard the organization as a “community of interests,” and they are unwilling to pay extra effort and be enthusiastic to create value for the organization. Even if they know the possible value opportunities and resources, they will give up the development of opportunities due to the opposition and interference from internal members and the expected negative impact of failure on their career. Jingwei Technology, which represents a typical case of this kind of configuration, has experienced a series of investment, operation, and management errors due to corporate corruption, bankruptcy, and liquidation of related businesses as well as salary arrears. Together, they led to a downturn in the development and operation of new businesses for a certain period.
Regardless whether an enterprise is in a highly uncertain environment or not, with ∼ IIC and low ORC and RIC, even if EE is high, it is not conducive to the development of EI. The typical cases of this kind of configuration are Changfei and Fangu Groups. Most of these cases are family enterprises, which have been engaged in a single field for a long time. The operating environment and efficiency are relatively stable. The technical content of the main business and the education level of the employees are generally low. The ability to identify new opportunities and integrate new resources is weak, which ultimately results in this type of enterprises always in a tepid market competition.
By comparing the coverage indexes of configurations L1 and L2, the former is slightly higher than the latter, which explains 61% and 51% of the result variables, respectively. Enterprises’ EI activity is mainly restrained by these two configurations.
By comparing the five configurations, the causes of EI activity are asymmetric, that is, low EI activity (L1 and L2) are not the opposite of high EI activity. Nonetheless, the existence and absence of necessary conditions (high ORC and IIC) determine the EI activity to a certain extent.
Conclusion
Twenty domestic enterprises are investigated through interviews and questionnaires. From the perspectives of environment and organization, the five factors of these two levels are reconfigured by configuration thinking and QCA to explore the multiple concurrent factors and causal complex mechanism that affect the differences in EI activities among enterprises. The main conclusions of this study are as follows: High ORC is the necessary condition for high EI activity, and ∼ IIC is the necessary condition for low EI activity. The driving mechanism of high EI activity is divided into three paths. The first path refers to the configuration of high ORC, high RIC, and high EE. The second path refers to high EU, high ORC, and high RIC. The third path refers to the configuration of high EU, high IIC, high ORC, and high EE. The driving mechanism of low EI activity has two paths, and it has an asymmetric relationship with the driving mechanism of high EI activity.
This study bears limitations, which are worthy of further discussion. First, this study explores the configuration effect of case comparison, and the dynamic continuous process of EI is a very interesting research topic. In the future, we can consider collecting panel data, using dynamic QCA for research. We can also try to calibrate the set membership in time dimension so as to move forward the step for verifying the complex causal relationship between EI and the configurations of different types of environmental and organizational factors. Second, the cases cannot be analyzed comprehensively and presented in detail due to the structural advantages of questionnaire data collection but also the disadvantages of lacking in-depth phenomenon. In the future, grounded theory can be used or combined with the open enterprise case database to collect and analyze a variety of data. Finally, part of the research involves the privacy of entrepreneurs, so this study only focuses on the impact of the environmental and organizational factors on EI. In the future, we can build a comprehensive EI model from different theoretical perspectives and levels (e.g., entrepreneurs’ personal factors) to explore the impact of the configuration effect of various factors on EI.