Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises
Glorious Sun School of Business and Management, Donghua University, 1882, Yan’an Road West, Shanghai 200051, China
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Author to whom correspondence should be addressed.
Sustainability 2024, 16(16), 6954; https://doi.org/10.3390/su16166954
Submission received: 23 July 2024
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Revised: 10 August 2024
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Accepted: 11 August 2024
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Published: 14 August 2024
(This article belongs to the Section Sustainable Management)
Abstract
:This study is the first to comprehensively investigate the impact mechanism of organizational resilience on the sustainable competitive advantage of enterprises based on dynamic capability theory, social network theory, and resource dependence theory. It systematically analyzes the multidimensional effects of organizational resilience and reveals the moderating effect of the network digital atmosphere and environmental dynamism on strategic capabilities. Herein, six basic hypotheses and 19 sub-hypotheses are proposed. Through the analyses of 386 valid questionnaires in the Yangtze River Delta and Pearl River Delta regions, the results show that organizational resilience has a positive impact on the sustainable competitive advantage of enterprises, and strategic capability plays a mediating role through two dimensions, which are strategic formulation capability and resource integration capability. In addition, the network digital atmosphere and environmental dynamics regulate the relationship between organizational resilience and strategic capability in different dimensions. The research results provide empirical support for strengthening corporate strategic capabilities, responding to environmental changes, maintaining competitive advantages, and achieving the sustainable development of enterprises.
1. Introduction
The dynamic capability theory emphasizes that enterprises can achieve sustainable competitive advantages in a constantly changing market environment by matching their organizational capabilities with the external environment. Previous studies have generally focused on the role of organizational resilience in responding to environmental changes and adverse events. Previous studies have shown that organizational resilience can significantly promote business model innovation and quickly respond to market changes [1]. It can reduce the degree of losses caused by environmental turbulence, and accelerate the resumption of normal operations, promoting the speed advantage of a rapid response and recovery for enterprises. Moreover, the resilience of small hotels can have an impact on the development of the tourism industry through their performance [2].
Although organizational resilience is considered by the academic community to be a key dynamic ability for enterprises to respond to environmental challenges, the mechanism by which organizational resilience affects the long-term competitive advantage of enterprises has not been fully elucidated, and the relationship between organizational resilience and enterprise performance in different market environments still commands further research. The investigation in these unknown areas is of great significance for understanding the practical application of organizational resilience in enterprises’ strategic management.
This study constructs a comprehensive theoretical model that includes organizational resilience (independent variable), sustainable competitive advantage (dependent variable), strategic capability (mediating variable), network digital atmosphere, and environmental dynamics (moderating variable). Based on the theoretical model and measurement results, the impact mechanism of organizational resilience on the sustainable competitive advantage of enterprises is clarified. The results indicate that organizational resilience directly affects a company’s competitive advantage and indirectly affects its performance through the improvement of its strategic capabilities, especially in highly dynamic environments where the role of strategic capabilities is more significant. This discovery provides a theoretical basis and practical guidance for enterprises to formulate and adjust strategies in unstable markets.
The structure of this article is as follows: The second part provides the detailed methods of the theoretical model constructed in this study, including the definitions and interrelationships of variables such as organizational resilience, strategic capability, network digital atmosphere, and environmental dynamism, and explains the basic assumptions and expected mechanisms of this study. The third part describes the data collection process, sample characteristics, and statistical methods and techniques used for data analysis in this study and report the empirical research results, including descriptive statistics, reliability and validity analysis, and the test results of the main effects and moderating effects of each variable in the model. The fourth part discusses the research results and explores whether the empirical results conform to the relevant hypotheses proposed in the second part; The fifth part summarizes the main results of this study, emphasizes the important contributions of the research results in both theoretical and practical fields, proposes the limitations of the research, and suggests possible directions for future research.
2. Materials and Methods
2.1. Research Hypothesis
To construct a comprehensive theoretical model, this study first proposes the following hypotheses:
Hypothesis H1.
Organizational resilience has a positive impact on sustainable competitive advantage. Organizational resilience refers to the ability of an enterprise to maintain operational continuity, quickly resume normal operations, and learn and grow from adversity when facing internal challenges and external pressures. Organizational resilience includes the ability to recover to its original state and the ability to improve and strengthen systems and processes through crisis experience. Competitive advantage refers to the advantage that a company has relative to its competitors in a specific market or industry. This advantage enables enterprises to generate higher value or serve customers more effectively, thereby achieving better performance in the market. Competitive advantage can come from multiple aspects, such as cost advantage, brand recognition, unique technology, high-quality customer service, product differentiation, etc. Numerous studies [3,4,5] have shown that organizational resilience can enhance a company’s ability to adapt to environmental changes and respond quickly, promoting the formation and maintenance of its competitive advantage.
Hypothesis H1a.
Situational awareness has a positive impact on sustainable competitive advantage [6,7]. Situational awareness refers to the ability of individuals or organizations to perceive, understand, and predict real-time information in their environment. In organizational and management research, situational awareness involves an accurate understanding of a company’s internal state and external environmental changes, including market trends, competitor behavior, technological progress, and policy environment [8,9]. This understanding requires companies to be able to capture relevant information, and more importantly, to be able to interpret and utilize this information for effective strategy formulation. For enterprises, a high level of situational awareness means being able to identify and understand key factors that may affect the achievement of organizational goals in a complex and ever-changing business environment in a timely manner. By enhancing situational awareness, enterprises can better predict upcoming changes in the environment, adjust their strategies and operations accordingly, and maintain or enhance their competitive position in the market.
Hypothesis H1b.
Predictive capacity has a positive impact on sustainable competitive advantage [10]. Predictive capacity is the ability of a company to analyze and predict future environmental changes (including markets, technology, policies, etc.) in order to make timely strategic adjustments. Predictive capacity is the key for organizations to develop effective response strategies in uncertain environments, involving multiple aspects such as information collection, data analysis, trend prediction, and risk assessment [11]. Predictive capacity enables enterprises to predict and prepare for potential market changes and risks, thereby optimizing products and services to meet future market demands [12].
Hypothesis H1c.
Adaptability has a positive impact on sustainable competitive advantage [13,14]. Adaptability is the ability of an enterprise to adjust its own behavior and strategy in the face of external environmental changes, in order to maintain or enhance its competitive position. Adaptability includes the ability of enterprises to respond to changes in market demand, technological progress, updates in legal policies, and changes in socio-economic conditions. Enterprises with strong adaptability can quickly adjust their strategies, overcome difficulties, and maintain their market leadership position when facing environmental challenges [15,16].
Hypothesis H2.
Organizational resilience has a positive impact on strategic capability [17,18]. Strategic capability is the comprehensive ability demonstrated by enterprises in formulating and implementing strategies to respond to market and environmental changes. It includes the ability to identify and seize opportunities, and the ability to utilize the resources and capabilities of the enterprise to execute strategic formulation and achieve long-term goals. Strategic capability is the core of a company’s competitiveness. Due to the strengthening of organizational resilience, enterprises perceive and respond to external changes, prompting them to continuously optimize their strategic formulation and resource integration, thereby enhancing their overall strategic capabilities [19].
Hypothesis H2a.
Organizational resilience has a positive impact on strategic formulation capability. Organizational resilience enhances the sensitivity of enterprises to environmental changes and supports effective strategy formulation through the use of internal and external information in the strategic formulation process [20].
Hypothesis H2b.
Organizational resilience has a positive impact on resource integration capability. Organizational resilience enhances the ability of enterprises to adapt to environmental changes, promotes the rapid allocation and optimization of resources, and improves resource utilization efficiency.
Hypothesis H3.
Hypothesis H3a.
Strategic formulation capability has a positive impact on sustainable competitive advantage [23]. The strategic formulation capability enables enterprises to proactively formulate and execute strategies to cope with rapidly changing market conditions.
Hypothesis H3b.
Hypothesis H4.
Strategic capability plays a mediating role between organizational resilience and sustainable competitive advantage [26]. Strategic capability is a means for enterprises to adapt and respond to market changes and a bridge connecting organizational resilience and competitive advantage.
Hypothesis H4a.
Strategic formulation capability plays a mediating role between organizational resilience and sustainable competitive advantage [19]. The strategic formulation capability enables enterprises with high organizational resilience to quickly formulate and implement effective strategies in the face of market uncertainty, thereby enhancing their competitive advantage.
Hypothesis H4b.
Hypothesis H5.
The network digital atmosphere positively regulates the relationship between organizational resilience and strategic capability [27,28]. It refers to the level of digitalization and the popularity of digital activities in the network environment in which enterprises operate, including how organizations in the network utilize digital technology for interaction, collaboration, and information sharing. The network digital atmosphere can be reflected in a variety of forms, such as shared technology platforms, digital communication methods, and cooperation and innovation activities through the Internet. In a strong digital atmosphere, organizational resilience strengthens the development of strategic capabilities through more effective information flow and resource sharing.
Hypothesis H5a.
Network digital atmosphere positively regulates the relationship between organizational resilience and strategic formulation capability [29]. The digital network environment enhances the acquisition and processing of information by enterprises, making the strategic formulation process more precise and efficient.
Hypothesis H5b.
The network digital atmosphere positively regulates the relationship between organizational resilience and resource integration capability [30]. In the more developed digital network environment, enterprises can better utilize digital tools and platforms to integrate internal and external resources, improving response speed and efficiency.
Hypothesis H6.
Environmental dynamism positively regulates the relationship between organizational resilience and strategic capability [31,32]. Environmental dynamism describes the speed, uncertainty, and complexity of changes in the external environment of a company, covering the rapid changes in market, technology, policy, economic, and social factors. The level of environmental dynamism directly affects how quickly an organization needs to adjust its resources and strategies to cope with external changes [33]. In dynamic environments, organizational resilience plays a more significant role in promoting strategic capabilities, as constantly changing market conditions require companies to quickly adapt and adjust their strategies.
Hypothesis H6a.
Environmental dynamism positively regulates the relationship between organizational resilience and strategic formulation capability [34]. In a dynamic market environment, enterprises with high organizational resilience are more effective at formulating strategies that meet market demand and enhance competitiveness.
Hypothesis H6b.
Environmental dynamism positively regulates the relationship between organizational resilience and resource integration capability [27]. In a rapidly changing environment, enterprises with high organizational resilience are more effective at adjusting resource allocation to adapt to market and technological changes.
2.2. Theoretical Model Construction
This study constructs a comprehensive theoretical model based on the “input-process-output” model, as well as the dynamic capability theory, social network theory, and resource dependence theory, to explore the relationship between organizational resilience, strategic capability, network digital atmosphere, environmental dynamism, and sustainable competitive advantage. This model reflects the role of internal organizational capabilities and integrates the impact of changes in the network environment and external environment in which the organization operates, including four aspects (Figure 1).
Investment stage: This stage considers the macro environment in which the organization operates and the embedded network digital atmosphere. The dynamic characteristics of the environment and the degree of digitalization in the network provide organizations with constantly changing challenges and opportunities, requiring them to have a high degree of organizational resilience to cope with external changes.
Process stage: This study focuses on how organizations can utilize their organizational resilience to enhance strategic capabilities, namely, strategic formulation and resource integration capabilities. Organizational resilience supports enterprises in effectively utilizing internal and external information for the strategic formulation process by enhancing their perception of environmental changes. In addition, by dynamically coordinating external resources and internal capabilities, organizations can better adapt to environmental turbulence.
Output stage: The organization achieves sustainable competitive advantage through effective strategic capability enhancement. The strategic formulation and resource integration capabilities serve as mediating variables, connecting organizational resilience and sustainable competitive advantage, manifested as a company’s sustained advantage and growth ability in the market.
Moderating variables: The network digital atmosphere and environmental dynamics play a moderating role in the model, affecting the strength of the relationship between organizational resilience and strategic capability. The strong degree of network digital atmosphere can enhance information flow and resource sharing, thereby strengthening the development of strategic capabilities; The environmental dynamism strengthens the promoting effect of organizational resilience on strategic capabilities, since constantly changing market conditions require companies to quickly adapt and adjust their strategies.
In summary, the model constructed in this study reveals how organizational resilience affects sustainable competitive advantage through strategic capabilities and considers how the network digital atmosphere and environmental dynamics play a regulatory role in this process. Through this theoretical framework, enterprises can better understand how to build and maintain competitive advantages in dynamic and complex environments.
2.3. Data Collection
Based on the above theoretical model, this study designed relevant survey questionnaires, mainly in the form of online questionnaires, and designed and distributed electronic questionnaires based on the Questionnaire Star platform. The research subjects mainly included middle and senior management personnel of enterprises in the Yangtze River Delta and Pearl River Delta regions. These participants, due to their in-depth understanding of corporate strategies and crisis response measures, were able to provide accurate feedback on the survey questionnaire. The data collection period was from December 2023 to March 2024, and a total of 600 questionnaires were distributed.
Through strict screening, questionnaires with a missing answer rate exceeding 10% and obvious regularity in answers were excluded. A total of 386 questionnaires were ultimately collected and confirmed to be valid, with an effective response rate of 64.3%. This sample size met the sample size requirements of a multiple regression and structural equation modeling analyses, ensuring the effectiveness and reliability of the data analysis.
The questionnaire was divided into three parts: background information, measurement of core variables, and control variables. Background information included the personal information of participants and their basic information about the company they belonged to. The core variables included organizational resilience, strategic capability, sustainable competitive advantage, network digital atmosphere, and environmental dynamism. All core measurement variables were evaluated using the 5-point Likert scale to ensure data consistency and comparability.
To ensure the rigor of the research, this study conducted preliminary research tests in some enterprises in Shenzhen before the formal investigation. The feedback from the preliminary survey helped to further correct some issues in the questionnaire design and optimize the accuracy of measurements. In addition, through communication with enterprise personnel, a snowball approach was adopted to expand the coverage of the sample, improving the breadth and representativeness of the research.
The final research data were used to validate research hypotheses and analyze the relationship between organizational resilience, strategic capabilities, network digital atmosphere, environmental dynamics, and sustainable competitive advantage. The results of the data analysis are discussed in detail in this paper, providing theoretical and empirical support for enterprise strategy formulation and resource allocation.
2.4. Quantification of Indicators
Based on the theoretical model research framework and research hypotheses obtained in the previous section, this section transforms the concept into measurable operational measurement items, with core variables including organizational resilience (independent variable), sustainable competitive advantage (dependent variable), strategic capability (mediating variable), and network digital atmosphere and environmental dynamics (moderating variable). The selected scales were all mature scales published in mainstream domestic and foreign journals, and all measurement items in the questionnaire used the more conventional 5-point Likert scale, which was convenient for respondents to answer. Among them, “5” represented complete conformity, “4” represented basic conformity, “3” represented uncertainty, “2” represented basic nonconformity, and “1” represented complete nonconformity. The questionnaire items were presented in multiple-choice format. The participants were asked to answer based on their own and the actual situation of the company, and there was no right or wrong answer.
2.4.1. Organizational Resilience
Based on the scales of Duchek et al. [19], this study developed a scale consisting of 15 measurement items in three dimensions: situational awareness, predictive capacity, and adaptability, combined with semi-structured interviews with enterprise practitioners. The empirical test of this scale showed that it had high reliability and validity and could well explain the organizational resilience of Chinese enterprises in the context of emerging economies (Table S1).
2.4.2. Sustainable Competitive Advantage
At present, there is no consistent indicator and measurement item for sustainable competitive advantage in domestic and foreign research. Various research schools have conducted empirical analyses on sustainable competitive advantage from different research perspectives. Except for listed companies, most manufacturing companies are unwilling to provide information about their financial situation, and sustainable competitive advantage is a comparative advantage. Therefore, this study adopted the self-report method to measure sustainable competitive advantage. Referring to previous research, this study used a subjective measurement method to measure it, taking into account the special situation of Chinese organizations, and ultimately formed a measurement scale with 6 items, as shown in Table S2.
2.4.3. Strategic Capabilities
Strategic capability is the mediating variable assumed in this study, which is the combination of corporate strategy and capability. Strategic capability refers to the ability of an enterprise to carry out strategic formulation and achieve long-term sustainable development in the dynamic external environment, including two dimensions: strategic formulation capability and resource integration capability. This study ultimately formed a measurement scale consisting of 14 items, as shown in Table S3.
2.4.4. Network Digital Atmosphere
According to the theoretical model constructed in this study, the network digital atmosphere is the moderating variable. The operation of enterprises are influenced by the strong degree of digital atmosphere embedded in the network. This study considered the special situation of Chinese organizations and ultimately formed a measurement scale consisting of four items, as shown in Table S4.
2.4.5. Environmental Dynamism
This study identified commonly used and relatively mature measurement items for various variables, and ultimately developed a measurement scale for environmental dynamics, taking into account the special circumstances of Chinese organizations. A measurement scale consisting of four items was developed, as shown in Table S5.
2.4.6. Control Variables
This study selected variables that could affect the empirical results, including the establishment time of the enterprise, enterprise property, enterprise scale, and the industry to which the enterprise belonged as control variables. The results showed that companies established for a longer time may accumulate more resources and capabilities, thereby performing better in terms of organizational resilience. Therefore, this study incorporated time factors to control for their potential impact on the results. In addition, large enterprises usually have sufficient capital and can withstand risks well, but may have shortcomings in flexibility. This study measured the enterprise scale through the number of employees.
The enterprise’s property also affects strategic formulation and resource integration. Based on the actual situation in China, this study divided enterprises into state-owned enterprises, private enterprises, Sino-foreign joint ventures, and wholly foreign-owned enterprises to deeply analyze the specific impact of different enterprise properties on strategic capabilities. Considering the significant impact of industry background on organizational resilience, this study focused on the manufacturing industry, further subdivided into the light textile industry, resource processing industry, and mechanical and electronic manufacturing industry. This classification helped to ensure the relevance and accuracy of the research data, while avoiding potential biases caused by industry differences.
2.5. Empirical Methods
At present, most empirical research in the field of management adopts questionnaire survey methods to collect data. This study used online means to distribute electronic questionnaires, collect data, and then conduct empirical research. The empirical methods used in this article mainly included descriptive statistics, a reliability and validity analysis, and a correlation and regression analysis.
2.5.1. Descriptive Statistical Analysis
This analysis organized the valid sample data and analyzed the personal and company information of the subjects, mainly including the frequency and percentage of the sample data. The descriptive statistical analysis was carried out on core variables based on indicators such as mean, kurtosis, skewness, and standard deviation.
2.5.2. Reliability and Validity Testing
Reliability is used to reflect the consistency, stability, and reliability of measurement results. When Cronbach’s alpha coefficient is greater than 0.7, it indicates good questionnaire reliability [35]. In addition, many scholars use the alpha-if-item-deleted value and the corrected item–total correlation (CITC) in their research results as supplementary reference indicators. Validity testing mainly includes content validity, convergent validity, and discriminant validity. Content validity refers to the use of expert consultation and other methods to determine whether the selected scale can appropriately measure variables. Convergence validity is determined by whether the standardized factor loadings of all variables are greater than 0.7, the variance extracted value (AVE) is greater than 0.5, and the combination reliability (CR) is greater than 0.7. Differential validity refers to the significant differences between measurement items of different concepts, and the square root of the AVE of latent variables should be greater than the correlation coefficient.
2.5.3. Correlation and Regression Analysis
Correlation analysis reflects the level of correlation between research variables, measured by Pearson’s coefficient. Regression analysis is the testing of possible causal relationships between variables based on correlation analysis. The key measure is usually whether the standardized regression coefficient β is significant, that is, whether the p-value is less than 0.05 [36]. This article used multi-level regression to test the mediating effect. In the moderating effect test, this article first multiplied and related the moderating variable with the independent variable and then regressed the dependent variable to test for the presence of moderating effect.
3. Results
3.1. Descriptive Statistics
3.1.1. Descriptive Statistics of Samples
According to the 386 valid questionnaires collected from the survey, this study collected data on the gender, age, highest education level, years of work experience of the respondents, as well as the basic information of the surveyed companies on their establishment time, property, scale, and industry. The specific descriptive statistics of the sample are shown in Table S6.
3.1.2. Descriptive Statistical Analysis of Variables
This section determines preliminary statistics on each item in the measurement scale of organizational resilience, strategic capability, sustainable competitive advantage, network digital atmosphere, and environmental dynamics. The descriptive statistics of each variable are shown in Table S7. In the research results, the sample size for all items was 386, and there was no missing sample size. The average and standard deviation of each item were different, and the absolute kurtosis of all items was between 0.02 and 0.768, which was far below the critical value of 10. The absolute skewness of all items was between 0.612 and 1.053, which was far below the critical value of 3, indicating that the collected sample data followed a normal distribution and could be utilized for the subsequent empirical analysis.
3.2. Reliability and Validity Analysis
3.2.1. Common Method Bias Testing
Firstly, a Common Method Variance (CMV) test was conducted on the questionnaire data. The cause of CMV is the presence of covariates among variables caused by the same investigators, measurement environment, questionnaire content, or measurement context. To minimize such errors as much as possible, this study aimed to reduce the bias impact caused by common methods from two aspects: research arrangement and data analysis. For the research arrangement, it was clearly stated in the questionnaire design and distribution process that the data collected in this study were only for academic research, emphasizing the importance of truthfully answering the questions to the participants. Simultaneously, we promised full confidentiality. For the data analysis, this study used Harman’s univariate test to determine the presence of CMV in the questionnaire data, in order to ensure the effective conduct of subsequent studies.
Before conducting the factor analysis, it was necessary to determine whether the data were suitable for a factor analysis through KMO and Bartlett’s test values. In this study, KMO values > 0.7 and Bartlett’s test statistical values were less than the significance level used as the appropriate criteria for the factor analysis. According to Table S8, the KMO values of each variable were all greater than the standard of 0.7, and the p-value of each variable was 0.000. The Bartlett sphere test was significant, indicating that each variable met the statistical criteria and was suitable for the factor analysis.
Specifically, an exploratory factor analysis was conducted on all dimensions of variables involved in the study, including organizational resilience, strategic capability, sustainable competitive advantage, network digital atmosphere, and environmental dynamics. As shown in Table S9, a total of eight common factors with eigenvalues greater than one were extracted, accounting for 66.248% of the total variance. Among them, the largest factor accounted for 25.728% of the total variance, which did not exceed the critical standard of 40% and did not reach half of the total variance. This indicated that the influence of the common method variation bias could be excluded.
3.2.2. Reliability Analysis
This study used Cronbach’s alpha coefficient and the CITC as indicators to test the reliability of the scale. The overall Cronbach’s alpha coefficient of the questionnaire was found to be 0.929.
- (i)
- Reliability analysis of organizational resilience
The overall alpha coefficient of the organizational resilience scale was 0.863, which was higher than 0.8 and had high reliability. Among them, the alpha coefficient of situational awareness was 0.845, and the CITC of all four items was greater than 0.5. There were no items that could improve the alpha if item deleted of the organizational resilience scale, indicating its favorable reliability. The alpha coefficient of predictive capacity was 0.861, and the CITC of all five items was greater than 0.5. There were no items that could improve the alpha if item deleted of predictive capacity, indicating its favorable reliability. The alpha coefficient of adaptability was 0.884, and the CITC of all six items was greater than 0.5. There were no items that could improve the alpha if item deleted of adaptability, also indicating its favorable reliability. The reliability indicators of organizational resilience are shown in Table S10.
- (ii)
- Reliability analysis of sustainable competitive advantage
There were a total of six measurement items for sustainable competitive advantage, and the overall Cronbach’s alpha coefficient of the scale was 0.896. The CITC of all six measurement items was greater than 0.5, and there were no items that could improve the alpha if item deleted. The reliability of the sustainable competitive advantage scale was good, and the specific indicators are shown in Table S11.
- (iii)
- Reliability analysis of strategic capability
There are a total of 14 measurement items for strategic capability, and the overall Cronbach’s alpha coefficient of the scale was 0.896, which was higher than 0.8 and had high reliability. Among them, the alpha coefficient of strategic formulation capability was 0.864, and the CITC of all five items was greater than 0.5. There were no items that could improve the alpha if item deleted, indicating that the reliability of strategic formulation capability was favorable. The alpha coefficient of resource integration capability was 0.919, and the CITC of all nine items was greater than 0.5. There were no items that could improve the alpha if item deleted, also indicating the good reliability of resource integration capability. The reliability indicators of strategic capability are shown in Table S12.
- (iv)
- Reliability analysis of network digital atmosphere
There were a total of four measurement items for the network digital atmosphere, and the overall Cronbach’s alpha coefficient of the scale was 0.852. The CITC of all four items was greater than 0.5, and there were no items that could improve the alpha if item deleted. The reliability of the network digital atmosphere scale was favorable, and the specific indicators are shown in Table S13.
- (v)
- Reliability analysis of environmental dynamism
There were a total of four measurement items for environmental dynamism, and the overall Cronbach’s alpha coefficient of the scale was 0.877. The CITC of all four items was greater than 0.5, and there were no items that could improve the alpha if item deleted. The reliability of the environmental dynamics scale was favorable, and the specific indicators are shown in Table S14.
3.2.3. Validity Analysis
The validity analysis of this study included four aspects: content validity, structural validity, convergent validity, and discriminant validity. In terms of content validity, the measurement scales used were derived from mature research in mainstream domestic and foreign journals and combined with feedback from management experts and senior management in enterprises to form a survey questionnaire. These measurement scales covered organizational resilience, sustainable competitive advantage, strategic capability, network digital atmosphere, and environmental dynamism, all demonstrating good content validity.
To verify the structural validity, this study tested the fitting parameters of the model using the maximum likelihood method. Based on the results of an exploratory factor analysis, this study established an eight-factor benchmark model that included situational awareness, predictive capacity, adaptability, sustainable competitive advantage, strategic formulation capability, resource integration capability, network digital atmosphere, and environmental dynamism, and compared it with several competition models. By conducting a confirmatory factor analysis (CFA), the goodness of fit of the model was measured using x2/df, RMSEA, GFI, NFI, IFI, TLI, and CFI values (Table S15). The results showed that the eight-factor model had the best fit, with an x2/df value of less than 3, an RMSEA value less than 0.1, GFI and NFI close to 0.90, and IFI, TLI, and CFI greater than 0.90, indicating a favorable fit of the model.
In addition, this study also constructed seven competitive models for a comparative analysis: the seven-factor model combined strategic formulation capability and resource integration capability as one factor; the six-factor model combined situational awareness, predictive capacity, and adaptability into one factor; the five-factor model further combined the two sets of factors mentioned above; the four-factor model combined organizational resilience and strategic capability into one factor; on this basis, the three-factor model combined the network digital atmosphere and environmental dynamics into one factor; the two-factor model combined all the above factors into one factor; the single-factor model combined all factors into one total factor. These analyses validated the structural validity of the model in this study.
Next, this study used standardized factor loadings and AVE values to test the convergence validity of all variables, with specific testing indicators shown in Table S16. The minimum standardized factor loading coefficient for situational awareness, predictive capacity, adaptability, sustainable competitive advantage, strategic formulation capability, resource integration capability, network digital atmosphere, and environmental dynamism was 0.696, which was greater than the threshold of 0.5. The AVE was above 0.5, with a minimum of 0.554, indicating that the information extracted from each factor could explain more than 50% of the variance. Moreover, the combined reliability CR of each variable was greater than 0.7, with a minimum value of 0.845. In summary, the scale used in this study had favorable convergent validity.
Finally, we tested the discriminant validity. The correlation analysis results between variables are shown in Table S17. There was a pairwise correlation between situational awareness, predictive capacity, adaptability, strategic formulation capability, resource integration capability, network digital atmosphere, environmental dynamism, and sustainable competitive advantage, and the correlation coefficients were all significant. All correlation coefficients were less than 0.7, indicating no excessive correlation. The diagonal number is the square root of the AVE value of each variable, which was greater than the correlation coefficients between its adjacent variables. Therefore, the questionnaire used in this study had favorable discriminant validity.
3.3. The Test Results of the Main Effect of Organizational Resilience on Sustainable Competitive Advantage
This study examined the main effect of organizational resilience on the sustainable competitive advantage of enterprises in theoretical models. A regression analysis was conducted using organizational resilience and its various dimensions (situational awareness, predictive capacity, adaptability) as independent variables, and sustainable competitive advantage as the dependent variable. The results of the regression analysis are shown in Table 1. Model 1 was a benchmark model that only included control variables and sustainable competitive advantage. Model 2 added organizational resilience to Model 1 and was a model that tested the direct effect between organizational resilience and sustainable competitive advantage. Model 3, Model 4, and Model 5 were models used to test the direct effect between situational awareness, predictive capacity, adaptability and sustainable competitive advantage, respectively.
3.4. Test Results of the Mediating Effect of Strategic Capability
This study adopted a multi-level regression analysis to examine the mediating effect of strategic capabilities between organizational resilience and sustainable competitive advantage in the model. Testing was based on the three-step test of Baron and Kenny for mediating effects. Firstly, we examined the impact of the independent variable (organizational resilience) on the mediating variable (strategic capability and its various dimensions), and the regression results are shown in Table 2.
Secondly, the impact of mediating variables (strategic capability and its various dimensions) on the dependent variable (sustainable competitive advantage) was tested, and the regression results are shown in Table 3.
Finally, the independent variable (organizational resilience) and the mediating variable (strategic capability and its dimensions) were simultaneously added to the model, and the regression results are shown in Table 4.
3.5. Test Results of the Moderating Effect of Network Digital Atmosphere
To test whether there was a moderating effect of the network digital atmosphere on the impact of organizational resilience on strategic capability and its various dimensions, this study used the hierarchical regression method for testing. To reduce the interference of multicollinearity in the product term, the independent and moderating variables were standardized, and the product term between the two was constructed. Using strategic capability and its various dimensions as dependent variables, control variables, independent variables (organizational resilience), and moderating variables (network digital atmosphere) were placed in the regression model for testing; then, the product term of the independent variable (organizational resilience) and the moderating variable (network digital atmosphere) was placed in the regression model for analysis, and the test results are shown in Table 5.
3.6. Test Results of Regulatory Effects of Environmental Dynamics
To examine whether there was a moderating effect of environmental dynamism on the impact of organizational resilience on strategic capability and its various dimensions, the hierarchical regression method was utilized in this study. To reduce the interference of multicollinearity in the product term, the independent and moderating variables were standardized, and the product term between the two was constructed. Using strategic capability and its various dimensions as dependent variables, control variables, independent variables (organizational resilience), and moderating variables (environmental dynamism) were placed in the regression model for testing; then, the product term of the independent variable (organizational resilience) and the moderating variable (environmental dynamism) was placed in the regression model for analysis, and the test results are shown in Table 6.
4. Discussion
4.1. The Main Effect of Organizational Resilience on Sustainable Competitive Advantage
Based on the results in Table 1, it can be concluded that after controlling for variables such as establishment time, property, scale, and industry type, organizational resilience has a significant positive impact on sustainable competitive advantage (β = 0.518, p < 0.001), and hypothesis H1 is valid. Situational awareness has a significant positive impact on sustainable competitive advantage (β = 0.442, p < 0.001), assuming H1a holds. Predictive capacity has a significant positive impact on sustainable competitive advantage (β = 0.271, p < 0.001), assuming H1b holds. Adaptability has a significant positive impact on sustainable competitive advantage (β = 0.422, p < 0.001), assuming H1c holds. Meanwhile, the maximum VIF value of the above model was 1.155, which was less than the critical value of 10, indicating that there was no multicollinearity problem in the sample data. Model 6 incorporated three dimensions of organizational resilience into the regression model simultaneously, and the regression results remained robust. In summary, the sample data empirically confirmed hypotheses H1, H1a, H1b, and H1c, that is, organizational resilience and its three dimensions (situational awareness, predictive capacity, and adaptability) have a significant positive impact on sustainable competitive advantage.
4.2. The Mediating Effect of Strategic Capabilities
Based on the results in Table 2, after adding control variables in the first layer, organizational resilience has a significant positive impact on strategic capability (β = 0.476, p < 0.001), assuming that H2 is valid. Organizational resilience has a significant positive impact on strategic formulation capability (β = 0.541, p < 0.001), assuming H2a holds. Organizational resilience has a significant positive impact on resource integration capability (β = 0.304, p < 0.001), assuming H2b holds. Meanwhile, the maximum VIF value of the above model was 1.152, which was less than the critical value of 10, indicating that there was no multicollinearity problem in the sample data. In summary, the sample data empirically confirmed hypotheses H2, H2a, and H2b, that is, organizational resilience has a significant positive impact on strategic capability and its two dimensions (strategic formulation capability and resource integration capability).
According to the results in Table 3, strategic capability has a significant positive impact on sustainable competitive advantage (β = 0.475, p < 0.001), assuming H3 holds. The strategic formulation capability has a significant positive impact on sustainable competitive advantage (β = 0.516, p < 0.001), assuming H3a holds. The resource integration capability has a significant positive impact on sustainable competitive advantage (β = 0.323, p < 0.001), assuming H3b holds. Meanwhile, the maximum VIF value of the above model was 1.154, which was less than the critical value of 10, indicating that there was no multicollinearity problem in the sample data. In summary, the sample data empirically confirmed hypotheses H3, H3a, and H3b, that is, strategic capability and its two dimensions (strategic formulation capability and resource integration capability) have a significant positive impact on sustainable competitive advantage.
Based on the results in Table 4, it was found that after adding strategic capability, it still had a significant positive impact on the sustainable competitive advantage of enterprises (β = 0.295, p < 0.001) compared to Model 2 and Model 13. However, the impact of organizational resilience on the sustainable competitive advantage of enterprises weakened, and the regression coefficient changed from (β = 0.518, p < 0.001) to (β = 0.378, p < 0.001). The regression coefficient decreased, indicating that strategic capability plays a partial mediating role in the relationship between organizational resilience and sustainable competitive advantage. Hence, hypothesis H4 holds. Specifically, comparing Model 2 and Model 14, it was found that the addition of strategic formulation capability still had a significant positive impact on the sustainable competitive advantage of enterprises (β = 0.328, p < 0.001), but the impact of organizational resilience on the sustainable competitive advantage of enterprises weakened. The regression coefficient changed from (β = 0.518, p < 0.001) to (β = 0.341, p < 0.001), indicating that strategic formulation capability plays a partial mediating role in the relationship between organizational resilience and sustainable competitive advantage. Hence, hypothesis H4a holds. Comparing Model 2 and Model 15, it was found that after adding resource integration capability, it still had a significant positive impact on the sustainable competitive advantage of enterprises (β = 0.182, p < 0.001). However, the impact of organizational resilience on the sustainable competitive advantage of enterprises weakened, and the regression coefficient changed from (β = 0.518, p < 0.001) to (β = 0.463, p < 0.001). The regression coefficient decreased, indicating that resource integration capability plays a partial mediating role in the relationship between organizational resilience and sustainable competitive advantage. Hence, hypothesis H4b holds.
4.3. The Regulatory Effect of Network Digital Atmosphere
Based on the results in Table 5, when testing the moderating effect of network digital atmosphere on the relationship between organizational resilience and strategic capability, Model 16 showed that organizational resilience (β = 0.422, p < 0.001) and network digital atmosphere (β = 0.246, p < 0.001) had a significant positive impact on strategic capability. Model 17 added a product term of organizational resilience and network digital atmosphere on the basis of Model 16. The results showed that organizational resilience (β = 0.402, p < 0.001), network digital atmosphere (β = 0.244, p < 0.001), and product term (β = 0.136, p < 0.01) all had a significant positive impact on strategic capability. The interaction term was significant, indicating that network digital atmosphere positively regulates the impact of organizational resilience on strategic capability. Hence, hypothesis H5 is valid.
When examining the moderating effect of network digital atmosphere on the relationship between organizational resilience and strategic formulation capability, Model 18 showed that organizational resilience (β = 0.494, p < 0.001) and network digital atmosphere (β = 0.218, p < 0.001) had a significant positive impact on strategic formulation capability. Model 19 added a product term of organizational resilience and network digital atmosphere on the basis of Model 18. The results showed that although organizational resilience (β = 0.485, p < 0.001) and network digital atmosphere (β = 0.217, p < 0.001) both had a significant positive impact on strategic formulation capability, the product term (β = 0.061, p > 0.05) did not have a significant positive impact on strategic formulation capability, and the interaction term was not significant, indicating that network digital atmosphere does not positively regulate the impact of organizational resilience on strategic formulation capability. Hence, hypothesis H5a is not valid.
When examining the moderating effect of network digital atmosphere on the relationship between organizational resilience and resource integration capability, Model 20 showed that organizational resilience (β = 0.261, p < 0.001) and network digital atmosphere (β = 0.194, p < 0.001) had a significant positive impact on resource integration capability. Model 21 added a product term of organizational resilience and network digital atmosphere on the basis of Model 20. The results showed that organizational resilience (β = 0.241, p < 0.001), network digital atmosphere (β = 0.192, p < 0.001), and product term (β = 0.143, p < 0.01) all had a significant positive impact on resource integration capability. The interaction term was significant, indicating that network digital atmosphere positively regulates the impact of organizational resilience on resource integration capability. Hence, hypothesis H5b holds.
4.4. Testing the Regulatory Effects of Environmental Dynamics
Based on the results in Table 6, when testing the moderating effect of environmental dynamism on the relationship between organizational resilience and strategic capability, Model 22 showed that organizational resilience (β = 0.422, p < 0.001) and environmental dynamism (β = 0.164, p < 0.01) had a significant positive impact on strategic capability. Model 23 added a product term of organizational resilience and environmental dynamism on the basis of Model 22. The research results showed that organizational resilience (β = 0.359, p < 0.001), environmental dynamism (β = 0.175, p < 0.001), and product term (β = 0.295, p < 0.001) all had a significant positive impact on strategic capability. The interaction term was significant, indicating that environmental dynamism positively regulates the impact of organizational resilience on strategic capability. Hence, hypothesis H6 holds.
When examining the moderating effect of environmental dynamism on the relationship between organizational resilience and strategic formulation capability, Model 24 showed that organizational resilience (β = 0.503, p < 0.001) and environmental dynamism (β = 0.116, p < 0.01) had a significant positive impact on strategic formulation capability. Model 25 added a product term of organizational resilience and environmental dynamism on the basis of Model 24. The results showed that organizational resilience (β = 0.459, p < 0.001), environmental dynamism (β = 0.123, p < 0.01), and product term (β = 0.205, p < 0.001) all had a significant positive impact on strategic formulation capability. The interaction term was significant, indicating that environmental dynamism positively regulates the impact of organizational resilience on strategic formulation capability. Hence, hypothesis H6a holds.
When examining the moderating effect of environmental dynamism on the relationship between organizational resilience and resource integration capability, Model 26 showed that organizational resilience (β = 0.255, p < 0.001) and environmental dynamism (β = 0.148, p < 0.01) had a significant positive impact on resource integration capability. Model 27 added a product term of organizational resilience and environmental dynamism on the basis of Model 26. The results showed that organizational resilience (β = 0.198, p < 0.001), environmental dynamism (β = 0.157, p < 0.01), and product term (β = 0.267, p < 0.001) all had a significant positive impact on resource integration capability. The interaction term was significant, indicating that environmental dynamism positively regulates the impact of organizational resilience on resource integration capability. Hence, hypothesis H6b holds.
4.5. Summary of Hypothesis Testing
Based on the above analyses, the hypothesis testing results are shown in Table 7.
5. Conclusions
Based on the dynamic capability theory, social network theory, resource dependence theory, and logical paradigm of resilience capability advantage, this study investigated the mechanism by which organizational resilience affects the sustainable competitive advantage of enterprises. It first combined relevant literature studies to fully and normatively propose corresponding research hypotheses, totaling 6 basic hypotheses and 19 sub-hypotheses. Secondly, 386 valid sample data were collected through a questionnaire survey, and descriptive statistical analysis and reliability and validity tests were conducted on the data. Finally, the main effects, mediating effects, and moderating effects involved were discussed and analyzed.
The results indicate that organizational resilience significantly promotes the sustainable competitive advantage of enterprises. Specifically, strategic capability plays a mediating role in the relationship between organizational resilience and sustainable competitive advantage. Organizational resilience enhances a company’s strategic capabilities by strengthening its strategic formulation capability and resource integration capability. Although the network digital atmosphere has a positive moderating effect on the relationship between organizational resilience and resource integration capabilities, its moderating effect on strategic formulation capabilities is not significant. The environmental dynamism plays a significant positive moderating role between organizational resilience and strategic capabilities and their dimensions (strategic formulation ability and resource integration capability). These findings not only confirm that organizational resilience significantly enhances a company’s sustainable competitive advantage by improving strategic capabilities, but also reveal the differential effects of network digital atmosphere and environmental dynamism, providing empirical support for companies to maintain competitive advantage in dynamic environments.
One limitation of this study is that the research data were only based on the Yangtze River Delta and Pearl River Delta regions, which may limit the generalizability of the research results. In addition, the research was based on cross-sectional data, which may limit our in-depth analysis of causal relationships. Future research can use multi-source data, tracking data, and data from a wider geographic region or different industries to enhance the reliability and universal applicability of our research results. Meanwhile, future studies can adopt a longitudinal research design to obtain panel data, in order to more accurately track the long-term impact of organizational resilience on the sustainable competitive advantage of an enterprise. Moreover, considering the trend of regional economic integration, research can further explore the impact of organizational resilience on the sustainable competitive advantage of enterprises in cross-cultural and transnational cultural environments.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su16166954/s1.
Author Contributions
Methodology, software, resources, formal analysis, visualization, data curation, and writing—original draft preparation, X.L.; conceptualization, review and editing, D.Z. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data used in this manuscript are available by writing to the corresponding authors.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Des Jardine, M.; Bansal, P.; Yang, Y. Bouncing Back: Building Resilience Through Social and Environmental Practices in the Context of the 2008 Global Financial Crisis. J. Manag. 2019, 45, 1434–1460. [Google Scholar]
- Sobaih, A.E.E.; Elshaer, I.; Hasanein, A.M.; Abdelaziz, A.S. Responses to COVID-19: The role of performance in the relationship between small hospitality enterprises’ resilience and sustainable tourism development. Int. J. Hosp. Manag. 2021, 94, 102824. [Google Scholar] [CrossRef] [PubMed]
- Ortiz-de-Mandojana, N.; Bansal, P. The long-term benefits of organizational resilience through sustainable business practices. Strateg. Manag. J. 2016, 37, 1615–1631. [Google Scholar] [CrossRef]
- Linnenluecke, M.K. Resilience in Business and Management Research: A Review of Influential Publications and a Research Agenda. Int. J. Manag. Rev. IJMR 2017, 19, 4–30. [Google Scholar] [CrossRef]
- Trieu, H.D.; Nguyen, P.V.; Tran, K.T.; Vrontis, D.; Ahmed, Z. Organisational resilience, ambidexterity and performance: The roles of information technology competencies, digital transformation policies and paradoxical leadership. Int. J. Organ. Anal. 2023, 32, 1302–1321. [Google Scholar] [CrossRef]
- Jerome, J.J.J.; Sonwaney, V.; Bryde, D.; Graham, G. Achieving competitive advantage through technology-driven proactive supply chain risk management: An empirical study. Ann. Oper. Res. 2024, 332, 149–190. [Google Scholar] [CrossRef]
- Fabrizio, C.M.; Kaczam, F.; de Moura, G.L.; Da Silva, L.S.C.V.; Da Silva, W.V.; Da Veiga, C.P. Competitive advantage and dynamic capability in small and medium-sized enterprises: A systematic literature review and future research directions. Rev. Manag. Sci. 2022, 16, 617–648. [Google Scholar] [CrossRef]
- Chatzoglou, P.; Chatzoudes, D. The role of innovation in building competitive advantages: An empirical investigation. Eur. J. Innov. Manag. 2017, 21, 44–69. [Google Scholar] [CrossRef]
- Azeem, M.; Ahmed, M.; Haider, S.; Sajjad, M. Expanding competitive advantage through organizational culture, knowledge sharing and organizational innovation. Technol. Soc. 2021, 66, 101635. [Google Scholar] [CrossRef]
- Eikelenboom, M.; de Jong, G. The impact of dynamic capabilities on the sustainability performance of SMEs. J. Clean. Prod. 2019, 235, 1360–1370. [Google Scholar] [CrossRef]
- Shahadat, M.H.; Chowdhury, A.H.M.Y.; Nathan, R.J.; Fekete-Farkas, M. Digital technologies for firms’ competitive advantage and improved supply chain performance. J. Risk Financ. Manag. 2023, 16, 94. [Google Scholar] [CrossRef]
- Nayak, B.; Bhattacharyya, S.S.; Krishnamoorthy, B. Explicating the role of emerging technologies and firm capabilities towards attainment of competitive advantage in health insurance service firms. Technol. Forecast. Soc. 2021, 170, 120892. [Google Scholar] [CrossRef]
- Dubey, R.; Bryde, D.J.; Dwivedi, Y.K.; Graham, G.; Foropon, C.; Papadopoulos, T. Dynamic digital capabilities and supply chain resilience: The role of government effectiveness. Int. J. Prod. Econ. 2023, 258, 108790. [Google Scholar] [CrossRef]
- Banerjee, C.S.; Farooq, A.; Upadhyaya, S. The relationship between dynamic capabilities, competitive advantage & organizational performance. Int. J. Interdiscip. Res. Innov. 2018, 6, 603–610. [Google Scholar]
- Uhl-Bien, M.; Arena, M. Leadership for organizational adaptability: A theoretical synthesis and integrative framework. Leadersh. Q. 2018, 29, 89–104. [Google Scholar] [CrossRef]
- van de Wetering, R.; Mikalef, P.; Dennehy, D. Artificial Intelligence Ambidexterity, Adaptive Transformation Capability, and Their Impact on Performance under Tumultuous Times; Conference on e-Business, e-Services and e-Society, 2022; Springer International Publishing: Cham, Switzerland, 2022; pp. 25–37. [Google Scholar]
- Wided, R. IT capabilities, strategic flexibility and organizational resilience in SMEs post-COVID-19: A mediating and moderating role of big data analytics capabilities. Glob. J. Flex. Syst. Manag. 2023, 24, 123–142. [Google Scholar] [CrossRef]
- Liang, L.; Li, Y. How does organizational resilience promote firm growth? The mediating role of strategic change and managerial myopia. J. Bus. Res. 2024, 177, 114636. [Google Scholar] [CrossRef]
- Duchek, S. Organizational resilience: A capability-based conceptualization. Bus. Res. 2020, 13, 215–246. [Google Scholar] [CrossRef]
- Browder, R.E.; Dwyer, S.M.; Koch, H. Upgrading adaptation: How digital transformation promotes organizational resilience. Strateg. Entrep. J. 2024, 18, 128–164. [Google Scholar] [CrossRef]
- Sondhi, S.S.; Salwan, P.; Behl, A.; Niranjan, S.; Hawkins, T. Evaluation of strategic orientation-led competitive advantage: The role of knowledge integration and service innovation. J. Knowl. Mana. 2024, 28, 1937–1962. [Google Scholar] [CrossRef]
- Drago, H.F.; de Moura, G.L.; Da Silva, L.S.C.V.; Da Veiga, C.P.; Kaczam, F.; Rita, L.P.S.; Da Silva, W.V. Reviewing the relationship between organizational performance, dynamic capabilities and strategic behavior. SN Bus. Econ. 2022, 3, 5. [Google Scholar] [CrossRef] [PubMed]
- Cavallo, A.; Sanasi, S.; Ghezzi, A.; Rangone, A. Competitive intelligence and strategy formulation: Connecting the dots. Compet. Rev. An. Int. Bus. J. 2021, 31, 250–275. [Google Scholar] [CrossRef]
- Hsiao, M. Resource integration and firm performance through organizational capabilities for digital transformation. Digit. Transform. Soc. 2024; ahead-of-print. [Google Scholar]
- Cahyani, E.; Agusria, L. Integration of Strategy Human Resource Management (SHRM) and Competitive Advantage as a Human Capital Mediator in the Performance of Private Universities. Int. J. Bus. Manag. Econ. 2023, 4, 56–72. [Google Scholar] [CrossRef]
- Wang, J.; Chen, R.; Zhang, S. The mediating and moderating effect of organizational resilience on competitive advantage: Evidence from Chinese companies. Sustainability 2022, 14, 13797. [Google Scholar] [CrossRef]
- He, Z.; Huang, H.; Choi, H.; Bilgihan, A. Building organizational resilience with digital transformation. J. Serv. Manag. 2023, 34, 147–171. [Google Scholar] [CrossRef]
- Sarwar, Z.; Gao, J.; Khan, A. Nexus of digital platforms, innovation capability, and strategic alignment to enhance innovation performance in the Asia Pacific region: A dynamic capability perspective. Asia Pac. J. Manag. 2024, 41, 867–901. [Google Scholar] [CrossRef]
- Gao, Y.; Yang, X.; Li, S. Government supports, digital capability, and organizational resilience capacity during COVID-19: The moderation role of organizational unlearning. Sustainability 2022, 14, 9520. [Google Scholar] [CrossRef]
- Zhang, J.; Long, J.; Von Schaewen, A.M.E. How does digital transformation improve organizational resilience?—Findings from PLS-SEM and fsQCA. Sustainability 2021, 13, 11487. [Google Scholar] [CrossRef]
- Li, D.; Liu, J. Dynamic capabilities, environmental dynamism, and competitive advantage: Evidence from China. J. Bus. Res. 2014, 67, 2793–2799. [Google Scholar] [CrossRef]
- Kurtz, D.J.; Varvakis, G. Dynamic capabilities and organizational resilience in turbulent environments. In Competitive Strategies for Small and Medium Enterprises; Springer International Publishing AG: Cham, Switzerland, 2016; pp. 19–37. [Google Scholar]
- Kyrdoda, Y.; Balzano, M.; Marzi, G. Learn to survive crises: The role of firm resilience, innovation capabilities and environmental dynamism. Technol. Soc. 2023, 74, 102285. [Google Scholar] [CrossRef]
- Wang, X.; Sun, J.; Tian, L.; Guo, W.; Gu, T. Environmental dynamism and cooperative innovation: The moderating role of state ownership and institutional development. J. Technol. Transf. 2021, 46, 1344–1375. [Google Scholar] [CrossRef]
- Krieglstein, F.; Beege, M.; Rey, G.D.; Ginns, P.; Krell, M.; Schneider, S. A Systematic Meta-analysis of the Reliability and Validity of Subjective Cognitive Load Questionnaires in Experimental Multimedia Learning Research. Educ. Psychol. Rev. 2022, 34, 2485–2541. [Google Scholar] [CrossRef]
- Wu, W.; Huang, X.; Li, X. Technology moral sense: Development, reliability, and validity of the TMS scale in Chinese version. Front. Psychol. 2023, 14, 1056569. [Google Scholar] [CrossRef] [PubMed]
Figure 1.
The theoretical model.
Table 1.
Test of the direct effect of organizational resilience on sustainable competitive advantage.
Table 1.
Test of the direct effect of organizational resilience on sustainable competitive advantage.
| Variable | Sustainable Competitive Advantage | ||||||
|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | ||
| Control variable | Establishment time | −0.069 | −0.061 | −0.061 | −0.065 | −0.067 | −0.060 |
| Enterprise property | 0.026 | 0.021 | 0.011 | 0.029 | 0.024 | 0.016 | |
| Enterprise scale | 0.008 | 0.020 | −0.014 | 0.014 | 0.033 | 0.012 | |
| Industry type | −0.032 | −0.028 | −0.040 | −0.017 | −0.040 | −0.035 | |
| Independent variable | Organizational resilience | 0.518 *** | |||||
| Situational awareness | 0.442 *** | 0.303 *** | |||||
| Predictive capacity | 0.271 *** | 0.138 ** | |||||
| Adaptability | 0.422 *** | 0.269 *** | |||||
| R2 | 0.006 | 0.275 | 0.201 | 0.080 | 0.184 | 0.290 | |
| △R2 | 0.006 | 0.268 | 0.195 | 0.073 | 0.178 | 0.284 | |
| F value | 0.615 | 28.789 *** | 19.115 *** | 6.565 *** | 17.143 *** | 22.075 *** | |
**: p < 0.01; ***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 2.
Regression analysis of organizational resilience on strategic capability.
| Variable | Strategic Capability | Strategic Formulation Capability | Resource Integration Capability | |
|---|---|---|---|---|
| Model 7 | Model 8 | Model 9 | ||
| Control variable | Establishment time | −0.026 | −0.124 | 0.040 |
| Enterprise property | 0.015 | 0.025 | 0.004 | |
| Enterprise scale | 0.013 | 0.056 | −0.017 | |
| Industry type | −0.019 | −0.035 | −0.004 | |
| Independent variable | Organizational resilience | 0.476 *** | 0.541 *** | 0.304 *** |
| R2 | 0.228 | 0.311 | 0.093 | |
| △R2 | 0.226 | 0.293 | 0.092 | |
| F value | 22.440 *** | 34.305 *** | 7.834 *** | |
***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 3.
Regression analysis of strategic capability on sustainable competitive advantage.
| Variable | Sustainable Competitive Advantage | |||
|---|---|---|---|---|
| Model 10 | Model 11 | Model 12 | ||
| Control variable | Establishment time | −0.053 | −0.001 | −0.081 |
| Enterprise property | 0.017 | 0.010 | 0.023 | |
| Enterprise scale | 0.007 | −0.015 | 0.016 | |
| Industry type | −0.021 | −0.012 | −0.030 | |
| Independent variable | Strategic capability | 0.475 *** | ||
| Strategic formulation capability | 0.516 *** | |||
| Resource integration capability | 0.323 *** | |||
| R2 | 0.231 | 0.267 | 0.111 | |
| △R2 | 0.225 | 0.261 | 0.104 | |
| F value | 22.892 *** | 27.753 *** | 9.453 *** | |
***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 4.
Test results of the mediating effect of strategic capability.
| Variable | Sustainable Competitive Advantage | |||
|---|---|---|---|---|
| Model 13 | Model 14 | Model 15 | ||
| Control variable | Establishment time | −0.053 | −0.020 | −0.068 |
| Enterprise property | 0.016 | 0.013 | 0.020 | |
| Enterprise scale | 0.016 | 0.001 | 0.023 | |
| Industry type | −0.022 | −0.016 | −0.027 | |
| Independent variable | Organizational resilience | 0.378 *** | 0.341 *** | 0.463 *** |
| Mediating variable | Strategic capability | 0.295 *** | ||
| Strategic formulation capability | 0.328 *** | |||
| Resource integration capability | 0.182 *** | |||
| R2 | 0.342 | 0.349 | 0.305 | |
| △R2 | 0.067 | 0.074 | 0.030 | |
| F value | 32.819 *** | 33.846 *** | 27.708 *** | |
***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 5.
The moderating effect of network digital atmosphere on organizational resilience and strategic capability.
Table 5.
The moderating effect of network digital atmosphere on organizational resilience and strategic capability.
| Variable | Strategic Capability | Strategic Formulation Capability | Resource Integration Capability | ||||
|---|---|---|---|---|---|---|---|
| Model 16 | Model 17 | Model 18 | Model 19 | Model 20 | Model 21 | ||
| Control variable | Establishment time | −0.003 | 0.001 | −0.104 | −0.102 | 0.058 | 0.062 |
| Enterprise property | 0.015 | 0.026 | 0.025 | 0.030 | 0.005 | 0.017 | |
| Enterprise scale | 0.009 | 0.012 | 0.053 | 0.054 | −0.020 | −0.016 | |
| Industry type | −0.007 | −0.011 | −0.025 | −0.027 | 0.005 | 0.001 | |
| Independent variable | Organizational resilience | 0.422 *** | 0.402 *** | 0.494 *** | 0.485 *** | 0.261 *** | 0.241 *** |
| Moderating variables | Network digital atmosphere | 0.246 *** | 0.244 *** | 0.218 *** | 0.217 *** | 0.194 *** | 0.192 *** |
| Product term | Organizational resilience × Network digital atmosphere | 0.136 ** | 0.061 | 0.143 ** | |||
| R2 | 0.285 | 0.303 | 0.356 | 0.359 | 0.129 | 0.149 | |
| △R2 | 0.057 | 0.018 | 0.045 | 0.004 | 0.036 | 0.020 | |
| F value | 25.173 *** | 23.455 *** | 34.899 *** | 30.300 *** | 9.353 *** | 9.444 *** | |
**: p < 0.01; ***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 6.
The moderating effect of environmental dynamism on organizational resilience and strategic capability.
Table 6.
The moderating effect of environmental dynamism on organizational resilience and strategic capability.
| Variable | Strategic Capability | Strategic Formulation Capability | Resource Integration Capability | ||||
|---|---|---|---|---|---|---|---|
| Model 22 | Model 23 | Model 24 | Model 25 | Model 26 | Model 27 | ||
| Control variable | Establishment time | −0.020 | −0.007 | −0.120 | −0.111 | 0.046 | 0.058 |
| Enterprise property | 0.018 | 0.034 | 0.027 | 0.038 | 0.007 | 0.022 | |
| Enterprise scale | 0.011 | 0.010 | 0.055 | 0.054 | −0.018 | −0.019 | |
| Industry type | −0.033 | −0.028 | −0.045 | −0.042 | −0.016 | −0.012 | |
| Independent variable | Organizational resilience | 0.422 *** | 0.359 *** | 0.503 *** | 0.459 *** | 0.255 *** | 0.198 *** |
| Moderating variables | Environmental dynamism | 0.164 ** | 0.175 *** | 0.116 ** | 0.123 ** | 0.148 ** | 0.157 ** |
| Product term | Organizational resilience × Environmental dynamism | 0.295 *** | 0.205 *** | 0.267 *** | |||
| R2 | 0.252 | 0.335 | 0.323 | 0.363 | 0.113 | 0.181 | |
| △R2 | 0.024 | 0.083 | 0.012 | 0.040 | 0.019 | 0.068 | |
| F value | 21.257 *** | 27.181 *** | 30.120 *** | 30.791 *** | 8.022 *** | 11.901 *** | |
**: p < 0.01; ***: p < 0.001; the regression coefficients are all standardized coefficient values.
Table 7.
Summary of hypothesis testing.
| Hypothesis | Result | Hypothesis | Result |
|---|---|---|---|
| H1 | Valid | H4 | Valid |
| H1a | Valid | H4a | Valid |
| H1b | Valid | H4b | Valid |
| H1c | Valid | H5 | Valid |
| H2 | Valid | H5a | Invalid |
| H2a | Valid | H5b | Valid |
| H2b | Valid | H6 | Valid |
| H3 | Valid | H6a | Valid |
| H3a | Valid | H6b | Valid |
| H3b | Valid |
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Liu, X.; Zhang, D. Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises. Sustainability 2024, 16, 6954. https://doi.org/10.3390/su16166954
AMA Style
Liu X, Zhang D. Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises. Sustainability. 2024; 16(16):6954. https://doi.org/10.3390/su16166954
Chicago/Turabian StyleLiu, Xi, and Dan Zhang. 2024. "Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises" Sustainability 16, no. 16: 6954. https://doi.org/10.3390/su16166954
APA StyleLiu, X., & Zhang, D. (2024). Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises. Sustainability, 16(16), 6954. https://doi.org/10.3390/su16166954
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