Keywords
Enabling infrastructure
Intelligence cycle
Intelligence governance
Psychological adaptability
Organizational performance
Chinese manufacturing
How to Cite
Abstract
Purpose: This study examines whether competitive-intelligence enabling infrastructure (CIEI) is associated with a cognitive-horizon proxy of psychological adaptability and subsequent organizational performance in Chinese manufacturing firms. It addresses the distinction between digital and analytical infrastructure and a complete competitive-intelligence system comprising intelligence planning, collection, analysis, dissemination, utilization, feedback, ethics, and governance.
Methodology/Approach: The study analyzes 19,035 firm-year observations from 3,169 listed Chinese manufacturing firms during 2014–2023. CIEI is modeled as a formative archival index comprising big-data capability, digital-intelligence investment, and analytical capability. Low managerial myopia is used as a limited cognitive-horizon proxy of psychological adaptability, while organizational performance combines Tobin’s Q, gross profitability, and asset turnover. The analytical hierarchy includes descriptive diffusion analysis, pooled models, firm and year fixed effects, one-year-lagged specifications, component-level and principal-component composition analyses, a 1,000-replication firm-cluster bootstrap, and dynamic-panel GMM. China’s 2024 World Bank Enterprise Survey is used only as a separate contextual source because consistently defined 2024–2025 firm-level observations are unavailable for the primary panel.
Originality/Relevance: The study does not equate digital infrastructure with competitive intelligence. Instead, it identifies an empirically observable enabling layer while explicitly separating it from unmeasured intelligence-cycle processes, including governance, dissemination, utilization, feedback, and accountable decision use. This distinction provides a more defensible basis for using archival corporate data in competitive-intelligence research.
Key Findings: CIEI diffused substantially across the observed firms; 76.3% of the 772 firms in the ten-year balanced cohort moved to a higher infrastructure quartile. Prior-year CIEI was positively associated with subsequent organizational performance (b = 0.054, p = .019), while low managerial myopia showed a smaller positive association (b = 0.016, p = .048). Prior CIEI was not significantly associated with the adaptability proxy, and the cluster-bootstrap indirect-effect interval included zero. Component-level estimates were heterogeneous, and GMM results varied with instrument classification; consequently, the findings do not establish causality or validate a complete competitive-intelligence system.
Theoretical/Methodological Contributions: The study reconnects archival analytics research with classical competitive-intelligence process, maturity, governance, and decision-use perspectives. Methodologically, it establishes explicit construct boundaries, treats CIEI as a formative enabling index rather than a reflective CI scale, separates primary from sensitivity specifications, and combines temporal ordering, firm fixed effects, clustered inference, bootstrap analysis, and dynamic-panel diagnostics. The results show that analytical infrastructure can be monitored through public data, but its conversion into competitive intelligence requires organizational processes that cannot be inferred from technology indicators alone.
References
Agazu, B. G., Kero, C. A., & Debela, K. L. (2025). Transformational leadership and firm performance: A systematic literature review. Journal of Innovation and Entrepreneurship, 14, 29. https://doi.org/10.1186/s13731-025-00476-x
Ali, M., Jabri, A., Shaloh, S., Shakhoor, N., Yacine, M., & Yousef, B. (2024). The impact of dynamic capabilities on enterprise agility: The intervening roles of digital transformation and IT alignment. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), 100266. https://doi.org/10.1016/j.joitmc.2024.100266
Alkandi, I. G., & Helmi, M. A. (2024). The impact of strategic agility on organizational performance: The mediating role of market orientation and innovation capabilities in emerging industrial sector. Cogent Business & Management, 11(1), 2396528. https://doi.org/10.1080/23311975.2024.2396528
Atanassova, I., Bednar, P., Khan, H., & Khan, Z. (2025). Managing the VUCA environment: The dynamic role of organizational learning and strategic agility in B2B versus B2C firms. Industrial Marketing Management, 125, 12–28. https://doi.org/10.1016/j.indmarman.2024.12.008
Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, 103745. https://doi.org/10.1016/j.jfineco.2023.103745
Badghish, S., & Soomro, Y. A. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: Application of the technology–organization–environment framework. Sustainability, 16(5), 1864. https://doi.org/10.3390/su16051864
Barata, S. F. P. G., Ferreira, F. A. F., Carayannis, E. G., & Ferreira, J. J. M. (2023). Determinants of e-commerce, artificial intelligence, and agile methods in small- and medium-sized enterprises. IEEE Transactions on Engineering Management, 71, 6903–6917. https://doi.org/10.1109/TEM.2023.3269601
Beyari, H., & Hashem, T. (2025). The role of artificial intelligence in personalizing social media marketing strategies for enhanced customer experience. Behavioral Sciences, 15(5), 700. https://doi.org/10.3390/bs15050700
Carter, J. W., & Youssef-Morgan, C. (2022). Psychological capital development effectiveness of face-to-face, online, and micro-learning interventions. Education and Information Technologies, 27(5), 6553–6575. https://doi.org/10.1007/s10639-021-10824-5
Chatterjee, S., Chaudhuri, R., Vrontis, D., & Thrassou, A. (2023). Revisiting the resource-based view (RBV) theory: From cross-functional capabilities perspective in post COVID-19 period. Journal of Strategic Marketing, 33(6), 822–837. https://doi.org/10.1080/0965254X.2023.2182447
Chen, C. (2024). Influence of big data analytical capability on new product performance – the effects of collaboration capability and team collaboration in high-tech firms. Chinese Management Studies, 18(1), 1–23. https://doi.org/10.1108/CMS-02-2022-0053
Chen, N., & Yang, Y. (2023). The role of influencers in live streaming e-commerce: Influencer trust, attachment, and consumer purchase intention. Journal of Theoretical and Applied Electronic Commerce Research, 18(3), 1601–1618. https://doi.org/10.3390/jtaer18030081
Chen, Y., Li, J., & Zhang, J. (2024). Digitalisation, data-driven dynamic capabilities and responsible innovation: An empirical study of SMEs in China. Asia Pacific Journal of Management, 41(3), 1211–1251. https://doi.org/10.1007/s10490-022-09845-6
Cheng, H., & Chen, C. (2022). Evolution of competitive intelligence research in the big data era. Information Processing & Management, 58(1), 102564. https://doi.org/10.1016/j.ipm.2021.102564
Cheng, W., Li, C., & Zhao, T. (2024). The stages of enterprise digital transformation and its impact on internal control: Evidence from China. International Review of Financial Analysis, 92, 103079. https://doi.org/10.1016/j.irfa.2024.103079
De las Heras-Rosas, C. J., & Herrera, J. (2021). Innovation and competitive intelligence in business: A bibliometric analysis. International Journal of Financial Studies, 9(2), 31. https://doi.org/10.3390/ijfs9020031
Eng, I., Aboagye, E., Bergsten, E. L., & Strömberg, A. (2025). Balancing employee flexibility and organizational performance: Implications for innovation, productivity, and company attractiveness in SMEs. Frontiers in Psychology, 16, 1518284. https://doi.org/10.3389/fpsyg.2025.1518284
Haftor, D. M., Costa Climent, R., & Ribeiro-Navarrete, S. (2024). Firms’ use of predictive artificial intelligence for economic value creation and appropriation. International Journal of Information Management, 79, 102836. https://doi.org/10.1016/j.ijinfomgt.2024.102836
Hossain, M. A., Agnihotri, R., Islam Rushan, M. R., Rahman, M. S., & Sumi, S. F. (2022). Marketing analytics capability, artificial intelligence adoption, and firms’ competitive advantage: Evidence from the manufacturing industry. Industrial Marketing Management, 106, 240–255. https://doi.org/10.1016/j.indmarman.2022.08.017
Huang, B., Song, J., Xie, Y., Li, Y., & He, F. (2022). The effect of big data analytics capability on competitive performance: The mediating role of resource optimization and resource bricolage. Frontiers in Psychology, 13, 882810. https://doi.org/10.3389/fpsyg.2022.882810
Katsaros, K. K. (2024). Gen Z employee adaptive performance: The role of inclusive leadership and workplace happiness. Administrative Sciences, 14(8), 163. https://doi.org/10.3390/admsci14080163
Kim, S.-S., & Yoon, D.-Y. (2025). Impact of empowering leadership on adaptive performance in hybrid work: A serial mediation effect of knowledge sharing and employee agility. Frontiers in Psychology, 16, 1448820. https://doi.org/10.3389/fpsyg.2025.1448820
Li, Z., Shu, K., Cheng, M., & Nian, J. (2024). Exploring the nexus between international perspective, innovation resources, and entrepreneurial internationalization: A resource-based and behavioral perspective. Journal of the Knowledge Economy. Advance online publication. https://doi.org/10.1007/s13132-024-02012-w
Loghman, S., Quinn, M., Dawkins, S., Woods, M., Om Sharma, S., & Scott, J. (2023). A comprehensive meta-analyses of the nomological network of psychological capital (PsyCap). Journal of Leadership & Organizational Studies, 30(1), 108–128. https://doi.org/10.1177/15480518221107998
Ma, G., Wu, W., Liu, C., Ji, J., & Gao, X. (2024). Empathetic leadership and employees’ innovative behavior: Examining the roles of career adaptability and uncertainty avoidance. Frontiers in Psychology, 15, 1371936. https://doi.org/10.3389/fpsyg.2024.1371936
Mueller-Saegebrecht, S., & Walter, A.-T. (2025). Strategic agility—An urgent capability for successful business model innovation? A conceptual process model and theoretical framework. Strategic Change, 34(4), 407–428. https://doi.org/10.1002/jsc.2645
Pelletier, C., L’Écuyer, F., & Raymond, L. (2025). Building organizational agility through digital transformation: A configurational approach in SMEs. Industrial Management & Data Systems, 125(4), 1503–1529. https://doi.org/10.1108/IMDS-05-2024-0488
Su, X., Zeng, W., Zheng, M., Jiang, X., Lin, W., & Xu, A. (2021). Big data analytics capabilities and organizational performance: The mediating effect of dual innovations. European Journal of Innovation Management, 25(4), 1142–1160. https://doi.org/10.1108/EJIM-10-2020-0431
Sun, P., Yuan, C., Li, X., & Di, J. (2024). Big data analytics, firm risk and corporate policies: Evidence from China. Research in International Business and Finance, 70, 102371. https://doi.org/10.1016/j.ribaf.2024.102371
Tang, G., Abu Bakar, R., & Omar, S. (2024). Positive psychology and employee adaptive performance: A systematic literature review. Frontiers in Psychology, 15, 1417260. https://doi.org/10.3389/fpsyg.2024.1417260
Weichselbraun, A., Süsstrunk, N., Waldvogel, R., Glatzl, A., Braşoveanu, A. M. P., & Scharl, A. (2024). Anticipating job market demands—A deep learning approach to determining the future readiness of professional skills. Future Internet, 16(5), 144. https://doi.org/10.3390/fi16050144
Wu, Q., Yan, D., & Umair, M. (2023). Assessing the role of competitive intelligence and practices of dynamic capabilities in business accommodation of SMEs. Economic Analysis and Policy, 77, 1103–1114. https://doi.org/10.1016/j.eap.2022.11.024
Wu, S., & Luo, X. (2024). How does big data analytics capability affect firm performance? Unveiling the role of organisational resilience and environmental dynamism. European Journal of Information Systems. Advance online publication. https://doi.org/10.1080/0960085X.2024.2375262
Xu, Q., Hou, Z., Zhang, C., Cui, Y., & Hu, X. (2023). Influences of human, social, and psychological capital on career adaptability: Net and configuration effects. Current Psychology. https://doi.org/10.1007/s12144-023-04373-y
Zhang, J., & Li, H. (2022). The impact of big data management capabilities on the performance of manufacturing firms in Asian economy during COVID-19: The mediating role of organizational agility and moderating role of information technology capability. Frontiers in Psychology, 13, 833026. https://doi.org/10.3389/fpsyg.2022.833026
Zhao, S., Zhang, L., Peng, L., Zhou, H., & Hu, F. (2024). Enterprise pollution reduction through digital transformation? Evidence from Chinese manufacturing enterprises. Technology in Society, 77, 102520. https://doi.org/10.1016/j.techsoc.2024.102520
Zhuo, C., & Chen, J. (2023). Can digital transformation overcome the enterprise innovation dilemma: Effect, mechanism and effective boundary? Technological Forecasting and Social Change, 190, 122378. https://doi.org/10.1016/j.techfore.2023.122378