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Assessing the role of competitive intelligence and practices of dynamic capabilities in business accommodation of SMEs

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  • Wu, Qihan
  • Yan, Dong
  • Umair, Muhammad

Abstract

Dynamic capability is an emerging topic for organizations confronting a chaotic environment. Previous research has emphasized that organizations with low dynamic capacities boost performance suffers from several survival issues. This paper discusses how small and medium-sized enterprises (SMEs) may strengthen their dynamic capabilities using metrics and knowledge management procedures encompassing information planning, collecting, analyzing, and distributing. Specifically, this research explores the influence of social media analytics on four stages of competitive intelligence to strengthen the dynamic capacities inside manufacturing enterprises. Social media analytics is better utilized in some major corporations but less accepted in small and medium enterprises. However, little empirical research has applied the dynamic capabilities method and studied the causal linkages between social media monitoring and data-driven business processes. A survey was undertaken among 150 manufacturing small and medium enterprises in Shanghai to understand this connection better. Consequently, a closed-structured questionnaire was issued to the small and medium enterprises’ chief executive officers and management. The data gathered was examined using structural equation modeling. Our study results suggest that social media analytics favorably influences four stages of competitive intelligence, notably the phases of collecting and analysis.

Suggested Citation

  • Wu, Qihan & Yan, Dong & Umair, Muhammad, 2023. "Assessing the role of competitive intelligence and practices of dynamic capabilities in business accommodation of SMEs," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 1103-1114.
    • Handle: RePEc:eee:ecanpo:v:77:y:2023:i:c:p:1103-1114
    DOI: 10.1016/j.eap.2022.11.024
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    2. Huimin Zhang & Meng Li & Wen Chen, 2023. "Assessing Competitiveness in New Energy Vehicle Enterprises: A Group Decision Model with Interval Multiplicative Preference Relations," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
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