Market Intelligence Adoption and Supply Chain Efficiency in the E-Commerce Industry

作者

  • Liu Tang Lyceum of the Philippines University - Batangas ##default.groups.name.author##
  • Marc Joseph Ian Generoso Lyceum of the Philippines University - Batangas ##default.groups.name.author##

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https://doi.org/10.65166/8y5xw056

关键词:

market intelligence adoption, supply chain efficiency, e-commerce strategy, predictive analytics, logistics management, inventory management

摘要

This study examined the relationship between market intelligence adoption and supply chain efficiency in the e-commerce industry, focusing on selected e-commerce companies in Sichuan Province, China. Market intelligence adoption was assessed in terms of competitor monitoring, predictive analytics, and market environment scanning, while supply chain efficiency was evaluated through inventory management, transportation and logistics, and warehousing and distribution. Using a descriptive research design, data were gathered through a structured questionnaire administered to employees of e-commerce firms. The instrument demonstrated excellent internal consistency, with Cronbach’s alpha values ranging from 0.924 to 0.943 across the study variables. Data were analyzed using weighted mean, rank, Shapiro-Wilk test, and Spearman rho correlation. Findings showed that respondents strongly agreed that market intelligence adoption was highly practiced, with market environment receiving the highest assessment, followed by predictive analytics and competitor monitoring. Respondents also strongly agreed that supply chain efficiency was high, with transportation and logistics ranking first, followed by warehousing and distribution and inventory management. Correlation results indicated statistically significant positive relationships between the dimensions of market intelligence adoption and supply chain efficiency. The findings suggest that e-commerce firms that systematically use market intelligence are better positioned to improve operational responsiveness, optimize logistics and inventory practices, and strengthen supply chain performance. The study offers managerial implications for integrating market intelligence into strategic and operational decision-making in e-commerce firms.

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参考

Abualigah, L., Hanandeh, E. S., Zitar, R. A., Thanh, C. L., Khatir, S., & Gandomi, A. H. (2023). Revolutionizing sustainable supply chain management: A review of metaheuristics. Engineering Applications of Artificial Intelligence, 126, Article 106839. https://doi.org/10.1016/j.engappai.2023.106839

Álvarez-Rodríguez, C., Martín-Gamboa, M., & Iribarren, D. (2020). Sustainability-oriented efficiency of retail supply chains: A combination of life cycle assessment and dynamic network data envelopment analysis. Science of the Total Environment, 705, Article 135977. https://doi.org/10.1016/j.scitotenv.2019.135977

Atento, A. G., & Atento, R. G. (2025). A case study of Mercury Drug Corporation: Strategic adaptation to universal healthcare and digital disruption in the Philippines. International Journal of Health & Business Analytics, 1(1). https://doi.org/10.65166/zhw7dd39

Atento, A. G. B., & Atento, R. G. O. (2026). Legacy retail under digital disruption: Strategic insights from National Book Store's omnichannel transition in the Philippines. Journal of Enterprise Strategy & Management Innovation, 1(1). https://doi.org/10.65166/nny9z718

Atento, R. G., & Espelita, C. A. M. H. (2025). From community voice to marketing strategy: The feeder-school ecosystem as basis for a consumer-centered marketing framework. International Journal of Health and Business Analytics, 1(2). https://doi.org/10.65166/mt4em434

Atento, R. G., Quinto, L., Espelita, C. A. M., & Castaneda, C. (2025). Integrating business and health analytics: A conceptual framework for dual outcomes in healthcare. International Journal of Health & Business Analytics, 1(1). https://doi.org/10.65166/04pdc866

Banerjee, A. (2019). Blockchain with IoT: Applications and use cases for a new paradigm of supply chain driving efficiency and cost. Advances in Computers, 115, 259-292. https://doi.org/10.1016/bs.adcom.2019.07.007

Bendal, A., Sabasa, S. A., Espelita, C. A. M. H., & Atento, R. G. O. (2026). Artificial intelligence as disruptive technology in accounting: A qualitative study of practitioner perceptions on automation, judgment, and decision support. Journal of Enterprise Strategy & Management Innovation, 1(1). https://doi.org/10.65166/0sdayg70

Carandang, D., Baran, B., Espelita, C. A. M. H., Atento, A. G. B., & Atento, R. G. O. (2026). Perceptions of accounting software among SMEs in Calamba City, Philippines: A Technology-Organization-Environment (TOE) framework. Journal of Enterprise Strategy & Management Innovation, 1(1). https://doi.org/10.65166/dxqbny15

Cuellar, S., Grisales, S., & Castaneda, D. I. (2023). Constructing tomorrow: A multifaceted exploration of Industry 4.0 scientific, patents, and market trend. Automation in Construction, 156, Article 105113. https://doi.org/10.1016/j.autcon.2023.105113

Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961-974. https://doi.org/10.1016/j.jbusres.2020.08.024

Falahat, M., Ramayah, T., Soto-Acosta, P., & Lee, Y. Y. (2020). SMEs internationalization: The role of product innovation, market intelligence, pricing and marketing communication capabilities as drivers of SMEs’ international performance. Technological Forecasting and Social Change, 152, Article 119908. https://doi.org/10.1016/j.techfore.2020.119908

Haon, C., Gotteland, D., & Nelson, R. (2023). Creating a market orientation: An empirical validation of Gebhardt, Carpenter, and Sherry’s (2006) Market Orientation Development Process (MODeP). Journal of Business Research, 168, Article 114232. https://doi.org/10.1016/j.jbusres.2023.114232

Hernández-Cruz, X., Villalobos, J. R., Runger, G., & Neal, G. (2023). Building an intelligent system to identify trends in agricultural markets. Journal of Cleaner Production, 425, Article 138956. https://doi.org/10.1016/j.jclepro.2023.138956

Hong, L. J., Li, J., Wu, X., & Yi, S. (2023). Future research of supply chain resilience: Network perspectives and incorporation of more stakeholders. Fundamental Research. Advance online publication. https://doi.org/10.1016/j.fmre.2023.07.012

Lorentz, H., Aminoff, A., Kaipia, R., Pihlajamaa, M., Ehtamo, J., & Tanskanen, K. (2020). Acquisition of supply market intelligence: An information processing perspective. Journal of Purchasing and Supply Management, 26(5), Article 100649. https://doi.org/10.1016/j.pursup.2020.100649

Lu, L., Marín-Solano, J., & Navas, J. (2019). An analysis of efficiency of time-consistent coordination mechanisms in a model of supply chain management. European Journal of Operational Research, 279(1), 211-224. https://doi.org/10.1016/j.ejor.2019.05.031

Monostori, J. (2021). Mitigation of the ripple effect in supply chains: Balancing the aspects of robustness, complexity and efficiency. CIRP Journal of Manufacturing Science and Technology, 32, 370-381. https://doi.org/10.1016/j.cirpj.2021.01.013

Singh, G., Singh, S., Daultani, Y., & Chouhan, M. (2023). Measuring the influence of digital twins on the sustainability of manufacturing supply chain: A mediating role of supply chain resilience and performance. Computers & Industrial Engineering, 186, Article 109711. https://doi.org/10.1016/j.cie.2023.109711

Wu, C., Xu, C., Zhao, Q., & Zhu, J. (2023). Research on financing strategy under the integration of green supply chain and blockchain technology. Computers & Industrial Engineering, 184, Article 109598. https://doi.org/10.1016/j.cie.2023.109598

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已出版

2026-05-28