Analysis of Competitive Intelligence in Retail Management in The Jordanian Market from the Consumer’s Perspective


  • Khaled Khalaf Alafi The World Islamic Sciences and Education University
  • Bader Ismaeel The World Islamic Sciences & Education University
  • Mohammad Nassar Almarshad Department of Administrative Sciences, Al-Huson University college, Al-Balqa Applied University, Jordan
  • Majdi Azzam Al-habash Department of Financial and Administration, Balqa Applied University, Amman, Jordan
  • Rowaida Al-Aqrabawi Al-Ahliyya Amman University, 19328, Amman, Jordan



Competitive Intelligence, Jordanian Retail Management, Market Performance, PLS-SEM


Using a consumer-centered approach, this study investigates the dynamics of competitive intelligence (CI) in Jordanian retail management. The goal of the study is to determine how various aspects of competitive intelligence relate to market performance in the Jordanian retail industry. A total of 334 participants make up the study's sample size; they were carefully chosen using stratified random sampling to minimise bias and guarantee a thorough representation of the various retail segments. The Partial Least Squares Structural Equation Modelling (PLS-SEM) method is used in the study to fully explore the connections between the intelligence and store performance factors. The findings highlight a number of significant relationships. The market performance of Jordanian retailers is positively correlated with competitors' intelligence, consumer intelligence, market intelligence, technological intelligence, and the intelligence of strategic alliances. These findings highlight the central role of understanding competitive strategies, consumer behaviour, market trends, strategic alliances, and technological advancements in market success. In contrast, the study finds an insignificant positive relationship between social intelligence and market performance in Jordanian retailing. This suggests that while social intelligence is important, its direct impact on immediate market performance in this specific environment may be limited. Generally, this study provides valuable insights into the intricate interplay between intelligence factors and market performance in Jordanian retailing from the consumer’s perspective. The implications of these findings are significant for retail practitioners, as they urge strategic focus on competitor analysis, consumer-centric approaches, technology adoption, and strategic collaborations to improve market competitiveness and performance. The study not only contributes to the academic discourse but also provides actionable insights for retail management strategies in the dynamic and competitive Jordanian market. Keywords: Competitive Intelligence, Jordanian Retail Management, Market Performance, PLS-SEM

Author Biography

Bader Ismaeel, The World Islamic Sciences & Education University



Ain, N., Vaia, G., DeLone, W. H., & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success–A systematic literature review. Decision Support Systems, 125, 113113.

Alfawaire, F., & Atan, T. (2021). The effect of strategic human resource and knowledge management on sustainable competitive advantages at Jordanian universities: The mediating role of organizational innovation. Sustainability, 13(15), 8445.

Alghamdi, M. I. (2020). Assessing factors affecting intention to adopt AI and ML: The case of the Jordanian retail industry. Periodicals of Engineering and Natural Sciences, 8(4), 2516-2524.

Ali, B. J., & Anwar, G. (2021). Measuring competitive intelligence Network and its role on Business Performance. International Journal of English Literature and Social Sciences, 6(2).

Al-Okaily, A., Al-Okaily, M., Teoh, A. P., & Al-Debei, M. M. (2022). An empirical study on data warehouse systems effectiveness: the case of Jordanian banks in the business intelligence era. EuroMed Journal of Business.

Atkinson, P., Hizaji, M., Nazarian, A., & Abasi, A. (2022). Attaining organisational agility through competitive intelligence: the roles of strategic flexibility and organisational innovation. Total Quality Management & Business Excellence, 33(3-4), 297-317.

Caronni, A., Ramella, M., Arcuri, P., Salatino, C., Pigini, L., Saruggia, M., ... & Converti, R. M. (2023). The Rasch Analysis Shows Poor Construct Validity and Low Reliability of the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0) Questionnaire. International Journal of Environmental Research and Public Health, 20(2), 1036.

Cavallo, A., Sanasi, S., Ghezzi, A., & Rangone, A. (2021). Competitive intelligence and strategy formulation: connecting the dots‏. Competitiveness Review: An International Business Journal, 31(2), 250-275.

Cekuls, A. (2015). Leadership Values in Transformation of Organizational Culture to Implement Competitive Intelligence Management: the Trust Building Through Organizational Culture‏. European Integration Studies, 9(1), 244-256.

Cekuls, A. (2010). COMPETITIVE INTELLIGENCE MODEL IN LATVIAN ENTERPRISES‏. Bridges/Tiltai, 53(4), 35-44.

Chen, S., Ding, Y., & Liu, X. (2023). Development of the growth mindset scale: Evidence of structural validity, measurement model, direct and indirect effects in Chinese samples. Current Psychology, 42(3), 1712-1726.

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2023). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 1-39.

Dos Santos, P. M., & Cirillo, M. Â. (2023). Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions. Communications in Statistics-Simulation and Computation, 52(4), 1639-1650.

Hassani, A., & Mosconi, E. (2022). Social media analytics, competitive intelligence, and dynamic capabilities in manufacturing SMEs. Technological Forecasting and Social Change, 175, 121416.

Jafar, M. (2020). The impact of competitive intelligence (CI) management on the competitiveness and performance of retail companies in Indonesia. Journal of Social Science Advanced Research, 1(2), 138-159.

Jaradat, Z., Al-Dmour, A., Alshurafat, H., Al-Hazaima, H., & Al Shbail, M. O. (2022). Factors influencing business intelligence adoption: evidence from Jordan. Journal of Decision Systems, 1-21.

Köseoglu, M. A., Yick, M. Y. Y., & Okumus, F. (2021). Coopetition strategies for competitive intelligence practices-evidence from full-service hotels. International Journal of Hospitality Management, 99, 103049.

Kurdi, B., Alshurideh, M., Akour, I., Alzoubi, H., Obeidat, B., & Alhamad, A. (2022). The role of digital marketing channels on consumer buying decisions through eWOM in the Jordanian markets. International Journal of Data and Network Science, 6(4), 1175-1186.

Kyriazos, T., & Poga, M. (2023). Dealing with Multicollinearity in Factor Analysis: The Problem, Detections, and Solutions. Open Journal of Statistics, 13(3), 404-424.

Madureira, L., Popovič, A., & Castelli, M. (2023). Competitive intelligence empirical validation and application: Foundations for knowledge advancement and relevance to practice. Journal of Information Science, 01655515231191221.

Maluleka, M. L., & Chummun, B. Z. (2023). Competitive intelligence and strategy implementation: Critical examination of present literature review. South African Journal of Information Management, 25(1), 1610.

Mariani, M. M., & Wamba, S. F. (2020). Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies. Journal of Business Research, 121, 338-352.

Paap, M. C., Pedersen, G., Kvarstein, E., & Hummelen, B. (2023). Evaluating the construct validity of the Norwegian version of the level of personality functioning scale–brief form 2.0 in a large clinical sample. Journal of Personality Assessment, 1-11.

Ram, J., & Zhang, C. (2021). Examining the role of social media analytics in providing competitive intelligence: The impacts and limitations. Journal of Global Information Management (JGIM), 29(6), 1-18.

Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231.

Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231.

Shiekh, H. H. (2023). In-Store Environment and Impulsive Buying: Development and Validation of Measurement Scale. IUP Journal of Marketing Management, 22(3).

Sureshchandar, G. S. (2023). Quality 4.0–a measurement model using the confirmatory factor analysis (CFA) approach. International Journal of Quality & Reliability Management, 40(1), 280-303.

Tahmasebifard, H. (2018). The role of competitive intelligence and its sub-types on achieving market performance. Cogent Business & Management, 5(1), 1540073.

Van der Pol, J. (2021). Collaboration network analysis for competitive intelligence. Journal of Intelligence Studies in Business, 11(3).

Welhaf, M. S., Meier, M. E., Smeekens, B. A., Silvia, P. J., Kwapil, T. R., & Kane, M. J. (2023). A “Goldilocks zone” for mind-wandering reports? A secondary data analysis of how few thought probes are enough for reliable and valid measurement. Behavior Research Methods, 55(1), 327-347.

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.