BUSINESS INTELLIGENCE ON SUPPLY CHAIN RESPONSIVENESS AND AGILE PERFORMANCE: EMPIRICAL EVIDENCE FROM MALAYSIAN LOGISTICS INDUSTRY

Authors

  • Kashveenjit Kaur Graduate School of Business, National University of Malaysia

DOI:

https://doi.org/10.47604/ijscm.1351

Keywords:

Business Intelligence, Agile Performance, Supply Chain Management, Business Performance, Third Party Logistics

Abstract

Purpose: This study examine how BIS implementation affects the agile efficiency of the supply chain with the logistics industry's supply chain responsiveness. As a variable for assessing the relationship and effect on agile efficiency, business intelligence competence (managerial competence, technological competence and cultural competence) and supply chain responsiveness will be investigated.

Methodology: A survey questionnaire comprised of 39 questions using the purposive method of sampling used to select the target group and replied to the survey with the outcome of a total of 50 respondents, via SPSS, the data was further analysed to examine the relationship between all variables.

Findings: The study finds that (1) business intelligence competence has a significant positive impact on the response to the supply chain, (2) business intelligence competence has a significant positive impact on the supply chain's agile performance, (3) responsiveness to the supply chain has a significant positive impact on agile performance.

Unique contribution to theory, practice and policy: This study contributes to enhancing the quality and effectiveness of the business operation of the 3PL service provider, government customs and port department.

Downloads

Download data is not yet available.

References

Acharya, B. (2010). Questionnaire Design. https://doi.org/10.2307/2965735

Adams, J., Khan, H. T. A., Raeside, R., & White, D. (2007). Regression. In Research Methods for Graduate Business and Social Science Students (pp. 198-200). SAGE Publications Ltd.

Al-hawajreh, K. M., & Attiany, M. S. (2014). The Effect of Supply Chain Responsiveness on Competitive Advantage : A Field Study of Manufacturing Companies in Jordan. European Journal of Business and Management, 6(13), 151-163.

Alzoubi, H. M., Alnazer, N. N., & Alzoubi, A. A. (2016). Exploring the Impact of the use of Business Information systems BIS on the organizational performance effectiveness in banks in Jordan. International Journal of Business and Management Invention, 5(3), 48-55.

Azhar, K. (2015). Malaysia as Asean's logistics hub? The Edge Markets. Retrieved from https://www.theedgemarkets.com/article/malaysia-asean's-logistics-hub

Bach, M. P., ÄŒeljo, A., & Zoroja, J. (2016). Technology Acceptance Model for Business Intelligence Systems : Preliminary Research. In Procedia Computer Science (pp. 995-1001). https://doi.org/10.1016/j.procs.2016.09.270

Banister, D. (2016). Transport planning. In Handbook of Transport Systems and Traffic Control, 9-19.

Barhmi, A. (2019). Agility and Responsiveness Capabilities: Impact on Supply Chain Performance. European Scientific Journal, 15(7), 212-224. https://doi.org/10.19044/esj.2019.v15n7p212

Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139-1160. https://doi.org/10.1177/0018726708094863

Beglar, D., & Nemoto, T. (2014). Developing Likert-scale questionnaires. In JALT2013 Conference Proceedings (pp. 1-8).

Bilandžić, M., & Lucić, D. (2014). Predicting Business Opportunities and/or Threats - Business Intelligence in the Service of Corporate Security (Empirical Analysis of the Usage in the Economy of Republic of Croatia). Collegium Antropologicum, 38, 25-33.

Boehm, B., & Turner, R. (2004). Balancing agility and discipline: Evaluating and integrating agile and plan-driven methods. In 26th International Conference on Software Engineering (pp. 718-719). https://doi.org/10.1109/icse.2004.1317503

Britta, G., & Larson, P. D. (2001). Logistics skills and competencies for supply chain management. Journal of Business Logistics, 22(2), 27-50.

Brown, J. D. (2002). The Cronbach alpha reliability estimate. Shiken: JALT Testing & Evaluation SIG Newsletter, 6(1), 17-18.

Burns, R. B., & Burns, R. A. (2008). Sampling Issues. In Business Research Methods and Statistics Using SPSS (pp. 180-206). SAGE Publications Ltd.

Canelas, J. A. F., Martin, Q. M., & Rodriguez, J. M. C. (2013). Argumentative SOX compliant and intelligent decision support systems for the suppliers contracting process. Applied Computational Intelligence and Soft Computing, 2013. https://doi.org/10.1007/978-3-319-17906-3_14

Charness, N., & Boot, W. R. (2016). Technology, Gaming, and Social Networking. Handbook of the Psychology of Aging. Academic Press. https://doi.org/10.1016/B978-0-12-411469-2.00020-0

Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data To Big Impact. MIS Quarterly, 36(4), 1165-1188. https://doi.org/10.1016/S0140-6736(09)61833-X

Choy, L. T. (2014). The Strengths and Weaknesses of Research Methodology: Comparison and Complimentary between Qualitative and Quantitative Approaches. IOSR Journal of Humanities and Social Science, 19(4), 99-104. https://doi.org/10.9790/0837-194399104

Christopher, M. (2000). The Agile Supply Chain Competing in Volatile Markets. Industrial Marketing Management 29, 29(1), 37-44.

Christopher, M., & Towill, D. (2001). An integrated model for the design of agile supply chains. International Journal of Physical Distribution & Logistics Management, 31(4), 235-246. https://doi.org/10.1108/09600030110394914

Chua, C. L. (2006). Sample Size Estimation Using Krejcie And Morgan And Cohen Statistical Power Analysis: A Comparison. Jurnal Penyelidikan IPBL, 7(1), 78-86.

Davis, F. D. (2014). User acceptance of business intelligence (BI) application: Technology, individual difference, social influence, and situational constraints. In In 2014 47th Hawaii International Conference on System Sciences (pp. 3785-3766). https://doi.org/10.2307/249008

Dezso, C. L., & Ross, D. G. (2012). Does Female Representation in Top Management Improve Firm Performance? A Panel Data Investigation. Strategic Management Journal, 33(9), 1072-1089. https://doi.org/10.1002/smj

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11

Etin Malaysia. (2012, October 14). Low Digital Literacy Amongst Malaysian Business Leaders May Hamper Business Growth. Entreprise IT News. Retrieved from http://www.enterpriseitnews.com.my/cio-study-shows-that-low-digital-literacy-amongst-malaysian-business-leaders-may-hamper-business-growth/

Fernandez, D. J., & Fernandez, J. D. (2008). Agile project management"”agilism versus traditional approaches. Journal of Computer Information Systems, 49(2), 10-17. https://doi.org/10.1080/08874417.2009.11646044

Gindy, N. N., Saad, S. M., & Yue, Y. (2015). Manufacturing responsiveness through integrated process planning and scheduling. International Journal of Production Research, 37(11), 2399-2418. https://doi.org/10.1080/002075499190572

Golafshani, N. (2003). Understanding and Validity in Qualitative Research. The Qualitative Report, 8(4), 597-607. https://doi.org/10.17763/haer.62.3.8323320856251826

Goldsby, T. J., Griffis, S. E., & Roath, A. S. (2006). Modeling lean, agile, and leagile supply chain strategies. Journal of Business Logistics, 27(1), 57-80. https://doi.org/10.1002/j.2158-1592.2006.tb00241.x

Goyder, J., Warriner, K., & Miller, S. (2002). Evaluating Socio-Economic Status (SES) Bias in Survey Nonresponse. Journal of Official Statistics, 18(1), 1-11. https://doi.org/10.1016/0022-2860(91)87111-T

Grant, C., & Osanloo, A. (2014). Understanding, Selecting, and Integrating a Theoretical Framework in Dissertation Research: Creating the Blueprint for Your "House." Administrative Issues Journal Education Practice and Research, 12-26. https://doi.org/10.5929/2014.4.2.9

Greener, S. (2008). Choosing Sample From Population. In Business Research Methods (pp. 47-52). Ventus Publishing ApS.

Gu, J. (2014). The Use of Business Intelligence Techniques in Supply Chain Performance. Purdue University.

Hassan, Z. A., Schattner, P., & Mazza, D. (2006). Doing a pilot study: Why is it essential. Malaysian Family Physician, 1(2), 70-73.

Helo, P., Xiao, Y., & Jiao, J. R. (2006). A web-based logistics management system for agile supply demand network design. Journal of Manufacturing Technology Management, 17(8), 1058-1077. https://doi.org/10.1108/17410380610707384

Herschel, R. T., & Jones, N. E. (2005). Knowledge management and business intelligence: the importance of integration. Journal of Knowledge Management, 9(4), 45-55. https://doi.org/10.1108/13673270510610323

Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. https://doi.org/10.1016/j.ejor.2009.05.009

Hoek, R. I. Van, Harrison, A., & Christopher, M. (2001). Measuring agile capabilities in the supply chain. International Journal of Operations & Production Management, 21(1), 126-147.

Holt, D., Smith, T. M. F., & Winter, P. D. (1980). Regression analysis of data from complex surveys. Journal of the Royal Statistical Society, 143(4), 474-487.

Holweg, M. (2005). An investigation into supplier responsiveness Empirical evidence from the automotive industry. The International Journal of Logistics Management, 16(1), 96-119. https://doi.org/10.1108/09574090510617376

Iacobucci, D., & Duhachek, A. (2003). Advancing Alpha : Measuring Reliability With Confidence. Consumer Psychology, 13(4).

Institute of Labour Market Information and Analysis. (2017). Study of Manpower in the Malaysian Logistics Subsector.

Ismail, H. S., & Sharifi, H. (2006). A balanced approach to building agile supply chains. International Journal of Physical Distribution and Logistics Management, 36(6), 431-444. https://doi.org/10.1108/09600030610677384

Jayaram, J., & Tan, K. (2010). Supply chain integration with third-party logistics providers. International Journal of Production Economics, 125(2), 262-271. https://doi.org/10.1016/j.ijpe.2010.02.014

Karlsson, J., & Ryan, K. (1997). A cost-value approach for prioritizing requirements. IEEE Software, 14(5), 67-74. https://doi.org/10.1109/52.605933

King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740-755. https://doi.org/10.1016/j.im.2006.05.003

Konecka, S. (2010). Lean and agile supply chain management concepts in the aspect of risk management. LogForum, 6(4), 22-33.

Koo, T. K., & Li, M. Y. (2015). A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. Journal of Chiropractic Medicine, 15(2), 155-163. https://doi.org/10.1016/j.jcm.2016.02.012

Kropp, M., Meier, A., Mateescu, M., & Zahn, C. (2014). Teaching and Learning Agile Collaboration. In In 2014 IEEE 27th conference on software engineering education and training (CSEE&T) (pp. 139-148). https://doi.org/10.1109/CSEET.2014.6816791

Lam, J. S. L., & Yap, W. Y. (2008). Competition for transhipment containers by major ports in Southeast Asia: slot capacity analysis. Maritime Policy & Management, 35(1), 89-101. https://doi.org/10.1080/03088830701849043

Lanphear, J. H. (2001). Commentary : Pilot Studies. Education for Health, 14(1), 33-35.

Lederman, N. G., & Lederman, J. S. (n.d.). What Is A Theoretical Framework? A Practical Answer. Journal of Science Teacher Education, 26(7), 593-597. https://doi.org/10.1007/s10972-015-9443-2

Lee, C. K. M., Lau, H. C. W., Ho, G. T. S., & Ho, W. (2009). Design and development of agent-based procurement system to enhance business intelligence. Expert Systems with Applications, 36(1), 877-884. https://doi.org/10.1016/j.eswa.2007.10.027

Lee, H. L. (2002). Aligning Supply Chain Strategies with Product Uncertainties. California Management Review, 44(3), 105-119.

Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information Systems, 12(1), 752-780. https://doi.org/10.17705/1cais.01250

Li, J., Krohn, M., Mazières, D., & Shasha, D. (2004). Secure Untrusted Data Repository (SUNDR). Operating Systems Design and Implementation, 4, 122-136.

Li, X. (2014). Operations Management of Logistics and Supply Chain: Issues and Directions. Discrete Dynamics in Nature and Society, 2014, 1-7.

Lin, C. (2007). Argumentative SOX compliant and quality decision support intelligent expert system over the suppliers selection process. Journal of Technology Management in China, 2(1), 22-37. https://doi.org/10.1108/17468770710723604

Machuca, M. M., & Costa, C. M. (2012). A study of knowledge culture in the consulting industry. Industrial Management & Data Systems, 112(1), 24-41. https://doi.org/10.1108/02635571211193626

Malhotra, M. K., & Mackelprang, A. W. (2012). Are internal manufacturing and external supply chain flexibilities complementary capabilities? Journal of Operations Management, 30(3), 180-200. https://doi.org/10.1016/j.jom.2012.01.004

Marill, K. A. (2004). Advanced Statistics : Multiple Linear Regression. Acad Emerg Med, 11(1), 94-102. https://doi.org/10.1197/S1069-6563(03)00601-8

Marjanovic, O. (2007). The next stage of operational business intelligence: Creating new challenges for business process management. In 40th Annual Hawaii International Conference on System Sciences (HICSS'07). https://doi.org/10.1109/HICSS.2007.551

Mathi, K. (2004). Key Success Factors for Knowledge Management. University of Applied Sciences/FH Kempten.

Mehra, A., Kilduff, M., & Brass, D. J. (2011). The Social Networks of High and Low Self-monitors: Implications for Workplace Performance. Administrative Science Quarterly, 46(1), 121-146.

Melnyk, S. A., Davis, E. W., Spekman, R. E., & Sandor, J. (2010). Outcome-Driven Supply Chains. MIT Sloan Management Review, 51(2), 33-38.

Mohajan, H. K. (2017). Two Criteria for Good Measurements in Research: Validity and Reliability. Annals of Spiru Haret University. Economic Series, 17(4), 59-82. https://doi.org/10.26458/1746

Moniruzzaman, M., Kurnia, S., Parkes, A., & Maynard, S. B. (2015). Business Intelligence and Supply Chain Agility. Australasian Conference on Information Systems.

Najafabadi, M. M., Villanustre, F., Khoshgoftaar, T. M., Seliya, N., Wald, R., & Muharemagic, E. (2015). Deep learning applications and challenges in big data analytics. Journal of Big Data, 2(1), 1-21. https://doi.org/10.1186/s40537-014-0007-7

Nasab, S. M. H., Ziaei, S. M., & Alifiah, M. N. (2015). The Mediating Effect of Supply Chain Agility on the Relationship Between SCOR Business Analytic Solution and Supply Chain Performance. American Journal of Business, Economics and Management, 3(4), 171-176.

Negash, S., & Gray, P. (2008). Business Intelligence. In Handbook on Decision Support Systems 2 (pp. 175-193). Springer.

NST Business. (2018, January 17). Gartner says Malaysian IT spending to reach RM65.2b in 2018. New Straits Times. Retrieved from https://www.nst.com.my/business/2018/01/325876/gartner-says-malaysian-it-spending-reach-rm652b-2018

Nwaubani, J. (2011). Business intelligence and logistics. In In Proceedings of the 1st Olympus International Conference on Supply Chain (pp. 1-26).

Olexová, C. (2014). Business intelligence adoption: A case study in the retail chain. WSEAS Transactions on Business and Economics, 11(1), 95-106.

Olszak, C. M., & Ziemba, E. (2007). Approach to Building and Implementing Business Intelligence Systems. Interdisciplinary Journal of Information, Knowledge, and Management, 2, 136-148.

Osadchy, E. A., & Akhmetshin, E. M. (2015). Development of the financial control system in the company in crisis. Mediterranean Journal of Social Sciences, 6(5), 390-398. https://doi.org/10.5901/mjss.2015.v6n5s2p390

Petrini, M., & Pozzebon, M. (2009). Managing sustainability with the support of business intelligence: Integrating socio-environmental indicators and organisational context. Journal of Strategic Information Systems, 18(4), 178-191. https://doi.org/10.1016/j.jsis.2009.06.001

Popovi, A., Coelho, P. S., & Jakliþ, J. (2009). The impact of business intelligence system maturity on information quality. Information Research, 14(4).

Port, D., & Bui, T. (2009). Simulating mixed agile and plan-based requirements prioritization strategies: Proof-of-concept and practical implications. European Journal of Information Systems, 18(4), 317-331. https://doi.org/10.1057/ejis.2009.19

Power, D. J., & Sohal, A. S. (2001). Critical success factors in agile supply chain management- An empirical study factors. International Journal of Physical Distribution & Logistics, 31(4), 247-265.

Qi, L., & Zhang, S. (2002). Data mining techniques for customer relationship management. Technology in Society, 24(4), 483-502. https://doi.org/10.1007/978-3-642-34240-0_43

Qrunfleh, S., & Tarafdar, M. (2013). Lean and agile supply chain strategies and supply chain responsiveness: the role of strategic supplier partnership and postponement. Supply Chain Management: An International Journal, 18(6), 571-582. https://doi.org/10.1108/SCM-01-2013-0015

Ram, J., Zhang, C., & Koronios, A. (2016). The implications of Big Data analytics on Business Intelligence: A qualitative study in China. Procedia Computer Science, 87, 221-226. https://doi.org/10.1016/j.procs.2016.05.152

Razmi, J., Sangari, M. S., & Ghodsi, R. (2009). Advances in Engineering Software Developing a practical framework for ERP readiness assessment using fuzzy analytic network process. Advances in Engineering Software, 40(11), 1168-1178. https://doi.org/10.1016/j.advengsoft.2009.05.002

Richards, G., Yeoh, W., Chong, A. Y. L., & PopoviÄ, A. (2019). Business intelligence effectiveness and corporate performance management: an empirical analysis. Journal of Computer Information Systems, 59(2), 188-196. https://doi.org/10.1080/08874417.2017.1334244

Ritchie, B., & Brindley, C. (2004). Risk Characteristics of the Supply Chain- A Contingency Framework. In Supply Chain Risk (pp. 28-43). Routledge.

Robinson, G., & Dechant, K. (1997). Building a business case for diversity. Academy of Management Executive, 11(3), 21-31. https://doi.org/10.5465/ame.1997.9709231661

Robinson, J. (1934). What is Perfect Competition? The Quarterly Journal of Economics, 49(1), 104-120.

Roscoe, J. T. (1975). Fundamental research statistics for the behavioral sciences (2nd ed.). Holt, Rinehart and Winston.

Sahay, B. S., & Ranjan, J. (2008). Real time business intelligence in supply chain analytics. Information Management and Computer Security, 16(1), 28-48. https://doi.org/10.1108/09685220810862733

Salant, P., Dillman, L., & Don, A. (1994). How to conduct your own survey.

Sangari, M. S., & Razmi, J. (2015). Business intelligence competence, agile capabilities, and agile performance in supply chain: An empirical study. The International Journal of Logistics Management, 26(2), 356-380.

Sarangi, S. (2016). Business Intelligence Systems: A Necessity for Agile Supply Chains. Parikalpana: KIIT Journal of Management, 12(2), 52-65. https://doi.org/10.23862/kiit-parikalpana/2016/v12/i2/132991

Schilling, M. A., & Hill, C. W. L. (1998). Managing the new product development process: Strategic imperatives, product introduction. Academy of Management Perspectives, 12(3), 67-81. https://doi.org/10.5465/ame.1998.1109051

Sekaran, U., & Bougie, R. (2016). Research Methods For Business: A Skill Building Approach (7th ed.). New York: John Wiley and Sons, Inc.

Seufert, A., & Schiefer, J. (2005). Enhanced Business Intelligence - Supporting business processes with real-time business analytics. In In 16th International Workshop on Database and Expert Systems Applications (DEXA'05) (pp. 919-925). https://doi.org/10.1109/DEXA.2005.86

Shariat, M., & Hightower, R. (2007). Conceptualizing Business Intelligence Architecture. Marketing Management Journal, 17(2), 40-46.

Shehzad, R., & Khan, M. N. A. (2013). Integrating Knowledge Management with Business Intelligence Processes for Enhanced Organizational Learning. International Journal of Software Engineering and Its Applications, 7(2), 83-92.

Sileyew, K. J. (2016). Research Design and Methodology. Intech, 13. https://doi.org/http://dx.doi.org/10.5772/57353

Sillitti, A., Hazzan, O., Bache, E., & Albaladejo, X. (2011). Agile Processes in Software Engineering and Extreme Programming. In 12th International Conference, XP 2011 (pp. 1-

Skyrius, R., Katin, I., Kazimianec, M., Nemitko, S., Rumšas, G., & Žilinskas, R. (2016). Factors Driving Business Intelligence Culture. Informing Science and Information Technology, 13, 171-186.

Sohail, M. S., & Sohal, A. S. (2003). The use of third party logistics services : A Malaysian perspective. Technovation, 23, 401-408. https://doi.org/10.1016/S0166-4972(02)00003-2

Soltan, H., & Mostafa, S. (2015). Lean and agile performance framework for manufacturing enterprises. In 2nd International Materials, Industrial, and Manufacturing Engineering Conference

Srinivasa, R. P., & Swarup, S. (2001). Business Intelligence and Logistics. Wipro Technologies.

Stefanovic, N., & Stefanovic, D. (2009). Supply Chain business intelligence: Technologies, Issues and Trends. Computer Science, 5640 LNAI, 217-245. https://doi.org/10.1007/978-3-642-03226-4_12

Storrle, H. (2005). Making Agile Processes Scalable. In International Workshop on Process Simulation and Modelling (ProSim03) (pp. 1-8).

Sutherland, J., Viktorov, A., Blount, J., & Puntikov, N. (2007). Distributed scrum: Agile project management with outsourced development teams. Proceedings of the Annual Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2007.180

Sutton, J., & Austin, Z. (2015). Qualitative research: Data collection, analysis, and management. Canadian Journal of Hospital Pharmacy, 68(3), 226-231. https://doi.org/10.4212/cjhp.v68i3.1456

Tahiduzzaman, Rahman, M., Dey, S. K., Rahman, S., & Akash, S. M. (2017). Big data and its impact on digitized supply chain management. Journal of Business Management, 3(9), 196-208.

Tan, C. S., Sim, Y. W., & Yeoh, W. (2011). A maturity model of enterprise business intelligence. Communications of the IBIMA, 1, 1-11. https://doi.org/10.5171/2011.417812

Tarafdar, M., & Qrunfleh, S. (2017). Agile supply chain strategy and supply chain performance: Complementary roles of supply chain practices and information systems capability for agility. International Journal of Production Research, 55(4), 925-938.

The World Bank. (2018). International LPI. Retrieved from https://lpi.worldbank.org/international/global/2018

Towill, D. R., & McCullen, P. (1999). The Impact of Agile Manufacturing on Supply Chain Dynamics. The International Journal of Logistics Management, 10(1), 83-96.

Trochim, W. M. (2006). The Research Methods Knowledge Base (2nd ed.). Atomic Dog Publishing.

Wakefield, R. L., & Whitten, D. (2006). Mobile computing: A user study on hedonic/utilitarian mobile device usage. European Journal of Information Systems, 15(3), 292-300. https://doi.org/10.1057/palgrave.ejis.3000619

Wang, H., & Wang, S. (2008). A knowledge management approach to data mining process for business intelligence. Industrial Management and Data Systems, 108(5), 622-634. https://doi.org/10.1108/02635570810876750

Wang, J., Hu, X., & Zhu, D. (2007). Diminishing downsides of data mining. International Journal of Business Intelligence and Data Mining, 2(2), 177-196. https://doi.org/10.1504/IJBIDM.2007.013936

Wang, Y. (2016). Business intelligence. Journal of Knowledge Management, Economics and Information Technology, 10(3), 300-317. https://doi.org/10.1002/sej.1229

Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. Computer, 40(9), 96-99. https://doi.org/10.1109/MC.2007.331

Yeoh, W., & Koronios, A. (2010). Critical Success Factors for Business Intelligence Systems. Journal of Computer Information Systems, 50(3), 23-32.

Yoon, T. E., Ghosh, B., & Jeong, B. K. (2014). User acceptance of business intelligence (BI) application: Technology, individual difference, social influence, and situational constraints. In 47th Hawaii International Conference on System Sciences (pp. 3758-3766). IEEE. https://doi.org/10.1109/HICSS.2014.467

Zhu, B., & Yuan, J. (2015). Pressure transfer modeling for an urban water supply system based on Pearson correlation analysis. Journal of Hydroinformatics, 17(1), 90-98. https://doi.org/10.2166/hydro.2014.037

Zikmund, W. G., Carr, J. C., Griffin, M., & Babin, B. J. (2013). Simple Refression and Hypothesis testing. In Business Research Methods (9th ed., pp. 576-577). South-Western, Cengage Learning.

Downloads

Published

2021-08-23

How to Cite

Kaur , K. . (2021). BUSINESS INTELLIGENCE ON SUPPLY CHAIN RESPONSIVENESS AND AGILE PERFORMANCE: EMPIRICAL EVIDENCE FROM MALAYSIAN LOGISTICS INDUSTRY. International Journal of Supply Chain Management, 6(2), 31 – 63. https://doi.org/10.47604/ijscm.1351

Issue

Section

Articles