Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediation-moderation model

    Malek Al-edenat   Affiliation
    ; Nayel Alhawamdeh   Affiliation


The purpose of this study is to investigate the impact of individuals’ competencies in business intelligence (BI) and analytics (BA) on process effectiveness (PE). Moreover, to investigate the mediating role of user participation (UP) and the moderating role of gender in this relationship. An empirical analysis based on survey data was conducted. A sample of 215 middle and upper management levels from SMEs located in Jordan was surveyed to collect the data. Structural equation modelling through partial least squares-multi group analysis (PLS-MGA) is used to analyze the data. The results support the direct positive impact of individuals’ competencies in business intelligence (BA) and business analytics (BA). Moreover, user participation has been found to mediate this relationship. Additionally, the results showed that gender moderates the relationship between individuals’ competencies in business intelligence (BI) and analytics (BA) on process effectiveness (PE). The findings improve the understanding of the needed individuals’ competencies in business intelligence (BI) and analytics (BA) that affect process effectiveness (PE). This will help develop and arrange strategies that increase individuals’ competencies in business intelligence (BI) and analytics (BA) among employees. Furthermore, managers and owners should put plans for strategies to augment confidence amongst female employees.

Keyword : business intelligence (BI), business analytics (BA), process effectiveness (PE), user participation (UP)

How to Cite
Al-edenat, M., & Alhawamdeh, N. (2022). Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediation-moderation model. Business: Theory and Practice, 23(2), 239–259.
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Aamodt, M. G. (2015). Industrial organizational psychology: An applied approach (6th ed.). Cengage Learning.

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.

Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M., & Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514–538.

Amin, H., Hamid, M. R. A., Tanakinjal, G. H., & Lada, S. (2006). Undergraduate attitudes andexpectations for mobile banking. Journal of Internet Banking and Commerce, 11(3), 1–10.

Andersson, L. M., & Bateman, T. S. (1997). Cynicism in the workplace: Some causes and effects. Journal of Organizational Behavior, 18(5), 449–469.<449::AID-JOB808>3.0.CO;2-O

Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44.

Arnott, D., Lizama, F., & Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, 58–68.

Austin, J., Stevenson, H., & Wei-Skillern, J. (2006). Social and commercial entrepreneurship: Same, different, or both? Entrepreneurship Theory and Practice, 30(1), 1–22.

Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., & Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of Business Research, 96(November 2018), 228–237.

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

Barki, H., & Hartwick, J. (1994). Measuring user participation, user involvement, and user attitude. MIS Quarterly, 18(1), 59–82.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

Barney, J., Wright, M., & Ketchen, D. J. (2001). The resource-based view of the firm: Ten years after 1991. Journal of Management, 27(6), 625–641.

Bedeley, R. T., Ghoshal, T., Iyer, L. S., & Bhadury, J. (2018). Business analytics and organizational value chains: A relational mapping. Journal of Computer Information Systems, 58(2), 151–161.

Borissova, D., Cvetkova, P., Garvanov, I., & Garvanova, M. (2020). A framework of business intelligence system for decision making in efficiency management. In K. Saeed & J. Dvirsky (Eds), Computer Information Systems and Industrial Management. CISIM 2020. Lecture Notes in Computer Science (Vol. 12133). Springer.

Brill, C. (2019). The influence of management support on the drivers of business intelligence success [Doctoral dissertation, University of Pretoria, March].

Bronzo, M., de Resende, P. T. V., de Oliveira, M. P. V., McCormack, K. P., de Sousa, P. R., & Ferreira, R. L. (2013). Improving performance aligning business analytics with process orientation. International Journal of Information Management, 33(2), 300–307.

Burke, R. R. (2002). Technology and the customer interface: What consumers want in the physical and virtual store. Journal of the Academy of Marketing Science, 30(4), 411–432.

Cao, G., Duan, Y., & Li, G. (2015). Linking business analytics to decision making effectiveness: A Path model analysis. IEEE Transactions on Engineering Management, 62(3), 384–395.

Carranza, R., Díaz, E., Martín-Consuegra, D., & Fernández-Ferrín, P. (2020). PLS–SEM in business promotion strategies. A multigroup analysis of mobile coupon users using MICOM. Industrial Management and Data Systems, 120(12), 2349–2374.

Cavaye, A. L. M. (1995). User participation in system development revisited. Information and Management, 28(5), 311–323.

Cepeda-Carrion, G., Cegarra-Navarro, J. G., & Cillo, V. (2019). Tips to use partial least squares structural equation modelling (PLS-SEM) in knowledge management. Journal of Knowledge Management, 23(1), 67–89.

Chawla, D., & Joshi, H. (2020). The moderating role of gender and age in the adoption of the mobile wallet. Foresight, 22(4), 483–504.

Chen, H., Chiang, R. H. L., Storey, V. C., & Robinson, J. M. (2012). Business intelligence research business intelligence and analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188.

Cheng, X., Su, L., Luo, X., Benitez, J., & Cai, S. (2021). The good, the bad, and the ugly: Impact of analytics and artificial intelligence-enabled personal information collection on privacy and participation in ridesharing. European Journal of Information Systems, 31(3), 339–363.

Cheung, C. M. K., & Lee, M. K. O. (2011). Exploring the gender differences in student acceptance of an internet-based learning medium. In Technology Acceptance in Education (pp. 183–199). Sense Publishers.

Chowdhury, S. (2005). Demographic diversity for building an effective entrepreneurial team: Is it important? Journal of Business Venturing, 20(6), 727–746.

Clulow, V., Barry, C., & Gerstman, J. (2007). The resource-based view and value: The customer-based view of the firm. Journal of European Industrial Training, 31(1), 19–35.

Cosic, R., Shanks, G., & Maynard, S. (2012, 3–5 December). Towards a business analytics capability maturity model. In ACIS 2012: Proceedings of the 23rd Australasian Conference on Information Systems (pp. 1–11).

Cosic, R., Shanks, G., & Maynard, S. (2015). A business analytics capability framework. Australasian Journal of Information Systems, 19, S5–S19.

Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98–108.

Davenport, T., & Harris, J. (2017). Competing on analytics: The new science of winning (1st ed.). Harvard Business Press.

Department of Statistics. (2020). Jordan in figures 2017.

Diochon, M., & Anderson, A. R. (2009). Social enterprise and effectiveness: A process typology. Social Enterprise Journal, 5(1), 7–29.

Duan, Y., Cao, G., & Edwards, J. S. (2020). Understanding the impact of business analytics on innovation. European Journal of Operational Research, 281(3).

El-Adaileh, N. A., & Foster, S. (2019). Successful business intelligence implementation: A systematic literature review. Journal of Work-Applied Management, 11(2), 121–132.

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.

Fornell, C., & Larcker, D. F. (2016). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

Foshay, N., & Kuziemsky, C. (2014). Towards an implementation framework for business intelligence in healthcare. International Journal of Information Management, 34(1), 20–27.

Galbraith, J. R. (1965). Organization design: An information processing view. Interfaces, 4(3), 28–36.

Gbosbal, S., & Kim, S. K. (1986). Building effective intelligence systems for competitive advantage. Sloan Management Review, 28(1), 49–58.

Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 1–7.

Gessner, G., & Scott, R. A. (2009). Using business intelligence tools to help manage costs and effectiveness of business-to-business inside-sales programs. Information Systems Management, 26(2), 199–208.

Ghatasheh, N., Faris, H., AlTaharwa, I., Harb, Y., & Harb, A. (2020). Business analytics in telemarketing: Cost-sensitive analysis of bank campaigns using artificial neural networks. Applied Sciences (Switzerland), 10(7), 8–13.

Goswami, A., & Dutta, S. (2015). Gender differences in technology usage: A literature review. Open Journal of Business and Management, 4(1), 51–59.

Guimaraes, T., & Igbaria, M. (1997). Client/server system success: Exploring the human side. Decision Sciences, 28(4), 851–876.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.

Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.

Hair Jr., J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107.

Hamad, F., Al-Aamr, R., Jabbar, S. A., & Fakhuri, H. (2021). Business intelligence in academic libraries in Jordan: Opportunities and challenges. IFLA Journal, 47(1).

Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information system use. Management Science, 40(4), 440–465.

Hawking, P., & Sellitto, C. (2010). Business Intelligence (BI) critical success factors. In ACIS 2010 Proceedings – 21st Australasian Conference on Information Systems. AIS Electronic Library (AISeL).

Howson, C., Sallam, R. L., Richardson, J. L., Tapadinhas, J., Idoine, C. J., & Woodward, A. (2018). Magic quadrant for analytics and business intelligence platforms. Gartner (Issue Tech Rep).

Hostmann, B., Rayner, N., & Herschel, G. (2009). Gartner’s business intelligence, analytics and performance management framework. Gartner (Issue October).

Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453.

Hunton, J. E., & Price, K. H. (1997). Effects of the user participation process and task meaningfulness on key information system outcomes. Management Science, 43(6), 797–812.

Hunton, J. E., & Beeler, J. D. (1997). Effects of user participation in systems development: A longitudinal field experiment. MIS Quarterly, 21(4), 359–383.

Işik, Ö., Jones, M. C., & Sidorova, A. (2013). Business intelligence success: The roles of BI capabilities and decision environments. Information and Management, 50(1), 13–23.

Işik, Ö., Sidorova, A., & Jones, M. C. (2012). Business intelligence success and the role of BI capabilities. Intelligent Systems in Accounting, Finance and Management, 18(January), 161–176.

Jordanian Young Economists Society. (2017). Challenges facing SMEs and what is needed to empower SMEs sector in Jordan.

Kohtamäki, M., & Farmer, D. (2017). Strategic agility – integrating business intelligence with strategy. In M. Kohtamäki (Ed.), Real-time strategy and business intelligence (pp. 11–36). Palgrave Macmillan.

Krishnamoorthi, S., & Mathew, S. K. (2018). Business analytics and business value: A comparative case study. Information and Management, 55(5), 643–666.

Kristoffersen, E., Mikalef, P., Blomsma, F., & Li, J. (2021). Towards a business analytics capability for the circular economy. Technological Forecasting and Social Change, 171, 120957.

Kulkarni, U. R., Robles-Flores, J. A., & Popovič, A. (2017). Business intelligence capability: The effect of top management and the mediating roles of user participation and analytical decision making orientation. Journal of the Association for Information Systems, 18(7), 516–541.

Lahrmann, G., Marx, F., Winter, R., & Wortmann, F. (2011). Business intelligence maturity: Development and evaluation of a theoretical model. In The Proceedings of the Annual Hawaii International Conference on System Sciences, February. IEEE.

Lin, W. T., & Shao, B. B. M. (2000). The relationship between user participation and system success: A simultaneous contingency approach. Information and Management, 37(6), 283–295.

Liu, F., Zhao, X., Chau, P. Y. K., & Tang, Q. (2015). Roles of perceived value and individual differences in the acceptance of mobile coupon applications. Internet Research, 25(3), 471–495.

Lonnqvist, A., & Puhakka, V. (2006). The measurement of business intelligence. Information Systems Management, 23(1), 32–40.

Masa’Deh, R., Obeidat, Z., Maqableh, M., & Shah, M. (2021). The impact of business intelligence systems on an organization’s effectiveness: The role of metadata quality from a developing country’s view. International Journal of Hospitality and Tourism Administration, 22(1), 64–84.

McKeen, J. D., & Guimaraes, T. (1997). Successful strategies for user participation in systems development. Journal of Management Information Systems, 14(2), 133–150.

Michalewicz, Z., Schmidt, M., Michalewicz, M., & Chiriac, C. (2006). Adaptive business intelligence. Springer.

Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: A systematic literature review and research agenda. Information Systems and E-Business Management, 16(3), 547–578.

Naala, M., Nordin, N., Omar, W. A. B. W. (2017). Innovation capability and firm performance relationship: A study of PLS-structural equation modeling (PLS-SEM). International Journal of Organization & Business Excellence, 2(1), 39–50.

Nadler, D. A., & Tushman, M. L. (1980). A congruence model for organizational assessment. Organizational Dynamics, 9(2), 35–51.

Nandi, M. L., Nandi, S., Moya, H., & Kaynak, H. (2020). Blockchain technology-enabled supply chain systems and supply chain performance: A resource-based view. Supply Chain Management, 25(6), 841–862.

Niu, Y., Ying, L., Yang, J., Bao, M., & Sivaparthipan, C. B. (2021). Organizational business intelligence and decision making using big data analytics. Information Processing and Management, 58(6), 102725.

Okkonen, J., Pirttimäki, V., Hannula, M., & Lonnqvist, A. (2002, May 9–11). Triangle of business intelligence, performance measurement and knowledge management. In Proceedings of the 2nd Annual Conference on Innovative Research in Management, EURAM 2002. Stockholm, Sweden.

Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427.

Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404–428.

Otoo, F. N. K. (2019). Human resource development (HRD) practices and banking industry effectiveness: The mediating role of employee competencies. European Journal of Training and Development, 43(3–4), 250–271.

Pandya, V. M. (2012, 6–7 September). Comparative analysis of development of SMEs in developed and developing countries. International Conference on Business and Management, (pp. 426–433). Phuket-Thailand.

Pee, L. G., & Kankanhalli, A. (2016). Interactions among factors influencing knowledge management in public-sector organizations: A resource-based view. Government Information Quarterly, 33(1), 188–199.

Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management, 30(6), 467–480.

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.

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.

Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decision Support Systems, 54(1), 729–739.

Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2014). How information-sharing values influence the use of information systems: An investigation in the business intelligence systems context. The Journal of Strategic Information Systems, 23(4), 270–283.

Popovič, A., Puklavec, B., & Oliveira, T. (2019). Justifying business intelligence systems adoption in SMEs: Impact of systems use on firm performance. Industrial Management and Data Systems, 119(1), 210–228.

Popovič, A., Turk, T., & Jaklič, J. (2010). Conceptual model of business value of business intelligence systems. Management: Journal of Contemporary Management Issues, 15(1), 5–30.

Potnuru, R. K. G., & Sahoo, C. K. (2016). HRD interventions, employee competencies and organizational effectiveness: An empirical study. European Journal of Training and Development, 40(5), 345–365.

Premkumar, G., Ramamurthy, K., & Saunders, C. S. (2005). Information processing view of organizations: An exploratory examination of fit in the context of interorganizational relationships. Journal of Management Information Systems, 22(1), 257–294.

Presbitero, A. (2021). Communication accommodation within global virtual team: The influence of cultural intelligence and the impact on interpersonal process effectiveness. Journal of International Management, 27(1), 100809.

Ramakrishnan, T., Khuntia, J., Kathuria, A., & Saldanha, T. (2016, March). Business intelligence capabilities and effectiveness: An integrative model. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 5022–5031). IEEE.

Ramakrishnan, T., Khuntia, J., Kathuria, A., & Saldanha, T. J. V. (2020). An integrated model of business intelligence & analytics capabilities and organizational performance. Communications of the Association for Information Systems, 46, 722–750.

Ransbotham, S., Kiron, D., & Prentice, P. (2016). Beyond the hype: The hard work behind analytics success. MIT Sloan Management Review, 57(3), 6–6.

Richter, N. F., Sinkovics, R. R., Ringle, C. M., & Schlägel, C. (2016). A critical look at the use of SEM in international business research. International Marketing Review, 33(3), 376–404.

Riggio, R. E. (2017). Introduction to industrial/organizational psychology. Routledge.

Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. International Journal of Human Resource Management, 31(12), 1617–1643.

Sahay, B. S., & Ranjan, J. (2008). Real time business intelligence in supply chain analytics. Information Management and Computer Security, 16(1), 28–48.

Salman, M., & Ganie, S. A. (2020). Employee competencies as predictors of organizational performance: A study of public and private sector banks. Management and Labour Studies, 45(4), 416–432.

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

Santiago Rivera, D., & Shanks, G. (2015). A dashboard to support management of business analytics capabilities. Journal of Decision Systems, 24(1), 73–86.

Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115.

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students (6th ed.). Pearson Education Limited.

Savlovschi, L. I., & Robu, N. R. (2011). The role of SMEs in modern economy. Economia, Seria Management, 14(1), 277–281.

Schuberth, F. (2021). Confirmatory composite analysis using partial least squares: Setting the record straight. Review of Managerial Science, 15(5), 1311–1345.

Shin, D. H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343–1354.

Sosik, J. J., Kahai, S. S., & Piovoso, M. J. (2009). Silver bullet or voodoo statistics? A primer for using the partial least squares data analytic technique in group and organization research. Group and Organization Management, 34(1), 5–36.

Spears, J. L., & Barki, H. (2010). User participation in information systems security risk management. MIS Quarterly, 34(3), 503–522.

Steers, R. M. (1976). When is an organization effective? A process approach to understanding effectiveness. Organizational Dynamics, 5(2), 50–63.

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111–133.

Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human Computer Studies, 64(2), 53–78.

Sun, Z., Sun, L., & Strang, K. (2018). Big Data analytics services for enhancing business intelligence. Journal of Computer Information Systems, 58(2), 162–169.

Taylor, M., Reilly, D., & Wren, Ch. (2020). Internet of things support for marketing activities. Journal of Strategic Marketing, 28(2), 149–160.

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.

Tian, H., Iqbal, S., Anwar, F., Akhtar, S., Khan, M. A. S., & Wang, W. (2021). Network embeddedness and innovation performance: A mediation moderation analysis using PLS-SEM. Business Process Management Journal, 27(5), 1590–1609.

Toepoel, V., & Schonlau, M. (2017). Dealing with nonresponse: Strategies to increase participation and methods for postsurvey adjustments. Mathematical Population Studies, 24(2), 79–83.

Trauth, E. M., Quesenberry, J. L., & Morgan, A. J. (2004). Understanding the under representation of women in IT. In SIGMIS Conference on Computer Personnel Research: Careers, Culture, and Ethics in a Networked Environment (pp. 114–119). ACM Digital Library.

Trieu, V. H. (2017). Getting value from Business Intelligence systems: A review and research agenda. Decision Support Systems, 93, 111–124.

Tripathi, A., Bagga, T., & Aggarwal, R. K. (2020). Strategic impact of business intelligence: A review of literature. Prabandhan: Indian Journal of Management, 13(3), 35–48.

Trkman, P., McCormack, K., De Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318–327.

Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application (JITTA), 11(2), 5–40.

Venkatesh, V., & Morris, M. G. (2000). Why don’t men stop asking for directions? Gender, social influence and their role in society. MIS Quarterly, 24(1), 115–139.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3).

Verona, G. (1999). A resource-based view of product development. The Academy of Management Review, 24(1), 132–142.

Viaene, S., & Van den Bunder, A. (2011). The secrets to managing business analytics projects. MIT Sloan Management Review, 53(1), 65–69.

Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626–639.

Wan, W. W. N., Luk, C. L., & Chow, C. W. C. (2005). Customers’ adoption of banking channels in Hong Kong. International Journal of Bank Marketing, 23(3), 255–272.

Wang, Y., & Byrd, T. A. (2019). Business analytics-enabled decision making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517–539.

Wang, Y., Kung, L. A., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3–13.

Watson, W. E., Ponthieu, L. D., & Critelli, J. W. (1995). Team interpersonal process effectiveness in venture partnerships and its connection to perceived success. Journal of Business Venturing, 10(5), 393–411.

Watson, W., Stewart, W. H., & BarNir, A. (2003). The effects of human capital, organizational demography, and interpersonal processes on venture partner perceptions of firm profit and growth. Journal of Business Venturing, 18(2), 145–164.

Wieder, B., & Ossimitz, M. L. (2015). The impact of business intelligence on the quality of decision making – a mediation model. Procedia Computer Science, 64, 1163–1171.

Williams, N., Williams, S., & Planning, S. (2010). The profit impact of business intelligence. In The Profit Impact of Business Intelligence (1st ed.). Elsevier Inc.

Wixom, B. H., & Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), 17–41.

Wright, P. M., Dunford, B. B., & Snell, S. A. (2001). Human resources and the resource based view of the firm and the resource based view of the firm. Journal of Management, 27(6), 701–721.

Wright, P. M., McMahan, G. C., McCormick, B., & Sherman, W. S. (1998). Strategy, core competence, and HR involvement as determinants of HR effectiveness and refinery performance. Human Resource Management, 37(1), 17–29.<17::AID-HRM3>3.0.CO;2-Y

Yeoh, W., & Popovič, A. (2016). Extending the understanding of critical success factors for implementing business intelligence systems. Journal of the Association for Information Science and Technology, 67(1), 134–147.

Zhang, K. Z. K., Cheung, C. M. K., & Lee, M. K. O. (2014). Examining the moderating effect of inconsistent reviews and its gender differences on consumers’ online shopping decision. International Journal of Information Management, 34(2), 89–98.