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http://dx.doi.org/10.7838/jsebs.2022.27.2.037

A Study on the Factors Influencing a Company's Selection of Machine Learning: From the Perspective of Expanded Algorithm Selection Problem  

Yi, Youngsoo (School of Management, Kyung Hee University)
Kwon, Min Soo (School of Management, Kyung Hee University)
Kwon, Ohbyung (School of Management, Kyung Hee University)
Publication Information
The Journal of Society for e-Business Studies / v.27, no.2, 2022 , pp. 37-64 More about this Journal
Abstract
As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.
Keywords
Algorithm Selection Process; Task-Technology Fit; IS Success Model; Machine Learning Empirical Study;
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1 Schein, E. H., "Organizational Culture and Leadership," John Wiley & Sons, Vol. 2, 2010.
2 Shahbaz, M., Gao, C., Zhai, L. L., Shahzad, F., and Hu, Y., "Investigating the adoption of big data analytics in healthcare: The moderating role of resistance to change," Journal of Big Data, Vol. 16, No. 1, pp. 1-20, 2019.
3 Simon, H., "The new science of management decision," New York: Harper & Row, 1960.
4 Smith-Miles, K. A., "Cross-disciplinary perspectives on meta-learning for algorithm selection," ACM Computing Surveys, Vol. 41, No. 1, pp. 1-25, 2008.   DOI
5 Sedera, D. and Gable, G., "A factor and structural equation analysis of the enterprise systems success measurement model," In Systems Success Measurement Model. International Conference of Information, p. 449, 2004.
6 Aubert, B. A., Rivard, S., and Patry, M., "A transaction cost approach to outsourcing behavior: Some empirical evidence," Information and Management, Vol. 30, No. 2, pp. 51-64, 1996.   DOI
7 Alyoussef, I. Y., "Massive Open Online Course (MOOCs) acceptance: The role of Task-Technology Fit (TTF) for higher education sustainability," Sustainability, Vol. 13, No. 13, p. 7374, 2021.   DOI
8 Rejikumar, G., Asokan A. A., and Sreedharan, V. R., "Impact of data-driven decision-making in lean six sigma: An empirical analysis," Total Quality Management & Business Excellence, Vol. 31, No. 3, pp. 279-296, 2020.   DOI
9 Ryan, R. M. and Deci, E. L., "Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being," American Psychologist, Vol. 55, No. 1, pp. 68-78, 2000.   DOI
10 Brock V. and Khan, H. U., "Big data analytics: Does organizational factor matters impact technology acceptance?," Journal of Big Data, Vol. 4, No. 1, pp. 1-28, 2017.   DOI
11 Aral, S., Brynjolfsson, E., and Wu, D, "Which came first, it or productivity? The virtuous cycle of investment and use in enterprise systems," SSRN Electronic Journal, pp. 1-22, 2006.
12 de Almeda, A. R., Medeiros, P. Y., and Halpern, E. E., "Why internal clients are dissatisfied with the quality of information technology services provided by their organizations?," Procedia Computer Science, Vol. 55, pp. 922-930, 2015.   DOI
13 Dharanikota, S. and Marakas, G. M., "Does AI reliance lead to performance? A task-technology fit theory perspective," 2021.
14 Elbanna, A., "Top management support in multiple-project environments: An in-practice view," European Journal of Information Systems, Vol. 22, No. 3, pp. 278-294, 2013.   DOI
15 Gan, Q. and Cao, Q., "Adoption of electronic health record system: Multiple theoretical perspectives," In: 2014 47th Hawaii International Conference on System Sciences, pp. 2716-2724, 2014.
16 Alsheibani, S. and Cheung, Y., "Artificial intelligence adoption: AI-readiness at firm-level," PACIS 2018 Proceedings, p. 37, 2018.
17 Tam, C. and Oliveira, T., "Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective," Computers in Human Behavior, Vol. 61, pp. 233-244, 2016.   DOI
18 Lee, I. and Shin, Y. J., "Machine learning for enterprises: Applications, algorithm selection, and challenges," Business Horizons, Vol. 63, No. 2, pp. 150-170, 2020.
19 Hayduk, L. A., "Structural equation modeling with LISREL: Essentials and advances," Social Forces, Vol. 69, No. 1, pp. 338, 1987.
20 Yoo, K. W., Hwang, K., and Kwon, O., "The effects of vr-based cultural heritage experience on visit intention," The Journal of Society for e-Business Studies Vol. 26, No. 2, pp. 95-122, May 2021.   DOI
21 Anthony R. N., "Planning and control systems: A framework for analysis," Boston: Harvard Business School, Division of Research, 1965.
22 Attaran, M. and Deb, P., "Machine learning: The new 'big thing' for competitive advantage," Int. J. Knowledge Engineering and Data Mining, Vol. 5, No. 4, pp. 277-305, 2018.   DOI
23 Bagozzi, R. P. and Yi, Y., "On the evaluation of structural equation models," Journal of the academy of marketing science, Vol. 16, No. 1, pp. 74-94, 1988.   DOI
24 Bradley, S. and Nolan, R., "Sense & Respond," Boston: Harvard Business School Press, 1998.
25 Chen, Y., Wang, H., Li, W., Sakaridis, C., Dai, D., and Van Gool, L., "Scale-aware domain adaptive faster R-Cnn," International Journal of Computer Vision, Vol. 129, No. 7, pp. 2223-2243, 2021.   DOI
26 Dahlberg, T. and Nyrhinen, M., "A new instrument to measure the success of IT outsourcing," In Proceedings of the 39th Hawaii International Conference on System Sciences (HICSS'06), Vol. 8, pp. 200a-200a, 2006.
27 Davenport, T. H., "Competing on analytics," Harvard Business Review, Vol. 84, No. 1, p. 98, 2006.
28 Victor, J. G., Francisco, J. L., and Antonio, J. V., "Antecedents and Consequences of Organizational Innovation and Organizational Learning in Entrepreneurship," Industrial Management & Data Systems, Vol. 106, No. 1, 2006.
29 Sultana, S., Akter, S., and Kyriazis, E., "How data-driven innovation capability is shaping the future of market agility and competitive performance?," Technological Forecasting and Social Change, Vol. 174, 2022.
30 Tanaka, M., Bloom, N., David, J. M., and Koga, M., "Firm Performance and Macro Forecast Accuracy," Journal of Monetary Economics, Vol. 114, pp. 26-41, 2020.   DOI
31 Wang, R. Y. and Strong, D. M., "Beyond accuracy: What data quality means to data consumers," Journal of Management Information Systems, Vol. 12, No. 4, pp. 5-33, 1996.   DOI
32 Dishaw, M. T. and Strong, D. M., "Extending the technology acceptance model with task-technology fit constructs," Information & Management, Vol. 36, No. 1, pp. 9-21, 1999.   DOI
33 Aljarboa, S. and Miah, S. J., "An integration of UTAUT and task-technology fit frameworks for assessing the acceptance of clinical decision support systems in the context of a developing country," In of Sixth International Congress on Information and Communication Technology, pp. 127-137, 2022.
34 DeLone, W. H. amd McLean, E. R., "The delone and mclean model of information system success," Journal of Management Information System, Vol. 19, No. 4, pp. 9-30, 2003.   DOI
35 Dennis, A. R., Wixom, B. H., and Vandenberg, R. J., "Understanding fit and appropriation effects in group support systems via meta-analysis understanding fit and appropriation effects in group support systems via meta-analysis," MIS Quaterly, pp. 167-193, 2001.
36 Domberger, S., Fernandez, P., and Fiebig, D. G., "Modelling the price, performance and contract characteristics of it outsourcing," Journal of Information Technology, Vol. 15, No, 2, pp. 107-118, 2000.   DOI
37 Feng, L., Lu, J., and Wang, J., "A Systematic Review of Enterprise Innovation Ecosystems," Sustainability, Vol. 13, No. 10, p. 5742, 2021.   DOI
38 Fornell, C. and Larcker, D. F., "Structural equation models with unobservable variables and measurement error: Algebra and statistics," Journal of Marketing Research, Vol. 18, No. 3, pp. 382-388, 1981.   DOI
39 Operskalski, J. T. and Barbey, A. K., "Risk literacy in medical decision-making," Science, Vol. 352, No. 6284, pp. 413-414, 2016.   DOI
40 Agrawal, A., McHale, J., and Oettl, A., "Finding needles in haystacks: Artificial intelligence and recombinant growth," University of Chicago Press, pp. 149-17, 2020.
41 Patterson, M. G. and West, M. A., "Validating the organizational climate measure: Links to managerial practices, productivity and innovation," Journal of Organizational Behavior, Vol. 26, No. 4, pp. 379-408, 2005.   DOI
42 Perrow, C., "A framework for the comparative analysis of organizations," American Sociological Review, Vol. 32, No. 2, pp. 194-208, 1967.   DOI
43 Poppo, L. and Zenger, T., "Do formal contracts and relational governance function as substitutes or complements?," Strategic Management Journal, Vol. 23, No. 8, pp. 707-725, 2002.   DOI
44 Goodhue, D. L., "Development and measurement validity of a task-technology fit instrument for user evaluations of information systems," Decision Sciences, Vol. 29, No. 1, pp. 105-138, 1998.   DOI
45 Khan, I. U., Hameed, Z., Yu, Y., Islam, T., Sheikh, Z., and Khan, S. U., "Predicting the Acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory," Telematics and Informatics, Vol. 35, No. 4, pp. 964-978, 2018.   DOI
46 Garbelli, M. E., "Market-Driven Management, Competitive Markets, and Performance Metrics," Symphonya-Emerging Issues in Management, Vol. 1, pp. 72-87, 2008.
47 Gebauer, J., Shaw, M. J., Gribbins, M. L., Gebauer, J., Shaw, M. J., and Gribbins, M. L., "Towards a specific theory of task-technology fit for mobile information systems," Journal of Strategic Information Systems, pp. 12-15, 2005.
48 Gorry, G. A. and Scott Morton, M. S., "A Framework for Management Information systems," Sloan Management Review Vol. 13, No. 1, pp. 55-70, 1971.
49 Junglas, I., Abraham, C., and Watson, R. T., "Task-technology fit for mobile locatable information systems," Decision Support Systems, Vol. 45, No. 4, pp. 1046-1057, 2008.   DOI
50 Ifinedo, P., "Measuring africa's e-readiness in the global networked economy: A nine-country data analysis," International Journal of Education and development using ICT, Vol. 1, No. 1, pp. 53-71, 2005.
51 Kim, N. J., Kim, J. O., Lee, J. E., Mydin, O., and Marzuki, A., "An influence of outdoor recreation participants' perceived restorative environment on wellness effect, satisfaction and loyalty," SHS Web of Conferences, Vol. 12, p. 01082, 2014.   DOI
52 Jubraj, R., Graham, T., and Ryan, E., "Redefine banking with artificial intelligence," Intell. Bank, pp. 1-20, 2018.
53 Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C., "Multivariate data analysis prentice hall," Upper Saddle River, NJ, 730, 1998.
54 Ho, V. T., Ang, S., and Straub, D., "When subordinates become it contractors: persistent managerial expectations in IT outsourcing," Information System Research, Vol. 14, No. 1, pp. 66-125, 2003.   DOI
55 Jeffery, M., "Data-Driven marketing: The 15 metrics everyone in marketing should know," John Wiley & Sons, 2010.
56 Karimi-Alaghehband, F. and Rivard, S., "IT outsourcing success: A dynamic capability-based model," Journal of Strategic Information Systems, Vol. 29, No. 1, pp. 101599, 2020.   DOI
57 Klopping, I. M. and Mckinney, E., "Extending the technology acceptance model and the task-technology fit model to consumer e-commerce," Information Technology, Learning and Performance Journal, Vol. 22, No. 1, pp. 35-48, 2004.
58 Wade, M. and Hulland, J., "Review: The resource-based view and information systems research: Review, extension, and suggestions for future research," MIS Quarterly, Vol. 28, No. 1, pp. 107-142, 2004.   DOI
59 Koh, C., Ang, S., and Straub, D. W., "IT outsourcing success: A psychological contract perspective," Information Systems Research, Vol. 15, No. 4, pp. 356-373, 2004.   DOI
60 Kuo, R. Z. and Lee, G. G., "KMS adoption: The effects of information quality", Management Decision, Vol. 47 No. 10, pp. 1633-1651, 2009.   DOI
61 Lee, C. C., Cheng, H. K., and Cheng, H. H., "An empirical study of mobile commerce in insurance industry: task-technology fit and individual differences," Decision Support Systems, Vol. 43, No. 1, pp. 95-110, 2007.   DOI
62 Mohamed, M. S., Khalifa, G. S. A., and Hamoud, A., "The mediation effect of innovation on the relationship between creativity and organizational productivity: An empirical study within public sector organizations in the UAE," Journal of Engineering and Applied Sciences, Vol. 14, No. 10, pp. 3234-3242, 2019.   DOI
63 Goodhue, D. L. and Thompson, R. L., "Task-technology fit and individual performance," MIS Quarterly, Vol. 19, No. 2pp. 213-236, 1995.   DOI
64 Grant, A. M., "The significance of task significance: Job performance effects, relational mechanisms, and boundary conditions," Journal of Applied Psychology, Vol. 93, No. 1, pp. 108-124, 2008.   DOI
65 Markus, M. L., "Power, politics and MIS implementation," Communication of the ACM, Vol. 26, No. 6, pp. 430-444, 1983.   DOI
66 Munoz, M. A., Kirley, M., and Halgamuge, S. K., "The algorithm selection problem on the continuous optimization domain," In Computational Intelligence in Intelligent Data Analysis, pp. 75-89, 2013.
67 Koo, C., Watia, Y., and Jungb, J.J., "Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations," International Journal of Information Management, Vol. 31, No. 5, pp. 445-459, 2011.   DOI
68 Muller, R. and Jugdev, K., "Critical success factors in projects," International Journal of Managing Projects in Business, Vol. 5, No. 4, pp. 757-775, 2012.   DOI
69 Li, L., Wang, Y., Xu, Y., and Lin, K. Y., "Meta-learning based industrial intelligence of feature nearest algorithm selection framework for classification problems," Journal of Manufacturing Systems, 2021.
70 Mihet, R. and Thomas, P., "The economics of big data and artificial intelligence," Disruptive Innovation in Business and Finance in the Digital World, Vol. 20, pp. 29-43, 2019.   DOI
71 Vansteenkiste, M., Lens, W., and Deci, E. L., "Intrinsic versus extrinsic goal contents in self-determination theory: Another look at the quality of academic motivation," Educational Psychologist, Vol. 41, No. 1, pp. 19-31, 2006.   DOI
72 Venkatesh, V., Ramesh, V., and Massey, A. P., "Understanding usability in mobile commerce," Communications of the ACM, Vol. 46, No. 12, pp. 53-56, 2003.   DOI
73 Nelson, R. R., Todd, P. A., and Wixom, B. H., "Antecedents of information and system quality: An empirical examination within the context of data warehousing," Journal of Management Information Systems, Vol. 21, No. 4, pp. 199-235, 2005.   DOI
74 Preacher, K. J. and Hayes, A. F., "Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models," Behavior Research Methods, Vol. 40, No. 3, pp. 879-891, 2008.   DOI
75 Rice, J. R., "The algorithm selection problem-abstract models," Department of Computer Science Technical Reports. Paper 99, 1975.
76 McAfee, A., "The impact of enterprise information technology adoption on operational performance: An empirical investigation," Production and Operations Management, Vol. 11, No. 1, pp. 33-53, 2002.   DOI
77 Li, Y. H., "An empirical investigation on the determinants of e-procurement adoption in Chinese manufacturing enterprises," In International Conference on Management Science & Engineering 15th Conference Proceedings, IEEE, pp. 32-37, 2008.
78 Rizwan, M., Hussain, S., Nawaz, M. S., and Hameed, W. U., "Impact of effective training program, job satisfaction and reward management system on the employee motivation with mediating role of employee commitment," Journal of Public Administration and Governance , Vol. 3, No. 3, p. 278, 2013.   DOI
79 Cunha, T., Soares, C., and de Carvalho, A. C., "Metalearning and recommender systems: A literature review and empirical study on the algorithm selection problem for collaborative filtering," Information Sciences, Vol. 423, pp. 128-144, 2018.   DOI
80 Narasimhaiah and Toni, "The impact of IT outsourcing on information systems success," Information & Management, Vol. 51, No. 3, pp. 320-335, 2014.   DOI
81 Ooka, R., Miyoshi, T., and Yamazaki, T., "Unit traffic classification and analysis on P2P video delivery using machine learning," IEICE Communications Express, Vol. 8, No. 12, pp. 640-645, 2019.   DOI
82 Park Y. J. and Rim, M. H., "The relationship analysis of RFID adoption and organizational performance," In ICSNC 2011, The Sixth International Conference on Systems and Networks Communications, pp. 76-82, 2011.
83 Yang, Z., Sun, J., Zhang, Y., and Wang, Y., "Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model," Computers in Human Behavior, Vol. 45, pp. 254-264, 2015.   DOI
84 Voola, R., Casimir, G., Carlson, J., and Agnihotri, M. A., "The effects of market orientation, technological opportunism, and e-business adoption on performance: A moderated mediation analysis," Australasian Marketing Journal, Vol. 20, No. 2, pp. 136-146, 2012.   DOI
85 Soon, K. W. K., Lee, C. A., and Boursier, P., "A study of the determinants affecting adoption of big data using integrated technology acceptance model (TAM) and diffusion of innovation (DOI) in Malaysia," Internation Journal of Applied Business and Economic Research, Vol. 14, No. 1, pp. 17-47, 2016.
86 Sultan, F. and Chan, L., "The adoption of new technology: The case of object-oriented computing in software companies," IEEE Transactions on Engineering Management, Vol. 47, No. 1, pp. 106-126, 2000.   DOI
87 Van de Ven, A. H. and Drazen, R., "Alternative forms of in contingency theory," Administrative Science Quarterly, Vol. 30, No. 4, pp. 514-539, 1985.   DOI
88 Webb, M., "The Impact of Artificial Intelligence on the Labor Market," Available at SSRN 3842150, 2019.
89 Brynjolfsson, E., Hitt, L. M., and Kim, H. H., "Strength in numbers: How does data-driven decision making affect firm performance?," Available at SSRN 1819486, 2011.
90 Hu, L. T. and Bentler, P. M., "Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification," Psychological Methods, Vol. 3, No. 4, pp. 424-453, 1998.   DOI
91 Wells, J. D., Sarker, S., Urbaczewski, A., and Sarker, S. U., "Studying customer evaluations of electronic commerce applications: A review and adaptation of the task-technology fit perspective," In 36Th Annual Hawaii International Conference On System Sciences, p. 10, 2003.
92 Wen, B., Jin, Y., and Kwon, O., "Effects of artificial intelligence functionalities on online store's image and continuance intention: A resource-based view perspective," The Journal of Society for e-Business Studies Vol.25, No.2, pp. 65-98, 2020.
93 Yuce, A., Abubakar, A. M., and Ilkan, M., "Intelligent tutoring systems and learning performance," Online Information Review, Vol.43, No. 4, pp. 600-616, 2019.   DOI
94 Saunders, C., Gebelt, M., and Hu, Q., "Achieving success in information systems outsourcing," California Management Review, Vol. 39, No. 2, pp. 63-79, 1997.   DOI
95 Zepeda, L., "Simultaneity of technology adoption and productivity," Journal of Agriculture and Resource Economics, pp. 46-57, 1994.
96 Zhou, T., Lu, Y., and Wang, B., "Integrating TTF and UTAUT to explain mobile banking user adoption," Computers in Human Behavior, Vol. 26, No. 4, pp. 760-767, 2010.   DOI
97 Zha, X., Yang, H., Yan, Y., Liu, K., and Huang, C., "Exploring the effect of social media information quality, source credibility and reputation on informational fit-to-task: Moderating role of focused immersion," Computers in Human Behavior, Vol. 79, pp. 227-237, 2018.   DOI
98 Zhai, C., "Research on post-adoption behavior of B2B e-marketplace in China," In 2010 International Conference on Management and Service Science, pp. 1-5, 2010.
99 Yuan, Y., Archer, N., Connelly, C. E., and Zheng, W., "Identifying the ideal fit between mobile work and mobile work support," Information & Management, Vol. 47, No. 3, pp. 125-137, 2010.   DOI