Investigating the Intention to Use an Electronic Performance Management System at XYZ Holdings Limited: Towards a Revised Technology Acceptance Model
DOI:
https://doi.org/10.14738/abr.91.9602Keywords:
e-PMS, Technology Acceptance Model, Intention to Use.Abstract
This paper investigates the intention to use an electronic Performance Management System (e-PMS) through a conceptual framework derived from the Technology Acceptance Model where several constructs were put under investigation. The positivist approach was adopted in view of collecting primary data from a sample of 52 employees working at XYZ Holdings Limited through a structured survey questionnaire comprising of 25 items segregated under 6 sections. Research findings revealed a positive individual relationship between each independent variable; perceived usefulness, perceived ease of use, attitude and accessibility with intention to use the e-PMS respectively. Gender, age, grade and working experience were found to be statistically insignificant. However, when analyzing the constructs simultaneously as a whole model, only perceived ease of use and attitude were found to be statistically significant towards the intention to use the software. The derived model will be useful not only to the management of XYZ Holdings Limited but also to other companies which intend to adopt a new technology while at the same time serves as a base for future research in this field.
References
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Caligiuri P (2000), The big Five Personality Characteristics as Predictors of Expatriate’s Desire to Terminate the Assignment and Supervisor-rated Performance. Personnel Psychology, Vol. 5, No. 3, pp. 67-88.
Chau, P. and Hu, P. (2001) Information Technology Acceptance by Individual Professionals: A Model of Comparison Approach’, Decision Sciences, Vol. 32, No. 4, pp. 699‐719.
Cho, Y. C. and Esen, S. (2015), Exploring Factors That Affect Usefulness, Ease Of Use, Trust, And Purchase Intention In The Online Environment, International Journal of Management and Information Systems, Vol. 19, No. 1, pp. 21-35.
Cochran, W. G. (1977), ‘Sampling Techniques’. Third Edition. New York: John Wiley & Sons.
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Davis, F. D. (1985), ‘A technology acceptance model for empirically testing new end-user information systems: theory and results’. PhD Thesis, Massachusetts Institute of Technology, Sloan School of Management, USA.
Davis, F. D. (1989), Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.
El-Roubi, A. ‘Evaluation of E-Performance Assessment System in the UNRWA Headquarter in Gaza’, MBA Thesis, The Islamic University, Gaza.
Frayne, C. A. and Geringer. J. M. (2005), Self-Management Training for Joint Venture General Managers, Journal of Human Resource Planning, Vol. 1, N0. 5, PP. 69-85.
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Goh, S. L., Zulkifli, M., Lada, S. and Amboala, T. (2011), An Exploration of Social Networking Sites (SNS) Adoption in Malaysia Using Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) And Intrinsic Motivation, Journal of Internet Banking and Commerce, Vol. 17, No. 3, pp. 1–14.
Hawking, P., Stein, A. and Foster, S. (2004), e-HR and Employee Self Service: A Case Study of a Victorian Public Sector Organisation, Issues in Informing Science and Information Technology, pp. 1017-1026.
Heijden, H. V. D. (2004), User Acceptance of Hedonic Information Systems, MIS Quarterly, Vol. 28, No. 4, pp. 695-704.
Henseler, J., Ringle, C. and Sinkovics, R. (2009), The use of partial least squares path modeling in international marketing, Advances in International Marketing, Vol. 20, pp. 277-320.
Hershey, P. and Blanchard, K. H. (1982), ‘Management of organizational behaviour: Utilizing human resources’. Englewood Cliffs: Prentice-Hall.
Hofstede, D (1997), ‘Culture and Organizations: Software of the Mind’. New York: McGraw-Hill.
Hong, I. B. (2018), Social and personal dimensions as predictors of sustainable intention to use facebook in Korea: An empirical analysis, Sustainability, Vol.10, No. 8.
Jarrar, Y. and Schiuma, G. (2007). ,Measuring performance in the public sector: challenges and trends, Measuring Business Excellence, Vol. 11, No. 4, pp. 4-8.
Johnson, R. and Gueutal, H. (2011), ‘The use of e-hr and HRIS in organizations’. Alexandria Virginia: SHRM Foundation.
Kasse, J. P, Moya, M., Nansubuga, A. K. (2016), Facilitating Condition for E-learning Adoption—Case of Ugandan Universities, Journal of Communication and Computer, Vol.12, No. 2015, pp. 244-249.
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Kettner, G. (2017), 7 risks of poorly implemented performance management programs [Online] https://www.govloop.com/community/blog/7-risks-poorly-implemented-performance-management-programs/ [Accessed on 01-02-2020].
Kim, S. (2008), Moderating effects of Job Relevance and Experience on mobile wireless technology acceptance: Adoption of a smartphone by individuals, Journal of Information and Management, Vol. 45, No. 6, pp. 387-393.
King, W. R. and He, J. (2006), A meta-analysis of the technology acceptance model, Journal of Information and Management, Vol. 43, No. 6, pp. 740-755.
Lee, Y., Kozar, K. A. and Larsen, K. R. T. (2003), The Technology Acceptance Model: Past, present, and Future. Communications of the Association for Information Systems, Vol. 12, pp. 752–780.
Mckenna, M., Shelton, C. and Darling, J. (2002), The Impact of Behavioral Style Assessment on Organization Effectiveness: A Call for action, Leadership Organisational Development Journal, Vol. 2, No.23, pp. 314-322.
Morris, G. and Venkatesh, V. (2000), Age differences in technology adoption decisions: Implications for a changing work force, Journal of Personnel Psychology, Vol. 53, No. 2, pp. 375-403.
Njeje, D., Chepkilot, R. and Ochieng, I. (2018), E-Performance Management Systems and Organisation Performance of Sacco’s in Kenya, Journal of Business and Management, Vol. 20, No.5, pp.89-98.
P. Legris, J. Ingham and P. Collerette (2003), Why do people use information technology? A critical review of the technology acceptance model, Journal of Information and Management, Vol. 40, No. 3), pp. 191–204.
Park, S. Y. (2009a), An Analysis of the Technology Acceptance Model in Understanding University Student‘s Awareness to Using Internet of Things, Proceedings of the 2017 International Conference on E-commerce, E-Business and E-Government June 2017, pp. 61–64.
Park, S. Y. (2009b), An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning, Journal of Educational Technology and Society, Vol. 12, No. 3, pp. 150–162.
Rambe, P. (2011), Exploring the Impacts of Social Networking Sites on Academic Relations in the University, Journal of Information Technology Education, Vol. 10, pp. 271-293.
Rauniar, R., Rawski, G., Yang, J. and Johnson, B. (2014), Technology acceptance model (TAM) and social media usage: An empirical study on Facebook, Journal of Enterprise Information and Management, Vol. 27, No. 1, pp. 6–30.
Researchgate.net (2020), Accessibility – Science topic [Online] https://www.researchgate.net/topic/Accessibility [Accessed on 27-04-2020]
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Salloum, S. A. and Shaalan, K. (2018), Investigating students’ acceptance of E-learning system in Higher Educational Environments in the UAE: Applying the Extended Technology Acceptance Model (TAM) [Online] https://www.researchgate.net/publication/327418762_Investigating_students'_acceptance_of_E_learning_system_in_Higher_Educational_Environments_in_the_UAE_Applying_the_Extended_Technology_Acceptance_Model_TAM [Accessed on 27-04-2020]
Sauro, J. (2011), Measuring Usability with the System Usability Scale (SUS) [Online] https://measuringu.com/sus/ [Accessed on 04-02-2020]
Suki, N. M. and Suki, N. M. (2011), Exploring the Relationship Between Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment, Attitude and Subscribers‘ Intention Towards Using 3G Mobile Services, Journal of Information Technology and Management, Vol. 22, No. 1, pp. 1-7.
Tao, D. (2009), Intention to use and actual use of electronic information resources: further exploring Technology Acceptance Model (TAM), AMIA Proceedings, Vol. 2009, pp. 629–633.
Tavakol, M. and Dennick, R. (2011), Making Sense of Cronbach’s Alpha, International Journal of Medical Education, Vo. 2, No. 2, pp. 53-55.
Venkatesh, V. and Davis, F. D. (2000), A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, Journal of Information and Management, Vol. 46, No. 2, pp. 186–204.
Wagner, H., Dainty, A., Hague, R., Tuck, C. and Ong, M. H. (2008), The effects of new technology adoption on employee skills in the prosthetics profession, International Journal of Production Research, Vol. 46, No. 22, pp. 6461-6478
Wang, W. and Liu, Y. J. (2015), Attitude, Behavioral Intention and Usage : An Empirical Study of Taiwan Railway’s Internet Ticketing System, Taiwan Natl. Taiwan Ocean Univ., Vol. 2, No. 2015, pp. 72–83.
Weng, F., Yang, R. J., Ho, H. J. and Su, H. M. (2018), A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers, Journal of Application System Innovation, Vol. 1, No. 3, pp. 36.
Wu, J. and Wang, S. (2005), What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, Journal of Information and Management, Vol 42, No.2, pp.719-729.
Alfridi, W. A. K., Hashim, H. and Mudiarasan, K. (2020), The Critical Success Factors of Professional Networking Sites‘ Adoption by University Students, Test Engineering and Management, Vol. 82, pp. 653-673.
Al-Raisi, A., Amin, S. and Tahir, S. (2011), Evaluation of e-performance analysis and assessment in the United Arab Emirates (UAE) Organizations, Journal of internet and information system, Vol. 2, No. 2, pp. 20 – 27.
Armstrong M (2006), ‘Performance Management: Key Strategies and Practical Guidelines’. London: Kogan Page Limited.
Armstrong, M. and Murlis, H. (1994), ‘Reward Management: A handbook of remuneration strategy and practice’. London: Kogan Page Limited.
Bagozzi, R. P., Davis, F. D., and Warshaw, P. R. (2012). Development and Test of a Theory of Technological Learning and Usage, Journal of Human Relations, Vol. 45, No. 7.
Bartlett, J. E., Kotrlik, J. W. and Higgins, C. C. (2001), Organisational Research: Determining Appropriate Sample Size in Survey Research, Information Technology, Learning, and Performance Journal, Vol. 19, No. 1, pp. 43–50.
Bell, S., Lee, S. and Yeung S. (2006), The Impact of eHR on Professional Competence in HRM: Implications for the Development of HR Professionals, Center for Advanced Human Resource Studies, Vol. 6, No. 3.
Bhattacharyya, D.K. (2020), Performance Management and Strategies [Online] https://www.oreilly.com/library/view/performance-management-systems/9789332503335/ xhtml/ch5-sub176.xhtml [Accessed on 02-02-2020].
Bhattacherjee, A. (2012), Social Science Research: Principles, Methods and Practices [Online] http://scholarcommons.usf.edu/oa_textbooks/3 [Accessed on 29-04-2020].
Budu, K. W. A., Yinping, M. and Mireku, K. K. (2018), Investigating The Effect of Behavioral Intention on E-learning Systems Usage: Empirical Study on Tertiary Education Institutions in Ghana, Mediterranean Journal of Social Sciences, Vol. 9, No. 3, pp. 201–216, 2018.
Caligiuri P (2000), The big Five Personality Characteristics as Predictors of Expatriate’s Desire to Terminate the Assignment and Supervisor-rated Performance. Personnel Psychology, Vol. 5, No. 3, pp. 67-88.
Chau, P. and Hu, P. (2001) Information Technology Acceptance by Individual Professionals: A Model of Comparison Approach’, Decision Sciences, Vol. 32, No. 4, pp. 699‐719.
Cho, Y. C. and Esen, S. (2015), Exploring Factors That Affect Usefulness, Ease Of Use, Trust, And Purchase Intention In The Online Environment, International Journal of Management and Information Systems, Vol. 19, No. 1, pp. 21-35.
Cochran, W. G. (1977), ‘Sampling Techniques’. Third Edition. New York: John Wiley & Sons.
Constantinides, E. and Lorenzo-Romero, C. (2013), Social Networking Sites as Business Tool: A Study of User Behavior, Business Process Management, SCI 444, pp. 221-240.
Davis, F. D. (1985), ‘A technology acceptance model for empirically testing new end-user information systems: theory and results’. PhD Thesis, Massachusetts Institute of Technology, Sloan School of Management, USA.
Davis, F. D. (1989), Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.
El-Roubi, A. ‘Evaluation of E-Performance Assessment System in the UNRWA Headquarter in Gaza’, MBA Thesis, The Islamic University, Gaza.
Frayne, C. A. and Geringer. J. M. (2005), Self-Management Training for Joint Venture General Managers, Journal of Human Resource Planning, Vol. 1, N0. 5, PP. 69-85.
Frost, J. (2020), How to interpret regression models that have significant variables but a low R-squared [Online] https://statisticsbyjim.com/regression/low-r-squared-regression/ [Accessed on 29-04-2020].
Fryer, K., Antony, J. and Ogden, S. (2009), Performance management in the public sector, International Journal of Public Sector Management, Vol.22, No. 6, pp. 478-498.
Gefen, D. and Straub, D. W. (1997), Gender differences in the perception and use of E-mail: An extension to the technology acceptance model, MIS Quarterly, Vol. 21, No. 4, pp. 389–400.
Goh, S. L., Zulkifli, M., Lada, S. and Amboala, T. (2011), An Exploration of Social Networking Sites (SNS) Adoption in Malaysia Using Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) And Intrinsic Motivation, Journal of Internet Banking and Commerce, Vol. 17, No. 3, pp. 1–14.
Hawking, P., Stein, A. and Foster, S. (2004), e-HR and Employee Self Service: A Case Study of a Victorian Public Sector Organisation, Issues in Informing Science and Information Technology, pp. 1017-1026.
Heijden, H. V. D. (2004), User Acceptance of Hedonic Information Systems, MIS Quarterly, Vol. 28, No. 4, pp. 695-704.
Henseler, J., Ringle, C. and Sinkovics, R. (2009), The use of partial least squares path modeling in international marketing, Advances in International Marketing, Vol. 20, pp. 277-320.
Hershey, P. and Blanchard, K. H. (1982), ‘Management of organizational behaviour: Utilizing human resources’. Englewood Cliffs: Prentice-Hall.
Hofstede, D (1997), ‘Culture and Organizations: Software of the Mind’. New York: McGraw-Hill.
Hong, I. B. (2018), Social and personal dimensions as predictors of sustainable intention to use facebook in Korea: An empirical analysis, Sustainability, Vol.10, No. 8.
Jarrar, Y. and Schiuma, G. (2007). ,Measuring performance in the public sector: challenges and trends, Measuring Business Excellence, Vol. 11, No. 4, pp. 4-8.
Johnson, R. and Gueutal, H. (2011), ‘The use of e-hr and HRIS in organizations’. Alexandria Virginia: SHRM Foundation.
Kasse, J. P, Moya, M., Nansubuga, A. K. (2016), Facilitating Condition for E-learning Adoption—Case of Ugandan Universities, Journal of Communication and Computer, Vol.12, No. 2015, pp. 244-249.
Kassim, N. H., Noor, N. M., Kasuma, J. and Saleh, J (2019), Impact of perceived usefulness, perceived ease of use and behavioural intention in using whatsapp towards job [Online] https://www.researchgate.net/publication/332190271_IMPACT_OF_PERCEIVED_USEFULNESS_PERCEIVED_EASE_OF_USE_AND_BEHAVIORAL_INTENTION_IN_USING_WHATSAPP_TOWARDS_JOB_PERFORMANCE [Accessed on 27-04-2020].
Kettner, G. (2017), 7 risks of poorly implemented performance management programs [Online] https://www.govloop.com/community/blog/7-risks-poorly-implemented-performance-management-programs/ [Accessed on 01-02-2020].
Kim, S. (2008), Moderating effects of Job Relevance and Experience on mobile wireless technology acceptance: Adoption of a smartphone by individuals, Journal of Information and Management, Vol. 45, No. 6, pp. 387-393.
King, W. R. and He, J. (2006), A meta-analysis of the technology acceptance model, Journal of Information and Management, Vol. 43, No. 6, pp. 740-755.
Lee, Y., Kozar, K. A. and Larsen, K. R. T. (2003), The Technology Acceptance Model: Past, present, and Future. Communications of the Association for Information Systems, Vol. 12, pp. 752–780.
Mckenna, M., Shelton, C. and Darling, J. (2002), The Impact of Behavioral Style Assessment on Organization Effectiveness: A Call for action, Leadership Organisational Development Journal, Vol. 2, No.23, pp. 314-322.
Morris, G. and Venkatesh, V. (2000), Age differences in technology adoption decisions: Implications for a changing work force, Journal of Personnel Psychology, Vol. 53, No. 2, pp. 375-403.
Njeje, D., Chepkilot, R. and Ochieng, I. (2018), E-Performance Management Systems and Organisation Performance of Sacco’s in Kenya, Journal of Business and Management, Vol. 20, No.5, pp.89-98.
P. Legris, J. Ingham and P. Collerette (2003), Why do people use information technology? A critical review of the technology acceptance model, Journal of Information and Management, Vol. 40, No. 3), pp. 191–204.
Park, S. Y. (2009a), An Analysis of the Technology Acceptance Model in Understanding University Student‘s Awareness to Using Internet of Things, Proceedings of the 2017 International Conference on E-commerce, E-Business and E-Government June 2017, pp. 61–64.
Park, S. Y. (2009b), An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning, Journal of Educational Technology and Society, Vol. 12, No. 3, pp. 150–162.
Rambe, P. (2011), Exploring the Impacts of Social Networking Sites on Academic Relations in the University, Journal of Information Technology Education, Vol. 10, pp. 271-293.
Rauniar, R., Rawski, G., Yang, J. and Johnson, B. (2014), Technology acceptance model (TAM) and social media usage: An empirical study on Facebook, Journal of Enterprise Information and Management, Vol. 27, No. 1, pp. 6–30.
Researchgate.net (2020), Accessibility – Science topic [Online] https://www.researchgate.net/topic/Accessibility [Accessed on 27-04-2020]
Robson, C. (2012), ‘Real World Research’. Second Edition. Oxford: Blackwell.
Salloum, S. A. and Shaalan, K. (2018), Investigating students’ acceptance of E-learning system in Higher Educational Environments in the UAE: Applying the Extended Technology Acceptance Model (TAM) [Online] https://www.researchgate.net/publication/327418762_Investigating_students'_acceptance_of_E_learning_system_in_Higher_Educational_Environments_in_the_UAE_Applying_the_Extended_Technology_Acceptance_Model_TAM [Accessed on 27-04-2020]
Sauro, J. (2011), Measuring Usability with the System Usability Scale (SUS) [Online] https://measuringu.com/sus/ [Accessed on 04-02-2020]
Suki, N. M. and Suki, N. M. (2011), Exploring the Relationship Between Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment, Attitude and Subscribers‘ Intention Towards Using 3G Mobile Services, Journal of Information Technology and Management, Vol. 22, No. 1, pp. 1-7.
Tao, D. (2009), Intention to use and actual use of electronic information resources: further exploring Technology Acceptance Model (TAM), AMIA Proceedings, Vol. 2009, pp. 629–633.
Tavakol, M. and Dennick, R. (2011), Making Sense of Cronbach’s Alpha, International Journal of Medical Education, Vo. 2, No. 2, pp. 53-55.
Venkatesh, V. and Davis, F. D. (2000), A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, Journal of Information and Management, Vol. 46, No. 2, pp. 186–204.
Wagner, H., Dainty, A., Hague, R., Tuck, C. and Ong, M. H. (2008), The effects of new technology adoption on employee skills in the prosthetics profession, International Journal of Production Research, Vol. 46, No. 22, pp. 6461-6478
Wang, W. and Liu, Y. J. (2015), Attitude, Behavioral Intention and Usage : An Empirical Study of Taiwan Railway’s Internet Ticketing System, Taiwan Natl. Taiwan Ocean Univ., Vol. 2, No. 2015, pp. 72–83.
Weng, F., Yang, R. J., Ho, H. J. and Su, H. M. (2018), A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers, Journal of Application System Innovation, Vol. 1, No. 3, pp. 36.
Wu, J. and Wang, S. (2005), What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, Journal of Information and Management, Vol 42, No.2, pp.719-729.
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Published
2021-01-28
How to Cite
Joomunbaccus, S. (2021). Investigating the Intention to Use an Electronic Performance Management System at XYZ Holdings Limited: Towards a Revised Technology Acceptance Model. Archives of Business Research, 9(1), 75–96. https://doi.org/10.14738/abr.91.9602
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