Theophilus Ehidiamen OAMEN


The technology acceptance model (TAM) is a popular measure of user adoption and acceptance of technology. The pharmaceutical marketing industry has largely incorporated technology-based applications to enhance operational efficiency, effectiveness, and client engagement in the past decade. No study has explored user acceptance by pharmaceutical executives in the context of technology's impact on performance. The study aims to explore the relationship between perceived ease of use (PEOU), perceived usefulness (PU), and behavioral intention (BIU) in the context of the perceived impact of technology on performance (TechIMP). Hypotheses were tested using factor-based structural equation modeling. A random sample of 282 marketing executives was drawn from pharmaceutical companies in Nigeria using an online questionnaire. The developed model provided acceptable measures of fit and validity. Significant positive relationships exist between PEOU, PU, and BIU, explaining 58% of the variance in TechIMP. PEOU had a stronger impact on BIU compared to PU. BIU was a significant link between PEOU and PU to TechIMP. Multigroup analysis showed key differences between male and female executives. The study adds to the existing literature by extending TAM to include TechIMP. Managers should enhance positive user perception and acceptance by engaging in simulated training before introducing new technology and ensuring flexibility of technology use.


Technology Acceptance Model; Human Resource Management; Pharmaceutical Marketing; Technology Impact; Performance

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Ahn, T., Ryu, S., and Han, I. 2004. The Impact of the Online and Offline Features on the User Acceptance of Internet Shopping Malls. Electronic Commerce Research and Applications, 3(4), pp. 405–20.

Alharbi, S. and Drew, S. 2014. Using the Technology Acceptance Model in Understanding Academics' Behavioral Intention to Use Learning Management Systems. International Journal of Advanced Computer Science and Applications, 5(1), pp. 143–155. DOI:

AlQudah, A. A., Al-Emran, M., and Shaalan, K. 2021. Technology Acceptance in Healthcare: A Systematic Review. Applied Sciences, 11(22), pp. 10537. DOI:

Amin, M., Rezaei, S., and Tavana, F. S. 2015. Gender Differences and Consumer's Repurchase Intention: The Impact of Trust Propensity, Usefulness and Ease of Use for the Implication of Innovative Online Retail. International Journal of Innovation and Learning, Vol. 17, No.2, pp. 217–233. DOI:

Bhattacharyya, S. S., Verma, S., and Sampath, G. 2020. Ethical Expectations and Ethnocentric Thinking: Exploring the Adequacy of Technology Acceptance Model for Millennial Consumers on Multisided Platforms. International Journal of Ethics and Systems, 36, pp. 465–489. DOI:

Blunch, N. 2016. Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS. Sage Publications: Thousand Oaks, CA, USA.

Chuah, S. H. W., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., and Lade, S. 2016. Wearable Technologies: The Role of Usefulness and Visibility in Smartwatch Adoption. Computers in Human Behavior, 65, pp. 276-284.

Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. 1989. User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), pp. 982–1003.

Davis, F. D., Granic, A., and Marangunic, N. 2023. The Technology Acceptance Model: 30 Years of TAM. Springer/Heldeberg, Germany.

Davis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance. MIS Quarterly, 13(3), pp. 319–39.

Davis, F. D. 1993. User Acceptance of Information Technology: System Characteristics, User Perceptions, and Behavioral Impacts. International Journal of Man-Machine Studies, 38 (3), pp. 475-487.

Diop, E. B., Zhao, S., and Duy, T. V. 2019. An Extension of the Technology Acceptance Model for Understanding Travelers' Adoption of Variable Message Signs. PLoS ONE 14(4): e0216007. DOI:

Falk, R. F. and Miller, N. B. 1992. A Primer for Soft Modeling. The University of Akron Press.

Fishbein, M. and Azjen, I. 1975. Belief, Attitude, Intention, and Behavior. Reading, MA: Addison-Wesley.

Goswami, A. and Dutta, S. 2016. Gender Differences in Technology Usage—A Literature Review. Open Journal of Business and Management, 4, pp. 51-59. DOI:

Greene, J. A. and Kesselheim, A. S. 2010. Pharmaceutical Marketing and the New Social Media. New England Journal of Medicine, 363(22), pp. 2087-2089.

Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. 2010. Multivariate Data Analysis (7th Ed). Upper Saddle River, NJ; Prentice Hall.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., and Ray, S. 2021. Evaluation of the Structural Model. in Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R Classroom Companion Business. Springer. DOI:

Henseler, J., Ringle, C. M., and Sarstedt, M. 2015. A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43, pp. 115-135.

Henseler, J., Ringle, C., and Sarstedt, M. 2016. Testing Measurement Invariance of Composites (PLS) Path Modeling: Alternative Methods and Empirical Results. Advances in International Marketing, 22, pp. 195–218.

Islam, M. A., Rahim, N. A. A., Liang, T. C., and Montaz, H. 2011. Effect of Demographic Factors on E-Learning Effectiveness in a Higher Learning Institution in Malaysia. International Education Studies, 4, pp. 112-122.

Jaradat, M. I. R. M. and Smadi, Z. M. A. 2013. Applying the Technology Acceptance Model to the Introduction of Mobile Healthcare Information Systems. International Journal of Behavioural and Healthcare Research, Vol. 4, No. 2, pp. 123–143.

Jordan, P. J. and Troth, A. C. 2020. Common Method Bias in Applied Settings: The Dilemma of Research in Organizations. Australian Journal of Management, 45(1), pp. 3-14. DOI:

Kim, H. W. and Chang, H. 2022. Medical Representatives' User Acceptance of Remote e-Detailing Technology: A Moderated Mediation Analysis of Technology Acceptance Model. Healthcare Informatics Research, 28(1), pp. 68-76. DOI:

Kock, N. and Hadaya, P. 2018. Minimum Sample Size Estimation in PLS-SEM. The Inverse Square Root and Gamma Exponential Method. Information Systems Journal, 28(1), pp. 227-261.

Kock, N. 2021. Harman's Single Factor Test in PLS-SEM; Checking for Common Method Bias. Data Analysis Perspective Journal, 2(2), pp. 1-6.

Kock, N. 2022. WarpPLS User Manual (latest version 8.0, 2022).

Kwak, H. W. and Chang, H. 2016. Medical Representatives' Intention to Use Information Technology in Pharmaceutical Marketing. Healthcare Informatics Research, 22(4), pp. 342-350. DOI:

Kwak, H. W. and Chang, H. 2022. Medical Representatives' User Acceptance of Remote E-Detailing Technology: A Moderated Mediation Analysis of Technology Acceptance Model. Healthcare Informatics Research, 28(1), pp. 68-76. DOI:

Lerer, L. 2002. E-business in the Pharmaceutical Industry. Journal of Medical Marketing, 3(1), pp. 69-73.

Liang, B. A. and Mackey, T. K. 2011. Prevalence and Global Health Implications of Social Media in Direct-to-Consumer Drug Advertising. Journal of Medical Internet Research, 13(3), pp. e64.

McKinsey. 2017. Winning in Nigeria: Pharma's Next Frontier. McKinsey and Company, May, 2017. [] [accessed January 2022].

Molloy. W., Strang, D., Guyatt, G., Lexchin, J., Bedard, M., Dubois, S., and Russo. 2002. Assessing the Quality of Drug Detailing. Journal of Clinical Epidemiology, 55(8), pp. 825-832. DOI:

Moqbel, M., Guduru, R., and Harun, A. 2020. Testing Mediation via Indirect Effects in PLS-SEM: A Social Networking Site Illustration. Data Analysis Perspectives Journal, 1(3), pp. 1-6.

Nguyen, M., Fujioka, J., Wentlandt, K., Onabajo, N., Wong, I., Bhatia, R. S., Bhattacharyya, O., and Stamenova, V. 2020. Using the Technology Acceptance Model to Explore Health Provider and Administrator Perceptions of the Usefulness and Ease of Using Technology in Palliative Care. BMC Palliative Care, 19, pp. 138.

Oamen, T. E. 2021. COVID-19 Pandemic and Impact on Pharmaceutical Sales Representatives' Operations in West Africa: A Socio-Demographic Case Study of Nigeria. African Journal of Social Science and Humanities Research, 4(1), pp. 59-72.

Oamen, T. E. 2023. The Moderating Role of Perceived Reward on Leadership and Policy Involvement Effects on Job Performance among Pharmaceutical Managers. Business Management Analysis Journal, 6(1), pp. 38-57.

Oamen, T. E. and Ihekoronye, M. R. 2022. Are there differences in perception of predictors of satisfaction with work among pharmaceutical executives? A WarpPLS Multigroup Assessment. Management Analysis Journal, 11(4), pp. 314-320.

Oamen, T. E., Idiake, J., and Omorenuwa, S. O. 2022. Assessment of Measurement Invariance of Psychometric Tool for Pharmaceutical Sales Executives: Implications for Social and Behavioral Pharmacy Research. Journal of Pharmaceutical Health Services Research, 13(4), pp. 262-268. DOI:

Okazaki, S. and Santos, L. M. R. 2012. Understanding E-Learning Adoption in Brazil: Major Determinants and Gender Effects. International Review of Research in Open and Distributed Learning, 13, pp. 91-106.

Ong, C. S. and Lai, J. Y. 2006. Gender Differences in Perceptions and Relationships among Dominants of E-Learning Acceptance. Computers in Human Behaviour, 22, pp. 816-826. DOI:

Onyeachu, P. and Clarke, M. 2022. A Patient Technology Acceptance Model (PTAM) for Adoption of Telehealth. Digital Medicine and Health Technology, 2022(0), pp. 1–19. DOI:

Pertiwi, F., Masudin, I., Zulfikarijah, F., Restuputri, D. P., and Setiawan, M. (2022) Technology Acceptance Model of Tuberculosis Integrated Information System in Indonesian Primary Healthcare. Cogent Public Health, 9(1), pp. 2151929. DOI:

Sarstedt, M., Henseler, J., and Ringle, C. 2011. Multigroup Analysis in Partial Least Squares Using Partial Least Squares. International Marketing Review, 33(3), pp. 405-431.

Shabaninejad, H., Mirsalehian, M. H., and Mehralian, G. 2014. Development of an Integrated Performance Measurement (PM) Model for the Pharmaceutical Industry. Iranian Journal of Pharmaceutical Research, 13, pp. 207-215.

Shen, A. X. L., Lee, M. K. O., Cheung, C. M. K., and Chen, H. 2010. Gender Differences in Intentional Social Action: We-Intention to Engage in Social Network-Facilitated Team Collaboration. Journal of Information Technology, 25, pp. 152-169. DOI:

Su, Y. and Li, M. 2021. Applying Technology Acceptance Model in Online Entrepreneurship Education for New Entrepreneurs. Frontiers in Psychology, 12, pp. 713239. DOI:

Suki, N. M. And Ramayah, T. 2010. User Acceptance of the E-Government Services in Malaysia: Structural Equation Modeling Approach. Interdisciplinary Journal of Information, Knowledge, and Management, 5, pp. 395-412.

Venkatesh, V. 2000. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, Volume 11, Issue 4, pp. 342-365. DOI:



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