The Effectiveness of e-Recruitment Adoption: A TAM Approach Examining User Perspectives

Jump To References Section

Authors

  • M.P. Birla Institute of Management, Associates Bharatiya Vidya Bhavan, Bangalore – 560001, Karnataka ,IN
  • Department of Management Studies, M. S. Ramaiah Institute of Technology, Bangalore – 560054, Karnataka ,IN
  • Department of Management, Yenepoya (Deemed to be University), Bengaluru – 560064, Karnataka ,IN
  • Department of Management Studies, M. S. Ramaiah Institute of Technology, Bangalore – 560054, Karnataka ,IN

DOI:

https://doi.org/10.18311/sdmimd/2024/41928

Keywords:

e-Recruitment, Innovation, Perceived Ease of Use, Perceived Enjoyment, Perceived Usefulness, Talent Management, Technology Acceptance Model
JEL Classification: O15, J24, E24, J62

Abstract

E-recruitment and its effective implementation is necessary for organizations that focus to channelize hiring, reduce costs, and attract a diverse talent pool in the present era. It is vital to understand and analyse the adoption of e-recruitment websites by job-seekers in India by focusing on factors like perceived usefulness, perceived enjoyment, and perceived ease of use. The main goal of this study is to establish the relationship between these antecedents and the user acceptance of e-recruitment in the Indian context. This cross-sectional study with descriptive research design used purposive sampling. The responses on pre-tested research instrument was collected from 612 respondents that validated the degree of relationship among the chosen factors. Perceived ease of use and pleasure positively correlated with perceived usefulness. Perceived usefulness positively impacts e-recruitment website usage. This research examined job-seekers’ acceptance of online recruiting using the Technology Acceptance Model (TAM). This study is beneficial for Human Resource (HR) recruiters, research scholars, HR professionals, job seekers, manpower consultants, and those who use technology to recruit employees. The study found that perceived enjoyment and perceived usefulness of the technology were two major drivers of job-seekers attitude towards adoption of e- recruitment websites in India at (p<0.001). The research would assist decision-makers understand recruiting website adoption antecedents. The widespread adoption of this technology will help in economizing for both firms and job-seekers, apart from knowing the job-seekers behavioural intent to adopt internet recruitment websites.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Downloads

Published

2024-03-28

How to Cite

Sathyanarayana, S., Mohanasundaram, T., Shanthi, D., & Rajendra, P. (2024). The Effectiveness of e-Recruitment Adoption: A TAM Approach Examining User Perspectives. SDMIMD Journal of Management, 15, 87–99. https://doi.org/10.18311/sdmimd/2024/41928

Issue

Section

Articles

 

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi. org/10.1016/0749-5978(91)90020-T. DOI: https://doi.org/10.1016/0749-5978(91)90020-T

Akinci, S., Aksoy, S., & Atilgan, E. (2004). Adoption of internet banking among sophisticated consumer segments in an advanced developing country. International Journal of Bank Marketing, 22(3), 212- 232. https://doi.org/10.1108/02652320410530322. DOI: https://doi.org/10.1108/02652320410530322

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi. org/10.1007/BF02723327. DOI: https://doi.org/10.1177/009207038801600107

Baker-Eveleth, L., & Stone, R. W. (2015). Usability, expectation, confirmation, and continuance intentions to use electronic textbooks. Behaviour and Information Technology, 34(10), 992-1004. https://doi.org/10.1080/0144929X.2015.1039061. DOI: https://doi.org/10.1080/0144929X.2015.1039061

Bartram, D. (2000). Internet recruitment and selection: Kissing frogs to find princes. International Journal of Selection and Assessment, 8(4), 261-274. https:// doi.org/10.1111/1468-2389.00155. DOI: https://doi.org/10.1111/1468-2389.00155

Buil, I., Catalan, S., & Martínez, E. P. (2020). Understanding applicants’ reactions to gamified recruitment. Journal of Business Research, 110, 41-50. https://doi.org/10.1016/j. jbusres.2019.12.041 DOI: https://doi.org/10.1016/j.jbusres.2019.12.041

Cappelli, P. (2001). Making the most of on-line recruiting. Harvard Business Review, 79(3), 139-148. https://doi.org/10.1016/j.heliyon.2022. e09208.

Chiu, C. M., & Wang, E. T. (2008). Understanding Web-based learning continuance intention: The role of subjective task value. Information and Management, 45(3), 194-201. https://doi. org/10.1016/j.im.2008.02.003. DOI: https://doi.org/10.1016/j.im.2008.02.003

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. https://doi.org/10.1007/BF02310555. DOI: https://doi.org/10.1007/BF02310555

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https:// doi.org/10.2307/249008. DOI: https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/ mnsc.35.8.982. DOI: https://doi.org/10.1287/mnsc.35.8.982

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of Applied Social Psychology, 22(14), 1111-1132. https://doi. org/10.1111/j.1559-1816.1992.tb00945.x. DOI: https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Dessler, G. (2004). A framework for human resource management. Pearson Education India.

Eriksson, K., Kerem, K., & Nilsson, D. (2005). Customer acceptance of internet banking in Estonia. International Journal of Bank Marketing, 23(2), 200- 216. https://doi.org/10.1108/02652320510584412. Everett, M. R. (1995). Diffusion of innovations. New York, 12. DOI: https://doi.org/10.1108/02652320510584412

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi. org/10.2307/3151312. DOI: https://doi.org/10.1177/002224378101800104

Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8. https://doi.org/10.17705/1jais.00008. DOI: https://doi.org/10.17705/1jais.00008

Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358-390. https://doi.org/10.1016/j.jengtecman.2012.03.007. DOI: https://doi.org/10.1016/j.jengtecman.2012.03.007

Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695- 704. https://doi.org/10.2307/25148660. DOI: https://doi.org/10.2307/25148660

Hong, W., Thong, J. Y., Wong, W. M., & Tam, K. Y. (2002). Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97-124. https://doi.org/10.1080/07421222.2002.11045692. DOI: https://doi.org/10.1080/07421222.2002.11045692

Kim, J., Ma, Y. J., & Park, J. (2009). Are US consumers ready to adopt mobile technology for fashion goods? An integrated theoretical approach. Journal of Fashion Marketing and Management: An International Journal, 13(2), 215-230. DOI: https://doi.org/10.1108/13612020910957725

Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications.

Lancaster, K. J. (1966). A new approach to consumer theory. Journal of Political Economy, 74(2), 132- 157. https://doi.org/10.1086/259131. DOI: https://doi.org/10.1086/259131

Lee, I. (2005). The evolution of e-recruiting: a content analysis of Fortune 100 career web sites. Journal of Electronic Commerce in Organizations, 3(3), 57-68. https://doi.org/10.4018/jeco.2005070104. DOI: https://doi.org/10.4018/jeco.2005070104

Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information and Management, 42(8), 1095-1104. https://doi.org/10.1016/j.im.2003.10.007. DOI: https://doi.org/10.1016/j.im.2003.10.007

Li, H., & Liu, Y. (2014). Understanding post-adoption behaviors of e-service users in the context of online travel services. Information and Management, 51(8), 1043-1052. https://doi.org/10.1016/j. im.2014.07.004. DOI: https://doi.org/10.1016/j.im.2014.07.004

Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology.

Lim, S. H., Hur, Y., Lee, S., & Koh, C. E. (2009). Role of trust in adoption of online auto insurance. Journal of Computer Information Systems, 50(2), 151-159. https://doi.org/10.1080/08874417.2009.1 1645394.

Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers and Education, 58(1), 88-99. https://doi.org/10.1016/j. compedu.2011.07.008. DOI: https://doi.org/10.1016/j.compedu.2011.07.008

Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International journal of medical informatics, 84(1), 36-47. https://doi.org/10.1016/j. ijmedinf.2014.09.004. DOI: https://doi.org/10.1016/j.ijmedinf.2014.09.004

Mathwick, C., Malhotra, N. K., & Rigdon, E. (2002). The effect of dynamic retail experiences on experiential perceptions of value: an Internet and catalog comparison. Journal of Retailing, 78(1), 51-60. https://doi.org/10.1016/S0022- 4359(01)00066-5. DOI: https://doi.org/10.1016/S0022-4359(01)00066-5

Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217-230. https://doi. org/10.1016/S0378-7206(00)00061-6. Palmer, J. W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151-167. https://doi.org/10.1287/ isre.13.2.151.88. DOI: https://doi.org/10.1016/S0378-7206(00)00061-6

Pin, J. R., Laorden, M., & Saenz-Diez, I. (2001). Internet recruiting power: Opportunities and effectiveness (No. D/439). IESE Business School.

Ployhart, R. E., Schneider, B., & Schmitt, N. (2005). Staffing organizations: Contemporary practice and theory. CRC Press. https://doi. org/10.1201/9781439847053. DOI: https://doi.org/10.1201/9781439847053

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. https://doi. org/10.1037/0021-9101.88.5.879. DOI: https://doi.org/10.1037/0021-9010.88.5.879

Polatoglu, V. N., & Ekin, S. (2001). An empirical investigation of the Turkish consumers’ acceptance of Internet banking services. International Journal of Bank Marketing, 19(4), 156-165. https://doi. org/10.1108/02652320110392527. DOI: https://doi.org/10.1108/02652320110392527

Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling. Psychology Press. DOI: https://doi.org/10.4324/9781410610904

Shen, J., & Eder, L. B. (2009). Exploring intentions to use virtual worlds for business. Journal of Electronic Commerce Research, 10(2), 94-103.

Singh, P., & Finn, D. (2003). The effects of information technology on recruitment. Journal of Labor Research, 24(3), 395-408. https://doi.org/10.1007/ s12122-003-1003-4. DOI: https://doi.org/10.1007/s12122-003-1003-4

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. https:// doi.org/10.1111/j.1540-5915.1996.tb00860.x. DOI: https://doi.org/10.1111/j.1540-5915.1996.tb00860.x

Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Science, 39(2), 273-312. https://doi.org/10.1111/j.1540- 5915.2008.00192.x. DOI: https://doi.org/10.1111/j.1540-5915.2008.00192.x

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/ mnsc.46.2.186.11926. DOI: https://doi.org/10.1287/mnsc.46.2.186.11926

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), 425-478. https://doi.org/10.2307/30036540. DOI: https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412. DOI: https://doi.org/10.2307/41410412

Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6), 747-762. https://doi.org/10.1016/j.im.2003.08.011. DOI: https://doi.org/10.1016/j.im.2003.08.011

Williams, M., & Klau, B. (1997). 10 easy tips for recruiting online. Workforce, 76(8), 13-17.

Wu, P. F. (2009). User acceptance of emergency alert technology: A case study. Proceedings of the 6th International ISCRAM Conference–Gothenburg, Sweden.