Journal of Organization and Human Behaviour

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Adoption of E-Recruitment Mobile Apps:A Study Based on UTAUT2 Framework


Affiliations
1 Department of HRM, Central University Jammu, Jammu & Kashmir, India
     

   Subscribe/Renew Journal


The growing role of technology has changed the prototype of E-recruitment process and transformed E-recruitment industry. Despite the popularity of technology and e-recruitment, there is a limited understanding of m-job search apps adoption in literature. To understand the adoption, a real version of extended unified theory of acceptance and use of technology was used. The data were collected from the students who were studying professionals’ courses at the Central Universities of Jammu and the Central University of Himachal Pradesh. The findings of the present study have numerous theoretical and practical implications. The contribution of this study will really help app developers to keep in mind various relevant things while developing apps.

Keywords

Smartphone-Job Search Apps, UTAUT2 and E-Recruitment, Mobile Apps.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Acheampong, P., Zhiwen, L., Boateng, F., Boadu, A. B., & Antwi, H. A. (2017). Determinants of behavioral intentions of ‘generation-y’adoption and use of computer-mediated communication tools in Ghana. British Journal of Interdisciplinary Research, 8(1).

  • Ahmed, M. S. (2016). Technology acceptance of smartphones as mobile learning tools: A contextual comparative study of engineering and education colleges.

  • Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.

  • Ajzen, I., & Fishbein, M. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

  • Alazzam, M. B., Basari, H., Samad, A., Sibghatullah, A. S., Doheir, M., Yaacob, N. M., & Aris, F. (2015). Physicians’ acceptance of electronic health records exchange: An extension of the with UTAUT2 model institutional trust. Advanced Science Letters, 21(10), 3248-3252.

  • Anonson, J. M., Desjarlais, J., Nixon, J., Whiteman, L., & Bird, A. (2008). Strategies to support recruitment and retention of First Nations youth in baccalaureate nursing programs in Saskatchewan, Canada. Journal of Transcultural Nursing, 19(3), 274-283.

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

  • Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430.

  • Bondarouk, T., & Brewster, C. (2016). Conceptualising the future of HRM and technology research. The International Journal of Human Resource Management, 27(21), 2652-2671.

  • Bondarouk, T., Parry, E., & Furtmueller, E. (2017). Electronic HRM: Four decades of research on adoption and consequences. The International Journal of Human Resource Management, 28(1), 98-131.

  • Buettner, R. (2017). Predicting user behavior in electronic markets based on personality-mining in large online social networks. Electronic Markets, 27(3), 247-265.

  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.

  • Cho, D. (2015). What influences people to purchase ingame mobile items?: Analysis of motivational drivers to use ingame mobile game items in the US. Michigan State University.

  • Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-211.

  • Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS quarterly, 145-158.

  • 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.

  • 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.

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.

  • Decman, M. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, 49, 272-281.

  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 307-319.

  • East, M. L., & Havard, B. C. (2015). Mental health mobile apps: From infusion to diffusion in the mental health social system. JMIR Mental Health, 2(1).

  • Edwards Jr, J. R. (2017). Undergraduate Student Acceptance and Use of Mobile Learning in Speech Preparation Using Skype (Doctoral dissertation, Indiana State University).

  • Erdogmuş, N., & Esen, M. (2011). An investigation of the effects of technology readiness on technology acceptance in e-HRM. Procedia-Social and Behavioral Sciences, 24, 487-495.

  • Felgenhauer, A., Klier, J., Klier, M., & Lindner, G. (2017). The Impact of Social Engagement on Customer Profitability-Insights from a Direct Banking Institution’s Online Customer Network.

  • Foon, Y. S., & Fah, B. C. Y. (2011). Internet banking adoption in Kuala Lumpur: an application of UTAUT model. International Journal of Business and Management, 6(4), 161.

  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 382-388.

  • Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing research, 440-452.

  • Gaitan, J. O. R. G. E., Peral, B. E. G. O. N. A., & Jeronimo, M. A. (2015). Elderly and internet banking: an application of UTAUT2. The Journal of Internet Banking and Commerce, 2015.

  • Goulao, A. P. B. A. (2014). E-Health individual adoption-empirical model based on UTAUT 2 (Doctoral dissertation).

  • Hair Jr, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., & Page, M. J. (2015). Essentials of business research methods. Routledge.

  • Harsono, L. D., & Suryana, L. A. (2014, August). Factors affecting the use behavior of social media using UTAUT 2 model. In Proceedings of the First Asia-Pacific Conference on Global Business, Economics, Finance and Social Sciences, Singapore.

  • Hashim, M. A., & Hassan, B. Z. (2015). A proposed model f or customer’s acceptance of m-banking based on UTAUT2 Model, 9(3), 43-50.

  • Helkkula, A. (2016). Consumers’ intentions to subscribe to music streaming services.

  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (pp. 277-319). Emerald Group Publishing Limited.

  • Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269-1291.

  • Hooft, E. A. V., Born, M. P., Taris, T. W., Flier, H. V. D., & Blonk, R. W. (2004). Predictors of job search behavior among employed and unemployed people. Personnel Psychology, 57(1), 25-59.

  • Hosain, M. D., Ullah, K. T., & Khudri, M. (2016). The Impact of E-Recruitment on Candidates’ Attitudes: A Study on Graduate Job Seekers of Bangladesh.

  • Huang, C. Y., & Kao, Y. S. (2015). Utaut2 based predictions of factors influencing the technology acceptance of phablets by DNP. Mathematical Problems in Engineering, 2015.

  • Indrawati, & Marhaeni, M. M. A. G. (2015). Predicting instant messenger application adoption using a unified theory of acceptance and use of technology. Proceedings of the 5th International Conference on Computing and Informatics, ICOCI 2015 2(030), 772-778.

  • Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying post-adoption phenomena. Management Science, 51(5), 741-755.

  • Kuo, Y. F., Wu, C. M., & Deng, W. J. (2009). The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Computers in human behavior, 25(4), 887-896.

  • Lai, C. F. (2012). Extended UTAUT model of mobile commerce: An empirical study of negative user acceptance behaviours of mobile commerce in Hong Kong.

  • Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 4(1), 3.

  • Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intentions: The case of IS continuance. MIS Quarterly, 31(4), 705-737.

  • Madan, K., & Yadav, R. (2016). Behavioural intention to adopt mobile wallet: A developing country perspective. Journal of Indian Business Research, 8(3), 227-244.

  • Mahfuz, M. A., Hu, W., & Khanam, L. (2016). The Influence of Cultural Dimensions and Website Quality on m-banking Services Adoption in Bangladesh: Applying the UTAUT2 Model Using PLS.

  • Miladinovic, J., & Hong, X. (2016). A Study on Factors Affecting the Behavioral Intention to use Mobile Shopping Fashion Apps in Sweden.

  • Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.

  • Moura, A. C., Gosling, M. S. G., Christino, J. M. M., & Gomes, S. B. M. (2017). Acceptance and use of technology by older adults for choosing a tourism destination: A study using UTAUT2, 11(2).

  • Nunnally, J. C., & Bernstein, I. H. (1994). Elements of statistical description and estimation. Psychometric Theory 3rd ed. (Edited by: Nunnally JC, Bernstein IH).

  • Pindeh, N., Suki, N. M., & Suki, N. M. (2016). User acceptance on mobile apps as an effective medium to learn Kadazandusun language. Procedia Economics and Finance, 37, 372-378.

  • Rajani, N. S., Reddy, V. B., & Parvathi, A. (2015). Recruitment Practices in IT Sector: A Comparative Analysis of Select Indian & Mnc Companies.

  • Ramayah, T. (2012). Determinants of attitude toward E-HRM: An empirical study among HR professionals. Procedia-Social and Behavioral Sciences, 57, 312-319.

  • Rodríguez, T., & Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70-88.

  • Segura, A. S., & Thiesse, F. (2015, May). Extending UTAUT2 to Explore Pervasive Information Systems. In ECIS.

  • Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing, 32(8), 860-873.

  • Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209-223.

  • Smith, A. (2015). Searching for work in the digital era. Pew Research Center: Internet, Science & Tech., Article published on, 19.

  • Sohn, S. Y., & Kim, Y. (2008). Searching customer patterns of mobile service using clustering and quantitative association rule. Expert systems with Applications, 34(2), 1070-1077.

  • Stone, D. L., & Dulebohn, J. H. (2013). Emerging issues in theory and research on electronic human resource management (eHRM).

  • Sung, H. N., Jeong, D. Y., Jeong, Y. S., & Shin, J. I. (2015). The relationship among self-efficacy, social influence, performance expectancy, effort expectancy, and behavioral intention in mobile learning service. International Journal of u-and e-Service, Science and Technology, 8(9), 197-206.

  • Tan, P. J. B. (2013). Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. Sage Open, 3(4), 2158244013503837.

  • Tarhini, A., Mohammed, A. B., & Maqableh, M. (2016). Modeling factors affecting student’s usage behaviour of e-learning systems in Lebanon. International Journal of Business and Management, 11(2), 299.

  • Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS quarterly, 125-143.

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

  • 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.

  • Vrsajkovic, D. (2016). Evaluating Determinants of Cloud Computing Acceptance in Croatian SME Organizations.

  • Wanberg, C. R. (2012). The individual experience of unemployment. Annual review of psychology, 63, 369-396.

  • Watson, D., Weber, K., Assenheimer, J. S., Clark, L. A., Strauss, M. E., & McCormick, R. A. (1995). Testing a tripartite model: I. Evaluating the convergent and discriminant validity of anxiety and depression symptom scales. Journal of Abnormal Psychology, 104(1), 3.

  • Yoganathan, D., & Kajanan, S. (2013). Persuasive Technology for Smartphone Fitness Apps. In PACIS (p. 185).

  • Zikmund, W. G., & Babin, B. J. (2010) Exploring marketing research (10th ed.). Thomson, Ohio.


Abstract Views: 444

PDF Views: 0




  • Adoption of E-Recruitment Mobile Apps:A Study Based on UTAUT2 Framework

Abstract Views: 444  |  PDF Views: 0

Authors

Neeraj Dhiman
Department of HRM, Central University Jammu, Jammu & Kashmir, India
Neelika Arora
Department of HRM, Central University Jammu, Jammu & Kashmir, India

Abstract


The growing role of technology has changed the prototype of E-recruitment process and transformed E-recruitment industry. Despite the popularity of technology and e-recruitment, there is a limited understanding of m-job search apps adoption in literature. To understand the adoption, a real version of extended unified theory of acceptance and use of technology was used. The data were collected from the students who were studying professionals’ courses at the Central Universities of Jammu and the Central University of Himachal Pradesh. The findings of the present study have numerous theoretical and practical implications. The contribution of this study will really help app developers to keep in mind various relevant things while developing apps.

Keywords


Smartphone-Job Search Apps, UTAUT2 and E-Recruitment, Mobile Apps.

References