Determinant Factors in Adopting Mobile Technology-based Services by Academic Librarians

Abdekhoda, Mohammadhiwa and Gholami, Zahra and Zarea, Vahideh Determinant Factors in Adopting Mobile Technology-based Services by Academic Librarians. DESIDOC Journal of Library & Information Technology, 2018, vol. 38, n. 4, pp. 271-277. [Journal article (Paginated)]

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English abstract

Nowadays, mobile technology seems to become integral part of our life. People with different careers have begun to use it in their jobs. This research aims to identify influential factors in mobile technology adoption at library context. To this end, a conceptual model was presented based on an integrated model of technology acceptance model (TAM) and technology organization and environment (TOE) model. A researcher-made questionnaire was distributed among 120 academic librarians. Seven factors out of the integrated model of TAM and TOE were chosen to investigate their influence on mobile technology adoption. The results of the study suggest that the proposed model (integrated model of TAM and TOE) is a favorable one to identify the influential factors in mobile technology adoption at library context. In addition, regression analysis indicated that out of these seven factors, perceived ease of use, perceived usefulness, compatibility, relative advantage and organizational competency are determinant factors in adopting mobile technology-based library services among academic librarians.

Item type: Journal article (Paginated)
Keywords: Academic librarians; Mobile technology adoption; Technology acceptance model
Subjects: A. Theoretical and general aspects of libraries and information.
A. Theoretical and general aspects of libraries and information. > AB. Information theory and library theory.
Depositing user: Dr. Mohammadhiwa Abdekhoda
Date deposited: 18 Jul 2018 22:22
Last modified: 18 Jul 2018 22:22
URI: http://hdl.handle.net/10760/33211

References

1. Shrivastav S. Use of mobile technology in library and information services. American Research Thought. 2015; 1(7).

2. Abdekhoda, M.; Ahmadi, M.; Dehnad, A.; Noruzi, A. & Gohari, M. Applying electronic medical records in health care: Physicians’ perspective. Applied Clinical Informatics. 2016, 7(2), 341. doi: 10.4338/aci-2015-11-ra-0165

3. Saxena, A. & Yadav, R. Impact of mobile technology on libraries: A descriptive study. Int. J. Digital Lib. Ser., 2013, 3(4), 1-13.

4. Davis, FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 1989, 319-40. doi: 10.2307/249008

5. Schillewaert, N.; Ahearne, M.J.; Frambach, R.T. & Moenaert, R.K. The adoption of information technology in the sales force. Industrial Marketing Management. 2005, 34(4), 323-36. doi: 10.1016/j.indmarman.2004.09.013

6. Gangwar, H.; Date, H. & Ramaswamy, R. Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. J. Enterp. Info. Manag. 2015, 28(1), 107-30. doi: 10.1108/JEIM-08-2013-0065

7. Zhu, K. The complementarity of information technology infrastructure and e-commerce capability: A resource based assessment of their business value. J. Manage. Inf. Systems. 2004, 21(1), 167-202. doi: 10.1080/07421222.2004.11045794

8. Angeles, R. Using the technology - organisation - environment framework for analyzing Nike’s Considered Index green initiative, a decision support system-driven system. J. Manag. Sustainability. 2014, 4(1), 96. doi: 10.5539/jms.v4n1p96

9. Rogers, E.M. Diffusion of innovations. Free Press. New York. 2003:551. doi: 10.2307/2573300

10. Peng, R.; Xiong, L. & Yang, Z. Exploring tourist adoption of tourism mobile payment: An empirical analysis. J. Theor. Appl. Electron. Commer. Res. 2012, 7(1), 21-33. doi: 10.4067/S0718-18762012000100003

11. Chen L-D, Tan J. Technology adaptation in e-commerce: Key determinants of virtual stores acceptance. Eur. Manage. J. 2004, 22(1), 74-86. doi: 10.1016/j.emj.2003.11.014

12. Calisir, F.; Altin, Gumussoy, C. & Bayram, A. Predicting the behavioural intention to use enterprise resource planning systems: An exploratory extension of the technology acceptance model. Manag. Res. News. 2009, 32(7), 597-613. doi: 10.1108/01409170910965215

13. Sonnenwald, D.H.; Maglaughlin, K.L. & Whitton, M.C.; editors. Using innovation diffusion theory to guide collaboration technology evaluation: Work in progress. In Proceedings Tenth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2001 WET ICE 2001. doi: 10.1109/ENABL.2001.953399

14. Tan, J.; Tyler, K. & Manica, A. Business-to-business adoption of eCommerce in China. Information Management. 2007, 44(3), 332-51. doi: 10.1016/j.im.2007.04.001

15. Intan, Salwani, M.; Marthandan, G.; Daud, Norzaidi, M. & Choy, Chong, S. E-commerce usage and business performance in the Malaysian tourism sector: Empirical analysis. Info. Manag. Comp. Security. 2009, 17(2), 166-85. doi: 10.1108/09685220910964027

16. Zhu, K. & Kraemer, K.L. Post-adoption variations in usage and value of e-business by organisations: crosscountry evidence from the retail industry. Info. Syst. Res., 2005, 16(1), 61-84.

17. Abdekhoda, M.; Ahmadi, M.; Gohari, M. & Noruzi, A. The effects of organisational contextual factors on physicians’ attitude toward adoption of electronic medical records. J. Biomed. Info. 2015, 53, 174-9. doi: 10.1016/j.jbi.2014.10.008

18. Kowitlawakul, Y. Technology Acceptance Model: Predicting nurses’ acceptance of telemedicine technology (eICU): George Mason University; 2008. doi: 10.1097/NCN.0b013e3181f9dd4a

19. Abdekhoda, M.; Dehnad, A.; Mirsaeed, S.J.G. & Gavgani V.Z. Factors influencing the adoption of e-learning in Tabriz University of Medical Sciences. Med. J. Islamic Repub. Iran. 2016, 30, 457.

20. Abdekhoda, M. & Salih, K.M. Determinant factors in applying picture archiving and communication systems (PACS) in Healthcare. Perspectives in health information management. 2017, 14 (Summer).

21. Sattari, A.; Abdekhoda, M. & Gavgani, V.Z. Determinant factors affecting the web-based training acceptance by health students, applying UTAUT Model. Int. J. Emerging Technol., 2017, 12(10), 112-26.

22. Tung F-C, Chang S-C, Chou C-M. An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int. J. Med. Inf. 2008, 77(5), 324-35. doi: 10.1016/j.ijmedinf.2007.06.006

23. Völlink, T.; Meertens, R. & Midden, C.J. Innovating ‘diffusion of innovation’ theory: Innovation characteristics and the intention of utility companies to adopt energy conservation interventions. J. Environ. Psychol. 2002, 22(4), 333-44. doi: 10.1006/jevp.2001.0237

24. Atkinson, N.L. Developing a questionnaire to measure perceived attributes of eHealth innovations. Am. J. Health Behaviour. 2007, 31(6), 612-21. doi: 10.5993/AJHB.31.6.6

25. Conrad, E.D. Willingness to use IT innovations: A hybrid approach employing diffusion of innovations and technology acceptance models: Southern Illinois University at Carbondale; 2009. doi: 10.1177/001112878202800110

26. Wu, J-H.; Shen, W-S.; Lin, L-M.; Greenes, R.A. & Gholami, et Al.: Determinant factors in adopting mobile technology-based services by academic librarians 277 Bates, D.W. Testing the technology acceptance model for evaluating healthcare professionals’ intention to use an adverse event reporting system. Int. J. Quality Health Care. 2008, 20(2), 123-9. doi: 10.1093/intqhc/mzm074

27. Zhang, N.; Guo, X. & Chen, G. IDT-TAM integrated model for IT adoption. Tsinghua Sci. Technol., 2008, 13(3), 306-11. doi: 10.1016/S1007-0214(08)70049-X

28. Chew, F.; Grant, W. & Tote, R. Doctors on-line: Using diffusion of innovations theory to understand internet use. Family Medicine-Kansas City. 2004, 36, 645-50. doi: 10.1111/cfs.12276

29. Y u P, Li H, Gagnon M-P. Health IT acceptance factors in long - term care facilities: A cross - sectional survey. Int. J. Med. Inf. 2009, 78(4), 219-29. doi: 10.1016/j.ijmedinf.2008.07.006

30. Piprani, B.; Borg, M.; Chabot, J. & Chartrand, É. editors. An adaptable ORM metamodel to support traceability of business requirements across system development life cycle phases. On the Move to Meaningful Internet Systems: OTM 2008 Workshops; 2008: Springer.

31. Morton, M.E. Use and acceptance of an electronic health record: factors affecting physician attitudes. 2008.


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