INTENTION TO ADOPT: USING OF BARCODE SYSTEM TO REDUCE HEALTH SERVICE ERRORS

Authors

  • Didik Setyawan Setia Budi University of Surakarta, Indonesia
  • Intatik Laelatul Makhfiroh Setia Budi University of Surakarta, Indonesia
  • Finisha Mahaestri Noor Setia Budi University of Surakarta, Indonesia

DOI:

https://doi.org/10.29040/ijebar.v4i03.1405

Abstract

This study aims to examine the factors driving the intention to adopt an information system through the use of patient barcode system at a hospital in Surakarta. This study is necessary to explore the variables forming the information system adoption intention in order to improve the performance of hospital medical personnel. Survey method and questionnaire were applied in data collection. The data were collected using a probability sampling technique resulting in a number of 100 questionnaires to be processed. SPSS was used to test the instrument of the study, while SEM using AMOS method was applied to test hypotheses. The results showed that to be able to increase the confidence of user to form the intention to adopt barcode systems in hospitals is influenced by the condition of the facility not because of management pressure and social pressure. Intention to Adopt Information System, Trust, Facility Condition, Managerial Pressure, Social Pressure, Barcode System.

References

Ahmadi, H., Nilashi, M., Ibrahim, O. (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals, International Journal of Medi al Informatics, 8(4): 166–188

Ahmad, M. O., Jouni, M., Markku, O. (2013). Factors affecting e-government adoption in Pakistan: A citizen’s perspective. Transforming Government: People, Process and Policy. 7(2): 225-239.

Al-Hadban, W. KH. M., Kamarul F. H., & Shafiz A. M. Y. (2016). Investigating the organizational and the environmental issues that influence the adoption of healthcare information systems in public hospitals of Iraq. Computer and Information Science. 9(2): 126-139.

Al-Mamary, Y.H., Alina, S., and Nor, A. (2015). Investigating the key factors influencing on management information systems adoption among telecommunication companies in Yemen: The conceptual framework development. International Journal of Energy, Information and Communications. 6(1): 59-68.

Amo, M.C.A., Carlota, L. R., and Giacomo, D.C. 2014. Adoption of social networking sites by Italian. Information System E-Bussiness Manage. Vol 12, pp. 165–187.

Bai, L.G.X. (2014). A unified perspective on the Factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics. 26(2): 211-231.

Cabanillas, F.L., Juan, S.F., Francisco, M.L. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior. 35: 464–478.

Choudrie, J., Sutee, P., Efpraxia, Z., George, G. (2014). Investigating The Adoption and Use of Smartphones in The UK: A Silver-Surfers Perspective. Hertfordshire Business School Working Paper.

Dwivedi, Y.K., Shareef, M.A., Simintiras, A.C., Lal, B., Weerakkody, V. (2016). A generalised adoption model for services: A cross-country comparison of mobile health (m-Health), Government Information Quarterly, 33(1): 174–187

Hajli, N. (2015). Social commerce constructs and consumer’s intention to buy, International Journal of Information Management, 35: 183–191

Hallikainen, H., Bert, P., Tommi, L., Deva, R., Mika, G. 2017. How Individual Technology Propensities and Organizational Culture Influence B2B Customer’s Behavioral Intention to Use Digital Services at Work. Proceedings of the 50th Hawaii International Conference on System Sciences.

Hanafizadeh, P. Behboudi, M.,Koshksaray, A.A.,Tabar, M.J.S. (2014). Mobile-banking adoption by Iranian Bank Clients, Telematics and Informatics, 31: 62–78

Hoque, R. Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT Model, International Journal of Medical Informatics, 101: 75-84

Huang, Y. M. (2015). Exploring the factors that affect the intention to use collaborative technologies: The differing perspectives of Sequential/Global Learners, Australasian Journal of Educational Technology. 31(3): 278-292.

Gangwar, H., Date, H., Ramaswamy, R. (2015). Understanding determinants of cloud computing adoption using An integrated TAM-TOE Model. Journal of Enterprise Information Management. 28(1): 1-31.

Li, S., Lin, B. (2006). Accessing information sharing and information quality in supply chain management, Decision Support System, 42: 1641-1656.

Liu, H., Ke, W., Wei, K.K., Gu, J., Chen, H. (2010). The role of institutional pressures and organizational culture in the firm’s intention to adopt internet-enabled supply chain management systems, Journal of Operations Management, 28: 372–384

Maillet, E., Mathieu, L., Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurse using an electronic patient record in Acute Care Settings: An Extension of UTAUT, International Journal of Medical Informatic, 84(1): 36-47

Maruping, L.M., Hillol, B., Viswanath, V., Susan, A.B. (2017). Going beyond intention: Integrating behavioral expectation into the unified theory of Acceptance and Use of Technology, Journal of The Association for Information Sciene and Technology. 68(3): 623–637.

Masa’deh, R.M.T., Ali, T., Ashraf, B.M., Mahmoud, M. (2016). Modeling factors affecting student’s usage behaviour of e-learning systems in Lebanon. International Journal of Business and Management. 11(2): 1833-3850.

Mignaret, M., Rivard, S. (2009). Positioning the institutional perspective in information systems Research, Journal of International Technology, 24: 369-361

Morid, M.A., Shajari, M. (2012). An enhanced e-commerce trust model for community based centralized systems, Electronic Commerce Research, 12(4): 409-427

Moya, M., Robinah, N., Gilbert, M., Kituyi, M. (2016). Attitude and behavioral intention as mediators in adoption of e-tax services in Ura, Uganda. ORSEA Journal. 6(1): 157-189.

Najaftorkaman, M., Ghapanchi, A.H., Khoei, A.T., Ray, P. (2015). A taxonomy of antecedents to user adoption of health information systems: A synthesis of thirty years of research, Journal of The Association for Information Science and Technology, 66(3): 576-598

Nikou, S.A., Economides, A.A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use, Computer & Education, 109: 56-73

Oliveira, T., Manoj, T., Goncalo, B., Filipe, C. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology, Computers in Human Behavior. 61: 404-414.

Safa, N.S., Solms, R.V. (2016). An information security knowledge sharing model in organizations, Computer in Human Behavior, 57: 442-451

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 and Marketing, 32(8): 860-873.

Susanto, T.D., Aljoza, M. (2015). Individual acceptance of e-government services in a developing country: Dimensions of perceived usefulness and perceived ease of use and the importance of trust and social influence, Procedia Computer Science, 72: 622-629

Witarsyah, D., Sjafrizal, T., Fudzee, M.F.M.D., Salamat, M.A. (2017). The critical factors affecting adoption in Indonesia: A conceptual framework, International Journal on Advanced Science Engineering Information Technology, 7(1): 160- 167

Wu, B., Chen, X. (2017). Continuance intention to use MOOCs: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) model, Computers in Human Behavior. 67: 221-232.

Yang, S. (2013). Understanding undergraduate students’ adoption of mobile learning model: A perspective of the extended UTAUT2, Journal of Convergence Information Technology. 8(10): 969-979.

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Published

2020-09-28

How to Cite

Setyawan, D., Makhfiroh, I. L., & Noor, F. M. (2020). INTENTION TO ADOPT: USING OF BARCODE SYSTEM TO REDUCE HEALTH SERVICE ERRORS. International Journal of Economics, Business and Accounting Research (IJEBAR), 4(03). https://doi.org/10.29040/ijebar.v4i03.1405

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