Factors Influencing the Adoption of Location Based Identification in Kurdistan Regional of Iraq

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Author: Sara Muhamad Amin
Department of Computer Science, Cihan University – Erbil
DOI: http://dx.doi.org/10.24086/cuesj.si.2017.n1a9

Abstract
This study examines the factors that affect the adoption of Location Based Identification LBI in the developing countries and more specific in Kurdistan Regional of Iraq (KRI). LBI has different names in different countries such as postcode in the United Kingdom and zip code in the United States. As a base model, the Technology Acceptance Model (TAM) and the Decomposed Theory of Planned Behaviour (DTPB) have been used to model the adoption factors of LBI in KRI. The latent variables used in this study are government support (GS), self-efficacy (SE), perceived usefulness (PU), perceived ease of use (PEU), compatibility (COM), Family and friends (FF), attitude (A), subjective norm (SN), perceived behaviour control (PBC) and behaviour intention (BI). A survey was conducted involving a total of 250 respondents. By using these models, the adoption of LBI system by the citizen of KRI has been proven. The results encourage the Kurdistan Regional Government decision makers to develop strategies that will lead to the adoption of LBI system in the region.
Keywords: component; Decomposed theory of planned behaviour (DTPB); Location Based Identification (LBI); Kurdistan Region of Iraq (KRI); Technology acceptance Model (TAM).
Reference
[1] Coetzee, S., et al., What address standards tell us about addresses. South African Journal of Science, 2007. 103(11): p. 449-458.
[2] Muhamad Amin, S. and D. Wilson, Designing a Postcode System for Arbil City Iraq. 2014.
[3] Fishbein, M. and I. Ajzen, Belief, attitude, intention and behavior: an introduction to theory and research. 1975, London (etc.); Reading, Mass: Addison-Wesley.
[4] Ajzen, I. and M. Fishbein, Understanding attitudes and predicting social behavior. 1980, London (etc.); Englewood Cliffs: Prentice-Hall.
[5] Davis, F.D., R.P. Bagozzi, and P.R. Warshaw, User acceptance of computer
technology: a comparison of two theoretical models. Management science, 1989. 35(8): p. 982-1003.
[6] Davis, F.D., Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 1989. 13(3): p. 319-340.

[7] Howell, D. W. Social media site use and the technology acceptance model: Social media sites and organization success (Doctoral dissertation, CAPELLA UNIVERSITY) (2016).
[8] Diatmika, I. W. B., Irianto, G., & Baridwan, Z. Determinants of Behavior Intention Of Accounting Information Systems Based Information Technology Acceptance. Imperial Journal of Interdisciplinary Research, (2016). 2(8).
[9] Paul, J., Modi, A., & Patel, J. Predicting green product consumption using theory of planned behavior and reasoned action. Journal of retailing and consumer services, (2016). 29, 123-134.
[10] Seuwou, P., Banissi, E., & Ubakanma, G. User Acceptance of Information
Technology: A Critical Review of Technology Acceptance Models and the Decision to Invest in Information Security. In International Conference on Global Security, Safety, and Sustainability (2017, January). (pp. 230-251). Springer, Cham.
[11] Howell, D. W. Social media site use and the technology acceptance model: Social media sites and organization success (Doctoral dissertation, CAPELLA UNIVERSITY). (2016).
[12] Ajzen, I., Residual Effects of Past on Later Behavior: Habituation and ReasonedAction Perspectives. Personality and Social Psychology Review, 2002. 6(2): p. 107-122.
[13] Mathieson, K., Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 1991. 2(3): p. 173-191.
[14] Taylor, S. and P.A. Todd, Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 1995. 6(2): p. 144-176.
[15] Rogers, E., Diffusion of Innovations, 5th edn Free Press. New York, 2003.
[16] Hartwick, J. and H. Barki, Explaining the role of user participation in information system use. Management science, 1994. 40(4): p. 440-465.
[17] Chua, E., Consumer intention to deposit at banks: An empirical investigation of its relationship with attitude, normative belief and confidence. Academic Exercise, Faculty of Business Administration, National University of Singapore, 1980.

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