Effect of motivation, opportunity and ability on human resources information security management considering the roles of Attitudinal, behavioral and organizational factors

Document Type : Original Article


1 Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran


English Abstract must be Times New The increasing penetration of mobile devices will lead to better use of it in youth business. Mobile marketing has received less attention in developing countries such as Iran. The purpose of this paper is to investigate the predictors of mobile marketing use by expanding the Unified Theory of Acceptance and Use of Technology (UTAUT2).The extended model has additional factors including perceived risk, trust, mobility, and personal innovativeness. Data were collected using online surveys and questionnaires from 350 students of K. N. Toosi University of Technology. To predict the use of mobile marketing, a novel partial Least Squares - Artificial Neural Networks (PLS-ANN) approach was used. The results show that personal innovativeness is the most effective factor in mobile marketing acceptance. Subsequently, the hedonic motivations, performance expectancy, mobility, social influence, trust, and facilitating conditions play a vital role. Furthermore, the results illustrate that price value, perceived risk, and effort expectancy were not effective.



    1. Hoffmann R., Napiórkowski J., Protasowicki T. , Jerzy Stanik, “Measurement Models of Information Security Based on the Principles and Practices for Risk-Based Approach”, 1st International Conference on Optimization-Driven Architectural Design, (2020), https://doi.org/10.1016/j.promfg.2020.02.244.
    2. Zare M. R., Aghaie A., Samimi Y., A. Hadad Asl, “A Novel Excellence Model of the Information and Communications Technology Industry: Case Study on Telecommunications Backbone Network of Iran”, International Journal of Engineering, Transactions A: Basics, Vol. 33, No. 10, (2020) 2016-2029, https://doi: 10.5829/ije.2020.33.10a.20.
    3. Roberts D. J., An Analysis of employee information security policy compliance behaviour: A generic qualitative inquiry, Capella University, 2021.
    4. Jeyanthi N., Shabeeb H., M. Saleem A. Durai, Thandeeswaran R., “Reputation Based Service for Cloud User Environment”, International Journal of Engineering, Transactions B: Applications, Vol. 27, No. 8, (2014), 1179-1184, https:// doi: 10.5829/idosi.ije.2014.27.08b.03.
    5. Kwesi Hughes-Lartey, Meng Li, Francis E. Botchey, Zhen, “Human factor, a critical weak point in the information security of an organization’s Internet of things”, Heliyon,(2021), https://doi.org/10.1016/j.heliyon.2021.e06522.
    6. Karjalainen M., Siponen M., Sarker S., “Toward a stage theory of the development of employees’ information security behaviour”, Computers & Security, (2020) https://doi.org/10.1016/j.cose.2020.101782.
    7. Bagheri Z., Safaie N., Strategic planning of human resources based on BSC model, Quarterly Journal of Human Resource Management Research, Imam Hossein University, 8th year, consecutive issue 25, 159-181. (2016).
    8. Azjen, I. The theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211, (1991). https://doi.org/10.1016/0749-5978(91)90020-T.
    9. Bagozzi, R. P., & Yi, Y. “Specification, evaluation, and interpretation of structural equation models Journal of the Academy of Marketing Science, 40, No. 1, 8-34, (2012), https://doi.org/10.1007/s11747-011-0278-x.
    10. Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F. J. Learning with mobile technologies–Students’ behavior. Computers in Human Behavior, Vol. 72, 612-620, (2017). https://doi.org/10.1016/j.chb.2016.05.027.
    11. Carlton M., Levy Y., "Expert assessment of the top platform independent cybersecurity skills for non-IT professionals." SoutheastCon, (2015), https://doi.org/ 10.1109/SECON.2015.7132932.
    12. Evans, M. "Evaluating information security core human error causes (IS-CHEC) technique in public sector and comparison with the private sector." International Journal of Medical Informatics, Vol. 127 109-119, (2019), https://doi.org/10.1016/j.ijmedinf.2019.04.019.
    13. Hamidi, H., Vafaei, A. and Monadjemi, S.A. (2012). Analysis and Evaluation of a New Algorithm Based Fault Tolerance for Computing Systems. International Journal of Grid and High Performance Computing (IJGHPC), 4, No. 1, 37-51. doi:10.4018/jghpc.2012010103
    14. Schwartz, Shalom H., "Normative influences on altruism." Advances in Experimental Social Psychology, Vol. 10. Academic Press, 221-279, (1977), https://doi.org/10.1016/S0065-2601(08)60358-5.
    15. Fornell, C., & Larcker, D. F. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, (1), 39-50, (1981), https://doi.org/10.1177/002224378101800104.
    16. Gao, L., "Application of the extended theory of planned behavior to understand individual’s energy saving behavior in workplaces." Resources, Conservation and Recycling, 127, 107-113, (2017) https://doi.org/10.1016/j.resconrec.2017.08.030.
    17. Gandel, Lloyd’s CEO: Cyber-attacks cost companies 400 billion every year, (2015). http://fortune.com/2015/01/23/cyber-attack-insurancelloyds/(accessed 03 October 2018).
    18. Gratian, M., Bandi S., Cukier M., Dykstra J., Ginther A.,"Correlating human traits and cyber security behavior intentions." Computers & Security, 73, 345-358, (2018) https://doi.org/10.1016/j.cose.2017.11.015.
    19. Hair, J. F., Ringle, C. M., & Sarstedt, MPLS-SEM, “Indeed a silver bullet”. Journal of Marketing theory and Practice, Vol. 19, No. 2, (2011), 139-152, https://doi.org/10.2753/MTP1069-6679190202.
    20. Altabash K., Happaa b., "Insider-threat detection using gaussian mixture models and sensitivity profiles." Computers & Security 77, 838-859., (2018) https://doi.org/10.1016/j.cose.2018.03.006.
    21. Ifinedo, P., "Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory." Computers &Security1,83-95, (2012), https://doi.org/10.1016/j.cose.2011.10.0076.
    22. Kuru, Damla, and Sema Bayraktar, "The effect of cyber-risk insurance to social welfare." Journal of Financial Crime 2 ,329-346, (2017), https://doi.org/10.1108/JFC-05-2016-0035.
    23. Xu, X., Chen C., Menassa C., "Understanding energy-saving behaviors in the American workplace: A unified theory of motivation, opportunity, and ability." Energy Research & Social Science 51, 198-209, (2019), https://doi.org/10.1016/j.erss.2019.01.020.
    24. Malekinezhad, F., Bin H. L. Investigation into University Students Restoration Experience: The Effects of Perceived Sensory Dimension and Perceived Restrictiveness, (2017), https://doi.org/doi: 10.20944/preprints201708.0085.
    25. Michie S., Stralen, M., West, R., "The behaviour change wheel: a new method for characterising and designing behaviour change interventions." Implementation Science1, 42, (2011), https://doi.org/10.1186/1748-5908-6-42.
    26. Nummally, J., Psychometric Theory. McGraw-Hill, Retrieved from. 1978.
    27. Osterhus, Thomas L., "Pro-social consumer influence strategies: when and how do they work? " Journal of Marketing4,16-29, (1997), https://doi.org/10.1177/002224299706100402.
    28. Hamidi, H., Vafaei, A., and Monadjemi, A. H., “Algorithm Based Fault Tolerant and Check Pointing for High Performance Computing Systems”, Journal of Applied Sciences, vol. 9, no. 22, 3947–3956, 2009. doi:10.3923/jas.2009.3947.3956.
    29. Hamidi, H., & Mohammadi, K. (2006). Modeling Fault Tolerant and Secure Mobile Agent Execution in Distributed Systems. International Journal of Intelligent Information Technologies (IJIIT), 2(1), 21-36. doi:10.4018/jiit.2006010102
    30. Rezaei, R.., "Drivers of farmers' intention to use integrated pest management: Integrating theory of planned behavior and norm activation model." Journal of Environmental Management, 236, 328-339, (2019) https://doi.org/10.1016/j.jenvman.2019.01.097.
    31. Sohrabi Safaab N., Maplea C., Watson T., Von Solms B., (2018), "Motivation and opportunity-based model to reduce information security insider threats in organisations." Journal of Information Security and Applications, 40, 247-257, (2018), https://doi.org/10.1016/j.jisa.2017.11.001.
    32. Schwartz, Shalom H., "Normative explanations of helping behavior: A critique, proposal, and empirical test." Journal of Experimental Social Psychology 4, 349-364, (1973), https://doi.org/10.1016/0022-1031(73)90071-1.
    33. Schmidt, K., "Predicting the consumption of expired food by an extended Theory of Planned Behavior" Food Quality and Preference, 78, 103746, (2019), https://doi.org/10.1016/j.foodqual.2019.103746.
    34. Shan, J., Jingmei, L., and Zhihua, X., "Estimating ecological damage caused by green tides in the Yellow Sea: A choice experiment approach incorporating extended theory of planned behavior" Ocean & Coastal Management, 181, 104901, (2019), https://doi.org/10.1016/j.ocecoaman.2019.104901.
    35. Hamidi, H., Vafaei, A. and Monadjemi, S.A., Analysis and design of an ABFT and parity-checking technique in high performance computing SYSTEMS. Journal of Circuits, Systems and Computers, Vol. 21, No. 03, 1250017 (2012) , https://doi.org/10.1142/S021812661250017X
    36. ‏ Sohrabi Safa N., Solms R., Futcher, L.,” Human aspects of information security in organisations”. Computer Fraud & Security 2, 15-8, (2016), https://doi.org/10.1016/S1361-3723(16)30017-3.
    37. ThØgersen, J., "Understanding of consumer behaviour as a prerequisite for environmental protection." Journal of Consumer Policy 18, No. 4, 345-385, (1995), https://doi.org/10.1007/BF01024160.
    38. Wilson, C., and Melissa R., "Insights from psychology about the design and implementation of energy interventions using the Behaviour Change Wheel." Energy Research & Social Science, 19, 177-191, (2016), https://doi.org/10.1016/j.erss.2016.06.015.
    39. Wolske, K. S., Paul, C., and Thomas, D., "Explaining interest in adopting residential solar photovoltaic systems in the United States: Toward an integration of behavioral theories" Energy Research & Social Science, 25, 134-151, (2017).
    40. Yazdanmehr, A., and Jingguo W. "Employees' information security policy compliance: A norm activation perspective." Decision Support Systems, 92, 36-46, (2016), https://doi.org/10.1016/j.erss.2016.12.023.
    41. ‏Zhao, X., Lynch Jr, J. G., & Chen, Q., “Reconsidering Baron and Kenny: Myths and truths about mediation analysis”. Journal of Consumer Research, 37(2), 197-206, (2010) https://doi.org/10.1086/651257.
    42. Torabi, A., Hamidi, H., Safaie, N., “Effect of Sensory Experience on Customer Word-of-mouth Intention, Considering the Roles of Customer Emotions, Satisfaction, and Loyalty”, International Journal of Engineering, Transactions C: Aspects, 34, No. 3, (2021), 682-699, https://doi.org/10.5829/ije.2021.34.03c.13.