News
Statistics
| Number of Journals | 34 |
| Number of Issues | 1,306 |
| Number of Articles | 9,427 |
| Article View | 9,188,648 |
| PDF Download | 5,620,937 |
Investigating the Effective Behavioral Factors on Forgiveness through New Technology (Internet) in Iran Case Study of Saman Bank Customers and Bank of Isfahan City | ||
| مدیریت اسلامی | ||
| Article 7, Volume 27, Issue 1, July 2019, Pages 141-167 PDF (872.55 K) | ||
| Document Type: Original Article | ||
| Authors | ||
| mohammad hackak* 1; amir hooshang nazaripour2; behrooz mosazadeh3 | ||
| 1University of Business Management, Faculty of Economics and Administration, Lorestan University | ||
| 2Assistant Professor, Department of Business Management, Faculty of Economics and Administrative Sciences, Lorestan University | ||
| 3PhD Student of Management, Organizational Behavior Tendency, Faculty of Economics and Administrative Sciences, Lorestan University | ||
| Receive Date: 31 May 2018, Revise Date: 20 July 2018, Accept Date: 19 January 2019 | ||
| Abstract | ||
| With the advent of cyberspace and Internet technology today, much of human affairs is done this way, and even some of the charity work is done through cyberspace. The purpose of this study was to investigate the behavioral factors influencing forgiveness and charity through internet in Iran. Samples are Saman Bank and Bank of Isfahan Province, which were selected through simple cluster sampling. The measurement tool was a standard questionnaire that was used for each part of previous research. Reliability of the constructs was higher than 85% to evaluate reliability. Cronbach's alpha was 88% and convergent validity was used for its validity, with AVE variables above 77%. The findings of the study indicate the direct impact of influencing factors such as: adaptation, relative advantage and facilities, on Internet forgiveness, and social and complexity factors have an adverse effect on Internet forgiveness. In addition, the effect of Internet forgiveness on religious satisfaction is direct and positive, with the highest effect being 62% beta. | ||
| Keywords | ||
| Social Factors; Compatibility; Comparative Advantage; Internet Forgiveness; Religious Satisfaction | ||
| References | ||
|
Abdel-Khalek, A.M. and Naceur, F. (2007), Religiosity and its association with positive and negative emotions among college students from Algeria, Mental Health, Religion and Culture, Vol. 10 No. 2, pp. 159-170.
Azzi, C. and Ehrenberg, R. (1975), Household allocation of time and church attendance, Journal of Political Economy, Vol. 84 No. 3, pp. 27-56.
Bekkers, R. (2010), who gives what and when? A scenario study of intentions to give time and money, Social Science Research, Vol. 39 No. 3, pp. 369-381.
Benbunan-Fich, R. and Koufaris, M. (2013), Public contributions to private-collective systems:the case of social bookmarking, Internet Research, Vol. 23 No. 2, pp. 183-203.
Bergeron, F., Raymond, L., Rivard, S. and Gara, M.F. (1995), Determinants of EIS use: testing a behavioural model, Decision Support Systems, Vol. 14 No. 2, pp. 131-146.
Casas, F., Gonzalez, M., Figuer, C. and Malo, S. (2009), Satisfaction with spirituality, satisfaction with religion and personal well-being among Spanish adolescents and young university students, Applied Research Quality Life, Vol. 4 No. 1, pp. 23-45.
Cheng, C.H., Cheung, W. and Chang, M.K. (2002), The use of the internet in Hong Kong: manufacturing vs service, International Journal of Production Economics, Vol. 75 Nos 1-2, pp. 33-45.
Cialdini, R.B., Darby, B.L. and Vincent, J.E. (1973), Transgression and altruism: a case for hedonism, Experimental Social Psychology, Vol. 9 No. 6, pp. 502-516.
Comrey, A.L. and Lee, H.B. (1992), A First Course in Factor Analysis, 2nd ed, Lawrence Erlbaum Associates, Hillsdale, NJ.
D. Barclay, D., Higgins, C. & Thompson, R. (1995). The Partial Least Squares (PLS) Approach to Causal Modelling: personal computer adoption and use as an illustration, Technology Studies, vol 2. 285-309.
de Hooge, I.E. (2014), Predicting consumer behavior with two emotion appraisal dimensions: emotion valence and agency in gift giving, International Journal of Research in Marketing, Vol. 31 No. 4, pp. 380-394.
Deb, R., Gazzale, R.S. and Kotchen, M.J. (2014), Testing motives for charitable giving: a revealed-preference methodology with experimental evidence, Journal of Public Economics, Vol. 120, pp. 181-192.
Dennis, B.S., Buchholtz, A.K. and Butts, M.M. (2009), the nature of giving: a theory of planned behaviour examination of corporate philanthropy, Business and Society, Vol. 10 No. 5, pp. 1-25.
Fornell, C., and Larcker, D. F. (1981), Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, Vol. 18, No. 3 , pp. 382-388
Hamdani, S.N.H. and Ahmad, E. (2002), towards divine economics: some testable propositions, The Pakistan Development Review, Vol. 41 No. 4, pp. 609-626.
Hernandez, J.M.C. and Mazzon, J.A. (2007), Adoption of internet banking: proposition and implementation of an integrated methodology approach, International Journal of Bank Marketing, Vol. 25 No. 2, pp. 72-88.
Kandrack, R. and Lundberg, G. (2014), on the influence of emotion on decision making: the case of charitable giving, in Guo, P. and Pedrycz, W. (Eds), Human-Centric Decision-Making Models for Social Sciences, Studies in Computational Intelligence, Springer-Verlag, Berlin, pp. 57-73.
Knowles, S.R., Hyde, M.K. and White, K.M. (2012), Predictors of young people’s charitable intentions to donate money: an extended theory of planned behaviour perspective, Journal of Applied Social Psychology, Vol. 42 No. 9, pp. 2096-2110.
Kolodinsky, J.M., Hogarth, J.M. and Hilgert, M.A. (2004), the adoption of electronic banking technologies by US consumers, International Journal of Bank Marketing, Vol. 22 No. 4, pp. 238-259.
Lee, E., Lee, J. and Schumann, D. (2002), the influence of communication source and mode on consumer adoption of technological innovations, Journal of Consumer Affairs, Vol. 36 No. 1, pp. 1-28.
Liu, Y. and Li, H. (2010), Mobile internet diffusion in China: an empirical study, Industrial Management & Data Systems, Vol. 110 No. 3, pp. 309-324.
Mano, R.S. (2014), Social media, social causes, giving behaviour and money contributions, Computers in Human Behavior, Vol. 31, pp. 287-293.
Moody, G.D. and Siponen, M. (2013), Using the theory of interpersonal behaviour to explain non-work-related personal use of the internet at work, Information & Management, Vol. 50 No. 6, pp. 322-335.
Palmore, E.B. (1982), Predictors of the longevity difference: a 25-year follow-up, The Gerontologist, Vol. 22 No. 6, pp. 513-518.
Pare, G. and Elam, J.J. (1995), Discretionary use of personal computers by knowledge workers: testing of a social psychology theoretical model, Behaviour & Information Technology, Vol. 14 No. 4, pp. 215-228.
Pee, L.G., Woon, I.M.Y. and Kankanhalli, A. (2008), Explaining non-work-related computing in the workplace: a comparison of alternative models, Information & Management, Vol. 45, No. 2, pp. 120-130.
Poloma, M.M. and Pendleton, B.F. (1989), Exploring types of prayer and quality of life: a research note, Review of Religious Research, Vol. 31 No. 1, pp. 46-53.
Premkumar, G. and Roberts, M. (1999), Adoption of new information technologies in rural small businesses, OMEGA The International Journal of Management Science, Vol. 27 No. 4, pp. 467-484.
Rogers, E. (1983), Diffusions of Innovations, 3rd Ed, the Free Press, New York, NY.
Smith, J.R. and McSweeney, A. (2007), Charitable giving: the effectiveness of a revised theory of planned behaviour model in predicting donating intentions and behaviour, Journal of Community & Applied Social Psychology, Vol. 17 No. 5, pp. 363-386.
Thompson, R.L., Higgins, C.A. and Howell, J.M. (1991), Personal computing: toward a conceptual model of utilization, MIS Quarterly, Vol. 15 No. 1, pp. 125-143.
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
Willer, R., Wimer, C. and Owens, L.A. (2015), what drives the gender gap in charitable giving? Lower empathy leads men to give less to poverty relief, Social Science Research, Vol. 52, pp. 83-98.
Wu, S.Y., Huang, J.T. and Kao, A.P. (2004), an analysis of the peer effects in charitable giving: the case of Taiwan, Journal of Family and Economic Issues, Vol. 25 No. 4, pp. 483-505 | ||
|
Statistics Article View: 1,332 PDF Download: 622 |
||