درک اعتماد اولیه کاربران به شبکه¬های اجتماعی
محورهای موضوعی : عمومىمحسن اکبری 1 , کامران زاهدفر 2 , زهرا ایاغ 3
1 - عضو هیات علمی
2 - دانشگاه گیلان
3 - دانشگاه گیلان
کلید واژه: اعتماد اولیه, خودکارآمدی, فیسبوک, مدل بسط احتمالی,
چکیده مقاله :
شبکه های اجتماعی یکی از انواع رسانه های اجتماعی محسوب می شوند که در سال های اخیر در زندگی کاربران اینترنتی آنچنان تأثیرگذار بوده اند که شکل های ارتباطات اجتماعی نیز از این رسانه های جدید تأثیر پذیرفته است و در آینده نقش به مراتب مهم تری را بازی خواهند کرد. از سوی دیگر اعتماد یکی از عوامل اصلی ایجاد رضایت و تکرار استفاده ی کاربران از خدمات برخط است. لذا این پژوهش مدل بسط احتمالی را برای شناخت عوامل مؤثر بر اعتماد اولیه کاربران به شبکه های اجتماعی (فیسبوک) به کار گرفته است و بیان می کند که کاربران از طریق دو مسیر مرکزی و جانبی نگرش خود را تغییر می دهند. نشانه‌های مرکزی شامل کیفیت اطلاعات و کیفیت خدمات و نشانه‌های جانبی شامل کیفیت سیستم، امنیت ساختاری و شهرت هستند. خودکارآمدی اثرات نشانه‌های مرکزی و نشانه‌های جانبی را بر اعتماد اولیه تعدیل می کند. جامعه آماري این پژوهش، کاربران ایرانی فیسبوک می باشند. داده های مورد نیاز پژوهش از طریق ارتباط با صفحات شخصی افراد و صفحات عمومی (مربوط به گروه ها، شهرها، فعالیت ها، دانشگاه ها و ...) فعال در این شبکه ی اجتماعی جمع آوری گردید. بدین منظور لینک پرسشنامه ی آنلاین طراحی شده بر روی تارنمای docs.google.com در اختیار آنان قرار گرفت. در این پرسشنامه از مقیاس ٥ گزینه ای لیکرت از کاملاً مخالفم (1) تا کاملاً موافقم (5) استفاده شد و در پایان تعداد ٤٠۶ پرسشنامه جمع آوری گردید که با توجه به جدول جرسی و مورگان، برای انجام پژوهش در جامعه ی بی نهایت، مطلوب می-باشد. روایی پرسشنامه از طریق نظرخواهی از خبرگان و اساتید دانشگاه و پایایی آن از طریق محاسبه ی آلفای کرونباخ تأمین گردید و نشان دهنده ی حد مطلوب پایایی است. داده ها با نرم افزار آماری SmartPLS2 تحلیل شد. طبق نتایج به دست آمده از میان متغیرهای مستقل این پژوهش خودکارآمدی، شهرت و امنیت ساختاری به ترتیب با ضریب مسیر 47/0، 23/0 و 20/0 بیشترین اثر را بر اعتماد اولیه دارند و کیفیت سیستم کمترین اثر را بر اعتماد اولیه با مقدار 07/0 دارد. همچنین نتایج بیانگر این مطلب بوده که خودکارآمدی تنها اثر کیفیت سیستم را بر اعتماد اولیه تعدیل می کند. بنابرین از آن جایی که خودکارآمدی جدای از نقش تعدیل گریش به طور مستقیم نیز بیشترین تأثیر را بر اعتماد اولیه دارد؛ طراحان شبکه های اجتماعی باید به این عامل توجه ویژه ای داشته باشند؛ به گونه ای که یادگیری آن آسان و فرآیند استفاده از آن برای کابران واضح و قابل فهم باشد.
۲٬۱۰۸ / ۵٬۰۰۰ Social networks are one of the types of social media that have been so influential in the lives of internet users in recent years that the forms of social communication have also been influenced by these new media and in the future the role will be far greater. They will play more important. On the other hand, trust is one of the main factors of creating satisfaction and repeating the use of online services by users. Therefore, this research has used the possible expansion model to identify the factors affecting users' initial trust in social networks (Facebook) and states that users change their attitude through two central and lateral paths. Central indicators include information quality and service quality, and peripheral indicators include system quality, structural security, and reputation. Self-efficacy moderates the effects of central cues and peripheral cues on initial trust. The statistical population of this research is Iranian Facebook users. The data needed for the research was collected through the connection with the personal pages of people and public pages (related to groups, cities, activities, universities, etc.) active in this social network. For this purpose, the link of the online questionnaire designed on the docs.google.com website was provided to them. In this questionnaire, a 5-point Likert scale from completely disagree (1) to completely agree (5) was used, and at the end, 406 questionnaires were collected, according to the Jersey and Morgan table, to conduct research in the infinite society. It is desirable. The validity of the questionnaire was obtained by asking experts and university professors and its reliability was determined by calculating Cronbach's alpha and it shows the optimal level of reliability. Data were analyzed with SmartPLS2 statistical software. According to the results obtained, among the independent variables of this research, self-efficacy, reputation, and structural security have the greatest effect on initial trust with path coefficients of 0.47, 0.23, and 0.20, respectively, and system quality has the least effect on initial trust with It has a value of 0.07. Also, the results show that self-efficacy only moderates the effect of system quality on initial trust. Therefore, since self-efficacy, aside from the role of attitude adjustment, directly has the greatest effect on primary trust; Social network designers should pay special attention to this factor; So that it is easy to learn and the process of using it is clear and understandable for users.
1. Bargh, J. A. & McKenna, K. Y. A., The Internet and social life. Annual Review of Psychology, 2004, 55: 573–590.
2. Hanafizadeh, P. Behboudi, M. Abedini Koshksaray, A., Mobile-banking adoption by Iranian bank clients. Telematics and Informatics, 2014, 31: 62-78.
3. Dong, T. P. Cheng, N.C. Jim wu, Y.Ch., A study of the social networking website service in digital content industries: The Facebook case in Taiwan. Computers in Human Behavior, 2014, http://dx.doi.org/10.1016/j.chb.2013.07.037.
4. Chang, C. Heo, j., Visiting theories that predict college students’ self-disclosure on Facebook. Computers in Human Behavior, 2014, 30: 79–86.
5. McKnight, D.H. Choudhury, N.L. Kacmar, C., The impact of initial consumer trust on intentions to transact with a web site: a trust building model. Journal of Strategic Information Systems, 2002b, 11: 297–323.
6. Ba, S. Whinston, A. Zhang, H., Building trust in online auction markets through an economic incentive mechanism. Decision Support Systems, 2003, 35: 273– 286.
7. Koufaris, M. Hampton-Sosa, W., The development of initial trust in an online company by new customers. Information & Management, 2004, 41: 377–397.
8. Zhou, T., Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective, Computers in Human Behavior, 2012, 28: 1518–1525.
9. McKnight, D.H. Chervany, N.L., Reflections on an initial trust-building model. Handbook of trust research, 2006, 29-51.
10. Mayer, R.C. Davis, J.H. Schoorman, F.D., An integrative model of organizational trust. Academy of Management Review, 1995, 20 (3): 709–734.
11. Szymczak, H., Kücükbalaban, P., Lemanski, S., Knuth, D., & Schmidt, S., Trusting Facebook in crisis situations: the role of general use and general trust toward Facebook. Cyberpsychology, Behavior, and Social Networking, 2016, 19(1), 23-27.
12. Kim, Y. H. Kim, D. J., A Study of Online Transaction Self-Efficacy, Consumer Trust, and Uncertainty Reduction in Electronic Commerce Transaction. 38th Hawaii International Conference on System Sciences, 2005.
13. Coulter, K.S. Coulter, R.A., The effects of industry knowledge on the development of trust in service relationships. Int J Res Mark, 2003, 20: 31–43.
14. Rodolfo, V.C. Leticia, S.A. Ana, M.D.M., Trust as a key factor in successful relationships between consumers and retail service providers. The Service Industries Journal, 2005, 25(1): 83-101.
15. Chang, Ch. Sh. Chen, Su. Y. Lan, Yi. T., Service quality, trust, and patient satisfaction in interpersonal-based medical service encounters. BMC Health Services Research, 2013, 13(22): 13-22.
16. Ayyash, M. M. Ahmad, K. Singh, D., Investigating the Effect of Information Systems Factors on Trust in E-Government Initiative Adoption in Palestinian Public Sector. Research Journal of Applied Sciences, Engineering and Technology, 2013, 5(15): 3865-3875.
17. Petty, R. Cacioppo, J., Issue involvement as a moderator of the effects on attitude of advertising content and context. Advances in Consumer Research,1981, 8: 20-24.
18. Bhattacherjee, A. Sanford, C., Influence processes for information technology acceptance. An elaboration likelihood model. MIS Quarterly, 2006, 30(4): 805–825.
19. Yi, M.Y. Yoon, J.J. Davis, J.M. Lee, T., Untangling the antecedents of initial trust in Web-based health information: The roles of argument quality, source expertise, and user perceptions of information quality and risk. Decision Support Systems, 2013, 55: 284–295.
20. Seddon, P.B., A respecification and extensions of the Delone and Mclean model of IS success. Information Systems Research, 1997, 8(3): 240-253.
21. Nicolaou, A. I. McKnight, D.H., Perceived Information Quality in Data Exchanges: Effects on Risk, Trust, and Intention to Use. Information Systems Research, 2006, 17 (4): 332-351.
22. McKinney, V. Yoon, K. Zahedi, F.M., The measurement of Web customer satisfaction: An expectation and disconfirmation approach. Information System Research, 2002, 13(3): 296-315.
23. Ha, H.Y., Factors influencing consumer perceptions of brand trust online. Journal of Product & Brand Management, 2004, 13(5): 329–342.
24. Beldad, A. de Jong, M. Steehouder, M., How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior, 2010, 26(5): 857–869.
25. Parasuraman, A. Zeithaml, V. A. Berry, L. L., SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing,1988, 64(1): 12-37
26. Prayag, G., Assessing international tourists’ perceptions of service quality at Air Mauritius. International Journal of Quality & Reliability Management, 2007, 24(5): 492-514.
27. Kim, H. W. Xu, Y. Koh, J., A comparison of online trust building factors between potential customers and repeat customers. Journal of the Association for Information Systems, 2004, 5(10): 392–420.
28.Grabner-Kräuter, S., & Bitter, S., Trust in online social networks: A multifaceted perspective. In Forum for social economics, 2015, Vol. 44, No. 1, pp. 48-68.
29. Bart, Y. Shankar, V. Sultan, F. Urban, G.L., Are the drivers and role of online trust the same for all Web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 2005, 69: 133–152.
30. Vance, A. Christophe, E.-D.-C. Straub, D. W., Examining trust in information technology artifacts: The effects of system quality and culture. Journal of Management Information Systems, 2008, 24(4): 73–100.
31. Teo, S.H. Liu, J., Consumer trust in e-commerce in the United States, Singapore and China. The international journal of management science, 2007, 22
32. Doney, PM. Cannon, JP., an examination of the nature of trust in buyer–seller relationships. Journal of Marketing, 1997, 61(2): 35–51.
33. Shi, S., & Chow, W. S., Trust development and transfer in social commerce: prior experience as moderator. Industrial Management & Data Systems, 2015, 115(7), 1182-1203.
34. Shapiro, S.P., The social control of impersonal trust. American Journal of Sociology, 1987, 93 (3): 623–658.
35. Head, M. Hassanein, K., Trust in e-Commerce: Evaluating the Impact of Third-Party Seals. Quarterly Journal of Electronic Commerce, 2002, 3(3): 307-325.
36. Bandura, A., Self-efficacy: Toward a unifying theory of behavior change. Psychological Review, 1977, 84: 191–215.
37. McKnight, D. H. Choudhury, V. Kacmar, C., Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 2002a, 13(3): 334–359.
38. Zhou, Zh., Zhang Q., Su Ch., Zhou N., How do brand communities generate brand relationships? Intermediate mechanisms, Journal of Business Research, 2012, 65: 890–895.
39. آذر، عادل؛ غلامزاده، رسول؛ قنواتی، مهدی، مدلسازی مسیری-ساختاری در مدیریت، کاربرد نرم‌افزار Smart PLS تهران، انتشارات نگاه دانش، 1391.
40. Cronbach, L.J., Coefficient Alpha and the Internal Structure of Tests. Psychometrical, 1951, 16: 297- 334.
41. Nunnally, J. C., & Bernstein, I. H., Psychometric theory (3rd ed). New York: McGraw-Hill, 1994.
42. Nunnally, J. C., Psychometric theory. New York, NY: McGraw-Hill, 1978.
43. Ha, H. Y., John, J., John, J. D., & Chung, Y. K., Temporal effects of information from social networks on online behavior: the role of cognitive and affective trust. Internet Research, 2016, 26(1), 213-235.
44. Magner, N. Welker, R. B. & Campbell, T. L., Testing a model of cognitive budgetary participation -processes in a latent variable structural equations framework. Accounting and Business Research, 1996, 27 (1): 41-50.
45. داوری، علی؛ رضازاده، آرش ؛ مدل¬سازی معادلات ساختاری با نرم افزار PLS، تهران: انتشارات سازمان جهاد دانشگاهی، 1392.
46. Wetzels, M., Odekerken-Schroder, G., & Van Oppen, C., Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 2009, 33(1): 177.
47. Amiri Aghdaie, F. Fathi, S. Piraman, A., Factors affecting the attitude of trust in Internet purchasing from the perspective of consumers. Institute of Interdisciplinary Business Research, 2011, 3 (5):208-221.
48. Xiaoni, Z. Kellie, B.K. Robert, J.P., Information Quality of Commercial Web Site Home Pages: An Explorative Analysis. Retrieved July 1, from: http://aisel.aisnet.org/icis2000/16.
49. Casalo, L. V. Flavian, C. Guinaliu, M., The influence of satisfaction, perceived reputation and trust on a consumer’s commitment to a website. Journal of Marketing Communications, 2007, 13(1): 1–17.
50. Fornell, C., & Larcker, D., Structural
equation models with unobservable variables and measurement error. Journal of Marketing Research, 1981, 18(1): 39–50.
