توسعه ی یک مدل دیمتل فازی برای شناسایی عوامل کلیدی مؤثر بر پذیرش فناوری¬های مخابراتی در ایران- مورد مطالعاتی: نسل چهارم شبکه های موبایل
الموضوعات : مدیریت تکنولوژیحسین سبزیان 1 , محمد علی شفیعا 2 , مهدي غضنفري 3
1 - دانشگاه علم و صنعت ایران
2 - علم وصنعت
3 - دانشگاه علم و صنعت
الکلمات المفتاحية: پذیرش و انتشار فناوری نسل چهارم (4G) فناوری تکامل بلندت مدت (LTE) منطق فازی دیمتل,
ملخص المقالة :
به رغم سرمایه گذاری های وسیع سه اپراتور اصلی ایران یعنی همراه اول، ایرانسل و رایتل در توسعه ی فناوری تکامل بلند مدت (LTE) بعنوان مهمترین نماینده ی نسل چهارم شبکه های موبایل، تا اوایل تابستان 1396، انتشاراین فناوری با ضریب نفوذ 0.06 در کل جامعه بسیار کند بوده است . چنین وضعیتی می تواند پیامدهای نامطلوبی را برای اپراتورهای مخابراتی بهمراه داشته باشد که عمده ترین آن ها عبارتند از 1) عدم توانایی در ارایه ی شمار زیادی از خدمات باکیفیت بالا، 2) ناتوانی در رقابت با فناوری های OTT نظیر تلگرام ، 3) طولانی شدن دوره ی بازگشت سرمایه، 4) عدم یکپارچه پذیری با شبکه ی نسل پنجم و از دست دادن فرصت های اینترنت اشیاء. از اینرو، برای حل این چالش؛ برنامه ریزان اپراتورهای مخابراتی می باید عوامل کلیدی مؤثر بر پذیرش فناوری شبکه های نسل چهارم در جامعه ایرانی را شناسایی کنند که چنین شناختی مستلزم توسعه مدلی علمی است که نتها محدودیت های پژوهش های پیشین را برطرف می سازد که امکان شناخت بهتری از جامعه هدف را نیز فراهم سازد که این مقاله با توسعه یک مدل دیمتل فازی به دنبال تحقق چنین هدفی است.
[1] Noh, H.; Song, Y.-K.; Lee, S. Identifying Emerging Core Technologies for the Future: Case Study of Patents Published by Leading Telecommunication Organizations. Telecomm. Policy, 2016, 40 (10–11), 956–970.
[2] Heuveldop, N. Ericsson Mobility Report June 2017. Ericsson, Tech. Rep., 2017.
[3] Union, I. T. ICT Facts and Figures: The World in 2015. ITU Geneva 2015.
[4] Vilches, J. Everything You Need to Know about 4G Wireless Technology. TechSpot. April, 2010, 29.
[5] Opensignal. The State of LTE (June 2017) Report | Opensignal; 2017.
[6] SNS. Wireless Network Infrastructure Forecasts: 2016 – 2030 – Macrocell RAN, Small Cells, C-RAN, RRH, DAS, Carrier Wi-Fi, Mobile Core, Backhaul & Fronthaul - SNS Telecom; 2016.
[7] forbes. Roundup Of Internet of Things Forecasts And Market Estimates https://www.forbes.com/sites/louiscolumbus/2015/12/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2015/#348b47004b93 (accessed Jun 6, 2019).
[8] Chong, A. Y.-L.; Darmawan, N.; Ooi, K.-B.; Lin, B. Adoption of 3G Services among Malaysian Consumers: An Empirical Analysis. Int. J. Mob. Commun., 2010, 8 (2), 129–149.
[9] Chen, L.; Meservy, T. O.; Gillenson, M. Understanding Information Systems Continuance for Information-Oriented Mobile Applications. Commun. Assoc. Inf. Syst., 2012, 30 (9), 127–146.
[10] Karaiskos, D. C.; Drossos, D. A.; Tsiaousis, A. S.; Giaglis, G. M.; Fouskas, K. G. Affective and Social Determinants of Mobile Data Services Adoption. Behav. Inf. Technol., 2012, 31 (3), 209–219.
[11] Lu, J.; Yao, J. E.; Yu, C.-S. Personal Innovativeness, Social Influences and Adoption of Wireless Internet Services via Mobile Technology. J. Strateg. Inf. Syst., 2005, 14 (3), 245–268.
[12] Lin, S.; Lin, S.; Chen, P. S.; Liu, Y. Adoption of 4G Wireless Services under Consideration of Technology and Economic Perspectives. Int. J. Mob. Commun., 2014, 13 (1), 71–91.
[13] Liu, C.-C. Measuring and Prioritising Value of Mobile Phone Usage. Int. J. Mob. Commun., 2010, 8 (1), 41–52.
[14] Phan, K.; Daim, T. U. Exploring Technology Acceptance for Mobile Services. J. Ind. Eng. Manag., 2011, 4 (2), 339–360.
[15] Nikou, S.; Mezei, J. Evaluation of Mobile Services and Substantial Adoption Factors with Analytic Hierarchy Process (AHP). Telecomm. Policy, 2013, 37 (10), 915–929.
[16] Shieh, L.-F.; Chang, T.-H.; Fu, H.-P.; Lin, S.-W.; Chen, Y.-Y. Analyzing the Factors That Affect the Adoption of Mobile Services in Taiwan. Technol. Forecast. Soc. Change, 2014, 87, 80–88.
[17] Büyüközkan, G. Determining the Mobile Commerce User Requirements Using an Analytic Approach. Comput. Stand. Interfaces, 2009, 31 (1), 144–152.
[18] Mirmousa, S.; Dehnavi, H. D. Development of Criteria of Selecting the Supplier by Using the Fuzzy DEMATEL Method. Procedia-Social Behav. Sci., 2016, 230, 281–289.
[19] Lin, H.-F. Determining the Relative Importance of Mobile Banking Quality Factors. Comput. Stand. Interfaces, 2013, 35 (2), 195–204.
[20] Rogers, E. M. Diffusion of Innovations, Fifth Edit.; Simon and Schuster, 2003.
[21] Fishbein, M.; Ajzen, I. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. 1977.
[22] Ajzen, I. From Intentions to Actions: A Theory of Planned Behavior. In Action control; Springer, 1985; pp 11–39.
[23] Davis, F. D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q., 1989, 319–340.
[24] Thompson, R. L.; Higgins, C. A.; Howell, J. M. Personal Computing: Toward a Conceptual Model of Utilization. MIS Q., 1991, 125–143.
[25] Davis, F. D.; Bagozzi, R. P.; Warshaw, P. R. Extrinsic and Intrinsic Motivation to Use Computers in the Workplace 1. J. Appl. Soc. Psychol., 1992, 22 (14), 1111–1132.
[26] Venkatesh, V.; Davis, F. D. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Manage. Sci., 2000, 46 (2), 186–204.
[27] Venkatesh, V.; Morris, M. G.; Davis, G. B.; Davis, F. D. User Acceptance of Information Technology: Toward a Unified View. MIS Q., 2003, 425–478.
[28] Boyd, T. C.; Mason, C. H. The Link between Attractiveness of “Extrabrand” Attributes and the Adoption of Innovations. J. Acad. Mark. Sci., 1999, 27 (3), 306–319.
[29] Keaveney, S. M.; Parthasarathy, M. Customer Switching Behavior in Online Services: An Exploratory Study of the Role of Selected Attitudinal, Behavioral, and Demographic Factors. J. Acad. Mark. Sci., 2001, 29 (4), 374–390.
[30] Sarker, S.; Wells, J. D. Understanding Mobile Handheld Device Use and Adoption. Commun. ACM, 2003, 46 (12), 35–40.
[31] Teo, T. S. H.; Pok, S. H. Adoption of WAP-Enabled Mobile Phones among Internet Users. Omega, 2003, 31 (6), 483–498.
[32] Pagani, M. Determinants of Adoption of Third Generation Mobile Multimedia Services. J. Interact. Mark., 2004, 18 (3), 46–59.
[33] Yang, K. C. C. Exploring Factors Affecting the Adoption of Mobile Commerce in Singapore. Telemat. informatics, 2005, 22 (3), 257–277.
[34] Lu, J.; Yu, C.-S.; Liu, C. Facilitating Conditions, Wireless Trust and Adoption Intention. J. Comput. Inf. Syst., 2005, 46 (1), 17–24.
[35] Scheepers, R.; Scheepers, H.; Ngwenyama, O. K. Contextual Influences on User Satisfaction with Mobile Computing: Findings from Two Healthcare Organizations. Eur. J. Inf. Syst., 2006, 15 (3), 261–268.
[36] Blechar, J.; Constantiou, I. D.; Damsgaard, J. Exploring the Influence of Reference Situations and Reference Pricing on Mobile Service User Behaviour. Eur. J. Inf. Syst., 2006, 15 (3), 285–291.
[37] Ranganathan, C.; Seo, D.; Babad, Y. Switching Behavior of Mobile Users: Do Users’ Relational Investments and Demographics Matter? Eur. J. Inf. Syst., 2006, 15 (3), 269–276.
[38] Schierz, P. G.; Schilke, O.; Wirtz, B. W. Understanding Consumer Acceptance of Mobile Payment Services: An Empirical Analysis. Electron. Commer. Res. Appl., 2010, 9 (3), 209–216.
[39] Hill, S. R.; Troshani, I. Factors Influencing the Adoption of Personalisation Mobile Services: Empirical Evidence from Young Australians. Int. J. Mob. Commun., 2010, 8 (2), 150–168.
[40] Lin, H.-F. An Empirical Investigation of Mobile Banking Adoption: The Effect of Innovation Attributes and Knowledge-Based Trust. Int. J. Inf. Manage., 2011, 31 (3), 252–260.
[41] Chong, J.-L.; Chong, A. Y.-L.; Ooi, K.-B.; Lin, B. An Empirical Analysis of the Adoption of M-Learning in Malaysia. Int. J. Mob. Commun., 2011, 9 (1), 1–18.
[42] Rockart, J. F. Chief Executives Define Their Own Data Needs. Harv. Bus. Rev., 1979, 57 (2), 81–93.
[43] Thierauf, R. J. Decision Support Systems for Effective Planning and Control: A Case Study Approach; Prentice Hall PTR, 1982.
[44] Zhou, Q.; Huang, W.; Zhang, Y. Identifying Critical Success Factors in Emergency Management Using a Fuzzy DEMATEL Method. Saf. Sci., 2011, 49 (2), 243–252.
[45] Shen, Y.-C.; Lin, G. T. R.; Tzeng, G.-H. Combined DEMATEL Techniques with Novel MCDM for the Organic Light Emitting Diode Technology Selection. Expert Syst. Appl., 2011, 38 (3), 1468–1481.
[46] Gabus, A.; Fontela, E. Perceptions of the World Problematique: Communication Procedure, Communicating with Those Bearing Collective Responsibility. Battelle Geneva Res. Centre, Geneva, Switz., 1973.
[47] Gabus, A.; Fontela, E. World Problems, an Invitation to Further Thought within the Framework of DEMATEL. Battelle Geneva Res. Center, Geneva, Switz., 1972.
[48] Given, L. M. The Sage Encyclopedia of Qualitative Research Methods; Sage publications, 2008.
[49] Bickman, L.; Rog, D. J. The SAGE Handbook of Applied Social Research Methods; Sage publications, 2008.
[50] Herrera, F.; Herrera-Viedma, E.; Martı́nez, L. A Fusion Approach for Managing Multi-Granularity Linguistic Term Sets in Decision Making. Fuzzy sets Syst., 2000, 114 (1), 43–58.
[51] Wang, R.-C.; Chuu, S.-J. Group Decision-Making Using a Fuzzy Linguistic Approach for Evaluating the Flexibility in a Manufacturing System. Eur. J. Oper. Res., 2004, 154 (3), 563–572.
[52] Wang, L.; Langari, R. Complex Systems Modeling via Fuzzy Logic. IEEE Trans. Syst. Man, Cybern. Part B, 1996, 26 (1), 100–106.
[53] Zadeh, L. A. Fuzzy Sets. Inf. Control, 1965, 8 (3), 338–353.
[54] Chang, B.; Chang, C.-W.; Wu, C.-H. Fuzzy DEMATEL Method for Developing Supplier Selection Criteria. Expert Syst. Appl., 2011, 38 (3), 1850–1858.
[55] Lee, Y.-C.; Li, M.-L.; Yen, T.-M.; Huang, T.-H. Analysis of Fuzzy Decision Making Trial and Evaluation Laboratory on Technology Acceptance Model. Expert Syst. Appl., 2011, 38 (12), 14407–14416.
[56] Wu, W.-W.; Lee, Y.-T. Developing Global Managers’ Competencies Using the Fuzzy DEMATEL Method. Expert Syst. Appl., 2007, 32 (2), 499–507.
[57] Wu, W.-W. Choosing Knowledge Management Strategies by Using a Combined ANP and DEMATEL Approach. Expert Syst. Appl., 2008, 35 (3), 828–835.
[58] Shieh, J.-I.; Wu, H.-H.; Huang, K.-K. A DEMATEL Method in Identifying Key Success Factors of Hospital Service Quality. Knowledge-Based Syst., 2010, 23 (3), 277–282.
[59] Precup, R.-E.; Hellendoorn, H. A Survey on Industrial Applications of Fuzzy Control. Comput. Ind., 2011, 62 (3), 213–226.
[60] Yager, R. R.; Filev, D. P. Essentials of Fuzzy Modeling and Control. New York, 1994, 388.
[61] Kaufmann, A.; Gupta, M. M. Fuzzy Mathematical Models in Engineering and Management Science; Elsevier Science Inc., 1988.
[62] Opricovic, S.; Tzeng, G.-H. Defuzzification within a Multicriteria Decision Model. Int. J. Uncertainty, Fuzziness Knowledge-Based Syst., 2003, 11 (05), 635–652.
[63] Van Leekwijck, W.; Kerre, E. E. Defuzzification: Criteria and Classification. Fuzzy sets Syst., 1999, 108 (2), 159–178.
[64] Wang, X.; Kerre, E. E. Reasonable Properties for the Ordering of Fuzzy Quantities (I). Fuzzy sets Syst., 2001, 118 (3), 375–385.
[65] Wang, X.; Kerre, E. E. Reasonable Properties for the Ordering of Fuzzy Quantities (II). Fuzzy sets Syst., 2001, 118 (3), 387–405.
[66] Rogers, E. M. Diffusion of Innovations; Simon and Schuster, 2010.
[67] Samuel Craig, C.; Douglas, S. P. Conducting International Marketing Research in the Twenty-First Century. Int. Mark. Rev., 2001, 18 (1), 80–90.
[68] Maxwell, S. An Expanded Price/Brand Effect Model-A Demonstration of Heterogeneity in Global Consumption. Int. Mark. Rev., 2001, 18 (3), 325–343.
[69] Rawwas, M. Y. A. Culture, Personality and Morality: A Typology of International Consumers’ Ethical Beliefs. Int. Mark. Rev., 2001, 18 (2), 188–211.