Share:


New hybrid FMADM model for mobile commerce improvement

    Shu-Kung Hu Affiliation
    ; James Liou Affiliation
    ; Yen-Ching Chuang Affiliation
    ; Gwo-Hshiung Tzeng Affiliation

Abstract

Internet of things (IoT) can provide an extensive scope of services via smart devices to promote the convenience of life. With advances being made in smart phones, enterprises are increasingly considering expanding their customer base through mobile commerce services. To promote m-commerce improvement, enterprises should organize an excellent m-commerce environment and attempt to realize user needs in the era of IoT. In a fuzzy environment of the real world, objective decision-making for m-commerce improvement is usually a FMADM problem involving feedback-effect and interdependence among the dimensions and criteria. But, many traditional decision models cannot conduct the complicated interrelationships among dimensions and criteria. This study proposes an improvement model that can promote m-commerce improvement towards achieving the aspiration level in fuzzy environment. The proposed hybrid model conducts the feedback-effect and dependence among attributes, and it combines the FDEMATEL technique, FDANP, and MFGRA methods. The empirical case study was conducted to prove the utility of the new hybrid FMADM model in evaluating an m-commerce environment. Comparative results exhibited that the proposed approach is superior to the traditional method and that it can obtain most real grey relational degree that can be used for establishing the best performance improvement strategy in reality.

Keyword : Internet of things (IoT), mobile commerce improvement, fuzzy multiple attribute decision-making (FMADM), fuzzy DEMATEL-based analytic network process (FDANP), modified fuzzy gray relation analysis (MFGRA)

How to Cite
Hu, S.-K., Liou, J., Chuang, Y.-C., & Tzeng, G.-H. (2018). New hybrid FMADM model for mobile commerce improvement. Technological and Economic Development of Economy, 24(5), 1801-1828. https://doi.org/10.3846/20294913.2017.1318311
Published in Issue
Oct 1, 2018
Abstract Views
1151
PDF Downloads
856
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Ajzen, I. 1991. The theory of planned behavior, Organizational Behavior and Human Decision Processes 50(2): 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Aldridge, A.; White, M.; Forcht, K. 1997. Security considerations of doing business via the Internet: cautions to be considered, Internet Research 7(1): 9–15. https://doi.org/10.1108/10662249710159809

Atzori, L.; Iera, A.; Morabito, G. 2010. The Internet of things: a survey, Computer Networks 54: 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

Barnes, S. J. 2002. The mobile commerce value chain: analysis and future developments, International Journal of Information Management 22(2): 91–108. https://doi.org/10.1016/S0268-4012(01)00047-0

Chellappa, P. K.; Pavlou, P. A. 2002. Perceived information security, financial liability and consumer trust in electronic commerce transactions, Logistics Information Management 15(5/6): 358–368. https://doi.org/10.1108/09576050210447046

Chiou, H. K.; Tzeng, G. H. 2001. Fuzzy hierarchical evaluation with grey relation model of green engineering for industry, International Journal of Fuzzy Systems 3(3): 466–475.

Chiu, W. Y.; Tzeng, G. H.; Li, H. L. 2014. Developing e-store marketing strategies to satisfy customers’ needs using a new hybrid gray relational model, International Journal of Information Technology & Decision Making 13(2): 231–261. https://doi.org/10.1142/S0219622014500357

Chong, A. Y. L. 2013a. Predicting m-commerce adoption determinants: a neural network approach, Expert Systems with Applications 40(2): 523–530. https://doi.org/10.1016/j.eswa.2012.07.068

Chong, A. Y. L. 2013b. Mobile commerce usage activities: the roles of demographic and motivation variables, Technological Forecasting and Social Change 80(7): 1350–1359. https://doi.org/10.1016/j.techfore.2012.12.011

Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly 13(3): 319–340. https://doi.org/10.2307/249008

Davis, F. D.; Bagozzi, R. P.; Warshaw, P. R. 1989. User acceptance of computer technology: a comparison of two theoretical models, Management Science 35(8): 982–1003. https://doi.org/10.1287/mnsc.35.8.982

Deng, J. L. 1982. Control problems of grey system, System and Control Letters 1(5): 288–294. https://doi.org/10.1016/S0167-6911(82)80025-X

Fang, Y.; Qureshi, I.; Sun, H.; McCole, P.; Ramsey, E.; Lim, K. H. 2014. Trust, satisfaction, and online repurchase intention: the moderating role of perceived effectiveness of e-commerce institutional mechanisms, MIS Quarterly 38(2): 407–427. https://doi.org/10.25300/MISQ/2014/38.2.04

Gabus, A.; Fontela, E. 1972. World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Centre, Geneva, Switzerland.

Gabus, A.; Fontela, E. 1973. Perceptions of the world problematique: communication procedure, communicating with those bearing collective responsibility (DEMATEL Report No. 1). Battelle Geneva Research Centre, Geneva, Switzerland.

Gefen, D. 2000. E-commerce: the role of familiarity and trust, Omega 28(6): 725–737. https://doi.org/10.1016/S0305-0483(00)00021-9

Gefen, D. 2002. Nurturing clients’ trust to encourage engagement success during the customization of ERP systems, Omega 30(4): 287–299. https://doi.org/10.1016/S0305-0483(02)00032-4

Gefen, D.; Karahanna, E.; Straub, D. W. 2003. Trust and TAM in online shopping: an integrated model, MIS Quarterly 27(1): 51–90.

Gefen, D.; Straub, D. W. 2004. Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services, Omega 32(6): 407–424. https://doi.org/10.1016/j.omega.2004.01.006

Gefen, D.; Wyss, S.; Lichtenstein, Y. 2008. Business familiarity as risk mitigation in software development outsourcing contracts, MIS Quarterly 32(3): 531–551.

Gubbi, J.; Buyya, R.; Marusic, S; Palaniswami, M. 2013. Internet of things (IoT): a vision, architectural elements, and future directions, Future Generation Computer Systems 29(7): 1645–1660. https://doi.org/10.1016/j.future.2013.01.010

Haq, A. N.; Kannan, G. 2006. An integrated approach for selecting a vendor using grey relational analysis, International Journal of Information Technology & Decision Making 5(2): 277–295. https://doi.org/10.1142/S0219622006001952

Hsu, C. Y.; Chen, K. T.; Tzeng, G. H. 2007. FMCDM with fuzzy DEMATEL approach for customers’ choice behavior model, International Journal of Fuzzy Systems 4(4): 236–246.

Huang, J. J.; Tzeng, G. H. 2014. New thinking of multi-objective programming with changeable spaces – in search of excellence, Technological and Economic Development of Economy 20(2): 242–261. https://doi.org/10.3846/20294913.2013.860931

Hu, S. K.; Lu, M. T.; Tzeng, G. H. 2015. Improving mobile commerce adoption using a new hybrid fuzzy MADM model, International Journal of Fuzzy Systems 17(3): 399–413. https://doi.org/10.1007/s40815-015-0054-z

Kim, C.; Tao, W.; Shin, N.; Kim, K. S. 2010. An empirical study of customers’ perceptions of security and trust in e-payment systems, Electronic Commerce Research and Applications 9(1): 84–95. https://doi.org/10.1016/j.elerap.2009.04.014

Kou, G.; Lu, Y.; Peng, Y.; Shi, Y. 2012. Evaluation of classification algorithms using MCDM and rank correlation, International Journal of Information Technology & Decision Making 11(1): 197–225. https://doi.org/10.1142/S0219622012500095

Leu, F. Y.; Huang, Y. L.; Wang, S. M. 2015. A Secure M-Commerce system based on credit card transaction, Electronic Commerce Research and Applications 14(5): 351–360. https://doi.org/10.1016/j.elerap.2015.05.001

Li, S.; Tryfonas,T.; Li , H. 2016. The Internet of things: a security point of view, Internet Research 26(2): 337–359. https://doi.org/10.1108/IntR-07-2014-0173

Liao, S.; Shao, Y. P.; Wang, H.; Chen, A. 1999. The adoption of virtual banking: an empirical study, International Journal of Information Management 19(1): 63–74. https://doi.org/10.1016/S0268-4012(98)00047-4

Liou, J. J. H.; Tzeng, G. H. 2012. Comments on multiple criteria decision making (MCDM) methods in economics: an overview, Technological and Economic Development of Economy 18(4): 672–695. https://doi.org/10.3846/20294913.2012.753489

Liou, J. J. H. 2013. New concepts and trends of MCDM for tomorrow – in honor of Professor Gwo-Hshiung Tzeng on the occasion of his 70th birthday, Technological and Economic Development of Economy 19(2): 367–375. https://doi.org/10.3846/20294913.2013.811037

Liou, J. J. H.; Chuang, Y. C.; Tzeng, G. H. 2014. A fuzzy integral-based model for supplier evaluation and improvement, Information Sciences 266: 199–217. https://doi.org/10.1016/j.ins.2013.09.025

Liou, J. J. H.; Tamošaitienė, J.; Zavadskas, E. K.; Tzeng, G. H. 2016. New hybrid COPRAS-GMADM model for improving and selecting suppliers in green supply chain management, International Journal of Production Research 54(1): 114–134. https://doi.org/10.1080/00207543.2015.1010747

Lu, M. T.; Tzeng, G. H.; Tang, L. L. 2013. Environmental strategic orientations for improving green innovation performance in fuzzy environment – using new fuzzy hybrid MCDM model, International Journal of Fuzzy Systems 15(3): 297–316.

Lu, M. T.; Hu, S. K.; Tzeng, G. H. 2015. Evaluating the implementation of business-to-business m-commerce by SMEs based on a new hybrid MADM model, Management Decision 53(2): 290–317. https://doi.org/10.1108/MD-01-2014-0012

Maity, M.; Dass, M. 2014. Consumer decision-making across modern and traditional channels: E-commerce, m-commerce, in-store, Decision Support Systems 61: 34–46. https://doi.org/10.1016/j.dss.2014.01.008

McKnight, D. H.; Chervany, N. L. 2001. What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology, International Journal of Electronic Commerce 6(2): 35–59. https://doi.org/10.1080/10864415.2001.11044235

McKnight, D. H.; Choudhury, V.; Kacmar, C. 2002. Developing and validating trust measures for e-commerce: an integrative typology, Information Systems Research 13(3): 334–359. https://doi.org/10.1287/isre.13.3.334.81

Ngai, E. W. T.; Gunasekaran, A. 2007. A review for mobile commerce research and applications, Decision Support Systems 43(1): 3–15. https://doi.org/10.1016/j.dss.2005.05.003

Opricovic, S.; Tzeng, G. H. 2003. Defuzzification within a fuzzy multicriteria decision model, International Journal of Uncertainty, Fuzziness and Knowledge-based Systems 11(5): 635–652. https://doi.org/10.1142/S0218488503002387

Peng, Y.; Kou, G.; Wang, G.; Shi, Y. 2011. FAMCDM: a fusion approach of MCDM methods to rank multiclass classification algorithms, Omega 39(6): 677–689. https://doi.org/10.1016/j.omega.2011.01.009

Pynpoo, B.; van Braak, J. 2014. Predicting teachers’ generative and receptive use of an educational portal by intention, attitude and self-reported use, Computers in Human Behavior 34: 315–322. https://doi.org/10.1016/j.chb.2013.12.024

Ridings, C. M.; Gefen, D.; Arinze, B. 2002. Some antecedents and effects of trust in virtual communities, Journal of Strategic Information Systems 11(3–4): 271–295. https://doi.org/10.1016/S0963-8687(02)00021-5

Ruan, J.; Shi, Y. 2016. Monitoring and assessing fruit freshness in IOT-based e-commerce delivery using scenario analysis and interval number approaches, Information Sciences 373: 271–295. https://doi.org/10.1016/j.ins.2016.07.014

Saaty, T. L. 1996. Decision making with dependence and feedback: the analytic network process. RWS Publications, Pittsburgh.

Sadeh, N. 2002. M-commerce: technologies, services, and business models. New York: John Wiley and Sons.

Simon, H. A. 1955. A behavioral model of rational choice, The Quarterly Journal of Economics 69(1): 99–118. https://doi.org/10.2307/1884852

Simon, H. A. 1972. Theories of bounded rationality, in C. B. McGuire, R. Radner (Eds.). Decision and Organization. Amsterdam: North-Holland, 161–176.

Su, C. H.; Tzeng, G. H; Hu, S. K. 2016. Cloud e-learning service strategies for improving e-learning innovation performance in a fuzzy environment by using a new hybrid fuzzy multiple attribute decision-making model, Interactive Learning Environments 24(8): 1812–1835. https://doi.org/10.1080/10494820.2015.1057742

Suh, B.; Han, I. 2003. The impact of customer trust and perception of security control on the acceptance of electronic commerce, International Journal of Electronic Commerce 7(3): 135–161.

Taylor, S.; Todd, P. 1995. Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions, International Journal of Research in Marketing 12(2): 137–155. https://doi.org/10.1016/0167-8116(94)00019-K

Tsiakis, T.; Sthephanides, G. 2005. The concept of security and trust in electronic payments, Computers & Security 24(1): 10–15. https://doi.org/10.1016/j.cose.2004.11.001

Tzeng, G. H.; Chiang, C. H.; Li, C. W. 2007. Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL, Expert Systems with Applications 32(4): 1028–1044. https://doi.org/10.1016/j.eswa.2006.02.004

Tzeng, G. H.; Huang, J. J. 2011. Multiple attribute decision making: methods and applications. CRC Press, Taylor & Francis Group, a Chapman & Hall Book.

Tzeng, G. H.; Huang, J. J. 2013. Fuzzy multiple objective decision making. CRC Press, Taylor & Francis Group, a Chapman & Hall Book.

Venkatesh, V.; Morris, M. G.; Davis, G. B.; Davis, F. D. 2003. User acceptance of information technology: toward a unified view, MIS Quarterly 27(3): 425–478.

Vijayasarathy, L. R. 2004. Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model, Information and Management 41(6): 747–762. https://doi.org/10.1016/j.im.2003.08.011

Watson, C.; McCarthy, J.; Rowley, J. 2013. Consumer attitudes towards mobile marketing in the smart phone era, International Journal of Information Management 33(5): 840–849. https://doi.org/10.1016/j.ijinfomgt.2013.06.004

Yang, K. C. C. 2005. Exploring factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics 22(3): 257–277. https://doi.org/10.1016/j.tele.2004.11.003

Zadeh, L. A. 1975. The concept of a linguistic variable and its application to approximate reasoning, Information Sciences 8(3): 199–249. https://doi.org/10.1016/0020-0255(75)90036-5