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The investigation of accuracy level prediction of Fintech customers loyalty by using data mining algorithm | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 20، دوره 14، شماره 6، شهریور 2023، صفحه 265-271 اصل مقاله (376.47 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.28219.3836 | ||
| نویسندگان | ||
| Hammadreza Babakhanian1؛ Seyed Abdollah Amin Mousavi* 2؛ Roya Soltani3؛ Hamidreza Vakilifard4 | ||
| 1Department of Information Technology Management, Qeshm Branch, Islamic Azad University, Qeshm, Iran | ||
| 2Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| 3Department of Industrial Engineering, Faculty of Engineering, Khatam University, Tehran, Iran | ||
| 4Department of Accounting, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran | ||
| تاریخ دریافت: 07 اردیبهشت 1401، تاریخ بازنگری: 30 خرداد 1401، تاریخ پذیرش: 07 مرداد 1401 | ||
| چکیده | ||
| The emergence of mobile applications is forcing ambitious companies hoping to build loyalty for customers’ brands to rush towards marketing their brand applications. The present research was conducted with the aim of classifying loyal customers and measuring their loyalty level using data mining algorithms. The present research method is based on applied-descriptive and the statistical population included the customers of Asan Pardakht Company which were considered number ten thousand people and with the number of 700,000 transactions. These customers were separated by clustering operation and classified for performing different tests. By using the data of Fintech customers of Asan Pardakht Company, it was attempted by using the decision tree algorithm, in addition, to identifying active customers, to implement this algorithm, a way is made in order to increase customer loyalty and ultimately increase their profitability and create satisfaction among managers. In the present research, by implementing the different stages of Crisp methodology, clustering and testing different artificial intelligence algorithms, the most useful algorithm in order to identify the best customers and also to make them loyal and policies and implementable programs to be formulated in order to increase the satisfaction percentage and finally customers’ loyalty was explained and mentioned. | ||
| کلیدواژهها | ||
| Fintech؛ Customer loyalty؛ Decision tree؛ Data mining algorithms | ||
| مراجع | ||
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[1] A. Akhmedova, F. Marimon and M. Mas-Machuca, Winning strategies for customer loyalty in the sharing economy: A mixed-methods study, J. Bus. Res. 112 (2020), 33–44. [2] D. Anand and M. Mantrala, Responding to disruptive business model innovations: The case of traditional banks facing fintech entrants, J. Bank. Financ. Technol. 3 (2019), no. 1, 19–31. [3] S. Bellman, R.F. Potter, S. Treleaven-Hassard, J.A. Robinson and D. Varan, The effectiveness of branded mobile phone apps, J. Interact. Market. 25 (2011), no. 4, 191–200. [4] P. Cabena, P. Hadjinian, R. Stadler, J. Verhees and A. Zanasi, Discovering data mining from concepts to implementation, Prentice Hall, 1998. [5] U. Fayyad, G. Piatetsky-Shapiro, P. Smith and R. Uthurusamy, Advances in knowledge discovery and data mining, AAAI/MIT Press, 1996. [6] M. Fraering and M.S. Minor, Beyond loyalty: customer satisfaction, loyalty, and fortitude, J. Serv. Market. 27 (2013), no. 4, 334–344. [7] W. Gao, H. Fan, W. Li and H. Wang, Crafting the customer experience in omnichannel contexts: The role of channel integration, J. Bus. Res. 126 (2021), 12–22. [8] M. Ghazanfari, S. Alizadeh and B. Teymorpour, Data mining and knowledge discovery, Iran University of Science and Technology Publication, First edition, Tehran, 2012. [9] D.S. Kumar, K. Purani and S.A. Viswanathan, Influences of ‘appscape’on mobile app adoption and m-loyalty, J. Retail. Consum. Serv. 45 (2018), 132–141. [10] A. Lele and N. Shaw, Augmented reality: does it encourage customer loyalty?, Int. Conf. Human-Comput. Interact., Springer, Cham., 2021, pp. 105–119. [11] H. Liu, L. Lobschat, P.C. Verhoef and H. Zhao, App adoption: The effect on purchasing of customers who have used a mobile website previously, J. Interact. Market. 47 (2019), 16–34. [12] W. Maroengsit, T. Piyakulpinyo, K. Phonyiam, S. Pongnumkul, P. Chaovalit and T. Theeramunkong, A survey on evaluation methods for chatbots, Proc. 7th Int. Conf. Inf. Educ. Technol., 2019, pp. 111–119. [13] G. McLean and A. Wilson, Evolving the online customer experience. . . is there a role for online customer support?, Comput. Human Behav. 60 (2016), 602–610. [14] G. McLean, K. Osei-Frimpong, K. Al-Nabhani and H. Marriott, Examining consumer attitudes towards retailers’m-commerce mobile applications–An initial adoption vs. continuous use perspective, J. Bus. Res. 106 (2020), 139–157. [15] S. Molinillo, R. Aguilar-Illescas, R. Anaya-S´anchez and E. Carvajal-Trujillo, The customer retail app experience: Implications for customer loyalty, J. Retail. Consum. Serv. 65 (2022). [16] S. Molinillo, R. Aguilar-Illescas, R. Anaya-Sanchez and F. Liebana-Cabanillas, Social commerce website design, perceived value and loyalty behavior intentions: the moderating roles of gender, age and frequency of use, J. Retail. Consum. Serv. 63 (2021). [17] S. Molinillo, A. Navarro-Garcıa, R. Anaya-Sanchez and A. Japutra, The impact of affective and cognitive app experiences on loyalty towards retailers, J. Retail. Consum. Serv. 54 (2020). [18] R.A. Mulyono and L.H. Pasaribu, The impact of mobile service quality and brand image on customer loyalty, Enrichment: J. Manag. 12 (2021), no. 1, 1–7. [19] E. Narvanen, H. Kuusela, H. Paavola and N. Sirola, A meaning-based framework for customer loyalty, Int. J. Retail Distrib. Manag. 48 (2020), no. 8, 825–843. [20] S. Omar, K. Mohsen, G. Tsimonis, A. Oozeerally and J.H. Hsu, M-commerce: The nexus between mobile shopping service quality and loyalty, J. Retail. Consum. Serv. 60 (2021), 102468. [21] K. Purani, D.S. Kumar and S. Sahadev, E-Loyalty among millennials: Personal characteristics and social influences, J. Retail. Consum. Serv. 48 (2019), 215–223. [22] I. Ranggadara, G. Wang and E.R. Kaburuan, Applying Customer Loyalty Classification with RFM and Naıve Bayes for Better Decision Making, Int. Seminar Appl. Technol. Inf. Commun. (iSemantic), 2019, pp. 564–568. [23] B.T. Ratchford, The history of academic research in marketing and its implications for the future, Spanish J. Market.-ESIC. 24 (2020), no. 1, 3—36. [24] U. Rehman and K.S. Ha, Factors influencing Fintech’s customer loyalty for cross border payments: Mediating customer satisfaction, Asia-Pacific J. Bus. Ventur. Entrepreneur. 16 (2021), no. 6, 287–297. [25] P.G. Rodrıguez, R. Villarreal, P.C. Valino and S. Blozis, A PLS-SEM approach to understanding E-SQ, satisfaction and e-loyalty for fashion e-retailers in Spain, J. Retail. Consumer Serv. 57 (2020), 102201. [26] S.K. Roy, W.M. Lassar and G.T. Butaney, The mediating impact of stickiness and loyalty on word-of-mouth promotion of retail websites: A consumer perspective, Eur. J. Market. 48 (2014), no. 9/10, 1828–1849. [27] S.S. Srinivasan, R. Anderson and K. Ponnavolu, Customer loyalty in e-commerce: an exploration of its antecedents and consequences, J. Retail. 78 (2002), no. 1, 41–50. [28] P.N. Tan, M. Steinbach and V. Kumar, Introduction to data mining, Pearson Education India, 2016. [29] C.T. Tien, H.K. Cheng and S. Pei-Ling, The mediated effect of relationship marketing on the influences of irritation advertising in fintech times, Proc. 2nd Int. Conf. E-Educ. E-Bus. E-Technol., 2018, pp. 99–101. [30] R. Thakur, Understanding customer engagement and loyalty: a case of mobile devices for shopping, J. Retail. Consumer Serv. 32 (2016), 151–163. [31] T.H. Tseng and C.T. Lee, Facilitation of consumer loyalty toward branded applications: The dual-route perspective, Telemat. Inf. 35 (2018), no. 5, 1297–1309. [32] G. Van Noort and E.A. Van Reijmersdal, Branded apps: Explaining effects of brands’ mobile phone applications on brand responses, J. Interact. Market. 45 (2019), 16–26. [33] N. Vilkaite-Vaitone and I. Skackauskiene, Service customer loyalty: An evaluation based on loyalty factors, Sustainability 12 (2020), no. 6. [34] J. Xu, I. Benbasat and R.T. Cenfetelli, Integrating service quality with system and information quality: an empirical test in the e-service context, MIS Quart. 37 (2013), no. 3, 777–794. [35] V.A. Zeithaml, L.L. Berry and A. Parasuraman, The behavioral consequences of service quality, J. Market. 60 (1996), no. 2, 31–46. [36] Z. Zhao and C. Balagu´e, Designing branded mobile apps: Fundamentals and recommendations, Bus. Horizons 58 (2015), no. 3, 305–315. | ||
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