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A Telemarketing Guidance in Selling Banking Services: A Data Mining Approach Kattareeya Prompreing
Indonesian Journal of Business Analytics Vol. 1 No. 1 (2021): April, 2021
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (532.176 KB) | DOI: 10.55927/ijba.v1i1.1

Abstract

In telemarketing activity, selecting the most potential customers are important because can reduce processing time and operational cost. Therefore, the ability to select the most likely buying customers are urgently needed. In this study, we propose a clear sequence in doing telemarketing activity based on the previous telemarketing data which applying data mining technique. We weight the importance of 16 customer characteristics through 45,211 observations from a Portuguese bank. Applying Random Forest algorithm along with Information Gain Ratio as a criterion and 10-fold Cross Validation, the model able to weight the importance of attributes and achieves 90.01 % accuracy in predicting telemarketing success. Furthermore, the rank of attribute importance was designed to be a guidance map in selecting potential targeted customers as a managerial implication.
Do Monetary Incentives Policy Drive EV Adoption? Evidence from Jakarta and Bangkok Andi Muhammad Sadat; Solikhah Solikhah; Agung Kresnamurti Rivai Prabumenang; Kattareeya Prompreing
International Journal of Applied Business and International Management Vol 11, No 1 (2026): April 2026
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijabim.v11i1.4551

Abstract

This study investigates the factors influencing consumers' intention to buy electric vehicles in Jakarta and Bangkok. It examines the impact of price value, driving range, charging station availability, and monetary incentive policies on purchase intention. The research employs a quantitative technique, which data was collected through an online survey using convenience sampling, targeting individuals aged 17 and above with knowledge and experience related to electric vehicles. The sample consists of 302 respondents, with 167 from Jakarta and 135 from Bangkok. Structural Equation Modeling (SEM) with Partial Least Square (PLS) is used for hypothesis testing. The results reveal that price value, driving range, and charging station availability significantly affect the intention to purchase electric vehicles, while monetary incentive policies do not show a significant impact in both cities. The moderating role of monetary incentive policy on the relationship between price value and purchase intention is also not supported in both cities. The findings provide valuable insights for manufacturers and policymakers in promoting electric vehicle adoption. Future studies could explore additional factors and cover a wider population to guide decision-makers in implementing appropriate adoption of electric vehicles.