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Article
Publication date: 8 April 2014

Yeliz Ekinci, Nimet Uray and Füsun Ülengin

The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a specific…

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Abstract

Purpose

The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a specific industry – namely the banking sector.

Design/methodology/approach

This study compares the results of the least square estimation (LSE) and artificial neural network (ANN) in order to select the best performing forecasting tool to predict the potential CLV. The performances of the models are compared by the hit ratio, which is calculated by grouping the customers as “top 20 per cent” and “bottom 80 per cent” profitable.

Findings

Due to its higher performance; LSE based linear regression model is selected. The results are found to be highly competitive compared with the previous studies. This study shows that, beside the indicators mostly used in the literature in measuring CLV, two additional groups, namely monetary value and risk of certain bank services, as well as product/service ownership-related indicators, are also significant factors.

Practical implications

Organisations in the banking sector have to persuade their customers to use certain routine risk-bearing transaction-based services. In addition, the product development strategy has a crucial role to increase the CLV of customers because some of the product-related variables directly increase the value of customers.

Originality/value

The proposed model predicts potential value of current customers rather than measuring current value considered in the majority of previous studies. It eliminates the limitations and drawbacks of the majority of models in the literature through simple and industry-specific method which is based on easily measurable and objective indicators.

Details

European Journal of Marketing, vol. 48 no. 3/4
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 19 May 2022

Amrita Priyadarsini and Ajit Kumar

Information technology (IT) governance (ITG) is a complex concept that researchers are still exploring in many dimensions. The literature in this area has grown at a fast pace. It…

Abstract

Purpose

Information technology (IT) governance (ITG) is a complex concept that researchers are still exploring in many dimensions. The literature in this area has grown at a fast pace. It required a review article to make sense of the growing body of literature. This study aims to provide a comprehensive view of ITG for understanding this phenomenon.

Design/methodology/approach

The framework of systematicity and transparency is used to search, select and report relevant articles. This study synthesized the identified pool of articles by using thematic analysis, wherein each article was attached to various identified categories.

Findings

This study presents a comprehensive overview of the ITG literature space, including themes and subthemes. It highlights future research avenues and identifies gaps in the ITG area.

Research limitations/implications

Information system researchers and senior practitioners can use this literature review to overview the up-to-date ITG literature. It can also be helpful for non-information system researchers who intend to conduct multi-disciplinary research.

Originality/value

This research looks at the ITG literature space by considering up-to-date literature and a fresh perspective.

Details

Digital Policy, Regulation and Governance, vol. 24 no. 3
Type: Research Article
ISSN: 2398-5038

Keywords

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