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Article
Publication date: 1 October 2006

Christopher Gan, Mike Clemes, Visit Limsombunchai and Amy Weng

In this paper the competitive landscape of financial institutions is shifting and internet banking is no longer a competitive advantage but a competitive necessity for banks…

6489

Abstract

Purpose

In this paper the competitive landscape of financial institutions is shifting and internet banking is no longer a competitive advantage but a competitive necessity for banks. However, a limited number of empirical studies have been published in the marketing literature about electronic banking. This paper seeks to examine consumers' choices between electronic banking and non‐electronic banking in New Zealand.

Design/methodology/approach

The paper shows that the data for this analysis were obtained through a mail survey sent to 1,960 households in New Zealand. The decision to use electronic banking is hypothesised to be a function of service quality dimensions, perceived risk factors, user input factors, price factors, service product characteristics, individual factors and demographic variables such as age, gender, marital status, income, etc. Logistic regression is used to analyse the data. The discrete dependent variable measures whether an individual is an electronic banking or non‐electronic banking user.

Findings

The findings in the paper show that the output from the logistic regression indicates that the service quality, perceived risk factors, user input factors, employment, and education are the dominant variables that influence consumers' choice of electronic banking and non‐electronic banking channels.

Practical implications

This paper provides an improved understanding of consumers' choice between electronic and non‐electronic banking. This paper also identifies new relationships, and provides findings that further support, confirm, or contradict previous studies. In addition, it provides insights into the links between electronic banking and consumer decision making, to help provide strategies, recommendations and guidelines for the banking industry.

Originality/value

The paper shows how banks are developing, and utilizing new alternative distribution channels to reach their customers.

Details

International Journal of Bank Marketing, vol. 24 no. 6
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 13 April 2015

Gemunu Nanayakkara and Jenny Stewart

The repayment performance of microfinancing loans funded by donors amounting to hundreds of millions of dollars is an important issue, because it indicates the effectiveness of…

1486

Abstract

Purpose

The repayment performance of microfinancing loans funded by donors amounting to hundreds of millions of dollars is an important issue, because it indicates the effectiveness of utilising these funds to alleviate poverty. The purpose of this paper is to develop models to predict the repayment success of microfinancing loans.

Design/methodology/approach

Analysing data relating to 1,109 random loan records from Indonesia and Sri Lanka, the study develops models to predict the repayment probability of microfinancing loans using logistic regression.

Findings

There are significant differences between the two countries. In Sri Lanka, the time to approve and disburse the loan, loan cycle, gender and age of the borrower, whether a group or individual borrower, the purpose for which the loan is used and visiting frequency by the loan officers were found to be significant when predicting the repayment. Only three factors were significant in Indonesia: time to approve and disburse the loan, interest repayment frequency and gender. Both models have over 70 per cent prediction accuracy.

Originality/value

The models developed can be used in the loan appraisal stage to improve the repayment performance of microfinancing institutions saving hundreds of millions of dollars in bad debt write offs.

Details

International Journal of Social Economics, vol. 42 no. 4
Type: Research Article
ISSN: 0306-8293

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Article
Publication date: 8 August 2022

Ean Zou Teoh, Wei-Chuen Yau, Thian Song Ong and Tee Connie

This study aims to develop a regression-based machine learning model to predict housing price, determine and interpret factors that contribute to housing prices using different…

780

Abstract

Purpose

This study aims to develop a regression-based machine learning model to predict housing price, determine and interpret factors that contribute to housing prices using different data sets available publicly. The significant determinants that affect housing prices will be first identified by using multinomial logistics regression (MLR) based on the level of relative importance. A comprehensive study is then conducted by using SHapley Additive exPlanations (SHAP) analysis to examine the features that cause the major changes in housing prices.

Design/methodology/approach

Predictive analytics is an effective way to deal with uncertainties in process modelling and improve decision-making for housing price prediction. The focus of this paper is two-fold; the authors first apply regression analysis to investigate how well the housing independent variables contribute to the housing price prediction. Two data sets are used for this study, namely, Ames Housing dataset and Melbourne Housing dataset. For both the data sets, random forest regression performs the best by achieving an average R2 of 86% for the Ames dataset and 85% for the Melbourne dataset, respectively. Second, multinomial logistic regression is adopted to investigate and identify the factor determinants of housing sales price. For the Ames dataset, the authors find that the top three most significant factor variables to determine the housing price is the general living area, basement size and age of remodelling. As for the Melbourne dataset, properties having more rooms/bathrooms, larger land size and closer distance to central business district (CBD) are higher priced. This is followed by a comprehensive analysis on how these determinants contribute to the predictability of the selected regression model by using explainable SHAP values. These prominent factors can be used to determine the optimal price range of a property which are useful for decision-making for both buyers and sellers.

Findings

By using the combination of MLR and SHAP analysis, it is noticeable that general living area, basement size and age of remodelling are the top three most important variables in determining the house’s price in the Ames dataset, while properties with more rooms/bathrooms, larger land area and closer proximity to the CBD or to the South of Melbourne are more expensive in the Melbourne dataset. These important factors can be used to estimate the best price range for a housing property for better decision-making.

Research limitations/implications

A limitation of this study is that the distribution of the housing prices is highly skewed. Although it is normal that the properties’ price is normally cluttered at the lower side and only a few houses are highly price. As mentioned before, MLR can effectively help in evaluating the likelihood ratio of each variable towards these categories. However, housing price is originally continuous, and there is a need to convert the price to categorical type. Nonetheless, the most effective method to categorize the data is still questionable.

Originality/value

The key point of this paper is the use of explainable machine learning approach to identify the prominent factors of housing price determination, which could be used to determine the optimal price range of a property which are useful for decision-making for both the buyers and sellers.

Details

International Journal of Housing Markets and Analysis, vol. 16 no. 5
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 11 September 2020

Raphael Mutisya Kieti and Walter Ogolla

This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can…

1135

Abstract

Purpose

This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can accurately estimate the value of apartments.

Design/methodology/approach

The research employed a case study design that was limited to transaction sales and attribute data of apartments in Nyali estate, Mombasa County in Kenya. A sample of 120 sales of apartments obtained from registered real estate firms was analyzed using quantitative methods.

Findings

According to the study results, the hedonic valuation model developed comprises four critical determinants of apartment value, namely, number of parking lots, presence of swimming pool, age of apartment and provision of balcony. The hedonic model was tested and found to be accurate and reliable in estimating apartment value.

Research limitations/implications

The model will improve accuracy, reliability and efficiency in valuation. The application of the model in the valuation of apartments is, however, limited to the case study area where the data are obtained. The scope of application of the model may be improved by increasing the sample size to include apartment sales data from other estates in Mombasa County.

Originality/value

Previous studies that have used the HPM technique in analysis of apartment values have focused on the “explanatory” and “contributory” power of attributes on apartment values, rather than the development and use of the model to measure value. The present study is the first to develop a HPM equation for property value estimation in the apartment real estate sector in Kenya.

Details

Property Management, vol. 39 no. 1
Type: Research Article
ISSN: 0263-7472

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Article
Publication date: 27 August 2019

Rotimi Boluwatife Abidoye, Ma Junge, Terence Y.M. Lam, Tunbosun Biodun Oyedokun and Malvern Leonard Tipping

Improving valuation accuracy, especially for sale and acquisition purposes, remains one of the key targets of the global real estate research agenda. Among other recommendations…

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Abstract

Purpose

Improving valuation accuracy, especially for sale and acquisition purposes, remains one of the key targets of the global real estate research agenda. Among other recommendations, it has been argued that the use of technology-based advanced valuation methods can help to narrow the gap between asset valuations and actual sale prices. The purpose of this paper is to investigate the property valuation methods being adopted by Australian valuers and the factors influencing their level of awareness and adoption of the methods.

Design/methodology/approach

An online questionnaire survey was conducted to elicit information from valuers practising in Australia. They were asked to indicate their level of awareness and adoption of the different property valuation methods. Their response was analysed using frequency distribution, χ2 test and mean score ranking.

Findings

The results show that the traditional methods of valuation, namely, comparative, investment and residual, are the most adopted methods by the Australian valuers, while advanced valuation methods are seldom applied in practice. The results confirm that professional bodies, sector of practice and educational institutions are the three most important drivers of awareness and adoption of the advanced valuation methods.

Practical implications

There is a need for all the property valuation stakeholders to synergise and transform the property valuation practice in a bid to promote the awareness and adoption of advanced valuation methods, (e.g. hedonic pricing model, artificial neural network, expert system, fuzzy logic system, etc.) among valuers. These are all technology-based methods to improve the efficiency in the prediction process, and the valuer still needs to input reliable transaction data into the systems.

Originality/value

This study provides a fresh and most recent insight into the current property valuation methods adopted in practice by valuers practising in Australia. It identifies that the advanced valuation methods could supplement the traditional valuation methods to achieve good practice standard for improving the professional valuation practice in Australia so that the valuation profession can meet the industry’s expectations.

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Article
Publication date: 2 November 2012

William McCluskey, Peadar Davis, Martin Haran, Michael McCord and David McIlhatton

The aim of this paper is to investigate the comparative performance of an artificial neural network (ANN) and several multiple regression techniques in terms of their predictive…

795

Abstract

Purpose

The aim of this paper is to investigate the comparative performance of an artificial neural network (ANN) and several multiple regression techniques in terms of their predictive accuracy and capability of being used within the mass appraisal industry.

Design/methodology/approach

The methodology first tested that the data set had neglected non‐linearity which suggested that a non‐linear modelling technique should be applied. Given the capability of ANNs to model non‐linear data, this technique was used along with an OLS regression model (baseline model) and two non‐linear multiple regression techniques. In addition, the models were evaluated in terms of predictive accuracy and their capability of use within the mass appraisal environment.

Findings

Previous studies which have compared the predictive performance of an ANN model against multiple regression techniques are inconclusive. Having superior predictive capability is important but equally important is whether the technique can be successfully employed for the mass appraisal of residential property. This research found that a non‐linear regression model had higher predictive accuracy than the ANN. Also the output of the ANN was not sufficiently transparent to provide an unambiguous appraisal model upon which predicted values could be defended against objections.

Research limitations/implications

The research provides an informative view as to the efficacy of ANN methodology within the real estate field. A number of issues have been raised on the applicability of ANN models within the mass appraisal environment.

Practical implications

This work demonstrates that ANNs whilst useful as a predictive tool have a limited practical role for the assessment of residential property values for property tax purposes.

Originality/value

The work has taken forward the debate on the usefulness of ANN techniques within the mass appraisal environment.

Details

Journal of Financial Management of Property and Construction, vol. 17 no. 3
Type: Research Article
ISSN: 1366-4387

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Article
Publication date: 8 July 2014

Georgia Giordani, Christos Floros and Guy Judge

The purpose of this paper is to examine if high branch fees, branch dissatisfaction as well as any previous experience of Greek banking customers with other banking technologies…

1836

Abstract

Purpose

The purpose of this paper is to examine if high branch fees, branch dissatisfaction as well as any previous experience of Greek banking customers with other banking technologies (i.e. Automated Teller Machines (ATMs)) have any impact on the probability of internet banking adoption. Further, the authors comment on the socio-economic and demographic characteristics of Greek banking customers, which effect the decision to adopt internet banking services.

Design/methodology/approach

The authors employed the logistic regression model to examine the probability of Greek customers adopting internet banking based on certain demographic characteristics but also due to high branch fees, any dissatisfaction with branch services or due to previous experience of electronic banking technologies (ATMs).

Findings

After estimating a logistic model, the authors report that branch dissatisfaction and high branch fees have no impact to the internet banking adoption in Greece, therefore Greek customers prefer to visit branches and are willing to pay high fees for the transactions. However, the authors find that ATM users are more likely to adopt internet banking services in Greece.

Research limitations/implications

The authors should employ a technology acceptance model, to test the effect of perceived ease-of-use, perceived usefulness and technology self-efficacy of customers on the probability of e-banking adoption. The authors should also examine other hypotheses using recent data from other European countries and compare the results with those from Greece.

Practical implications

The findings are strongly recommended to Greek bank managers.

Originality/value

The research is primarily motivated by the lack of similar studies to explain empirically the characteristics of Greek bank customers which affect the adoption of internet banking.

Details

Journal of Economic Studies, vol. 41 no. 4
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 10 October 2008

Sally Harridge‐March

The purpose of this paper is to show how interactive capability enabled by Web 2.0 has increased the potential for organisations to add value to their offerings by allowing…

728

Abstract

Purpose

The purpose of this paper is to show how interactive capability enabled by Web 2.0 has increased the potential for organisations to add value to their offerings by allowing customers to interact with the organisation and other customers of that organisation.

Design/methodology/approach

The paper briefly outlines the content of four articles contained within this special issue.

Findings

Technology has, and will continue to have, a great impact on the banking sector. However much financial service organisations want their customers to use technology, they must remember that technology should be there to enhance the service offering. It must be attractive to customers and offer them something of value. Once customers adopt internet banking and all it has to offer, organisations should continue to monitor operations to ensure that they are providing the best possible service to customers.

Originality/value

It is not enough for the organisation to benefit from reduced costs and speedier processes, the technology must be useful and helpful for customers. Customers need to feel reassured that the organisation and the technology are trustworthy, so that they will not expose themselves to risk when using it.

Details

International Journal of Bank Marketing, vol. 26 no. 7
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 13 February 2019

Amit Shankar and Charles Jebarajakirthy

Providing high-quality e-banking services is considered a basic strategy for attracting and retaining customers with electronic-banking platforms. The purpose of this paper is to…

8795

Abstract

Purpose

Providing high-quality e-banking services is considered a basic strategy for attracting and retaining customers with electronic-banking platforms. The purpose of this paper is to empirically investigate a comprehensive moderated mediated mechanism for enhancing customer loyalty toward e-banking platforms via e-banking service quality (EBSQ) practices. Reliability, website design, privacy and security and customer service and support are the dimensions of EBSQ.

Design/methodology/approach

Data were collected through structured questionnaires from a sample of 1,028 e-banking users in India. To test the hypotheses, a structural equation modeling approach was used.

Findings

The findings showed that of the EBSQ dimensions, reliability along with privacy and security enhanced customer loyalty to e-banking. The initial trust in e-banking mediates the effects of EBSQ dimensions on customer loyalty except for website design. The mediation effects of initial trust varied between high and low-involved consumers.

Research limitations/implications

This study was conducted with e-banking users in one country using cross-sectional data. Hence, the model should be replicated among e-banking users in other countries and with the longitudinal data.

Practical implications

Establishing a loyal customer base is an important goal for banks. This study demonstrates which specific EBSQ dimensions banks should emphasize to enhance consumers’ initial trust and loyalty toward e-banking services.

Originality/value

This study suggests a moderated mediated mechanism for enhancing customer loyalty to e-banking, which incorporates initial trust as a mediator and consumer involvement as a moderator. It applies cognitive-motivation-relational theory to link EBSQ dimensions with customer loyalty. Thus, this study enables a better understanding of this theory in the e-banking context.

Details

International Journal of Bank Marketing, vol. 37 no. 5
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 10 October 2008

Sonja Grabner‐Kräuter and Rita Faullant

This study seeks to investigate the role of internet trust as a specific form of technology trust in the context of internet banking. Furthermore, the integration of propensity to…

13536

Abstract

Purpose

This study seeks to investigate the role of internet trust as a specific form of technology trust in the context of internet banking. Furthermore, the integration of propensity to trust within the hierarchical structure of personality and its applicability to technological systems are investigated.

Design/methodology/approach

The approach takes the form of an empirical study with 381 bank customers in Austria (adopters and non‐adopters) and the use of a basic model of the adoption of internet banking with structural equation modelling (SEM).

Findings

The results confirm the influence of internet trust on risk perception and consumer attitudes towards internet banking. Propensity to trust is a determinant not only for interpersonal relationships but also for trust in technological systems.

Research limitations/implications

This is not a representative study. Future research is encouraged to systematically investigate further facets of the personality structure in trust and adoption research, as well as to test interaction effects of psychological determinants (from the study) and external stimuli (web site characteristics).

Practical implications

Making the internet banking interface for the customer more attractive and easier to navigate is not enough to increase the adoption rate of internet banking. Trust‐creating activities to increase internet trust and to diminish perceived risk must be continuously pursued. Propensity to trust is an important determinant in the fruitfulness of these actions.

Originality/value

The paper presents the conceptualization of internet trust as a specific form of technology trust, and its pivotal role in the adoption process of internet banking, together with the extension of the propensity to trust concept to technological systems.

Details

International Journal of Bank Marketing, vol. 26 no. 7
Type: Research Article
ISSN: 0265-2323

Keywords

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