Systematic Literature Review on Customer Switching Behaviour from Marketing and Data Science Perspectives

This paper systematically examines the literature review in the field of customer switching behavior. Based on the literature review, it can be concluded that customer switching behavior is a topic that has been widely researched, with a focus on various industries, particularly banking and telecommunications. Research trends in this area have shown a positive direction in recent years, and the amount of research being done in marketing and data science is relatively balanced. In marketing, correlational studies are predominant, with a focus on identifying relationships between customer satisfaction, price-related variables, attractiveness of alternatives, service failure, quality, and switching costs to switching behavior. The PPM model is also gaining popularity as an important development for switching behavior because it considers both push and pull factors. Data science research has shown promising results in predicting customer switching behavior, with each research paper achieving good predictive accuracy. However, research gaps spanning the fields of marketing and data science need to be addressed to provide a comprehensive understanding of the drivers of customer switching behavior. Overall, the literature review shows that customer switching behavior is an important concern for businesses, and further research in this area is essential to gain a better understanding of customer behavior and develop effective strategies to retain customers

Benefits of the application of web-mining methods and techniques for the field of analytical customer relationship management of the marketing function in a knowledge management perspective

Le Web Mining (WM) reste une technologie relativement méconnue. Toutefois, si elle est utilisée adéquatement, elle s'avère être d'une grande utilité pour l'identification des profils et des comportements des clients prospects et existants, dans un contexte internet. Les avancées techniques du WM améliorent grandement le volet analytique de la Gestion de la Relation Client (GRC). Cette étude suit une approche exploratoire afin de déterminer si le WM atteint, à lui seul, tous les objectifs fondamentaux de la GRC, ou le cas échéant, devrait être utilisé de manière conjointe avec la recherche marketing traditionnelle et les méthodes classiques de la GRC analytique (GRCa) pour optimiser la GRC, et de fait le marketing, dans un contexte internet. La connaissance obtenue par le WM peut ensuite être administrée au sein de l'organisation dans un cadre de Gestion de la Connaissance (GC), afin d'optimiser les relations avec les clients nouveaux et/ou existants, améliorer leur expérience client et ultimement, leur fournir de la meilleure valeur. Dans un cadre de recherche exploratoire, des entrevues semi-structurés et en profondeur furent menées afin d'obtenir le point de vue de plusieurs experts en (web) data rnining. L'étude révéla que le WM est bien approprié pour segmenter les clients prospects et existants, pour comprendre les comportements transactionnels en ligne des clients existants et prospects, ainsi que pour déterminer le statut de loyauté (ou de défection) des clients existants. Il constitue, à ce titre, un outil d'une redoutable efficacité prédictive par le biais de la classification et de l'estimation, mais aussi descriptive par le biais de la segmentation et de l'association. En revanche, le WM est moins performant dans la compréhension des dimensions sous-jacentes, moins évidentes du comportement client. L'utilisation du WM est moins appropriée pour remplir des objectifs liés à la description de la manière dont les clients existants ou prospects développent loyauté, satisfaction, défection ou attachement envers une enseigne sur internet. Cet exercice est d'autant plus difficile que la communication multicanale dans laquelle évoluent les consommateurs a une forte influence sur les relations qu'ils développent avec une marque. Ainsi le comportement en ligne ne serait qu'une transposition ou tout du moins une extension du comportement du consommateur lorsqu'il n'est pas en ligne. Le WM est également un outil relativement incomplet pour identifier le développement de la défection vers et depuis les concurrents ainsi que le développement de la loyauté envers ces derniers. Le WM nécessite toujours d'être complété par la recherche marketing traditionnelle afin d'atteindre ces objectives plus difficiles mais essentiels de la GRCa. Finalement, les conclusions de cette recherche sont principalement dirigées à l'encontre des firmes et des gestionnaires plus que du côté des clients-internautes, car ces premiers plus que ces derniers possèdent les ressources et les processus pour mettre en œuvre les projets de recherche en WM décrits.\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Web mining, Gestion de la connaissance, Gestion de la relation client, Données internet, Comportement du consommateur, Forage de données, Connaissance du consommateu

A Multi-Level Theory Approach to Understanding Price Rigidity in Internet Retailing

Price rigidity involves prices that do not change with the regularity predicted by standard economic theory, and is of long-standing interest to firms and industries, and our understanding of the economy as a whole. The previous IS literature has failed to identify the central role of IT and Internet retailing-related technologies to explain the rigidity of prices on the Internet. Instead, it has offered only limited explanations, such as menu costs and tacit collusion. These ideas, and quite a few other key theoretical perspectives were formulated in disciplines other than ours. Thus, the issue of price rigidity and price adjustment in Internet retailing should be given more scrutiny than the literature has provided to date. We review and synthesize what we know about price rigidity in non-electronic retailing contexts using a multi-level theory approach that identifies three unique levels of analysis: the firm-specific level, the firm-to-consumer level, and the firm-to-market level. We evaluate to what extent this knowledge is applicable to explain price-setting and price adjustment on the Internet. We conclude that there should not be less price rigidity in Internet retailing than in traditional retailing – even though the Internet is involved. To this end, we recommend a multi-level variance theory of Internet-based price rigidity. This study provides a foundation for the development of new theoretical perspectives at the crossroads of the academic disciplines of marketing, economics and IS. It encourages research that is able to probe for a deeper understanding of new economic phenomena associated with the digital economy’s growth

Framework of Six Sigma implementation analysis on SMEs in Malaysia for information technology services, products and processes

For the past two decades, the majority of Malaysia’s IT companies have been widely adopting a Quality Assurance (QA) approach as a basis for self-improvement and internal-assessment in IT project management. Quality Control (QC) is a comprehensive top-down observation approach used to fulfill requirements for quality outputs which focuses on the aspect of process outputs evaluation. However in the Malaysian context, QC and combination of QA and QC as a means of quality improvement approaches have not received significant attention. This research study aims to explore the possibility of integrating QC and QA+QC approaches through Six Sigma quality management standard to provide tangible and measureable business results by continuous process improvement to boost customer satisfactions. The research project adopted an exploratory case study approach on three Malaysian IT companies in the business area of IT Process, IT Service and IT Product. Semi-structured interviews, online surveys, self-administered questionnaires, job observations, document analysis and on-the-job-training are amongst the methodologies employed in these case studies. These collected data and viewpoints along with findings from an extensive literature review were used to benchmark quality improvement initiatives, best practices and to develop a Six Sigma framework for the context of the SMEs in the Malaysian IT industry. This research project contributed to both the theory and practice of implementing and integrating Six Sigma in IT products, services and processes. The newly developed framework has been proven capable of providing a general and fundamental start-up decision by demonstrating how a company with and without formal QIM can be integrated and implemented with Six Sigma practices to close the variation gap between QA and QC. This framework also takes into consideration those companies with an existing QIM for a new face-lift migration without having to drop their existing QIM. This can be achieved by integrating a new QIM which addresses most weaknesses of the current QIM while retaining most of the current business routine strengths. This framework explored how Six Sigma can be expanded and extended to include secondary external factors that are critical to successful QIM implementation. A vital segment emphasizes Six Sigma as a QA+QC approach in IT processes; and the ability to properly manage IT processes will result in overall performance improvement to IT Products and IT Services. The developed Six Sigma implementation framework can serve as a baseline for SMEs to better manage, control and track business performance and product quality; and at the same time creates clearer insights and un-biased views of Six Sigma implementation onto the IT industries to drive towards operational excellence

Framework of Six Sigma implementation analysis on SMEs in Malaysia for information technology services, products and processes

For the past two decades, the majority of Malaysia’s IT companies have been widely adopting a Quality Assurance (QA) approach as a basis for self-improvement and internal-assessment in IT project management. Quality Control (QC) is a comprehensive top-down observation approach used to fulfill requirements for quality outputs which focuses on the aspect of process outputs evaluation. However in the Malaysian context, QC and combination of QA and QC as a means of quality improvement approaches have not received significant attention. This research study aims to explore the possibility of integrating QC and QA+QC approaches through Six Sigma quality management standard to provide tangible and measureable business results by continuous process improvement to boost customer satisfactions. The research project adopted an exploratory case study approach on three Malaysian IT companies in the business area of IT Process, IT Service and IT Product. Semi-structured interviews, online surveys, self-administered questionnaires, job observations, document analysis and on-the-job-training are amongst the methodologies employed in these case studies. These collected data and viewpoints along with findings from an extensive literature review were used to benchmark quality improvement initiatives, best practices and to develop a Six Sigma framework for the context of the SMEs in the Malaysian IT industry. This research project contributed to both the theory and practice of implementing and integrating Six Sigma in IT products, services and processes. The newly developed framework has been proven capable of providing a general and fundamental start-up decision by demonstrating how a company with and without formal QIM can be integrated and implemented with Six Sigma practices to close the variation gap between QA and QC. This framework also takes into consideration those companies with an existing QIM for a new face-lift migration without having to drop their existing QIM. This can be achieved by integrating a new QIM which addresses most weaknesses of the current QIM while retaining most of the current business routine strengths. This framework explored how Six Sigma can be expanded and extended to include secondary external factors that are critical to successful QIM implementation. A vital segment emphasizes Six Sigma as a QA+QC approach in IT processes; and the ability to properly manage IT processes will result in overall performance improvement to IT Products and IT Services. The developed Six Sigma implementation framework can serve as a baseline for SMEs to better manage, control and track business performance and product quality; and at the same time creates clearer insights and un-biased views of Six Sigma implementation onto the IT industries to drive towards operational excellence

Empirical Findings On Persuasiveness Of Recommender Systems For Customer Decision Support In Electronic Commerce

More and more companies are making online presence by opening online stores and providing customers with company and products information but the overwhelming amount of information also creates information overload for the customers. Customers feel frustrated when given too many choices while companies face the problem of turning browsers into actual buyers. Online recommender systems have been adopted to facilitate customer product search and provide personalized recommendation in the market place. The study will compare the persuasiveness of different online recommender systems and the factors influencing customer preferences. Review of the literature does show that online recommender systems provide customers with more choices, less effort, and better accuracy. Recommender systems using different technologies have been compared for their accuracy and effectiveness. Studies have also compared online recommender systems with human recommendations 4 and recommendations from expert systems. The focus of the comparison in this study is on the recommender systems using different methods to solicit product preference and develop recommendation message. Different from the technology adoption and acceptance models, the persuasive theory used in the study is a new perspective to look at the end user issues in information systems. This study will also evaluate the impact of product complexity and product involvement on recommendation persuasiveness. The goal of the research is to explore whether there are differences in the persuasiveness of recommendation given by different recommender systems as well as the underlying reasons for the differences. Results of this research may help online store designers and ecommerce participants in selecting online recommender systems so as to improve their products target and advertisement efficiency and effectiveness

Service Quality, Customer Satisfaction and Customer Loyalty in Consumer Electronics E-Tailers: A Structural Equation Modeling Approach

The E-S-QUAL and E-RecS-QUAL scales have been successfully tested in a study by Parasuraman, Zeithaml, and Malhotra (2005). However, E-S-QUAL and E-RecS­ QUAL are newly developed and lack specific application to different types of e-business. This non-experimental, correlational study is the first to examine and explore the relationships among electronic service quality, customer satisfaction, and customer loyalty for consumer electronics e-tailers. Using quota and snowball sampling, participants from the continental United States received e-mail invitations and voluntarily forwarded the e-mail invitations to their friends and family. A total of 276 participants completed the online survey. This study\u27s demographic characteristics included most between the ages of 26 and 35 years (47%), mean age of 35.2, most with graduate degrees (40.6%), and with 40% earning a family income of $75,000 or more. Out of twenty hypotheses (including four sub-hypotheses for H1 and three for H2) in this study, 13 were supported, two were marginally supported, and five were not supported. Findings indicated that electronic service quality was measured by online shoppers\u27 perceptions of service quality of consumer electronic e-tailers through four dimensions of the 17-indicator modified E-S-QUAL (efficiency, system availability, fulfillment, and privacy) . Electronic recovery service quality was measured by online shoppers\u27 perceptions of recovery service quality of consumer electronic e-tailers through two dimensions of modified E-RecS-QUAL (responsiveness and contact, and compensation). Findings also indicated that perceived value and customer satisfaction were two significant variables that mediated the relationships among customer expectations, electronic service quality, customer loyalty, and customer complaints. However, this study also found that electronic service quality and customer expectations had no direct effect on customer satisfaction, but had indirect positive effects on customer satisfaction for consumer electronics e-tailers. Consumer electronics e-tailers\u27 managers could formulate plans to improve service quality and recovery service quality through dimensions of E-S-QUAL and E­ RecS-QUAL. They also could formulate a competitive strategy based on the modified Electronic Customer Satisfaction (e-CS) model to keep current customers and to enhance customer relation management. The limitations and recommendations for future research are also included in this study

Forecasting modeling and analytics of economic processes

The book will be useful for economists, finance and valuation professionals, market researchers, public policy analysts, data analysts, teachers or students in graduate-level classes. The book is aimed at students and beginners who are interested in forecasting modeling and analytics of economic processes and want to get an idea of its implementation

The mediating effect of e-satisfaction and the moderating effect of convenience towards e-loyalty among Internet banking users in northern region of Malaysia

Research on online customer loyalty among internet banking users is important because of the threat posed by phishing and other related issues. The literature has shown that it is a major concern, especially in Malaysia. This study examines the factors influencing eLoyalty such as eSatisfaction, eCommitment, eTrust, privacy, security, website quality and convenience among the internet banking users in Malaysia. The objectives of the study are to analyse the direct effect of eSatisfaction, eCommitment, eTrust towards eLoyalty and the mediating effect of eSatisfaction between privacy, security and website quality on eLoyalty. Another objective is to observe the moderating role of convenience between eSatisfaction and eLoyalty. The underpinning theory used to develop the study’s framework is based on Oliver’s Four-Stage Loyalty Model. An intercept data collection approach was chosen due to the nature of online users as well as the industry. A total of 427 datasets was employed for final analysis, performed using SPSS and SmartPLS-SEM (Partial Least Squares-Structural Equation Modeling). The results of the analysis show that all hypotheses are supported and only one is rejected. The study has established the direct relationship between eSatisfaction, eCommitment and eTrust towards eLoyalty. In addition, the study has confirmed the mediating effect of eSatisfaction between privacy and eLoyalty, security and eLoyalty and website quality on eLoyalty. However, the moderating role of convenience was found to be not significant indicating that there is a constant effect between eSatisfaction and eLoyalty. The study also discusses the theoretical and practical contributions as well as the limitations of the study and recommendations for future research

The Value of IT-Enabled Retailer Learning: Can Personalized Product Recommendations (PPRs) Improve Customer Store Loyalty in Electronic Markets?

Personalization is a strategy that has been widely adopted by online retailers to enhance their customers' shopping experience, with the ultimate goal of building a strong and enduring customer relationship. Personalized product recommendations (PPRs) are product recommendations adapted to individual customers' preferences and taste. So far, very few empirical studies have ever investigated the impact of PPRs from a consumer behavior perspective. Whether PPRs generate any value for consumers and ultimately, retailers, is still an open question. To fill this gap in the literature, in this study, drawing upon the household production function model in the consumer economics literature, I develop a theoretical framework that explains the mechanism through which PPRs influence customer store loyalty in electronic markets. Online shopping can be viewed as a household production process and customer store loyalty is driven by shopping efficiency. Building upon retailer learning, higher quality PPRs can increase consumers' online product brokering efficiency, which in turn increases their repurchase intention. A two-phase lab experiment was conducted among 253 undergraduate students in the business school. The subjects completed a simulated purchase at Amazon.com and the quality of PPRs they received was manipulated. Empirical analyses indicate that higher quality PPRs improve consumers' online product brokering quality, which in turn increases their repurchase intention. Consumers make higher quality purchase decisions and experience more fun during the online product brokering process. A surprising finding is that higher quality PPRs increase consumer online product brokering cost. Consumers spend more time on decision making and have more difficulty reaching a purchase decision. Implications, limitations, and contributions of this study are discussed and areas for future research are suggested