Critical review of the e-loyalty literature: a purchase-centred framework

Over the last few years, the concept of online loyalty has been examined extensively in the literature, and it remains a topic of constant inquiry for both academics and marketing managers. The tremendous development of the Internet for both marketing and e-commerce settings, in conjunction with the growing desire of consumers to purchase online, has promoted two main outcomes: (a) increasing numbers of Business-to-Customer companies running businesses online and (b) the development of a variety of different e-loyalty research models. However, current research lacks a systematic review of the literature that provides a general conceptual framework on e-loyalty, which would help managers to understand their customers better, to take advantage of industry-related factors, and to improve their service quality. The present study is an attempt to critically synthesize results from multiple empirical studies on e-loyalty. Our findings illustrate that 62 instruments for measuring e-loyalty are currently in use, influenced predominantly by Zeithaml et al. (J Marketing. 1996;60(2):31-46) and Oliver (1997; Satisfaction: a behavioral perspective on the consumer. New York: McGraw Hill). Additionally, we propose a new general conceptual framework, which leads to antecedents dividing e-loyalty on the basis of the action of purchase into pre-purchase, during-purchase and after-purchase factors. To conclude, a number of managerial implementations are suggested in order to help marketing managers increase their customers’ e-loyalty by making crucial changes in each purchase stage

Exploring the Success Factors of E-crm Implementation on B2c E-commerce: Satisfaction and Loyalty a Conceptual Framework

E-CRM has an important role in addressing the challenges that exist in the e-commerce industry and certainly affect the success of e-commerce. One measure of the success of e-commerce is the customer satisfaction. The purpose of this study was to determine the factors that influence the achievement of satisfaction of existing customers in the industry e-commerce, Business to Consumer (B2C) in particular, so customer will be loyal. The researchers used meta-analysis to integrate the findings of previous studies. The meta-analysis method used is sourced from 25 journals previous studies from 2006 to 2016. Based on the literature review, authors create a research model on these factors. The factors namely access to information, service, security and trust that significantly affect the achievement of customer satisfaction. The achievement of customer satisfaction will be improved the customer loyalty then will be impact on increased sales and profits of the company. The researches then discuss the findings of the integrated framework leading to theoretical and practical with implications for implementation in Indonesia and reviews directions for future research. In addition, researchers also suggested the e-commerce industry in Indonesia to implement the E-CRM strategy

Information security and privacy concerns in 4IR : the moderating role of trust in B2C e-commerce

Abstract: The development of B2C e-commerce success depends on establishing trust and satisfaction of e-services which contributes to the long-term B2C e-commerce customer loyalty. Prior research has examined the key attributes hampering the e-commerce success and making it difficult to maintain customer loyalty. The new types of technology devices introduced are not only vulnerable to internet risks but also slower the growth of B2C e-commerce. Prior studies have proposed and empirically tested B2C e-commerce frameworks guided by the objectives of establishing trusting, satisfied, and loyal customers in many countries. The empirical data presenting these key success factors of B2C e-commerce in an emerging African countries is mainly limited. The purpose here originates on documenting the effects of information security and privacy concerns on customer trust as a moderator of the effect of satisfaction on B2C e-commerce customer loyalty. The study sinks to the depth of prior studies to construct a conceptual research model which hypothesises the relationships between the B2C e-commerce factors and their antecedents. A survey collected primary data using a self-administered structured questionnaire targeting B2C e-commerce customers in Gauteng province of South Africa. Results show that information security is a strong predictor of customer trust and a weak predictor of their satisfaction. It was found that B2C e-commerce customer loyalty is strongly determined by satisfaction and weakly determined by trust in South Africa. Trust significantly moderates the effect of satisfaction on B2C e-commerce customer loyalty. The limitations of the study, implications, and the proposed future research directions are discussed

Diagnosing and Managing Online Business-to-Consumer (B2C) Relationships: Toward an eCommerce B2C Relationship Stage Theory

The emergence of eCommerce has provided organizations with an unprecedented opportunity to take advantage of business-to-consumer (B2C) interactions. Generally speaking, relationships move through various stages, when a customer chooses to establish a relationship with a person or an organization. Likewise, when a customer forms an ongoing relationship with an online organization, it progresses through similar stages. Yet, the IT-mediated nature of B2C eCommerce interactions causes the manifestation of these stages to be different from offline B2C interactions. As such, this paper proposes a theoretical framework for examining stages of online B2C relationships, based on Stage Theory. The proposed eCommerce B2C Relationship Stage Theory (eB2C-RST) highlights three stages of eCommerce B2C relationships from the customer’s perspective: Attraction, Build-Up, and Continuance. This theoretical framework provides a foundation for both research and practice in the areas of interface design and online B2C customer relationship management

What drives consumers' e-loyalty to airlines web site? Conceptual framework and managerial implications

This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure continuance intentions of online shopping for airlines web sites. The sample respondent 465online users in Saudi Arabia. A structural equation model confirms model fit. Perceived usefulness, enjoyment, social pressure, and loyalty incentives are determinants of online flight booking continuance in Saudi Arabia. This research moves beyond online booking intentions and includes factors affecting online booking continuance. The research model explains 53% of the intention to continue booking using airlines web sites

Evaluating Websites by Features: Do Independent Hotels in Singapore Get it Right?

This study aims to evaluate the websites of independent hotels in Singapore in the business-to-consumer (B2C) framework. The modified balanced scorecard (BSC) approach is incorporated into the evaluation by features method in order to avoid the dominance of the marketing perspective by including technical, customer, and destination information perspectives. A set of website evaluation criteria representing these four perspectives is then used to examine the websites of 37 independent hotels. Almost three of four hotels get it right in developing, utilizing, and maintaining their websites. These websites have the presence of features that are known to be contributing towards website effectiveness. Ten websites were found to function as brochureware with no capability to perform business transactions online. The results of the study propose areas for website improvement that include the destination information perspective in general and contemporary aspects of the marketing perspective

An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

The biological immune system (BIS) is characterized by networks of cells, tissues, and organs communicating and working in synchronization. It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. These randomly generated detectors suffer from not been able to adequately cover the non-self space, which diminishes the detection performance of the V-Detectors algorithm. This research therefore proposed CSDE-V-Detectors which entail the use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in optimizing the random detectors of the V-Detectors. The DE is integrated with CS at the population initialization by distributing the population linearly. This linear distribution gives the population a unique, stable, and progressive distribution process. Thus, each individual detector is characteristically different from the other detectors. CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness of the detector set in the search space. In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨ıve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. This signifies that CSDE-V-Detectors can efficiently attain highest detection rates and lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly detection tasks

Driving online shopping: Spending and behavioral differences among women in Saudi Arabia

This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia. The sample consists of 650 female respondents. A structural equation model confirms model fit. Perceived enjoyment, usefulness, and subjective norms are determinants of online shopping continuance in Saudi Arabia. High and low online spenders among women in Saudi Arabia are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived site quality to perceived usefulness is not invariant between high and low e-shoppers in Saudi Arabia. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the female respondents’ intention to continue shopping online. Online strategies cannot ignore either the direct and indirect spending differences on continuance intentions, and the model can be generalized across Saudi Arabia