21,617 research outputs found

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

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    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

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

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    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

    Informed Consent to Address Trust, Control, and Privacy Concerns in User Profiling

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    More and more, services and products are being personalised or\ud tailored, based on user-related data stored in so called user profiles or user\ud models. Although user profiling offers great benefits for both organisations and\ud users, there are several psychological factors hindering the potential success of user profiling. The most important factors are trust, control and privacy\ud concerns. This paper presents informed consent as a means to address the\ud hurdles trust, control, and privacy concerns pose to user profiling

    Adapting tam and ECT: continuance intention of e-shopping in Saudi Arabia

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    The objective of this study is to clarify the theoretical problem and identify factors that could explain the level of continuance intention of e-shopping in context of Saudi Arabia. The study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure age differences with regard to continuance online shopping intentions. Structural equation model confirms model fit. The research findings confirm that Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance. The structural weights are mostly equivalent between the young and old groups, but the regression path from subjective norms to perceived usefulness is not invariant, with that relationship being stronger for the younger respondents. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The model explains 65% of the intention to continue shopping online. The research findings suggest that online strategies cannot ignore either the direct and indirect effects on continuance intentions

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

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    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

    Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

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    The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented
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