Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.     

Perceived derived attributes of online customer reviews

The influence of online customer reviews (OCRs) on customers' purchase intention has recently gained considerable attention, in both academic and business communities. Technology allows customers to freely and easily post their comments and opinions online about any product or service; this type of customer review can have a significant effect on customers' purchase decisions. Previous studies, however, have mainly focused on the influence of the virtual attributes of OCRs such as volume and valence on consumers' intentions, while limited attention has been paid to understanding the effects of the derived attributes. This study, thus, aims to understand the impact of the perceived derived attributes of OCRs on customer trust and intention. This study develops a – Perceived Derived Attributes (PDA) - model, based on the inclusion of perceived control from the Theory of Planned Behaviour (TPB) with the Technology Acceptance Model (TAM), in order to investigate the effects of OCRs on customers’ purchasing intention. A total of 489 responses to a survey were collected from users of amazon.com. The findings from this study suggest that customer trust in an e-vendor and their intention to shop online are significantly affected by perceived usefulness, perceived ease of use and perceived enjoyment of OCRs. Furthermore, the sense of control derived from OCRs significantly affects customer intention and significantly affects customer trust in e-vendors, particularly for customers who frequently check OCRs before making a purchase. Clearly, those attributes of OCRs are linked to the development of the shopping environment, which consequently can affect sales.     

Which is more important in Internet shopping,perceived price or trust?

Price and trust are considered to be two important factors that influence customer purchasing decisions in Internet shopping. This paper examines the relative influence they have on online purchasing decisions for both potential and repeat customers. The knowledge of their relative impacts and changes in their relative roles over customer transaction experience is useful in developing customized sales strategies to target different groups of customers. The results of this study revealed that perceived trust exerted a stronger effect than perceived price on purchase intentions for both potential and repeat customers of an online store. The results also revealed that perceived price exerted a stronger influence on purchase decisions of repeat customers as compared to that of potential customers. Perceived trust exerted a stronger influence on purchase decisions of potential customers as compared to that of repeat customers.     

Online shopping viewed from a habit and value perspective

In this article, we study e-commerce customer behaviour towards online shops. The theoretical model is based on Triandis' behavioural framework. Prior value research has mostly focused on users' attitudes towards online shopping. We explore the role of perceived value and habit in e-commerce behaviour. Structure equation results suggest that the utilitarian as well as the hedonic values have a significant impact on affect, and indirectly also on e-commerce behaviour. We also assessed the importance of habit on shoppers' online behaviour. According to our results, online shoppers' habitual behaviour has a significant impact on affect. We also found that normative beliefs (social factors) are the preceding factor of habit in cases in which the shopping experience is not recurrent.     

Applying virtual reality for trust-building e-commerce environments

The application of virtual reality in e-commerce has enormous potential for transforming online shopping into a real-world equivalent. However, the growing research interest focuses on virtual reality technology adoption for the development of e-commerce environments without addressing social and behavioral facets of online shopping such as trust. At the same time, trust is a critical success factor for e-commerce and remains an open issue as to how it can be accomplished within an online store. This paper shows that the use of virtual reality for online shopping environments offers an advanced customer experience compared to conventional web stores and enables the formation of customer trust. The paper presents a prototype virtual shopping mall environment, designed on principles derived by an empirically tested model for building trust in e-commerce. The environment is evaluated with an empirical study providing evidence and explaining that a virtual reality shopping environment would be preferred by customers over a conventional web store and would facilitate the assessment of the e-vendor’s trustworthiness.     

Assessing the determinants of internet banking adoption intentions: A social cognitive theory perspective

Internet banking adoption is one area that has received attention from scholars. The extant studies have mainly used technology acceptance models and behavioural theories which do not account for changes in human behaviour. This study seeks to ascertain the determinants of Internet banking adoption intentions using the social cognitive theory, which accounts for changes in human behaviour. The study selected the sample from bank customers in Ghana through an intercept approach using structured questionnaires. A two stage-approach of confirmatory factor analysis and a structural equation modelling were used in analysing the data. The findings show that websites' social feature, trust, compatibility with lifestyle and online customer services have a significant effect on customers' intentions to adopt Internet banking. However, ease of use did not have a significant relationship with customers' intentions to adopt Internet banking. The significance of the study as well as recommendations for theory, practice and future studies have been discussed.     

Reliability,validity, and sensitivity of a single-item measure of online store usability

In an experimental study, we examined the validity and reliability of a single-item measure for customers' assessment of online store usability. Each of the 378 participants visited two out of 35 online stores and performed three shopping related tasks. Usability was rated using a single-item and an eight-item measure. In addition to trust in the online store and aesthetics, we also measured the participant's intention to buy. Results from factor analysis and the correction for attenuation formula revealed an adequate reliability of the single-item measure. Positive correlations with both trust and aesthetics supported the convergent validity of the single-item measure for usability. The positive correlation between the single-item and the intention to buy demonstrated the high predictive validity of this measure. Finally, results support the sensitivity of the single-item measure to differentiate between the usability for each online store.     

Usability beyond the website: An empirically-grounded e-commerce evaluation instrument for the total customer experience

A customer's experience with an e-commerce environment extends beyond the interaction with the website, including delivery of products, post-sales support, consumption of products and services, and so on. It is the total customer experience that influences the customers' perceptions of value and service quality, and which consequently affects customer loyalty. In our cross-disciplinary research in human-computer interaction (HCI) and relationship marketing, we have been investigating how HCI and customer relationship management (CRM) strategies can be integrated in the design of e-commerce so as to engender customer retention, trust and loyalty. We have performed a series of empirical studies to understand customers' requirements and perceptions about service-quality from e-shopping and e-travel environments. From these studies, we have developed an empirically-grounded evaluation instrument, E-SEQUAL, which we discuss in this paper. The development team can apply it at different phases of an e-commerce development life-cycle to integrate customers' perceived dimensions of service quality into the design and evaluation of e-commerce.     

E-banking in Jordan

The reasons why some customers use e-banking systems whereas others do not is the problem that motivated this study. This study examines the factors underlying customers' technology adoption based on the technology acceptance model (TAM). E-banking adoption is studied from the information systems acceptance point of view; banking customers use the information system to make financial transactions and hence more knowledge of the factors that affect information technology adoption is useful to better understand and facilitate their acceptance. Perceived ease of use, perceived usefulness, subjective norms, security and trust, Internet experience and enjoyment are the important factors that affect customers' adoption of e-banking in Jordan.     

The role of social presence in establishing loyalty in e-Service environments

Compared to offline shopping, the online shopping experience may be viewed as lacking human warmth and sociability as it is more impersonal, anonymous, automated and generally devoid of face-to-face interactions. Thus, understanding how to create customer loyalty in online environments (e-Loyalty) is a complex process. In this paper a model for e-Loyalty is proposed and used to examine how varied conditions of social presence in a B2C e-Services context influence e-Loyalty and its antecedents of perceived usefulness, trust and enjoyment. This model is examined through an empirical study involving 185 subjects using structural equation modeling techniques. Further analysis is conducted to reveal gender differences concerning hedonic elements in the model on e-Loyalty.     

An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM

To understand the first purchase mechanism in online shopping, this study established an integrated model of initial trust and TAM. According to the analysis results, initial trust beliefs were significantly influenced by initial trust bases such as company reputation, structural assurance, and trusting stance, and initial trust beliefs indirectly influenced the first purchase intention through consumer attitude. In TAM constructs, only perceived usefulness directly influenced the usage attitude of online shopping systems, then indirectly influenced the first purchase intention. These results imply that online consumers consider perceived ease of use as a basic requirement for system design. It was also found that there is a time cushion between the time of first purchase and the time of belief formation. On the whole, these results reinforced the theory that a relationship between belief (trust and perceived usefulness) and intention was better explained when it was mediated by attitude.     

基于客户喜好的双向个性化推荐算法

为了解决现有推荐算法仅考虑同类产品间单向推荐所缺乏的灵活性,提升产品的销量及用户的购物体验,提出一种基于客户喜好的双向个性化推荐算法,不仅可以为客户精准推荐产品,还可以为商家推荐潜在客户.首先,基于产品购买网络中客户及其邻居的购买信息,扩展客户购买信息;其次设计客户产品喜好权重计算办法,分析客户的购买喜好,并在客户喜好的指导下为客户提供个性化的产品推荐;最后,基于商家提供的样本客户,挖掘与样本客户相似的客户构成社区,为商家提供潜在客户推荐以及精准客户维护.在真实数据集上的实验验证了算法的有效性.该算法从客户和商家两个维度出发实现了产品与客户的双向推荐,为个性化推荐领域的研究提供有益的帮助.     

The effect of virtual sales agent (VSA) gender – product gender congruence on product advice credibility,trust in VSA and online vendor,and purchase intention

Online vendors are increasingly using virtual sales assistants (VSA), either in the form of an animated picture or a photograph of a real person, to help customers with their product-related information needs. Currently, what is known is that the use of a VSA in an online web shop results in positive outcomes such as trust and purchase intention. What remains unknown, however, is whether or not VSA gender-product gender congruence has a positive effect on customers' attitude towards the product-related advice, the VSA, and the online vendor and on customers' online purchase intention.To determine the hypothesized effect of VSA gender-product gender on variables such as trust and purchase intention, a 2 (VSA gender: male vs female)–×–3 (product gender: male, female, and neutral) experiment with 183 inhabitants (between the age of 18 and 30) of the Netherlands was implemented. Results of the multivariate analysis of variance (MANOVA) reveal that congruence between VSA gender and product gender (e.g. female VSA providing advice about a feminine product) positively influences customers' belief in the credibility of the product-related advice, their trust in the VSA and the online vendor, and their purchase intention. The separate main effects of VSA gender and product gender on the aforementioned dependent variables, however, are not statistically significant. Furthermore, customers' gender did not serve any moderating function in the relationship between VSA gender-product gender congruence and the dependent variables.     

A consumption system model integrating quality,satisfaction and behavioral intentions in online shopping

A consumption system has two constitutive dimensions: the structural elements and the transaction process. Little attention has been paid to the effect of the consumption system on customer satisfaction and behavioral intentions during online shopping. This paper develops and tests a consumption system model for online shopping that incorporates both product and e-service elements, and the online and offline stages of the transaction process. Applying the transaction process of online shopping, this paper dichotomizes perceived product quality into online perceived product quality (OnPPQ) and offline perceived product quality (OffPPQ), and proposes four dimensions of e-service quality integral to the transaction process. An integrative model is proposed to link OnPPQ, OffPPQ, e-service quality, satisfaction and behavioral intentions. The research was based on empirical data from over 260 university students with experience purchasing apparel from online shops. Structural equation modelling was used to test the model and the hypotheses. The results show that perceived e-service quality, OnPPQ and OffPPQ significantly affect customer satisfaction. However, only customer satisfaction and OffPPQ have a direct effect on behavioral intention. A consumption system model successfully theorizes the dimensions of perceived product quality and e-service quality. The model considers the simultaneous effects of the two structural elements, product and e-service, as well as the temporal effect of the online shopping transaction process. Different structural elements in separate transaction processes have distinct effects on satisfaction and behavioral intentions. The research and its results are especially valuable for online shopping for physical goods.     

基于商品引力的购物信息可视化系统

互联网的快速发展带动了人们的购物行为, 越来越多的人群习惯于进行网购, 随之产生的是各种各样的网购交易数据, 这些数据复杂、多维, 并且具有时序性, 消费者的购买行为是众多电商及分析人员的研究热点. 本文提出了一种以个体为中心, 基于商品引力对商品层级结构数据与消费者的购物行为特征的可视分析方法, 使分析者更方便地观察每位消费者的消费行为, 从而得到他们的购物特点. 最后, 给出实验结果, 证明方法的有效性.     

Exploiting long‐term and short‐term preferences and RFID trajectories in shop recommendation

Shop recommendation in large shopping malls is useful in the mobile internet era. With the maturity of indoor positioning technology, customers' indoor trajectories can be captured by radio frequency identification devices readers, which provides a new way to analyze customers' potential preferences. In this paper, we design three methods for the top‐N shop recommendation problem. The first method is an improved matrix factorization method fusing estimated prior customer preference matrix that is constructed by Session‐based Temporal Graph computing. The second method is a Bayesian personalized ranking method based on the first method. The third method is by tensor decomposition combined with Session‐based Temporal Graph. Besides, we exploit customer history radio frequency identification devices trajectory information to find customers' frequent paths and revise predicted rating values to improve recommendation accuracy. Our methods are effective in modeling customers' temporal dynamics. At the same time, our approach considers repeated recommendation of the same shop by designing rating update rules. The test dataset is formed by JoyCity customer behavior records. JoyCity is a large‐scale modern shopping center in downtown Shanghai, China. The results show that our approaches are effective and outperform previous state‐of‐the‐art approaches. Copyright © 2016 John Wiley & Sons, Ltd.     

Advertising value and credibility transfer: attitude towards web advertising and online information acquisition

China is undergoing a transition from offline to online advertising, but little is known about the causal relationship regarding credibility transfer from non-web advertising to web advertising. Meanwhile, web advertising usage behaviour is largely overlooked. The purpose of this study is to explore the formation of customers' attitude towards web advertising (ATT) which further impacts their online information acquisition behaviour, from the perspectives of advertising value and credibility transfer. This paper develops a research model drawing upon advertising value, credibility transfer, ATT and tie. Data collected from Chinese online shopping customers were used to test the model. The results indicate that perceived informativeness, perceived entertainment and credibility contribute to the formation of ATT, which further impacts web advertising usage for getting information. Meanwhile, tie positively moderates the credibility transfer from non-web advertising to web advertising. These findings and their implications for theory and practice are discussed.     

Building online trust through privacy practices

This study applies Mayer et al. [24] trust model to an Internet context. A model is presented linking privacy policy, through trustworthiness, to online trust, and then to customers’ loyalty and their willingness to provide truthful information. The model is tested using a sample of 269 responses. The findings suggest that consumers’ trust in a company is closely linked with the perception of the company’s respect for customer privacy. Trust in turn is linked to increased customer loyalty that can be manifested through increased purchases, openness to trying new products, and willingness to participate in programs that use additional personal information.     

Analysing complaint intentions in online shopping: the antecedents of justice and technology use and the mediator of customer satisfaction

Complaint behaviours are the key to the competition in an online market when service quality is a major concern of consumers. An understanding of complaint intentions can provide insight into a negative service experience and in turn, effectively redress consumer's problems. It is our purpose to examine the determinants of complaint intentions in the online shopping. When online consumers essentially involve the purchase of products/services and the use of web-based technologies, two major issues particularly arise in this context, exchange behaviour and technology use. This study thus integrates justice perception and expectation–confirmation model (ECM) of information system continuance to understand customer satisfaction and in turn, complaint intentions. Data were collected for online consumers with negative service experiences. The results of testing the structural model indicated that distributive and interactional justices significantly contribute to customer satisfaction and complaint intentions, but procedural justice does not. ECM-based features, such as perceived usefulness, are all important in determining customer satisfaction and complaint intentions. The implications for managers and scholars are further discussed.     

Understanding Perceived Trust to Reduce Regret

Trust is fundamental for promoting the use of online services, such as e‐commerce or e‐health. Understanding how users perceive trust online is a precondition to create trustworthy marketplaces. In this article, we present a domain‐independent general trust perception model that helps us to understand how users make online trust decisions and how we can help them in making the right decisions, which minimize future regret. We also present the results of a user study describing the weight that different factors in the model (e.g., security, look&feel, and privacy) have on perceived trust. The study identifies the existence of a positive correlation between the user's knowledge and the importance placed on factors such as security and privacy. This indicates that the impact factors as security and privacy have on perceived trust is higher in users with higher knowledge.