Search results

This study employed the commitment–trust theory in social psychology and relationship marketing to explore female customers' perception of channel integration quality in omnichannel retailing and its influence on their relationship commitment to and trust in the relationship with retailers, and thus on their stickiness. Channel integration quality consists of two dimensions: channel service configuration (channel choice breadth and channel service transparency) and integrated interactions (content consistency, process consistency and perceived fluency).

The study was carried out via a questionnaire survey, to which 868 valid responses were collected. The partial least squares technique was used to test the hypotheses.

Channel service transparency and perceived fluency influence relationship commitment; content consistency, process consistency and perceived fluency all have significant effects on trust. Interestingly, although less influential than integrated interactions, channel service configuration is the foundation of channel integration quality, testifying to its significant role.

This study provides strong evidence on how channel integration quality affects customer stickiness. Moreover, this study replicates the finding of significant relationships among relationship commitment, trust and stickiness in omnichannel retailing.

The purpose of this paper is to study the regularity of the e-commerce customer repeat purchase behavior, and provide new ideas and methods for e-commerce vendor’s e-commerce customer management.

Through analysis of the priority in activity mechanism and new customers’ dynamic growth in customer’s purchase behavior, this paper builds a model of the customer’s purchase frequency, which can be verified by the empirical data gathered from www.taobao.com, www.jd.com, www.yhd.com and www.amazon.com.

This paper discovers the regularity that the customer’s purchase frequency obeys power law distribution. Empirical data show that this model can represent the real repeat purchase process well. At the same time, it provides the theoretical basis for the vendor regional management by introducing the concept of stickiness and the corresponding methods of calculation.

This study only focuses on the basic model of e-commerce customer’s repeat purchase and lack of study on influence factors about the characteristics of different vendors and it needs to make extensions considering fluctuation of new customers, or customer aging and loss.

This study provides a theoretical basis for vendor to take different marketing strategies through classifying customers based on the characteristic of purchase stickiness.

The definition and calculation method of purchase stickiness is put forward for the first time, and the value of purchase stickiness changes with the number of purchase. It provides the theoretical basis for the vendor regional management, and will be good for further studying the e-commerce market about customer’s purchase behavior.

The purpose of this paper is to initially use a stochastic model to fit data of customer behavior stickiness and customer value, then estimate the corresponding parameters and use Bayesian rule to calculate its mathematical expectation.

The authors use expectations of customer behavior stickiness as an independent variable, expectations of customer value as a dependent variable, motivations of consumption as moderator and conduct regression analysis to research the relationship among the three. First, we will use the data of behavior for customer network shopping in the questionnaire to establish the random probability model and forecast. Second, we calculate the expected customer behavior stickiness and customer value. Finally, we use resurvey data of 100 subjects after three months (selected randomly from 373 objects) to test the model prediction.

The findings show that customer behavior stickiness has a significant effect on customer value, and the moderating effect of the hedonic motivation of consumption on the relationship above is proved. The value of customers who hold high hedonic motivation of consumption is mainly driven from website’s single visit time, whereas the value of customers who hold low or middle hedonic motivation of consumption is mainly driven from a website’s visit frequency.

The paper proves and quantifies the effects of the customer behavior stickiness for customer value in times of behavior. The results prove the moderation role of consumer motivation of the customer for the path of customer behavior stickiness→customer value, and make clear that the hedonic motivation is a necessary condition of average site visit time that has a significant impact on customer value.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

The purpose of the study is to develop and empirically test a model which examines the relationship between e-servicescape dimensions, website quality dimensions, website stickiness, website loyalty and word-of-mouth (WOM). The role of WOM in influencing consumer behaviour is documented in literature. However, despite its growing importance, research on the antecedents of WOM in the e-retail context is sparse.

Data were collected by circulating the questionnaire using an online survey from the graduate and undergraduate students enrolled in a large university in the northeastern USA. Out of 660 questionnaires distributed, 509 were usable. Data were analysed using confirmatory factor analysis and structural equation modelling.

Results show that website stickiness and website loyalty are two different constructs which form the immediate antecedents of WOM. Results also show the indirect effects of e-servicescape and website quality dimensions on WOM.

The findings of the study provides a better understanding of the factors likely to influence the WOM behaviour of e-retail store customers. Findings also provide valuable insights into the factors which managers need to focus on to make their e-retail website increasingly stickier.

The contribution of the paper lies in eliciting the differences between stickiness to and loyalty to retail websites and extending the research on e-servicescapes.

For entrepreneurs operating in an Internet-of-Things (IoT) environment, it is essential to monitor more systematically, both the interaction with the consumers and the sharing of information among the consumers. The purpose of this paper is to identify the antecedents of word-of-mouth (WOM) in the online SME’s context in terms of consumers “citing the site” to peers in personal communications. A research model integrates the determinants of retail website-specific positive WOM communication, and proposes that WOM about a particular website is influenced by: site-level variables, that is, website quality and interactivity; and consumer-level variables, these being the site user’s satisfaction with and commitment to the website. The research advances the study of IoT entrepreneurship.

Data were collected from graduate and undergraduate students with business and entrepreneurship majors from a reputed school in the Northeast region of the USA, using an online survey. The hypotheses were then tested with SEM using AMOS 18.0.

Findings suggest that in an IoT context, WOM is influenced by a variety of factors of which the e-satisfaction and attitude toward website constructs play important roles. The study highlights the importance of the e-satisfaction construct and its metrics. E-satisfaction is not only a critical outcome metric, but also a primary predictor of customer e-loyalty, measured in terms of the customer’s positive attitude, stickiness and propensity to spread positive WOM.

The paper contributes to the entrepreneurship and IoT literature with a comprehensive framework of information sharing, interactivity and WOM, showing that specific antecedents drive consumers to cite and advocate for a website to fellow customers. The framework helps retail SME entrepreneurs in the IoT context to design appropriate strategies to influence website visitors’ endorsement of the site to fellow customers.

Live streaming commerce enhances shopping experience and reduces uncertainty. However, with increasingly fierce competitions, it has become a challenging task for live streaming commerce platforms to retain existing customers. The purpose of this study to explore factors affecting customers’ stickiness intention toward live streaming commerce platforms.

A research model was developed by modifying e-commerce system success model (ES success model) based on the context of live streaming commerce and meanwhile integrating serendipity and flow into the model. Using the data collected from 380 customers who have live streaming shopping experience, the established model was empirically assessed by partial least squares based structural equation model.

The results show that vividness, real-time interaction and diagnosticity are antecedents of perceived value and customer satisfaction toward a live streaming commerce platform which in turn influence customers’ stickiness intention. Besides, as new factors introducing into the ES success model, serendipity and flow are two important motivators of satisfaction and stickiness.

This study establishes a well-organized framework to understand the mechanism regarding why customers stick with a live streaming commerce platform. It provides a socio-technical approach to analyze how the stickiness intention can be influenced.

Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

This study investigates the influence of artificial intelligence (AI) stimuli on customer stickiness (CS), the mediation effects of social presence (SP) and the moderating impacts of customer traits in this influencing process.

Drawing on the arousal theory and social response theory, a conceptual model was established and tested by a data set of 268 customers in the catering industry.

The results indicate that AI stimuli, such as perceived personalization and perceived interactivity, positively affect CS. SP partially mediates the influence of AI stimuli on CS. Customer traits such as customers' need for interaction (NFI) and novelty seeking (NS) actively moderate the mediating effects of SP.

This study advances the interactive marketing literature from three aspects. Firstly, instead of focusing on the functional aspects of AI stimuli, it extends our understanding of AI-enabled interactive marketing by examining the effects of social and emotional aspects of AI stimuli on customer response. Secondly, it extends our understanding of social response by illuminating the mediating effects of SP between AI stimuli and CS. Finally, it provides new insights and empirical evidence for the research focus on customer traits in AI-enabled interactive marketing.

This paper aims to investigate the temporal dynamics of users browsing activity on a hotel website in order to derive effective marketing strategies and constantly improve website effectiveness. Users' activities on the hotel's website on yearly, monthly, daily and hourly basis are examined and compared, demonstrating the power of informatics and data analytics.

A total of 29,976 hourly Weblog files from 1 August 2014 to 31 December 2017 were collected from a luxury hotel in Hong Kong. ANOVA and post-hoc comparisons were used to analyse the data.

Users' browsing behaviours, particularly stickiness, on the hotel website differ on yearly, monthly, daily and weekly bases. Users' activities increased steadily from 2014 to 2016, but dropped in 2017. Users are most active from July to September, on weekdays, and from noon to evening time. The month-, day-, and hour-based behaviours changed through years. The analysis of big data determines strategic and operational management and marketing decision-making.

Understanding the usage patterns of their websites allow organisations to make a range of strategic, marketing, pricing and distribution decisions to optimise their performance. Fluctuation of website usage and level of customer engagement have implications on customer support and services, as well as strategic partnership decisions.

Leveraging the power of big data analytics, this paper adds to the existing literature by performing a comprehensive analysis on the temporal dynamics of users' online browsing behaviours.