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The purpose of this paper is to examine the antecedents and consequences of trust in online shopping from an e-tail branding perspective.

A structured questionnaire was used to collect data online from Indian e-tail shoppers (n=309). A structural equation modelling (CB-SEM approach) was used to analyse the data.

The results found e-tailer awareness, e-tailer associations, and e-tailer perceived quality as antecedents of trust in online shopping. The results also showed online trust positively influences the behavioural intentions, namely, purchase intention, repurchase, and recommendation.

This study examines the applicability and branding and brand management principles in an e-tail branding context. Theoretical and managerial implications of these results are further discussed.

In this paper, the relation between the constructs operational complexity, Web‐based orientation of the company and the company’s distribution structure used for the fulfilment of Internet customer orders is investigated in the food home shopping branch. A model is proposed with relations between these constructs, which is researched through a survey among food e‐tailers. A positive association between operational complexity and the distribution structure used could be established, meaning that more complex operations (with a full‐line assortment and a large number of orders) tend to have special (Internet orders only) distribution centres for the fulfilment of Internet customer orders. Companies with a store infrastructure tend to keep using this existing infrastructure (unless the number of orders becomes large) and new Internet‐only companies tend to use special Internet‐orders only warehouses, unless the number of orders is small, in which case co‐operation with existing stores is preferred.

A total of 117 student consumers participated in a longitudinal survey of their purchasing behavior for three product categories: snack foods, CDs, and skin care. The Domain Specific Innovativeness Scale was included in the survey to measure how innovative participants were with regard to buying online. It was hypothesized that an innovative predisposition toward online buying would be associated positively with more hours of Internet use, greater Internet purchasing, higher likelihood of future Internet purchase, and use of the Internet to download music. The data analyses confirmed all these hypotheses. Few respondent demographics, however, were related to any of these variables. These results demonstrate that the Domain Specific Innovativeness Scale is a reliable and valid measure of this potentially important construct; and that Internet innovativeness functions as predicted by theories of consumer innovative behavior, thereby increasing the generalizability of these theories and yielding potentially important information for e‐commerce managers.

This study aims to explore the use of gamification elements by micro and small e-tailers to enhance customer loyalty. Additionally, this research seeks to identify the most promising gamification elements that can be utilised for this purpose.

The authors adopt a qualitative approach to examine the impact of gamification on online customer loyalty to micro and small e-tailers. Data were gathered using a combination of two types of expert interviews. Semi-structured interviews were held with micro and small e-tailers while large e-tailers served as the control group. Structured interviews based on multi-criteria decision analysis (MCDA) models were conducted to determine the most promising gamification elements.

The content analysis reveals that gamification has significant potential for fostering customer loyalty and offering various other benefits. However, small e-tailers often refrain from implementing gamification solutions due to the resource requirements in terms of finances, time, information technology and human capital. By assigning weights as an essential step in MCDA models, the authors determined that badges, medals, quests, avatars and competitions are the most promising gamification options for small e-tailers’ efforts to enhance customer loyalty.

The study makes a unique contribution to the understanding of the usefulness of gamification in augmenting customer loyalty and identifying essential gamification elements for micro and small e-tailers.

Research regarding the quality of e-tailers’ service during product returns is sparse and the little that has been performed treats returns as recovery from failure. However, that view is outdated. E-tailers' product return practices have substantially evolved and customers' return behavior has considerably increased, in turn, influencing expectations of customers. Thus, a need arises to revise the understanding of how customers evaluate the quality of e-tailers' service during product returns. This study conceptualizes customer-perceived e-return service quality, identifies e-return's current dimensions, and offers directions for measurement.

This study is conducted in two stages. The first stage follows an abductive approach, with a continuous back-and-forth movement between existing theory and two qualitative data sets to identify the dimensions of e-return service quality. Scale development process is started in the second stage to offer directions for measurement based on the empirically grounded dimensions.

The conceptualization of e-return service quality identifies six dimensions: (1) owning of responsibility, (2) return convenience, (3) return remedies, (4) service team support, (5) site's return friendliness, and (6) returns diligence. The factor analysis supports the six-factor solution that can be employed for developing a valid scale in future.

The study suggests that e-tailers who are looking to differentiate themselves through superior e-return service quality should focus on customizing their service through excellent performance on these dimensions.

The paper updates and refines the understanding of service quality in the context of product returns service provided by e-tailers and thus offers a novel contribution.

Building a customer base as an outcome of customer satisfaction has not been investigated empirically in e‐tailing industry. This paper seeks to fill this gap in the literature.

Explores the relationship between satisfying customers and building a customer base using data envelopment analysis (DEA). Data from the e‐retailing industry related to the input variables (e.g. customers' ratings on a set of e‐store attributes) and output variables (e.g. a proxy measure of “customer base”) are analyzed.

Performance scores for developing a customer base vary across product categories. Performance score is a good parameter for predicting future change on a unique number of visitors and on the competition pattern for a particular e‐tailer.

Further study can examine other drivers of a developing customer base (e.g. advertising, trust building, and strategic alliance) – thereby producing more robust evidence for customer base development in e‐tailing industry.

Good practices in the generation of customers and page view have been identified. Knowing the efficiency patterns of an e‐tailer makes it possible to guide managerial action by providing a measure of the extent to which different management actions at the e‐tailer can lead to higher future customer growth. Managers should realize that customers match realizations and expectations of product/service performance.

This study has identified satisfaction as the important driver of developing a customer base. It focuses on improving diagnosis of the performance of e‐tailers by assessing reach efficiency and page view efficiency separately.

The purpose of this paper is to qualitatively investigate various factors associated with e-tail store brand affect.

Data were collected by conducting semi-structured depth interviews following a storytelling approach. The data were coded using the grounded theory method.

Data analysis shows that anticipated service recovery, deal attractiveness and luxury e-tail brand image predict e-tail store brand affect. These predictors play their roles under the moderating influences of specific moderators. The desirable marketing outcomes of e-tail store brand affect are e-tail branded app usage, spreading positive word of mouth and secure attachment style toward e-tailer.

The value of this study lies in developing a grounded theory based causal process model that can provide managerial insights on how to enhance e-tail brand affect.

The purpose of this paper is to report results from an experimental study in which participants rank e-tailer quality on the basis of descriptions involving five attributes (reputation of retailer, site usability, security, delivery and customer support). The paper further explores how the relative importance of these attributes to perceived e-tailer quality is impacted by customer demographic and behavioral characteristics (such as gender, age, frequency of online purchasing and use of online reviews).

Individual-level conjoint models are estimated to determine the relative importance of these five attributes to perceptions of e-tailer quality.

The relative importance of these five attributes to perceived e-tailer quality are impacted by customer specific characteristics and online behaviors, namely, age, the frequency of prior online purchasing, the frequency of use of online reviews and the importance attached to the availability of a large number of online product reviews.

Managerial implications that help e-tailers develop more effective, targeted strategies for enhancing the quality of their websites and increasing customer loyalty are presented.

The use of conjoint analysis for decomposing overall judgments of e-tailer quality to derive the relative importance of specific e-tailing attributes offers a realistic way to understand how online customers perceive and evaluate e-tailer quality.

This paper studies the impact of social distancing causing crises (SDCC) such as pandemics in its early stages on e-tailers demand and supply side operations and provides a conceptual framework for adaptation.

A grounded theory-based approach has been used, wherein journal papers and news articles are the key data sources. Standard qualitative methodology, including open, axial and selective coding has been followed.

The study provides second order themes derived from first-order categories, the theoretical dimensions and their interrelationships on how e-tailers need to adapt to variations in online buying behaviour, manage manpower shortage and daily necessities inventory shortage, during SDCC. Panic buying emerges as a key disrupting factor as it has multiple repercussions on demand and supply side operations of e-tailers.

Exploratory qualitative research such as this is helpful in early development of a research stream and paves the way for future quantitative studies.

This study makes a valuable contribution on e-tailers adaptation to SDCC with significant managerial implications. There are social, economic and policy implications too. For academicians, this study provides a conceptual framework and serves as a springboard for future research.

The study is unique as perhaps it is one of the first to study e-tailers adaptation to SDCC. It contributes to a body of the literature which is currently scarce but expected to grow exponentially in the coming years.