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Product returns are a major challenge for e-businesses as they involve huge logistical and operational costs. Therefore, it becomes crucial to predict returns in advance. This study aims to evaluate different genres of classifiers for product return chance prediction, and further optimizes the best performing model.

An e-commerce data set having categorical type attributes has been used for this study. Feature selection based on chi-square provides a selective features-set which is used as inputs for model building. Predictive models are attempted using individual classifiers, ensemble models and deep neural networks. For performance evaluation, 75:25 train/test split and 10-fold cross-validation strategies are used. To improve the predictability of the best performing classifier, hyperparameter tuning is performed using different optimization methods such as, random search, grid search, Bayesian approach and evolutionary models (genetic algorithm, differential evolution and particle swarm optimization).

A comparison of F1-scores revealed that the Bayesian approach outperformed all other optimization approaches in terms of accuracy. The predictability of the Bayesian-optimized model is further compared with that of other classifiers using experimental analysis. The Bayesian-optimized XGBoost model possessed superior performance, with accuracies of 77.80% and 70.35% for holdout and 10-fold cross-validation methods, respectively.

Given the anonymized data, the effects of individual attributes on outcomes could not be investigated in detail. The Bayesian-optimized predictive model may be used in decision support systems, enabling real-time prediction of returns and the implementation of preventive measures.

There are very few reported studies on predicting the chance of order return in e-businesses. To the best of the authors’ knowledge, this study is the first to compare different optimization methods and classifiers, demonstrating the superiority of the Bayesian-optimized XGBoost classification model for returns prediction.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.

Discount grocery stores (DGSs) are attractive food supply chain (FSC) channels because many cost-conscious Indians use them for monthly needs. Despite capacity, DGSs must address customer concerns about store crowd densities and improve their COVID-19 preparedness. The purpose of this study is to learn how retail operations strategies can improve customer experience and how stores can benefit.

The study looked at a case study where retail operations are run more efficiently, and the customer experience is enhanced by standardizing and customizing customer transactions. The potential benefits that customers and retailers might anticipate are then statistically verified. Next, the potential benefits were examined to determine which ones from customers’ and retailers’ views should be prioritized to increase satisfaction.

The case situation analysis in the study demonstrates how DGSs can improve their retail operations to reduce customer wait times and provide greater convenience. The study also provides practitioners with potential benefits to pursue from the perspectives of retailers, customers and both retailers and customers.

This study requires many past transactions and can be considered an extension of the current study, so it does not capture floor space and capacity improvements.

This research can help FSC retailers compete with upstream supply chain partners and customers in omnichannel retailing. By improving DGS retailer capacity and customer experience, this study can benefit all FSC stakeholders.

Although there are numerous potential benefits that practitioners can pursue, the current study suggests that practitioners focus on those that can improve retailer and customer satisfaction.

The objective of this exploratory study was to investigate the communication themes that retailers should prioritise to convey terroir store brands’ (TSBs) authenticity and the impact of their authenticity on several variables (i.e. value, attitude, trust, intentions and effective purchases). TSBs combine a variety of products that adhere to stringent standards associated with a terroir. Charters et al. (2017) referred to a terroir as “a resource based on unique physical origins and shared cultural personification that shape a product’s benefits into a meaningful value proposition” (p. 755). Three communication themes were studied: the ingredients’ origin, traditional local recipes and the producer’s history in a region (terroir).

An experiment was conducted in a store laboratory. A total of 420 consumers representative of the French population were randomly assigned to four independent groups in a between-subjects study design. They shopped in the store laboratory with a section dedicated to a TSB. Each of the independent samples in this experiment was exposed to posters in the store laboratory related to the three communication themes studied. The control group did not see any posters.

The study showed that the level of TSB authenticity was highest for the communication theme related to the traditional local recipes of the culinary dishes offered by the TSB. Next came the theme related to the ingredients’ origin, followed by the producer’s history in the terroir. Moreover, for the communication theme related to the traditional local recipes, TSB authenticity had a direct impact on value, trust and intentions. Moreover, the link between intentions and effective purchases of TSB products has only been established for this specific communication theme.

First, this study adds to the limited research on TSBs’ authenticity and identifies the communication themes retailers should use to promote such brands. It also proposes an integrative model of the consequences of TSBs’ authenticity in the retailing field that highlights the direct and indirect links (through value, attitude, trust and intentions) between authenticity and consumers’ effective purchases. Finally, it indicates the kind of discourse on TSBs that conveys their authenticity.

Advances in digital technologies and the growing number of touch points have had a significant impact on the shopping behaviour of omnichannel customers. Several research papers have explored different facets of omnichannel, but only a few have thoroughly explored the literature on showrooming and webrooming simultaneously. This paper aims to identify the key groups of antecedents influencing customer buying behaviour in omnichannel, under the influence of digital technologies, with a particular focus on showrooming and webrooming.

Our study conducted a systematic literature review to identify the factors influencing customers’ buying behaviour in omnichannel, which have been the subject of academic discussion over the last decade. We finalized 149 articles for the thematic analysis and identified three groups of antecedents: channel-related, product-related and consumer-related with their subgroups.

Under channel-related antecedents, cost and perceived benefits, search convenience, need for interaction and situational circumstances have been identified as major attributes. The expressiveness of the product, product demonstration and search and experienced products have been identified under product-related antecedents, followed by price consciousness, past experiences, perceived risks and shopping motivations as leading attributes under consumer-related antecedents. The study revealed the multifaceted influence of digital technologies on omnichannel buying behaviour. Digital technologies are shaping the antecedents related to channels, products and consumers. Digital technologies simultaneously mediate between antecedents and the selection of a specific path within an omnichannel environment. Showrooming and webrooming should no longer be seen as general concepts. The rise of digital technologies has led to the development of new consumer journey patterns and the blurring of distinctions between showrooming and webrooming. A conceptual framework has been proposed to understand consumers' omnichannel behaviour, having considered the identified antecedents and the role of digital technologies.

This study advances the academic understanding of consumer behaviour in omnichannel under the influence of digital technologies and provides important implications for omnichannel management. With the advancement of digital technologies such as augmented reality and virtual reality, retailers should implement channel integration strategies to bridge the gap between online and offline channels, providing a memorable shopping experience for omnichannel customers.

This study is unique because it identifies and analyses the antecedents of consumer behaviour in omnichannel settings under the influence of digital technologies. It also uncovers new potential combinations of showrooming and webrooming patterns. The proposed framework can help retailers in their future planning of omnichannel strategies.

This study aims to examine marketing trends spanning a period of 26 years to scrutinize North American influence in marketing research, as well as enhance comprehension of interdisciplinary marketing knowledge and identify prominent scholars, universities, countries, and articles that warrant further scholarly exploration.

This paper uses bibliometric methods to analyze the publications of eight top-tier journals (Journal of Marketing, Journal of Consumer Research, Journal of Marketing Research, Journal of the Academy of Marketing Science, Marketing Science, Journal of Retailing, Journal of Consumer Psychology and International Journal of Research in Marketing) between 1996 and 2021, as found in the Scopus database.

The findings indicate that North American hegemony in the marketing discipline continues and that the impact of marketing on other disciplines remains controversial. Some universities have a deeply rooted tradition of marketing departments. Some articles from 26 years ago are still frequently cited.

The study covers the period from 1996 to 2021. It includes only articles, uses a single database and is cross-sectional. Future research should explore longer time periods by using various databases for comprehensive analysis.

To the best of the authors’ knowledge, this study constitutes one of the first attempts to understand the scholarly contributions of the marketing discipline by considering eight top-tier journals.

Esta investigación examina las tendencias de marketing durante un período de 26 años para analizar la influencia norteamericana en la investigación de marketing, así como para mejorar la comprensión del conocimiento interdisciplinario en marketing e identificar destacados académicos, universidades, países y artículos que merecen una mayor exploración académica.

Este documento emplea métodos bibliométricos para analizar las publicaciones de ocho revistas de primer nivel (Journal of Marketing, Journal of Consumer Research, Journal of Marketing Research, Journal of the Academy of Marketing Science, Marketing Science, Journal of Retailing, Journal of Consumer Psychology e International Journal of Research in Marketing) entre 1996 y 2021, según se encuentran en la base de datos de Scopus.

Los resultados indican que la hegemonía norteamericana en la disciplina del marketing continúa y que el impacto del marketing en otras disciplinas sigue siendo controvertido. Algunas universidades tienen una tradición arraigada en los departamentos de marketing. Algunos artículos de hace 26 años todavía son citados con frecuencia.

Este estudio constituye uno de los primeros intentos de comprender las contribuciones académicas de la disciplina del marketing considerando ocho revistas de primer nivel.

El estudio cubre el período de 1996 a 2021. Incluye solo artículos, utiliza una sola base de datos y es transversal. Futuras investigaciones deberían explorar períodos más largos de tiempo empleando diversas bases de datos para un análisis completo.

本研究调查了跨越26年的市场营销趋势, 以探讨北美在市场营销研究中的影响, 并增进对跨学科市场营销知识的理解, 识别值得进一步探索的杰出学者、大学、国家和文章。

本文采用文献计量学方法分析了1996年至2021年间八种顶级期刊 (Journal of Marketing、Journal of Consumer Research、Journal of Marketing Research、Journal of the Academy of Marketing Science、Marketing Science、Journal of Retailing、Journal of Consumer Psychology 和 International Journal of Research in Marketing）的出版物, 这些文章可在Scopus数据库中找到。

研究结果表明, 北美在市场营销学科中的霸权地位仍然存在, 并且市场营销对其他学科的影响仍然存在争议。同时, 研究发现一些大学具有根深蒂固的市场营销系传统, 且一些26年前的文章仍然经常被引用。

本研究首次尝试通过考虑八种顶级期刊来理解营销学科的学术贡献。

本研究涵盖了1996年至2021年的时间段。它仅包括文章, 使用了单一数据库, 并且是横断面研究。未来的研究应该通过使用各种数据库进行全面分析, 探索更长时间段。

This study aims to examine the research trends in fashion industry during the coronavirus disease 2019 (COVID-19) pandemic. Besides, it also provides an overview on the new marketing and operational strategies, and reveals the corresponding business challenges of a footwear enterprise in Hong Kong during the COVID-19 pandemic.

A comprehensive literature review is first conducted to identify the research trends in fashion industry during the COVID-19 pandemic. A qualitative exploratory case study is then used to illustrate how a footwear enterprise has coped with the COVID-19 pandemic.

The case study has showed that omni-channel retailing, collaboration with e-tailers, quick response system and mixed production strategy are adopted in the targeted case during the COVID-19 pandemic. Besides, the targeted case has also faced the challenges in the areas of sales, customer relationship management, and demand forecasting and inventory planning during the COVID-19 pandemic.

This study provides managerial insights on the real practices used to deal with the COVID-19 pandemic and proposes various academic future research directions in fashion industry based on the real-world observations.

The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

The purpose of this study is to draw from sustainable social innovation theory and the Consumer styles inventory (CSI) instrument to examine secondhand clothing consumption habits for Russia. The secondhand market is the logical outcome of efforts to adopt resale as a facet of sustainable social innovation, with which to drive sustainable decision-making and socially responsible marketing in the secondhand high-end clothing market. Resale represents the cornerstone of business model innovation (BMi) for the retail sector, offering substantial opportunities for retailers who understand changes in consumption behaviour. More cost-effective and arguably greener, the sale of secondhand clothing is expected to be double the volume of fast fashion by 2030 but it remains an understudied field of research in the literature relating to the fashion industry.

Hypotheses are developed from the existing literature. Survey methodology is used to collect data from 250 Russian consumers in the city of Petersburg. The objective is to test the veracity of CSI shopper orientations, focusing on nascent motivations for high-end branded secondhand clothing, to examine sustainable social innovation and resale in an emerging market.

Four new shopping orientations are identified. Based on the empirical data, the authors suggest that five (out of the original eight CSI shopping orientations) are of internal statistical relevance, and that our new orientations are relevant for not only this market, but for neighbouring Eastern European countries too. The findings reflect postmodern evolution in behavioural motivations for Russian consumers, that can inform retail strategy in terms of BMi consumer for harnessing opportunities offered by sustainable social innovation and resale.

Whilst the CSI has been widely used, research for Eastern Europe is limited. Understanding the shopping orientations for sustainable alternatives to newly produced clothing has theoretical and practical implications for improving circularity, post-war entry strategies and countries facing economic downturn. This study contributes novel insights by examining consumer decision-making and shopping orientations in an emerging market.

Online shoppers feel insecure due to the various unethical practices of e-tailers. It is, therefore, crucial for online retailers to alleviate customer concerns. Extant literature indicates that country-of-origin (COO) cues influence consumer perception. A relatively underexplored phenomenon in an emerging market context, the COO image of the online retailer, i.e. a foreign-origin online retailer (FOOR) or an Indian-origin online retailer (IOOR), needs validation. The current study investigates customer expectations of online retailers' ethical behaviour against the backdrop of online retailer-based signals in emerging markets.

The researchers floated an online questionnaire using a seven-point Likert scale. The authors sought recipient responses in Google Forms shared via e-mails and social media connections. The authors analysed 1,018 useable responses using partial least square structural equation modelling (PLS-SEM) in Smart PLS 3.

The empirical study examined the influence of the consumer perception of ethics of online retailers (CPEOR) and COO on consumer purchase intention. It validated the proposed research model. The research findings inform that the CPEOR and the COO influence purchase intention through the mediation effects of trust and satisfaction. Results indicate that privacy, security, non-deception, fulfilment, customer service, FOOR and IOOR strongly predict consumer trust. In contrast, privacy, non-deception, fulfilment, customer service and FOOR strongly predict consumer satisfaction. However, security and IOOR did not influence consumer satisfaction.

The study results have theoretical and practical implications for academic researchers and online retailing managers. Future studies can validate the model in different geo-demographic scenarios and e-commerce settings.

The study enriches the extant literature on CPEOR in the Indian context. This study is pioneering work examining consumer purchase intention by adding the COO construct to the CPEOR model.