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The primary purpose of this study is to investigate the strategic transition undertaken by e-retailers as they progress from meeting order-qualifier requirements to establishing order-winner elements within their operational frameworks. The overarching objective is to uncover how e-retailers can attain and sustain a competitive advantage in the marketplace.

This study adopted a focus group strategy, which involved collecting qualitative data. Evidence was collected from 41 customers and 16 business managers. The template analysis method was employed to code and organise themes identified during these discussions systematically.

The study identified 34 operational dimensions. 19 dimensions are related to e-retailing platforms and transaction processes, and 15 measurements are related to product or service characteristics. These dimensions were grouped into threshold resources, distinctive resources, threshold competencies and distinctive competencies. Distinctive resources and distinctive competencies are the most critical dimensions of e-retailing. These dimensions are subject to the “more is better” rule. Nevertheless, threshold resources are essential for e-retailing to be considered in the marketplace. It represents the “Must-be quality element.”

This study introduces the concept of a “cumulative model” in e-retailing. It offers strategic guidance for e-retailers seeking to navigate the complex landscape of competitive priorities. Companies can enhance their differentiation edge by identifying and emphasising distinctive resources and competencies. The study offers a nuanced understanding of the interplay between order-qualifier and order-winner elements in the pursuit of sustained competitiveness within the dynamic e-retail industry.

This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

This empirical study aims to examine luxury fashion retailers' localised multiple channel distribution strategies in China.

Through case studies of 15 participating retailers, qualitative data were collected from 33 semi-structured interviews.

Strong impacts of internationalisation strategies, distribution strategies and channel length towards multiple channel retailing are revealed. Multi-channel retailing is widely employed by firms who have entered China and further developed their businesses through local partnerships and adopted a selective distribution strategy via relatively longer channels. Omni-channel retailing is only suitable for the few retailers using an exclusive distribution strategy through direct marketing and wholly owned customer relationship management. As a dynamic transformation from multi- to omni-channel retailing, cross-channel retailing is adopted by those who are withdrawing from local partnerships and shifting to wholly owned expansions and operations in host markets.

The results are potentially challenged by relatively small sample size.

Practitioners are suggested to adapt multiple channel retailing to their international expansion strategies, distribution strategies and channel length in the host markets.

This paper contributes to the literature in both multiple channel retailing and international retailing by offering insights into the motives, development patterns and suitability of multiple channel retailing in the international retail marketing context.

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.

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.

Large digital platforms face intense scrutiny over self-preferencing, which involves a platform provider favoring its own offers over those of competitors. In online marketplaces, also called retail or e-commerce platforms, much of the academic and regulatory debate focuses on determining whether the marketplace provider gives preference to its own private labels, such as “Amazon Basics” or Walmart’s “Great Value” products. However, we outline, both conceptually and empirically, that self-preferencing can also occur through other dimensions of vertical integration – namely, retailing and fulfillment.

This article contributes by conceptualizing three dimensions of vertical integration in online marketplaces – private labels, retailing and fulfillment. Then, two studies empirically assess (1) which of the 20 most-visited global online marketplaces vertically integrates which dimension and (2) which share of 600 m available offers is vertically integrated to which degree in eleven international Amazon marketplaces.

The majority of the leading marketplaces vertically integrate all three dimensions, implying ample opportunities for self-preferencing. Across international Amazon marketplaces, only 0.02% of available offers consist of an Amazon private-label product. However, Amazon is a retailer for around 31% and fulfills around 38% of all available offers in its marketplaces. Hence, self-preferencing on Amazon can occur most frequently through retailing and fulfillment but comparatively infrequently through private-label offers. Still, these shares differ substantially by country – every second offer is vertically integrated in the USA, but only one in ten in India.

Most of the self-preferencing debate often focuses on private-label products. Instead, we present large-scale empirical results showing that self-preferencing on Amazon could occur most often through retailing and fulfillment because these channels affect much larger shares of offers. We also measure the variation of these shares across countries and relate them to regulatory environments.

This paper focuses on the last-mile logistics (LML) operations in fulfilling online grocery orders and the related sustainability considerations in sparsely populated areas like Australia. It aims to examine how online groceries in sparsely populated areas can benefit from online business. Specifically, this study seeks to investigate whether a centralized order fulfillment approach is better than the existing approach which fulfills online orders from local grocery stores.

A multi-method approach is employed to conduct a high level of cost and emission analysis between the existing and the proposed approaches to illustrate the ratios between the two approaches in terms of cost and carbon emissions. Mathematical models are developed with support from the literature. The model is empirically validated with a case study of grocery distribution in the city of Gold Coast, Australia.

It finds that the centralized order fulfillment approach in sparsely populated areas can achieve LML sustainability with low cost, high efficiency and less double handling. Meanwhile, the separation of in-store and online retailing processes improves the in-store shopping experience and online shopping visibility, jointly improves customer satisfaction, and consequently achieves a positive effect on long-term sustainability. Additionally, the possibility of automating order picking and dispatching at a central place can make the processes more efficient and help build more sustainable grocery retailing supply chains by using more environmentally friendly systems.

This paper offers analytical and empirical insights into the sustainability of multi-channel grocery retailing supply chains. The high-level model developed first incorporates the concept of online shopping adoption rates and can serve as a decision-making tool for practitioners to improve supply chain sustainability in LML.

This research aims to examine the integral elements of omnichannel retailing, an evolving approach that blends online and offline shopping experiences. It focuses on how various factors – merchandise variety, monetary saving, personal interaction, complaint handling, social influence, perceived crowd and skepticism – affect relative advantage, consumer satisfaction and word-of-mouth (WOM) advocacy in an omnichannel context.

A comprehensive survey was conducted with 258 participants, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). This methodology provided insights into the complex relationships between different omnichannel retailing factors and their impact on customer satisfaction and WOM.

The study found that monetary saving influences both relative advantage and satisfaction. Personal interaction was observed to affect complaint handling and relative advantage. Importantly, relative advantage was found to impact both satisfaction and WOM. Additionally, the study highlighted the roles of social influence and satisfaction in enhancing WOM.

This research adds to the existing literature by providing a nuanced understanding of the dynamics of consumer engagement in omnichannel retailing. It bridges a gap in existing research by concurrently examining the impact of online and offline retail factors on consumer satisfaction and WOM in an omnichannel setting.

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.

This paper aims to explore the factors influencing the behavioural intention of Gen Y consumers to avail omnichannel service and to identify the relative influence of predictors in explaining the behavioural intention of Gen Y consumers to use omnichannel service.

Data collected through surveys from 287 Gen Y consumers has been analysed through structural equation modelling to examine direct and mediated relationships between the constructs influencing behavioural intention to use omnichannel service.

Findings indicate that perceived ease of use, social influence, perceived trust, and personal innovativeness positively affect behavioural intention to use omnichannel service, with the result accounting for 48% of the variance. We also demonstrate that perceived value and perceived ease of use mediate the association between personal innovativeness and behavioural intention to use omnichannel service.

The study provides valuable insights into adopting technology-based offerings for Gen Y customers. The presented model can be extended for analysing consumers' behavioural intentions by considering additional variables, such as consumer personality traits and diverse cultural settings. The study may help managers and policymakers formulate a consumer-focussed strategy to win over modern retail consumers.

This study explores the behavioural intention of Gen Y consumers in availing omnichannel services. Further, the study contributes to the technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT) or UTAUT2 theories that may need to be extended in the omnichannel shopping context.