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The study aims to determine the role of online retail website experience on brand happiness and willingness to share personal information using the theoretical lens of the Stimulus-Organism-Response (SOR) framework. Further, it explores the role of brand intimacy and brand partner quality in mediating the path between brand happiness and willingness to share personal information.

This study used a cross-sectional survey design to collect data from 439 online retail consumers in India, using an online questionnaire. The data were analysed using Structural Equation Modelling in IBM Amos.

The present study found that online retail website experience is significantly related to brand happiness. The finding also supports that brand happiness was positively and significantly related to ‘consumers' willingness to share personal information. This relationship was fully mediated by brand intimacy. Brand happiness also mediated the relationship between website experience and the willingness to share personal information.

This study contributes to the emerging literature on brand happiness and willingness to share personal information. It establishes a central role of brand happiness as a driver and a mediator of consumers' willingness to share personal information with e-commerce retailers, extending the stimulus-organism-response framework in the context of brand happiness and willingness to share personal information. Further, the study establishes the role of website experience as a marketer (and brand) led driver of brand happiness.

The results have implications for the role of the website in enhancing the consumer experience, which in turn is a driver of brand happiness. Further, managers need to promote brand happiness with the help of website experience to enable consumers’ willingness to share personal information and help organizations customize their marketing campaigns.

This is among the first studies to evaluate brand happiness from the perspective of an online retail website experience and consider consumers’ willingness to share personal information from a branding rather than a technological perspective. Additionally, the study introduces the SOR framework in the context of brand happiness, with website experience acting as a stimulus for consumers, resulting in brand happiness, which is mediated by brand partner quality and brand intimacy (organism), leads to consumers' willingness to share personal information with online retail brands (response).

The primary aim of this study is to gain insight into the entrepreneurial marketing strategy (EMS) decisions made by microenterprises in the craft sector and draw comparisons between the marketing strategy formulation and implementation of conventional businesses and those of craft-based microenterprises with a specific focus on the context of emerging markets, particularly India.

This paper follows a qualitative interpretivist paradigm using a multiple-case methodology approach. It tracks craft-based microenterprises that make furniture or home décor products in India. The study participants were the founders, principal designers, studio managers or craftspersons.

This study’s findings reveal that craft-based microenterprises implement an EMS that adopts a hybrid form of market orientation strategy. In this approach, the product or creative concept is at the centre of the decision-making, and the customer needs are factored in at a later stage for customisation. These microenterprises prioritise product positioning over segmentation and targeting strategies.

This study tries to understand marketing strategy decision-making processes among craft-based microenterprises in India. Given that study participants came from only two-product-based craft businesses, this limits the generalisability of the findings to similar or related contexts. This study provides a framework and methodology for replication in other contexts and industries to formulate a nuanced understanding of micro, context-specific, craft-based businesses.

This study uses qualitative analysis to understand EMS in craft-based businesses in India. This study contributes to this fledgling stream of literature at the interface of marketing and entrepreneurship to understand entrepreneurial marketing. This study analyses the marketing strategy of craft-based businesses using the framework of Morgan et al. (2019).

The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.

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.

Consumer behavior has evolved because of technological development. Nowadays, consumers carry out the different stages of the decision-making process by combining multiple devices which has been defined as multi, cross and omnichannel behavior. These behaviors have attracted the attention of academics and become a hot topic in literature. As a result, vast amounts of studies on the subject need to be revised and clarified. Thus, the aim of this chapter is to synthetize the primary academic literature that analyzes multi, cross and omnichannel behavior from the consumer point of view. To do that, first, the main concepts (multi, cross and omnichannel) and their differences are clarified. Second, the major findings of channel mix literature regarding the topics, channel scope and theories are exposed and described. Third, the opportunities and future lines of research are presented. This chapter contributes to the literature by clarifying the conceptualization of multi, cross and omnichannel behaviors; offering a complete picture of the main topics, channel approaches and theories addressed in channel mix literature; and presenting future research opportunities and open research questions in a channel mix context that could serve as a starting point to build further research.

The current research has developed a novel method to update the decisions regarding real-time data, named the dynamic adjusted real-time decision-making (DARDEM), for updating the decisions of a grocery supply chain that avoids both frequent modifications of decisions and apathy. The DARDEM method is an integration of unsupervised machine learning and mathematical modeling. This study aims to propose a dynamic proposed a dynamic distribution structure and developed a bi-objective mixed-integer linear program to make distribution decisions along with supplier selection in the supply chain.

The constantly changing environment of the grocery supply chains shows the necessity for dynamic distribution systems. In addition, new disruptive technologies of Industry 4.0, such as the Internet of Things, provide real-time data availability. Under such conditions, updating decisions has a crucial impact on the continued success of the supply chains. Optimization models have traditionally relied on estimated average input parameters, making it challenging to incorporate real-time data into their framework.

The proposed dynamic distribution and DARDEM method are studied in an e-grocery supply chain to minimize the total cost and complexity of the supply chain simultaneously. The proposed dynamic structure outperforms traditional distribution structures in a grocery supply chain, particularly when there is higher demand dispersion. The study showed that the DARDEM solution, the online solution, achieved an average difference of 1.54% compared to the offline solution, the optimal solution obtained in the presence of complete information. Moreover, the proposed method reduced the number of changes in downstream and upstream decisions by 30.32% and 40%, respectively, compared to the shortsighted approach.

Introducing a dynamic distribution structure in the supply chain that can effectively manage the challenges posed by real-time demand data, providing a balance between distribution stability and flexibility. The research develops a bi-objective mixed-integer linear program to make distribution decisions and supplier selections in the supply chain simultaneously. This model helps minimize the total cost and complexity of the e-grocery supply chain, providing valuable insights into decision-making processes. Developing a novel method to determine the status of the supply chain and online decision-making in the supply chain based on real-time data, enhancing the adaptability of the system to changing conditions. Implementing and analyzing the proposed MILP model and the developed real-time decision-making method in a case study in a grocery supply chain.

Given that existing retail brand research tends to treat each level of a retail brand as a separate concept, this paper aims to unveil the holistic nature of a multi-level retail brand, considering the distinctiveness of each level and the interrelationships between the images of different levels.

This study uses a scoping review approach that includes 478 retail brand articles. Subsequently, a thematic analysis method is applied.

The brand attributes that shape the distinct image of each retail brand level encompass diverse intrinsic and extrinsic attributes. Moreover, the holistic nature of a multi-level retail brand is formed by the interrelationships between the images of different levels, which are reflected in the presence of common extrinsic attributes and their interplay at attribute, benefit and attitude levels.

Theoretically, this review provides conceptual clarity by unveiling the multi-level yet holistic nature of a retail brand, helping researchers refine and extend existing theories in retail branding, while also providing new research opportunities in this field. Practically, the findings could guide retailers in implementing differentiated branding strategies at each level while achieving synergy across all levels.

This study explores the role of knowledge management capabilities (KMCs) in enhancing competitive advantage and organisational performance in fashion retailing. Employing the resource-based view (RBV) and knowledge-based view (KBV) perspectives, it investigates the interplay between managing knowledge effectively and fashion products’ complexity. The goal is to provide new insights into optimising KMC for greater agility and success in the fashion retail industry.

The study analysed survey data from 322 US fashion retail professionals using partial least squares structural equation modelling (PLS-SEM).

The results revealed that knowledge infrastructure capability enhanced both competitive advantage and organisational performance significantly. In contrast, knowledge process capability did not significantly affect competitive advantage, it improved organisational performance. Importantly, product complexity moderated the relationship between competitive advantage and organisational performance negatively.

This study underscores the necessity for retailers in the fashion industry to enhance their KMC to bolster competitive advantage and organisational performance, while it also acknowledges product complexity’s effect on these strategies. These insights offer actionable guidance for industry leaders to optimise knowledge management to navigate the rapidly evolving retail landscape.

This research offers novel insights into the interplay of product complexity and KMC in fashion retail and highlights the unique effects on competitive advantage and organisational performance valuable for both academia and industry.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

Different age groups display different shopping patterns in terms of how and where consumers buy products. During times of crisis, such behavioural differences become even more striking yet remain under-researched with respect to elderly consumers. This paper investigates the impact of age on retail-related behavioural changes and behavioural stability of elderly shoppers (in comparison to younger consumers) during a crisis.

The authors surveyed 643 Austrian consumers to assess the impact of perceived threat on behavioural change and the moderating effect of age groups. Based on findings from this survey, they subsequently conducted 51 semi-structured interviews to understand the causes of behavioural change and behavioural stability during a crisis.

Elderly shoppers display more stable shopping behaviour during a crisis compared to younger consumers, which is influenced by perceived threat related to the crisis. Such findings indicate that elderly shoppers reinforce their learnt and embedded shopping patterns. The causes of change and stability in behaviour include environmental and inter-personal factors.

Through the lens of social cognitive theory, protection motivation theory and dual process theory, this research contributes to an improved understanding of changes in shopping behaviour of elderly consumers, its antecedents and consequences during a time of crisis. The authors reveal reasons that lead to behavioural stability, hence the absence of change, in terms of shopping during a crisis. They further outline implications for retailers that might wish to better respond to shopping behaviours of the elderly.