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This study was carried out to analyze the importance of consumer preference data in forecasting demand in apparel retailing.

To collect preference data, 729 hypothetical stock keeping units (SKU) were derived using a full factorial design, from a combination of six attributes and three levels each. From the hypothetical SKU's, 63 practical SKU's were selected for further analysis. Two hundred two responses were collected from a store intercept survey. Respondents' utility scores for all 63 SKUs were calculated using conjoint analysis. In estimating aggregate demand, to allow for consumer substitution and to make the SKU available when a consumer wishes to buy more than one item in the same SKU, top three highly preferred SKU's utility scores of each individual were selected and classified using a decision tree and was aggregated. A choice rule was modeled to include substitution; by applying this choice rule, aggregate demand was estimated.

The respondents' utility scores were calculated. The value of Kendall's tau is 0.88, the value of Pearson's R is 0.98 and internal predictive validity using Kendall's tau is 1.00, and this shows the high quality of data obtained. The proposed model was used to estimate the demand for 63 SKUs. The demand was estimated at 6.04 per cent for the SKU cotton, regular style, half sleeve, medium priced, private label. The proposed model for estimating demand using consumer preference data gave better estimates close to actual sales than expert opinion data. The Spearman's rank correlation between actual sales and consumer preference data is 0.338 and is significant at 5 per cent level. The Spearman's rank correlation between actual sales and expert opinion is −0.059, and there is no significant relation between expert opinion data and actual sales. Thus, consumer preference model proves to be better in estimating demand than expert opinion data.

There has been a considerable amount of work done in choice-based models. There is a lot of scope in working in deterministic models.

The proposed consumer preference-based demand estimation model can be beneficial to the apparel retailers in increasing their profit by reducing stock-out and overstocking situations. Though conjoint analysis is used in demand estimation in other industries, it is not used in apparel for demand estimations and can be greater use in its simplest form.

This research is the first one to model consumer preferences-based data to estimate demand in apparel. This research was practically tested in an apparel retail store. It is original.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

This research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the disruptions and work effectively in a resource-based view perspective.

Eight broad strategies and 32 sub-strategies are identified from the literature review. Delphi study was carried out, and detailed discussion with 16 experts helped in finalizing these strategies. Further, the best-worst method (BWM) prioritized these strategies.

The findings suggests that “building social capital,” improving “coordination capabilities,” “sensitivity towards market,” “flexibility in process and production,” “reduction in process and lead time,”and “having a resource efficiency and redundancy” are the top strategies on which the top management should focus to overcome the situations of disruptions and enhance performance of MSMEs.

The blockchain-based strategies will enable the companies in tracing the products from the company to customers. Further, the customers will be able to identify their manufacturers, the raw materials used in manufacturing, and the life and quality of raw used materials. Altogether the textile industry will become more sensitive toward environmental practices.

The previous research has not identified and evaluated the blockchain-based resilience strategies, and therefore this study tries to fill this gap. This study used a smaller sample from the experts, so the results may vary if the larger data set is used and hypothesis testing can be done.

The post-purchase behavioral responses of omnichannel shoppers, who mainly rely on physical stores (acknowledged as a crucial channel in providing a seamless shopping experience and fulfilling the dynamic needs of the shoppers), are still understudied. The purpose of this paper is to examine how integrated store service quality (ISSQ) can contribute to a more optimal shopping experience (cognitive, affective and relational) and have a subsequent impact on shoppers’ psychological ownership toward the store, resulting in the generation of (face-to-face, online and social media) word of mouth (WOM).

The research is descriptive, quantitative and cross-sectional investigation. A purposive sampling technique was used for selecting the study respondents. The data were collected from 786 Indian omnichannel shoppers using a validated self-administered questionnaire. The proposed conceptual model was tested using partial least squares structural equation modeling.

The results indicate that all three dimensions of omnichannel customer experience (cognitive, affective and relational) positively mediate the relationship between ISSQ and psychological ownership, subsequently impacting all three WOM behaviors of omnichannel shoppers (face-to-face, online store and social media). The customer’s perceived value with the store and their perceived retailer relationship investment significantly moderated the relationship between ISSQ and different WOM behaviors (face-to-face, online store and social media). This research also demonstrated the direct impact of ISSQ on WOM and the indirect impact through different customer experience dimensions and psychological ownership.

The sample used in the study was not probabilistic and, therefore, presents limitations for the possibility of generalizing the results. The study was performed in a cross-sectional methodology in the Indian context; there is a need for longitudinal investigation.

This study addresses the need to investigate different dimensions of omnichannel customer experience that might influence various post-purchase behavioral responses. This study is the first to show that ISSQ might affect omnichannel shoppers' online, offline and social media word-of-mouth behaviors through different customer experience dimensions and the customer’s sense of belongingness to the store. The moderating effect of customer perceived value with the retailer and their perception of retailers’ investment in a relationship on proposed hypotheses was also tested to give managerial recommendations.

The purpose is to replicate and extend Ambulkar et al.’s (2015) work testing resource reconfiguration as a mediator of the supply chain disruption/firm resilience relationship and testing risk management infrastructure as a moderator. This study extends the work of Ambulkar in that it uses analysis of survey data gathered from manufacturing firms during an actual disruption event (COVID-19). The previous work is also in extended in that the authors include a pandemic disruption impact variable and supply chain performance is an expanded model.

Partial least squares structural equation modeling techniques were used to analyze data gathered from 184 US manufacturing managers during the height (Summer 2021) of the COVID-19 pandemic.

Two of four of Ambulkars et al.’s (2015) hypotheses were confirmed as relevant to firm resilience during the pandemic while two were not confirmed. Results also show that supply chain disruption orientation, risk management infrastructure and resource reconfiguration combine to improve firm resilience, which in turn improves supply chain performance while mitigating the disruption impact of COVID-19.

Previous work is replicated and extended, using data from an actual disruption event (COVID-19). This study presents a more comprehensive model using a newly developed and validated scale to measure pandemic impact and including supply chain performance.

This study aims to explore supply chain resilience (SCR) and provides a unique resilience index. The work measures the resilience status of 37 organizations across 22 industries and provides insight into accessing the supply chain (SC) vulnerability in an uncertain environment.

This study involves measuring the resilience status of 37 organizations across 22 industries based on a subjective decision-making approach using fuzzy logic. Experts from industries rated the importance and level of implementation of 33 attributes of SCR, which are used to develop a fuzzy index of implementation that explains the resilience status of organizations.

A novel coexistent resilience index is computed based on mutualism to exhibit the proportion of contribution or learning of each attribute of an organization in an industry. The research will enhance the response plans and formation of strategic alliances for mutual coexistence by industry.

Evidence-based interpretations and suggestions are provided for each industry to enhance resilience through coexistence.

The work uniquely contributes to academic literature and SC strategy. The novel coexistent resilience index is computed based on mutualism, facilitating researchers to access SC resiliency.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

The current work aims to present a review of academic literature that systematizes the body of knowledge related to marketing and consumer behavior in order to identify the most effective variables that encourage the consumer towards a proper and better lifestyle, accordingly the paradigm of management, marketing and technology efforts to promote a “better” society preventing obesity.

A literature review was carried out to examine the studies of marketing and consumer behavior published in international peer-reviewed journals over the last twenty-three years (2000–2023). Our review finally considered a total amount of 46 articles.

Findings elucidate three overarching themes and associated sub-hemes, encompassing: (1) Product design for obesity prevention, including aspects such as labeling, nomenclature, packaging and assortment; (2) Technology-supported preventive measures, involving mobile applications, self-monitoring, short message services and digital therapeutics; and (3) Marketing and communication strategies, incorporating social advertising, nudge, social influence and initiatives targeting childhood obesity prevention. Furthermore, a comprehensive research agenda is presented, delineating potential avenues for future investigations predicated on the utility of the results in fostering subsequent endeavors within the realms of: efficacy and effectiveness studies; personalization and tailoring; behavioral change techniques and gamification; user experience and acceptance; cost-effectiveness and implementation; as well as ethical and privacy concerns.

Main limitations are related to the characteristics of the analyzed literature, resulting in only English journal articles, book chapter and so on. Thus, other relevant contributions in different languages discussing interesting insights might have been neglected.

This study offers several insights to managers, marketers and policymakers involved in the issue of the obesity prevention. Since obesity represents a crucial challenge for public health at a global level, with its incidence reaching epidemic proportions in recent decades, the results may be extremely useful and powerful because suggesting – by employing a robust resulting corpus of knowledge on this domain – several practical features, actions and tactics to face such an important challenge. Moreover, this paper offers for scholar and researcher a systematized knowledge around the issues of obesity prevention, together with a detailed research agenda emerging by the critical analysis of the emerging insights, and to practitioners systematized useful insights to project and develop their future business strategies.

By providing several actions and tactics for obesity prevention (e.g. as for product labeling, naming, packaging, assortment; the exploitation of new technologies for mobile applications design, self-monitoring, short message service (SMS) alert systems, digital therapeutics; the role of social advertising, nudge, social influence) this work perfectly match the emerging societal orientation related to business, marketing and technology efforts to create a “better” society.

The study shed lights the need for a holistic approach to obesity prevention, involving interaction between individual main topics. Importantly this is the first study to analyze the issue of obesity prevention by considering a multidisciplinary corpus of literature, analyzed trough an individual-centric orientation.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

This study aims to explore the impact of store atmospherics on urban bottom-of-the-pyramid consumers’ behavioural intentions to purchase apparel in an emerging African market context. This study also considers purchase antecedents to attitude, perceived behavioural control and social norms as determinants of urban bottom-of-the-pyramid consumers’ apparel behavioural intentions.

Using non-probability sampling, specifically purposive and interlocking sampling, data collection was secured from 881 economically active Namibian urban bottom-of-the-pyramid respondents through interviewer-administered questionnaires. Covariance-based structural equation modelling assessed the significant relationships among all constructs in the conceptual model.

This study found that for favourable apparel behavioural intentions of urban bottom-of-the-pyramid consumers to occur, apparel retailers should emphasise trust, perceived awareness and self-identity through apparel assortment and groupings, easy-to-read visible signage, together with competent, friendly and respectful sales personnel in their store atmospherics.

The findings of this study may guide apparel retailers in other emerging African markets to develop regional integration, market-based solutions and inclusive economic growth focusing on “non-essential” products, such as apparel, among urban bottom-of-the-pyramid consumers.

This study expands the intellectual boundaries of urban bottom-of-the-pyramid consumers’ behavioural intentions towards “non-essential” products. The theoretical framework supports the integration of both the stimulus-organism-response model and the theory of planned behaviour into one single model for empirical investigation. Additionally, adopting a novel theoretical framework helped identify the impact of store atmospherics from a bottom-of-the-pyramid perspective in an emerging African market context, such as Namibia.