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The objectives of this study are threefold: to delineate the phenomenon of “You Share, We Donate” (YSWD) campaigns and what distinguishes them from sales-based cause-related marketing; to contrast the effectiveness of YSWD and sales-based cause-related marketing campaigns and provide an explanation for the differences in the effectiveness; to explore boundary conditions of the proposed differences.

Three experiments were conducted to empirically test the differential effect of campaign formats (i.e. YSWD vs sales-based cause-related marketing), the underlying mechanism and structural as well as contextual features moderating the differential effect.

The findings suggest that YSWD messages elicit consumers’ message-sharing intentions more than traditional cause-related marketing messages. The effect is explained by consumers’ sense of empowerment and can be enhanced through donation cap non-specification. The findings further indicate that YSWD campaigns are especially fruitful in low power distance cultures.

This study contributes toward corporate donation campaign literature by focusing on the usage of social media.

From a managerial perspective, this research provides marketers with guidelines on how to choose between the two cause-related marketing campaign formats and how to enhance the effectiveness of YSWD campaigns.

This paper extends cause-related marketing literature by not only introducing the phenomenon of YSWD campaigns to the literature but also exploring strategies to enhance the effectiveness of such campaigns and shedding light on an outcome beyond the sales impact of cause-related marketing campaigns, i.e. an increase of visibility in social media. From a managerial perspective, this research provides marketers with guidelines on how to choose between the two cause-related marketing campaign formats and how to enhance the effectiveness of YSWD campaigns.

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

Purpose: Different approaches have been applied to define and measure service quality as both a process and a performance-intensive presentation. The literature agreed that service quality assessments are essential in measuring performance, however they could only reach a partial consensus. Although the Servqual scale is the most widely known and used tool in measuring service quality, it has received various criticisms. This study presents the difficulties encountered in measuring service quality and an evaluation of the Servqual scale.

Methodology: The study provides a conceptual framework, examining the research on the subject in the literature and the criticisms of the Servqual scale. It is designed as a compilation/assessment to improve the perspectives of the interested parties by bringing together evaluations about the pros and cons of the most well-known service quality scale.

Findings: Measurement of service quality is a complex business. Although it has received various criticisms, the Servqual scale which enables the measurement of quality in the services sector is still the most frequently used measurement tool.

Practical Implications: The difficulty of defining the service and its quality, which arises from the characteristics of the services, does not eliminate the necessity of measuring the quality of the service. With this study, a conceptual framework has been provided on the subject, a collective evaluation has been made for the most widely used scale, and the ground has been prepared for improvement and development in the criticisms of the scale.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Firms can benefit from designing sales promotion based on the analysis of consumers' physical exercise and purchase data. This study aims to study mobile exercise app data to explore how purchasing a promoted or nonpromoted product affects exercisers’ subsequent exercise and purchase behaviors.

Drawing from the theoretical framework of overjustification effect, this study empirically examines the effects of the purchase of promoted – monetary and nonmonetary – or nonpromoted products on relationships (1) between past and subsequent exercise behaviors and (2) between past exercise and subsequent purchase behaviors. Novel data of one million exercise activities and purchase transactions created by 7,517 mobile exercise app users were collected.

The results reveal that monetary and nonmonetary promotions have a negative effect on overall consumers’ amount of physical exercise but increase heavy exercisers’ exercise amount. In addition, nonmonetary (monetary) promotion has a positive (negative) effect on consumers’ purchase expenditure but has no moderating effect on the exercise–expenditure relationship.

This study provides a theoretical framework explaining how to mitigate the dark side of sales promotions while targeting right exercise consumer segments with the right promotion campaigns.

This study examines the influence of consumer skepticism on cause-related marketing (CRM) campaign participation intentions of Generation Z consumers from emerging market perspective. This study was undertaken due to the paucity of relevant literature in the public domain to directly investigate whether and how consumers' skepticism affects CRM participation intentions, specifically in the luxury retailing context.

A survey was conducted among 552 Generation Z consumers and path analysis was used to examine the direct and indirect effects of skepticism. The mediation and moderation analysis was used to explore and test the authors' hypotheses via partial least squares structural equation modeling (PLS SEM).

The authors' findings provide empirical evidence that corporate social responsibility, religiosity and cause involvement positively affects consumer participation intentions, and this link is also established indirectly through skepticism toward the CRM campaign. These findings provide novel theoretical contributions by establishing skepticism's complex role in determining the CRM participation intention in the Generation Z consumers' context. This study further demonstrates the moderating effect of gender and luxury store format on consumer skepticism and CRM participation intentions.

The Generation z group will represent a quarter of the Asia–Pacific region's population by 2025. However, little is known about Generation z consumers' CRM participation intentions. This research would help practitioners, including luxury retailers, CRM managers and advertising professionals, to effectively design CRM campaigns. The paper contributes by highlighting the theoretical implications and managerial implications based on the current findings in the emerging market context.

This study aims to explore the impact of women empowerment and gender-stereotypical advertising exposure on consumers’ attitudes and purchase intents.

The quantitative research approach was used to assess the women-empowerment and gender-stereotypical advertising on consumers’ attitudes and purchase intentions, explicating the most effective approach in marketing communication in the Arab context, specifically Egypt. Administrated questionnaires were distributed online cross-gender through the use of convenience sampling. The targeted average sample size sought was minimum of 370. Once the data was acquired, partial least square path modelling of structural equation modelling was conducted to test the hypotheses.

Results show that male consumers and female consumers react to a certain extent differently to women-empowerment and gender-stereotypical advertisings. For instance, gender-stereotypical advertisings effect attitude for both genders; it effects male consumers’ purchase intentions, but not female consumers. Women empowerment advertising is insignificant on brand attitude and purchase intention among male consumers; among female consumers, it has significant impact on brand attitude, but not purchase intention. Nevertheless, both categories of advertising contribute to male consumers’ and female consumers’ perception and attitude towards gender role portrayal.

This study provides noteworthy insights and perspectives on women-empowerment (Femvertising) and gender-stereotypical advertising effects on cross-gender consumers in the Arab region (a region of strong masculine culture values). The emerged conclusions aid as a reference and guide for scholars and practitioners to develop effective advertising that create prospect depictions and build inspired female customer base.

This case replaces UVA-M-0837. It can be used in a variety of marketing and strategy classes to understand how (1) at a macro level, a shift in consumer and environmental factors can impact firm strategy and (2) at a micro level, an e-mail-based marketing campaign designed to address these changes can impact firm-level performance.

The case puts the students in the position of CEO Robert Huth as he is preparing for a board meeting. He had taken David's Bridal from a loss in 1996 to sales of over $1 billion by 2011, but he was concerned about future growth. People were waiting longer and longer to get married and, once they decided to, were spending much less than in the past, so the industry had seen year-over-year declines since 2007. How would David's Bridal establish its brand in the minds of a new generation of brides who shopped, purchased, and decided differently than had brides in past generations?