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The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

Anti-racism has been practiced in various ways, with varying degrees of effectiveness. This chapter engages with the body of scholarship that focuses on approaches aimed at promoting anti-racist actions, policies and social change. It discusses some of the main anti-racism strategies that have been deployed across different countries and examines anti-racism practices in interpersonal, intergroup and community settings. These approaches encompass civil rights campaigns, legislative and policy interventions, affirmative action, diversity and inclusion training, prejudice reduction, intergroup contact, organisational development and holistic anti-racism approaches. Some anti-racism practices and policies, such as awareness campaigns, social marketing and diversity training, also extend to digital platforms, with social media and multimedia networks deployed to broaden the reach and impact of anti-racist endeavours. This chapter specifically engages with local anti-racism movements and draws principles for broader implementation of anti-racism policy and practice. It concludes with a brief discussion of the effectiveness of contemporary anti-racism approaches.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

Microfinance programs across the countries are designed on the self-help and peer pressure model, aim at microentrepreneurship development. Despite of significant studies on microfinance-supported microentrepreneurship (MSM), not a single literature examines it from the systems thinking. In addition to that, the extant literature did not look MSM from the behavioral perspectives. To address the above gaps, the present study aims to examine self-help group (SHG)-based microfinance programs from the systems approach using the Stimulus-Organism-Behavior-Consequence (SOBC) model.

Information gathered from 786 women SHG members from four states of India through a structured interview schedule. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were conducted to process data. Additional statistical tests were performed to test the reliability and validity.

It was found that the “positive stimulus” (social intermediation, financial intermediation and business development services) positively impacted; and “negative stimulus” (intermediation accountability, and intermediation assumption) negatively impact, to “motive” (attitude, subjective norms, and perceived control) for micro-entrepreneurship in the SHG-based microfinance. Further, “motive” positively predicted “behavioral intention”; the “behavioral intention” positively determined “consequences” of micro-entrepreneurship. Intermediation as stimuli acted as “input”; the motive and behavioral intention acted as the “process”, and the consequence acted as the “output” in the SHG-based microentrepreneurship system.

To the best of the author's knowledge, this paper is the first one to examine the behavioral systems of microentrepreneurship programs through the Stimulus-Organism-Behavior-Consequence (SOBC) model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0801

There remains a critical issue in sport management scholarship in that the field lacks a well-defined framework for delineating practical implications in research. This research aims to answer the following research questions: (1) What types of practical implications can be identified in sport management research? (2) How can sport management research frame the practical implications of the study in a way that is both theoretically sound and useful for practitioners?

Through a scoping review and within the lens of Jaworski (2011)'s framework for managerial relevance, the study examined 427 articles from European Sport Management Quarterly, Journal of Sport Management and Sport Management Review published between 2000 and 2020.

This study presents a five-pronged framework that identifies target managers, organizational tasks, time horizons, philosophical impact and desired outcomes. Furthermore, the current research offers suggestions for how to present managerial implications in sport management research.

The findings shed light on the managerial relevance of the recent sport management body of work, developing an important framework for practical implications for the field to reflect and incorporate into future studies. With a theoretical understanding of how to frame the practical implications of sport management research, the gap between academia and industry can continue to narrow, and the relevance to the industry may be more pertinent than ever before.

This study aims to explore the gendered nature of housing insecurity by investigating how gender affects women’s experience moving from transitional to market housing. By describing women’s pathways out of supportive or transitional housing support, the authors show how patriarchal forces in housing policies and practices affect women’s efforts to find secure housing. The authors argue that gender-neutral approaches to housing will fail to meet women’s needs.

This study explores the narratives from women accessing support services in Halifax, Canada. The first author conducted deep narrative interviews with women seeking to move from transition to market housing.

This research sheds light on the effects of gendered barriers to safe, suitable and affordable housing; how women’s experiences and expectations are shaped by these barriers; and, how housing-based supports must address the uniquely gendered experiences women face as they access market housing. In addition, this research reveals the importance of gender-responsive services that empower women facing a sexist housing market.

Little research has explored questions related to gender and housing among those seeking to move from transitional to marker housing, and existing research focuses on women’s housing insecurity as it relates to domestic violence. The sample of women included those having housing insecurity for a variety of reasons, including substance use and young motherhood.

The Central Bank of Nigeria (CBN) recently relaunched Nigeria’s cashless policy initiative which seeks to reduce financial crime and tax avoidance, decrease cash dependency, advance the adoption of digital financial services (DFS), decrease the risks to the payment system and foster financial inclusion. This study aims to identify the unique challenges of going cashless in Nigeria, particularly in terms of infrastructural, exclusionary and cost implications of the policy on the average citizens.

The author applies a doctrinal research methodology to identify and reflect on key challenges of the cashless policy from the economic, regulatory and transactional perspectives.

The cashless policy initiative in Nigeria heralds value for financial integrity, financial policy regulation and user convenience. The mode of introduction, however, ushers in significant challenges and hardly considers Nigeria’s inadequate payment infrastructure, persistent financial exclusion, low levels of financial and digital literacy and capability, high cost of using DFS and pervasive proclivity for cash. As Nigerians adjust albeit inconveniently to the policy, the CBN can ameliorate the hardship by strengthening the payment infrastructure, particularly for digital payments, fostering consumer trust by safeguarding user funds and enabling consumer preferences.

Research materials include the national regulator’s policy documents and newspaper articles that have not been published in formal reports but non-the-less adequately mirror the policy intention of the CBN and the lived experiences of Nigerians.

This study identifies the practical steps and regulatory measures that the CBN can take to improve acceptance and meaningful and sustainable adoption of the cashless policy by the majority of Nigerians.

The recommendations that are proffered provide some rich insights to inform regulatory direction for the CBN to seamlessly phase-in the cashless policy and consequently drive down financial exclusion in Nigeria.

This study contributes to the policy discussion around the introduction of the cashless Nigeria project. The doctrinal research method highlights the policy intentions of the regulator in juxtaposition with lived experiences of Nigerians. This study offers recommendations to bolster financial inclusion, stability and integrity.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The purpose of this paper is to examine the consumer response to brands offering gendered product differentiation (i.e. products “for her” or “for him”).

Across three experiments, the effect of gendered (vs gender-unrelated) product differentiation on perceived brand sexism and word-of-mouth intention was tested. The moderating effects of feminist identity (Studies 1 and 2), endorsement of sexist beliefs (Study 2) and basis (stereotypical vs biological) for product differentiation (Study 3) were also tested.

Consumers perceive brands that offer gendered product differentiation as sexist, which in turn leads to negative word-of-mouth intention. Moreover, consumers with a strong feminist identity are more likely to perceive brands that offer gendered product differentiation as sexist, whereas consumers who endorse sexist beliefs are less likely to do so. Finally, consumers respond negatively when the gendered product differentiation is based on a gender stereotype, but much less so when it seems based on a biological difference between sexes.

Although multiple brands offering gendered products have been denounced by consumers as sexist, no research has examined this phenomenon. This paper pioneers in examining the consumer response to brands offering gendered product differentiation and in demonstrating that consumers perceive such brands as sexist.