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This chapter argues that the National Basketball Association (NBA) and American mainstream sporting media produce and mediate a representation of India as underdeveloped and as an unmodern subject/nation as a way to enter the Indian basketball marketplace. The chapter emphasizes that the NBA produces the attendant discourse of the ‘white saviour’ through a multi-pronged process. The chapter shows how it draws upon the legacies of British colonialism, along with the expansion of US imperialism, to construct India in particular racialised ways as backward, unmodern, and not cosmopolitan. In this respect, Black NBA players’ modes of basketball reach India as part of the racialisation of Indian basketball. Finally, the chapter engages with the larger global circuits of race and racialisation to understand how India is then imagined within the US sporting landscape. This chapter underscores the capitalist desires of the NBA alongside the desires of South Asian Americans for an Indian basketball hero. Both desires, institutional and personal, showcase racialisation at work. The NBA uses the language and performance of Judeo-Christian modernity through NBA players in India to racialise Indians as in need of NBA mentorship and upliftment. On other hand, diasporic Indians in the US dream of an Indian NBA player as a way to unravel, destabilise, and challenge their racialisation as hypo-masculine subjects. These competing forms of racialisation provide important information on the global flows of capital, desire, and sport.

Despite the growing interest regarding companies' sustainability, its social dimension has mostly been neglected by academics and practitioners. Consequently, this study aims to address this issue by investigating if the adoption of human resource (HR) analytics can positively influence the impact of social sustainable operations practices (SSOP) on employees' motivation and engagement and the effect of these lasts on organizational retention.

Data were collected through online questionnaires addressed to 281 HR managers of heterogeneous companies from Europe and analyzed through a structural equation modeling (SEM) technique.

The findings confirmed the positive effect of SSOP on employees’ motivation and engagement, and of these last on employees’ retention. Furthermore, they confirmed that the usage of HR analytics positively moderates the relationship between SSOP and employees’ motivation and engagement.

This study contributes to both sustainable operations management and HR management literature streams. First, it adopts a multidisciplinary perspective which also considers evidence from HR management literature, allowing the authors to concentrate on the social dimension of sustainability. Second, it provided further insight regarding the adoption of a data-driven approach in relation to social sustainable operations management. Finally, it contributes to HR analytics-related literature by demonstrating its impact also on organizational aspects that are not directly controlled by the HR department.

This paper aims to utilize an extended involvement-commitment and trust commitment model to examine post-consumption decisions related to food delivery app use.

A self-administered online survey was used to collect data from food delivery app users in the USA.

Findings validate a favorable role of perceived app security and menu description on trust in app recommendations. Trust was found to be positively related to involvement, commitment and willingness to provide feedback. The positive moderating role of perceived convenience and rewards and incentives was also confirmed in relation to consumers’ trust in app recommendations, and involvement and commitment

A key contribution of this study includes the development of a comprehensive model to understand postconsumption decisions related to the usage of food delivery apps. To the best of the authors’ knowledge, this study is also the first to unveil the antecedent and moderating factors related to food delivery app users’ willingness to provide feedback, share personal data and to pay more.

This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

Gossip spreads like wildfire, damaging relationships, decaying trust and creating a negative work environment. This study aims to investigate the relationship between negative workplace gossip (NWG) and quiet quitting (QQ), while considering the mediating effects of workplace stress and emotional exhaustion (EE).

Drawing upon the conservation of resource theory, the study aimed to comprehend this association in the context of 267 employees from diverse sectors in India, including health care, IT, banking and education. Through a three-wave time lagged survey design, using partial least squares structural equation modeling, significant findings were uncovered.

The results revealed a positive link between NWG and QQ. There was also a positive correlation between NWG and workplace stress. In addition, workplace stress and EE were found to mediate the relationship between NWG and QQ.

The findings have implications for both theory and practice. Organizations should consider implementing strategies to mitigate the prevalence of negative gossip and foster a healthier work environment, promoting employee well-being and retention.

The study reveals the “black box” between NWG and QQ, adding to the body of knowledge on the novel concept of QQ. Second, the study expands the literature on NWG, by examining impact path of how it leads to stress and EE, leading to QQ.

This study aims to examine the antecedents of tourist citizenship behavior (TCB). It also investigates the role of digital halal literacy (DHL) and religiosity in enhancing TCB.

This quantitative research used survey with questionnaire as the data collection methods. The samples of this study were 400 tourists who visited tourist destinations in five cities/municipals in West Sumatra Indonesia. This research used partial least square structural equation model as the data analysis tools.

This study found that satisfaction, trust and DHL are significant antecedents of TCB. In addition, satisfaction had a direct impact on TCB and influenced TCB through trust as a mediator. This study also found that religiosity had a direct influence on DHL, satisfaction and trust.

The findings will provide insights to tourist destination managers as well as the government on how to motivate tourists to participate in the development of Halal tourism in Indonesia. The tourists should gain sufficient knowledge or literacy about Halal, and especially in the digital context. Therefore, this will lead to their satisfaction, trust and willingness to participate in tourism development such as providing assistance to other tourists in the destinations.

This research has identified a new variable, DHL, which has not been addressed previously. This research has extended social exchange theory by establishing a relationship between TCB and DHL that has also not been previously explored. In addition, this study has investigated several relationships between DHL, satisfaction, trust and TCB and has shed new insights in the context of Halal tourism. This study has also provided a more comprehensive model of the relationship between DHL, satisfaction, trust and citizenship behavior specifically in Halal tourism research.

This study explores the impact of ethical and authentic leadership on employees' workplace perceptions, focusing on organisational citizenship behaviour (OCB), trust in leader, commitment, employee voice and empowerment in independent hotels across two contrasting Global Leadership and Organizational Behaviour Effectiveness (GLOBE) clusters: Germanic and Middle-Eastern clusters. It examines how national culture influences these relationships in the hospitality industry.

Data were collected from 1,678 employees in independent hotels in the Germanic European cluster (Germany and the Netherlands) and the Middle-Eastern cluster (Qatar and Turkey) using selective and snowball sampling techniques. Hypotheses were tested using two-stage structural equation modelling.

Ethical leadership significantly affects employee voice in Germany and the Netherlands but not in Qatar and Turkey. Authentic leadership positively influences employee voice in Qatar, Turkey and Germany but does not significantly impact trust in leader in any of the four countries. The study underscores the role of cultural dimensions, particularly power distance, in shaping these relationships.

This research contributes to the literature by investigating the effects of ethical and authentic leadership on key organisational variables in culturally diverse contexts within the hospitality industry. The findings highlight the necessity of considering national culture in leadership practices and suggest practical implications for independent hotels to adapt their leadership approaches to enhance employee outcomes. Future research should explore cultural dimensions as moderators in organisational relationships.

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route heritage (CRH). The study intends to inspire further discussion on the theoretical and practical development of cultural routes since the development is still at a liminal stage in China.

A total of 253 research articles related to Chinese cultural rote heritage from major Chinese and English research databases China National Knowledge Infrastructure (CNKI), Web of Science (WOS) and Scopus have been comprehensively identified and reviewed for the purpose of the study.

Four major themes of research on Chinese CRH have been identified: conceptual evaluation, list of the routes and characteristics of the routes, conservation and utilization. The results revealed that China has very rich resources in CRH, many of which were formed a long time ago, which exist across vast geographic regions and have assumed multiple functions and undergone dynamic reciprocal exchanges among diverse cultures and ethnicities.

The paper summarizes some major obstacles faced by CRH in China and proposes a strategic model to address the need for a more sustainable development of CRH in the Chinese context.

The paper offers a comprehensive overview of CRH in China and discusses practical issues in management and development of heritage great in size, number and complexity.

Drawing upon person–supervisor fit theory, a model is developed to illustrate how leader–member trait mindfulness (in)congruence may impact leader–member exchange (LMX) and how such trait mindfulness (in)congruence can indirectly influence taking charge.

Polynomial regression and response surface methodology are used to analyze 237 valid matched leader–member dyads.

LMX increases as leaders' and members' trait mindfulness become more aligned; LMX is higher when leader–member dyads are congruent at high levels (vs low levels). In the case of incongruence, LMX is higher when the member's trait mindfulness exceeds that of the leader. Furthermore, the relationship between leader–member trait mindfulness (in)congruence and taking charge is mediated by LMX.

The joint and interactive role of high trait mindfulness in leader–member dyads can help them to generate high-quality interpersonal exchange, as well as to cope with challenges posed by present and future changes.

The linear, nonlinear, simultaneous and interactive effects of dyadic trait mindfulness expand previous research, clarifying that the evaluation of leader–member congruence and incongruence at various degrees, and for various patterns of trait mindfulness, is more informative than examining the direct effect alone.