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Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018.

The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA).

The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM.

The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM.

By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. The significance of the paper would be in its potential to shed light on emerging areas of interest and provide valuable implications for future research and practice in Sustainable HRM.

The level of consumer satisfaction (CS), dissatisfaction (CD) and complaint behaviours (CCB) is beginning to receive increased attention from practitioners and researchers. Most studies, however, have tended to investigate the cause and/or effects of (dis)satisfaction or complaint behaviours. Relatively less work has been done to understand the relationship between dissatisfaction (CD) and complaint behaviours (CCB). This relationship is examined expirically. From a critical evaluation of previous research, hypotheses for the non‐linear relationship and the moderating role for CD and CCB are developed for an exploratory study. Using data on banking and financial services dissatisfaction, these hypotheses are investigated empirically. The results suggest that CD plays a broad and pervasive role (i.e. linear, non‐linear, moderator) depending upon the CCB dimension considered. Several implications of the results for managers are discussed and guidelines for dissatisfaction management are provided.

This article documents instances of racism that have previously acted as barriers to Indian students' academic success in Australia. It is felt that such incidents would not have happened to students from, for example, China or Japan, as their governments would have taken more serious steps against the Australian government. There is a feeling in India that the Indian government can be seen as weak. Against this background, the article looks at potential reasons for racially motivated attacks against Indians in Australia, and at what can be done to reduce these, as well as both the Australian and Indian government responses to the particular instances reported.

This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.

Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.

The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.

Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.

The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.

Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.

Known for its motto “All Ages, All Races, All Genders,” MAC cosmetics reflects the brand’s commitment to inclusivity and diversity. It has been at the forefront of promoting a wide range of skin tones, ethnicities and gender identities in the beauty industry. If you have ever wondered about the secret behind the success of this mega-brand in the beauty industry, this case study aims to provide a comprehensive overview of the company’s history from its early days to the present and discusses the factors that might build or ruin a brand. Moreover, players in the industry will need to adapt to changing consumer preferences, focus on sustainability and leverage digital technologies to remain relevant and capture market opportunities. Therefore, would it be wise for MAC cosmetics to take forward their expansion plans in India, and what is the motivation behind the expansion? Alternatively, would the implementation of a proactive strategy for product innovation, combined with a stronger presence, result in a more viable and sustainable proposition?

This study relies on online resources for data collection. The data was collected from the secondary sources in the month of November and December 2022. Moreover, the information provided in the case study was validated and supplemented via using different websites, including the company’s website and social media profiles.

The commitment shown and the roles played will have a lasting impact on the society. Additionally, student will be able to learn when and how to seize opportunities, as well as how to manage obstacles that will arise in their entrepreneurial journey. Through this case study, they will be able to learn a variety of business strategies that can be implemented in emerging markets. The conclusion of the study provides the obstacles and hurdles faced by the industry in expanding in the Indian market. The potential solutions were made through providing information for the students, academicians, entrepreneurs and others to compete in the Indian market situation.

This is a real-world case that provides the audience with first-hand experience to comprehend the event and apply their knowledge to form a conclusion and is also effective for decision-making in the dynamic environment of the present day. However, the authors provide a comprehensive overview of the company’s history from its early days to the present and discuss the factors that might build or ruin a brand.

Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerism’s impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability.

A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023.

The findings reveal four prominent factors – behavioural, environmental, socioeconomic and technological – in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways.

Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour.

Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends.

The paper identifies the antecedents and consequences of integrated supply chain performance (ISCP) in healthcare systems.

Based on a review of the literature constructs of supply chain flexibility (SCF), employee relationships (ERs), organizational orientation (OO) and knowledge exchange (KE) were identified as antecedents of ISCP, and patient centricity (PC) emerged as its consequence. This structural relationship was tested using partial least square structural equation modeling (PLS-SEM).

ERs, SCF, OO and KE positively impacted the performance of an integrated healthcare supply chain. Furthermore, enhanced ISCP in operational processes of the hospital positively influenced patient centeredness and care quality.

Paper contributes by identifying antecedents and consequences of ISCP. Future researchers may explore the inter-relationships among the antecedents of ISCP.

Insights from this study will help practitioners in enhancing hospital operations by integrating processes along the healthcare service supply chain and developing a patient-centric approach.

This paper highlights how PC may be achieved by focusing on a facilitative internal environment. This understanding may help in designing processes that deliver health as a social good in an effective manner.

The empirical evidence from this study can help hospitals integrate their functions, thus, enabling them to deliver quality care.

Intraorganizational knowledge and information sharing are important steps toward more-accessible organizational knowledge. The aim of this study is to qualitatively explore factors that contribute to employees' motivations for sustaining intraorganizational knowledge-sharing behaviors and to examine the impact of these factors in a quantitative study with the Austrian Federal Ministry of Defense. This ministry faces a retirement wave in the next 5–10 years. Intraorganizational knowledge sharing before, during, and following this wave will play a decisive role for the organization in the near future.

An exploratory sequential mixed-methods study was conducted. The study design involved a qualitative study phase with expert interviews and stakeholder workshops (n = 9) and a quantitative study phase based on a cross-sectional online survey with an implicit association test on intraorganizational knowledge sharing (n = 59).

In the qualitative study phase, three main research topics regarding intraorganizational knowledge sharing were identified: employee attitude, organizational support, and specific relational aspects of knowledge transfer, such as reciprocal relationships among employees and opportunities for knowledge exchange. A hierarchical multiple regression analysis revealed that perceived organizational support was the only factor that was a significant predictor of motivation for engaging in knowledge sharing. We also analyzed the data for moderation effects and demonstrated that sociopsychological factors (e.g., the engagement or openness of colleagues to share their knowledge) further strengthened the positive relationship between employees' perceived support and personal willingness to share knowledge.

We conclude that an organizational culture that supports knowledge sharing within the organization is highly relevant for motivating employees to share their knowledge. Practitioners will also benefit from the insights of the various dimensions of employees' willingness to engage in knowledge-sharing behaviors to better design further interventions in organizations.

In accordance with an exploratory sequential mixed-methods approach, we followed a transdisciplinary process in which scientific and practical experiences and knowledge were integrated. For this purpose, interviews and workshops with experts and stakeholders in the organization were conducted. The qualitative findings were incorporated into a quantitative survey and an implicit association test for the employees of the organization. This approach demonstrates a different and more holistic approach to analyzing a real-world problem in the context of a governmental agency in order to investigate the multidimensional and complex topic of intraorganizational knowledge sharing.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.