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Researchers have tried analysing how the organizations’ practices of doing good can help improve their employees’ satisfaction over the past couple of decades. Employee satisfaction has a complicated relationship with a company’s corporate social responsibility (CSR) activities. Subsequently, the purpose of this paper is to conduct a bibliometric analysis and a literature review to trace the links between CSR and employee satisfaction, summarize and analyse the advances in this field, the knowledge gaps, publishing trends and further directions for future research.

The authors conducted a bibliometric analysis followed by a literature review of papers indexed in the Scopus database and published between 2000 and 2022. A total of 233 papers were identified, while 152 of them met the inclusion criteria for the analysis.

The subsequent analysis sheds light on the overlaps and connections between the two phenomena in human resource management (HRM). The authors outline potential avenues for future research and practical insight into how to leverage CSR activities for increasing work satisfaction.

By detailing the different ways CSR and employee satisfaction impact one another, analysing their relations and other supporting constructs, the authors contribute to the academic discourse by synthesizing prevailing literature and introducing practical guides for human resource (HR) professionals, managers and executives to manage turbulent surroundings more effectively, considering the major disruptions post-COVID-19 and the adoption of advanced technologies.

The study addresses gaps in sustainable luxury consumption research by analyzing the role of social norms in different cultural settings. It investigates how social norms, self-control, conspicuousness and future orientation shape sustainable luxury consumption in individualistic (UK) versus collectivist (China) national cultures.

The study was based on survey data from British and Chinese luxury product consumers collected through online panels. The final sample included 452 valid responses from the UK and 414 from China. Hypotheses were tested using structural equation modeling.

The study found that descriptive norms positively influence sustainable luxury consumption in individualistic (UK) and collectivist (China) cultures. Injunctive norms affect sustainable consumption only in the UK. Future consequences universally impact sustainable consumption. Conspicuous consumption negatively affects preferences for sustainable luxury brands. Self-control enhances the impact of descriptive norms in the UK but reduces the impact of injunctive norms in China.

This study uniquely explores how social norms and cultural influences impact sustainable luxury consumption in individualistic and collectivistic societies. It highlights the moderating role of national culture, providing actionable insights for luxury brands to enhance sustainable consumption with culturally tailored strategies. The research challenges the universality of the theory of normative social behavior, advocating for its refined application across different cultures.

This study aims to offer an overview of hospitality and tourism research on artificial intelligence (AI) and its impact on the industry. More specifically, this study examines hospitality and tourism AI research trends in hospitality and tourism customer service experience creation and delivery, service failure and recovery, human resources and organizational behavior. Based on the review, this study identifies the challenges and opportunities and provides directions for future studies.

A narrative synthesis approach was used to review the hospitality and tourism research on AI and its impact on various aspects of the industry.

AI and AI applications in customer service experience creation and delivery and its possible effects on employees and organizations are viewed as a double-edged sword. Although the use of AI and AI applications offers various benefits, there are also serious concerns over the ethical use of AI, the replacement of human employees by AI-powered devices, discomfort among customers and employees and trust toward AI.

The paper offers an updated holistic overview of AI and its implications in different facets of the hospitality and tourism industry. Challenges and opportunities are discussed to foster future discussions on the use of AI among scholars and industry professionals.

This research aims to explore whether or how organizations adopt people analytics (PA), its value and potential socio-technical factors that can enable or hinder PA projects by disrupting and reshaping human resource management. We do this by focusing on the Italian context.

We conduct a scoping review of data collected between 2018 and 2022 via Google Alerts (GA), a content change detection and notification service that is gaining popularity in scholarly research.

Our findings suggest that the diffusion of PA applications in Italy, especially those of a descriptive nature, is growing. Most of the existing PA applications are positioned in a positive technocratic light, envisioning the value of PA for both employees and organizations. The value for the latter appears to be direct, while the value for employees is realized through organizational initiatives. The findings also suggest that while enablers can vary between PA application types, the barriers, especially technological and environmental, are generic for both descriptive and predictive/prescriptive PA applications.

Theoretically, we propose a framework for analyzing PA applications, their values, enablers and barriers. Methodologically, we present and describe in detail a novel approach, drawing on GA that can be used to study PA in specific contexts. Practically, our study serves as a helpful point of reference for managers planning or implementing PA in Italy, for benchmarking PA in Italy over time and for comparative international studies.

The purpose of this study is to add to the currently limited research on individual level people analytics (PA) adoption by focusing on a vital resource in the implementation of PA, namely the technology used for PA. We draw on the unified theory of acceptance and use of technology (UTAUT) to examine antecedents of the use of technology for PA.

This study uses latent profile analysis to examine how different antecedents of PA (technology) adoption jointly act among 279 users of a specific PA technology.

This study identifies four user profiles, that we labeled the skeptic diplomats, the optimistic strugglers, the optimists, and the enthusiasts. These profiles relate to differences in user satisfaction and the frequency and versatility of PA technology use. This study demonstrates that performance benefits, social influence, required effort, and facilitating conditions jointly affect the use of PA technology, but that the latter two might be the most influential factors.

This study offers recommendations to practitioners and organizations on which actions by managers and the organization can be taken to support the use of PA technology.

Compared to previous research, we take a different approach by applying latent profile analysis to examine the combined effect of antecedents on user behavior and user satisfaction. In addition to a different analytical approach, we also extend existing research on individual PA adoption by focusing on actual behaviors and behavioral intention.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.

The research paper aims to analyse the scholarly literature on advancing HR analytics as an intervention for attrition, a problem that lingers on organisational performance. This study aspires to provide an in-depth literature review and critically assess the knowledge gaps in HR analytics and attritions within organisational performance.

The review analyses the corpus of 196 research articles published in ostensible journals between 2011 and 2023. To identify research gaps and provide valuable insights, this study synthesises relevant studies using School of thought (S), Context (C), Methodology (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) (SCM-TBFO framework). This study employs the R programming language to conduct a systematic literature review in accordance with the “preferred reporting items for systematic reviews and meta-analysis” (PRISMA) guidelines.

The emerging discipline of HR analytics encompasses the potential to manage attrition and drive organisational performance enhancements effectively. The study of SCM-TBFO encompasses a multidimensional approach, incorporating diverse perspectives and analysing its complex aspects compared to various approaches. The School of thought includes the human capital theory, expectancy theory and resource-based view. The varied research contexts entail the USA, United Kingdom, China, France, Italy and India. Further, the methodologies adopted in the studies are artificial neural networking (ANN), regression, structure equation modelling (SEM) case studies and other theoretical studies. HR analytics and attrition triggers are data mining decision systems, forecasting for firm performance and employee satisfaction. The barriers include leadership styles, cultural adaptability and lack of analytic skills, data security and organisational orientation. The facilitators were categorised into data and technology-related facilitators, human resource policies and organisational growth and performance-related facilitators. The study's primary outcomes are technology adoption, effective HR policies, HR strategies, employee satisfaction, career and organisational expansion and growth.

The primary goal of the literature review is to provide a comprehensive overview of the current state of HR analytics and its impact on organisational performance, particularly in relation to attrition. Further, the study suggests that attrition, a critical organisational concern, can be effectively managed by strategically utilising HR analytics and empowering data-driven interventions that optimise performance and enhance overall organisational outcomes.

Building upon the cognition-affect-behavior (CAB) model and script theory, this research aims to enrich the existing literature on historic town tourism consumption by offering empirical evidence of how the cognitive and affective images of historic towns contributes to tourists' memorable tourism experiences (MTE) and revisit intention, while identifying the cognitive image dimensions that are relevant for evaluating historic towns.

An on-site survey was conducted with 486 local tourists who visited the historic towns in Chengdu. partial least squares-structural equation modeling (PLS-SEM) was utilized to assess both the measurement and structural models.

(1) Cognitive image emerged as a significant predictor of affective image; (2) Both cognitive image and affective image had a positive influence on MTE, in which cognitive image played a more dominant role in shaping MTE; (3) MTE was found to strongly predict revisit intention among tourists; (4) MTE and affective image mediated the relationship between cognitive image and revisit intention.

This research highlights the value of incorporating cognitive and affective constructs in predicting MTE, and the proposed integrated framework of the CAB model and script theory exhibits superior predictive power in understanding tourists' revisit intention.

This research provides empirical insights about how historic towns improve their marketing strategies as short day-trip destinations.

This research provides a novel insight on the applicability of an integrated model combining the CAB model and script theory in explaining the revisit behavior of local tourists within the context of historic towns.

Scholars have been sounding the alarm of novice teacher turnover crises for decades. South Africa is soon to be facing an educational catastrophe because of a shortage of experienced teachers. Globally and in South Africa, novice teacher attrition is high, and teachers entering the classroom often described feeling isolated and unsupported.

This qualitative study was underpinned by an interpretative phenomenology approach. The author reviewed the literature and newly emerged findings of novice teacher mentoring support needs through the theoretical lens of the Ubuntu philosophy “I am because we are” which emphasises the importance of interconnectedness and community. Using semi-structured interviews, this study aimed to explore novice teacher mentoring needs from an Ubuntu perspective.

Novice teachers report feeling overwhelmed with the complexities of teaching in their early careers and express the desire to be formally mentored by a knowledgeable “elder” teacher. This paper argues that a competent mentor who values Ubuntu in their mentoring could offer collaboration, respect, compassion and support to novices that may keep them in the profession. This paper further explores the potential benefit of a prescribed Ubuntu-orientated mentoring programme to formalise mentoring for novices. In addition, it explores the school micro-community from the Ubuntu principles to support novices.

While there is a plethora of studies about mentoring novice teachers, literature from an Africanised Ubuntu perspective is scarce. Perhaps the time has come to find African solutions to our African problems.

Image change through visit experience with a destination is a common assumption, yet with rare empirical support to date. Thus, this study treats destination image as an interactive system of cognitive and affective components that are dynamic and changing through the course of an experience with a destination.

This longitudinal study tracks the change in images of 162 European visitors to the Gran Canaria Island one month before a two-week trip, on the last day of the trip, one month after the trip, and one year after the trip. A one-way repeated-measures analysis of variance with Bonferroni post hoc tests was conducted to evaluate the change in visitors’ cognitive, affective, or holistic images of Gran Canaria Island.

The Gran Canaria Island’s one-month post-visit image was more positive than the pre-visit image reflecting an improvement because of visitation. However, this improvement did not last long since the one-year post-visit image was not as positive as the one-month post-visit image. Surprisingly though, principle component analysis revealed more factors with more image items in the pre-visit image, whereas post-visit image factors were fewer in numbers and more generic, reflecting a reduction of details in the image after the visit.

This study is one of the very few efforts that contribute empirical evidence for the role of visitation in destination image evolution. It focuses on the pre and post-visit changes in the cognitive image and pre-, during, and post-visit changes in affective and overall images of a tourist destination in Europe.