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This paper examines the effect of ESG ratings and its dimensions (environmental, social and governance) on the financial performance of JSE-listed firms included in FTSE/JSE Responsible Investment Index.

The paper employs panel data covering 40 JSE-listed firms included in FTSE/JSE Responsible Investment Index between 2015 and 2019. The paper employs the two-stage least squares (2SLS) instrumental variable regression technique to estimate the effect of ESG ratings and its dimensions (environmental, social and governance) on both accounting- and market-based performance indicators.

The results of the two-stage least squares instrumental estimation analysis reveal that investment in ESG initiatives improves both accounting- and market-based indicators of financial performance. Of the ESG pillars, the paper finds environmental initiatives improves firms' financial bottom line and market performance, while a firm's social and governance practices are observed to have no effect on a firm's accounting and market performance measures.

The insights from this study proffers policy implications for firms' management, investors and regulatory authorities.

As far as the authors are concerned, this paper presents the first empirical analysis on the contribution of ESG ratings on financial performance in South Africa.

This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of internal and external supervision.

The authors draw on a sample of Chinese non-financial A-share-listed firms from 2013 to 2020 to explore the effect of ESG ratings on leverage manipulation. Robustness and endogeneity tests confirm the validity of the regression results.

ESG ratings inhibit leverage manipulation by improving social reputation, information transparency and financing constraints. This effect is weakened by internal supervision, captured by the ratio of institutional investor ownership, and strengthened by external supervision, captured by the level of marketization. The effect is stronger in non-state-owned firms and firms in non-polluting industries. The governance dimension of ESG exhibits the strongest effect, with comprehensive environmental governance ratings and social governance ratings also suppressing leverage manipulation.

Firms should strive to cultivate environmental awareness, fulfil their social responsibilities and enhance internal governance, which may help to strengthen the firm’s sustainability orientation, mitigate opportunistic behaviours and ultimately contribute to high-quality firm development. The top managers of firms should exercise self-restraint and take the initiative to reduce leverage manipulation by establishing an appropriate governance structure and sustainable business operation system that incorporate environmental and social governance in addition to general governance.

Policymakers and regulators should formulate unified guidelines with comprehensive criteria to improve the scope and quality of ESG information disclosure and provide specific guidance on ESG practice for firms. Investors should incorporate ESG ratings into their investment decision framework to lower their portfolio risk.

This study contributes to the literature in four ways. Firstly, to the best of the authors’ knowledge, it is among the first to show that high ESG ratings may mitigate firms’ opportunistic behaviours. Secondly, it identifies the governance factor of leverage manipulation from the perspective of firms’ subjective sustainability orientation. Thirdly, it demonstrates that the relationship between ESG ratings and leverage manipulation varies with the level of internal and external supervision. Finally, it highlights the importance of governance in guaranteeing the other two dimensions’ roles by decomposing overall ESG.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

Relative performance evaluation (RPE) is a widely practiced employee appraisal process in the services industry. In a global delivery model, teams are spread across different geographical locations. The team members work on various tasks under the guidance of different managers and at times under more than one manager for performing the same task. Such complexities make RPE of the team members quite challenging. The paper proposes a methodical step-by-step approach to simplify the evaluation process without compromising on the rigour.

RPE has followed three different approaches. First is the traditional way, wherein evaluators had a common meeting to discuss and arrive at relative evaluation and ranking of members of the peer group employees. In the second, the number of evaluators and employees in a peer group were split in to 2 subgroups. The evaluators provided independent ratings and rankings. Simple mathematical tool then derived the combined ranking. In the third approach, each evaluator evaluated each employee in the peer group and provided the relative ranking for each employee. Again, mathematical tools provided the final ranking considering inputs from all evaluators. All the three evaluation approaches were analysed through an inter-rater agreement method.

All the three approaches for evaluation provided similar results giving confidence that less time-consuming methods could be adopted by evaluators without compromising on the rigour of the evaluation. The outcome of the exercise proved effective as the complaints reaching the ombudsmen reduced as compared to the earlier years. Considerable evaluation time was also saved. The study described in this paper is carried out in a non-unionized, Indian private sector services firm. Its effectiveness in other set ups is yet to be tested.

The research is carried out in the Indian Engineering services firm operating in the Knowledge based sector. Though study results are encouraging, the adaptability of methodology across different sectors and geographies is yet to be tested. More broad based studies are needed to evaluate suitability across firms and regions.

Relative evaluation exercise is challenging for evaluators. Although openness in evaluation is desired, it also makes evaluators uncomfortable in appearing to be taking sides or being opposing a candidate's ranking. The proposed approach brings in anonymity to each evaluator without scarifying individual evaluation.

The proposed methodology can be deployed across different services industries as the proposed methodology is business domain agnostic. It can be easily ported and tailored to align with an individual organization's evaluation philosophy. The suitability and effectiveness of the method can be studied under various types of firms like manufacturing, private, public, NGO, labour oriented, etc. As the proposed method reduces efforts, the stake holders can focus on understanding the relation between employee performance measurement, employee engagement, and long-term outcomes related to employee performance evaluation.

The proposed employee evaluation method leverages inter-rater reliability and agreement tool as a consensus approach to the relative performance ranking exercise. Such an approach to relative performance ranking is original as no prior studies with such an approach are found in the existing Literature.

This study aims to explore the human resource management (HRM) practices related to training and feedback in the app work industry, specifically in online food delivery service, and investigate the emotional and behavioral responses of gig workers.

This study adopts a qualitative approach by interviewing 19 gig workers from six food delivery firms operating in different countries.

The results show limited training and feedback opportunities are provided to app workers, although the complexity of training and delivery methods differ across platforms. To address this shortage, app workers developed response strategies relying on social interaction.

This study adds to the research on HRM practices in the gig economy by portraying the way in which training and feedback unfold in the food delivery app ecosystem and by disclosing the gig workers’ emotional and behavioral responses to it.

This study shows that the way training activities are currently designed may provide little value to the ecosystem and are likely to produce negative emotional responses in gig workers. Thus, platform providers may make use of these findings by introducing more transparent feedback and social learning opportunities.

To the best of the authors’ knowledge, this study is among the first empirical studies on online delivery gig workers addressing specific HRM practices. It reveals significant insights for training and feedback, suggesting app economy characteristics strongly affect training and feedback practices for app workers.

Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources while providing quality service at an affordable price, and minimizing chances of stock-out, avoiding serious consequences on the illness or fatality of the patients. Presence of both qualitative and quantitative evaluation criteria, set of potential suppliers and participation of different stakeholders with varying interest make healthcare supplier selection a challenging task which can be effectively solved using any of the multi-criteria decision making (MCDM) methods.

To deal with various qualitative criteria, like cost, quality, delivery performance, reliability, responsiveness and flexibility, this paper proposes integration of grey system theory with a newly developed MCDM tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) to identify the best performing supplier for pharmaceutical items in a healthcare unit from a pool of six competing alternatives based on the opinions of three healthcare professionals.

While assessing importance of the six evaluation criteria and performance of the alternative healthcare suppliers against those criteria using grey numbers, and exploring use of three normalization procedures and two aggregation operations of MACONT method, this integrated approach singles out S5 as the most compromised healthcare supplier for the considered problem. A sensitivity analysis of its ranking performance against varying values of both balance parameters and preference parameters also validates its solution accuracy and robustness.

This integrated approach can thus efficiently solve healthcare supplier selection problems based on qualitative evaluation criteria in uncertain group decision making environment. It can also be deployed to deal with other decision making problems in the healthcare sector, like supplier selection for healthcare devices, performance evaluation of healthcare units, ranking of physicians etc.

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.

This paper aims to analyze the synergistic influence of performance appraisal (PA) practices and performance-driven culture (PDC) on the effectiveness of the performance management (PM) system, which is measured by employees' reactions, namely satisfaction and perceived utility. It also analyzes the type of relationship between PA practices and PA satisfaction, specifically whether it is additive or modeled as a latent factor.

This is a cross-sectional study. Data were collected from 513 managers and employees working in 135 public and private organizations. The research model and hypotheses were tested using structured equation modeling.

The results support the positive impact of a set of four PA best practices on PA satisfaction. It shows that PDC is an enabler for the effective deployment of PA practices. It also demonstrates that the perceived utility of the PM system plays a role as a mediator in the relationship between PA practices and PA satisfaction.

Data were collected using a questionnaire at a single point in time, and thus, cause-and-effect inferences were not possible.

The results provide guidance to organizations that are interested in designing and implementing PM systems and PA practices that contribute toward enhancing employees' managing performance experiences.

This study advances our understanding of the mechanisms by which organizational culture and PA practices influence the effectiveness of the PM system. It suggests that organizations, to benefit the most from a set of PA best practices, need to have a PDC.

This conceptual work examines how, in times of post-COVID-19 paradigm shift, the employee performance management (PM) process can help multinational corporations (MNCs) strengthen their talent management and, at the same time, meet their future needs.

We take a conceptual approach and present our perspective on what we see as the most critical trends shaping PM and talent management. Contingency theory and Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) theory provide a sound theoretical framework for understanding and responding to the complex and rapidly changing business context post-COVID-19.

Drawing on these theories, we create a framework providing a means of understanding why and how MNCs can maintain talent and, at the same time, develop new talent through the PM process.

Importantly, our study emphasizes the critical role that project management and talent management techniques play for both practitioners and scholars. In order to gain and sustain a competitive edge in the ever-changing VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) landscape, these processes necessitate ongoing reassessment and adaptation. As Plato eloquently stated, “Our Need Will Be the Real Creator,” encapsulating our vision for the proactive and dynamic nature of effective project management and talent management practices.

The study establishes the benefits of an agile and flexible PM approach to help develop talent and pave the way for future research in this increasingly critical area

Emotional intelligence (EI) has a profound effect on the performance of tour guides, though past studies on the subject have neglected to examine the effects of EI on neither the overall nor specific pattern of tour guides' performance. This study examines the overall link between four dimensions of EI (self-emotion appraisal [SEA], others' emotion appraisal [OEA], use of emotions [UOEs] and regulation of emotions [ROEs]) and five dimensions of citizenship performance (helping, self-development, initiative, compliance and adaptability), ultimately identifying the relationship between EI factors and each dimension of tour guides' citizenship performance.

The data from 244 Jordanian tour guides were gathered through a quantitative survey. A confirmatory factor analysis (CFA) and multiple regression analysis were performed to analyze the data.

The results reveal that emotionally intelligent tour guides are more likely to have higher levels of citizenship performance. The most significant factors in determining extra-role behaviors by tour guides are “UOEs” and “others’ emotion appraisal (OEA)”.

This study equips different professional entities in the tour guide industry with useful, contextualized links between EI and citizenship performance. This assists in developing new accreditation policies and business practices to augment tour guides' citizenship professionalism, thereby maximizing their valuable contributions to tourism growth.

This study advances the tourism studies by establishing a new theoretical link between tour guides' EI and citizenship performance. The study also uncovers unique factors of EI that significantly determine tour guides' citizenship behaviors.