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The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

The authors examine the effect of split environmental, social and governance (ESG) ratings on information asymmetry, corporate value and trading behavior. The authors test the risk-based hypothesis and the optimism-bias hypothesis on the relationship between diverging opinions and future stock prices. The authors results show that split ESG ratings is positively related to idiosyncratic volatility, an alternative measure for information asymmetry. Further, the negative effect of split ESG ratings on cumulative abnormal return under short-selling constraints is consistent with the optimism bias hypothesis. The authors find a negative relationship between split ESG ratings and the net purchase ratio (NPR) of pension funds. Considering that the NPR is a direct measure of net demand, ESG disagreement may hinder socially responsible investing (SRI) in a firm. This study directly demonstrates the negative effect of ESG disagreement on firm value and investment by Korea's National Pension Service (NPS). The results offer valuable insights into policymakers, as the wide divergence in ESG ratings requires urgent attention to expand SRI.

The purpose of this paper is to investigate the relationship between a company’s environmental, social and governance (ESG) performance and its financial performance. This paper also investigates the relationship between ESG performance and a company’s market valuation. This paper provides convincing empirical evidence that delivering superior ESG performance pays off financially.

The financial data and ESG scores of 150 publicly traded companies listed in the Standard and Poor’s 500 index for 2017–2020, comprising 5,750 observations, were collected. STATA was used to run a fixed-effect regression and a weighted least squares model to analyze the panel data.

The results of the empirical analysis suggest that companies with superior ESG performance perform better financially and are valued higher in the market compared to their industry peers. The ESG rating score impacts both return-on-capital-employed as a proxy for financial performance and Tobin’s Q as a proxy for the market valuation of a company.

This study contributes to the existing research on ESG performance and financial performance relationship by providing empirical evidence to resolve confusion in the existing literature caused by contradictory evidence. Taking advantage of worldwide crisis caused by the COVID-19 pandemic, this study shows that a positive relationship between ESG performance and a company’s market valuation holds even during times of unexpected crises. Further, this study contributes to business practitioners’ knowledge by showing that ESG aspects constitute highly relevant non-financial information that impact the market’s perception of a company and that investing in sustainability positively impacts a company’s bottom line.

The purpose of this study is, first, to determine which developments have shaped official hotel classification systems over recent years (including the impact of guest-review platforms) and second to establish the future of those systems through the eyes of the people who are actually in charge of operating them.

Semi-structured interviews were chosen as the most suitable method for approaching hotel classification system administrators. This method is in line with previous research on approaching key informants in their respective fields. Sixteen people representing 12 different official national hotel classification systems from across the world as well as one commercial hotel star rating system participated in the online interviews.

The first main conclusion is that hotel classification systems – especially voluntary ones – would not have survived the enormous impact of guest-review platforms without quickly adjusting to the ever-changing hotel industry landscape. The frequent review of classification criteria and procedures has become the main survival strategy of classification systems. The second conclusion is that system operators are strongly optimistic about the future outlook of hotel classification based on their proven flexibility to swiftly adapt to new market conditions.

Research about hotel classification systems is usually based on the views of the systems' users, i.e. hotels or hotel guests, whereas the present paper reflects the perspective of the systems' operators, an angle rarely analyzed in the literature.

This study aims to examine whether the internal locus of control, self-esteem and leadership self-efficacy can predict differences in self–other rating agreement on leader effectiveness. First, the authors predicted that the greater the internal locus of a leader the more their self-rating will be in agreement with others' rating of them (1a). Second, the authors proposed that the greater the self-esteem of a leader the more their self-rating will be in discrepancy with others' rating (1b). Third, the authors hypothesized that the greater the self-efficacy of a leader the more their self-rating will be in agreement with others' rating (1c).

To test the hypotheses, multisource data were collected from 128 banking leaders (who responded about different aspects of leadership self-efficacy, internal locus of control, self-esteem and leadership effectiveness) and 344 subordinates (who rated their leaders' effectiveness in performing leadership tasks).Multivariate regression was performed by jointly regressing both leaders' self-ratings and subordinates' ratings as a dependent variable on internal locus of control, self-esteem and leadership self-efficacy as predictor variables.

Self-esteem of a leader the more their self-rating will be in discrepancy with others' ratings.

The study tried to investigate the leader-subordinate dis(agreement) on leaders’ effectiveness taking banking leaders in the Ethiopian Context. The finding of the results is crucial and important for leadership development programs.

This paper investigates the effects of information asymmetry and Credit Rating Agency's reputation on bond yield spread, which is caused by the split bond rating of CRAs. For analysis, We do multivariate analysis, using bond rating and bond yield spread data in Korea from 2004 to 2015. The empirical results are as follows.

First, we examines whether information asymmetry affects the bond yield spread. using split rating data. As a result, the information asymmetry measured by split rating variable is significant, which supports the information asymmetry hypothesis. Additionally we can find bond yield spread is decided by negative credit grade rather than positive credit grade under split rating condition.

Next, we examines the relationship between the CRA’s reputation and the bond yield spread in case of split rating. Here, samples were divided into full samples and split rating samples. Summarizing the result, both samples are suggest similar result, the bond yield spread is changed depending on the specific CRA’s grading which having conservative rating tendency.

Thus, This result suggest information asymmetry caused by split rating and CRA’s reputation measured by CRA’s rating tendency affect bond yield spread in Korea

The credit ratings issued by the Big 3 ratings agencies are inaccurate and slow to respond to market changes. This paper aims to develop a rigorous, transparent and robust credit assessment and rating scheme for sovereigns.

This paper develops a regression-based model using credit default swap (CDS) data, and data on financial and macroeconomic variables to estimate sovereign CDS spreads. Using these spreads, the default probabilities of sovereigns can be estimated. The new ratings scheme is then used in conjunction with these default probabilities to assign credit ratings to sovereigns.

The developed model accurately estimates CDS spreads (based on RMSE values). Credit ratings issued retrospectively using the new scheme reflect reality better.

This paper reveals that both macroeconomic and financial factors affect both systemic and idiosyncratic risks for sovereigns.

The developed credit assessment and ratings scheme can be used to evaluate the creditworthiness of sovereigns and subsequently assign robust credit ratings.

The transparency and rigor of the new scheme will result in better and trustworthy indications of a sovereign’s financial health. Investors and monetary authorities can make better informed decisions. The episodes that occurred during the debt crisis could be avoided.

This paper uses both financial and macroeconomic data to estimate CDS spreads and demonstrates that both financial and macroeconomic factors affect sovereign systemic and idiosyncratic risk. The proposed credit assessment and ratings schemes could supplement or potentially replace the credit ratings issued by the Big 3 ratings agencies.

The purpose of this paper is to provide an insight in the future of hotel rating. It reviews the impact of social media, technology that provides integration of data for the consumer and the hotels, and the way that rating bodies may respond to the changing environment on how hotels are selected and reviewed.

By reviewing current trends, practices and technological possibilities, the impact of online reviews on conventional hotel rating systems is projected into the future.

The paper predicts a full integration of conventional rating systems with online guest reviews from the different guest review platforms leading to greater transparency for the consumer and better positioning opportunities for innovative hotels. It is further predicted that those conventional rating systems that do not seek integration and alignment will see a continued drop in hotel participation and will cease to exist.

Little research has been done on the relation between online guest reviews and conventional hotel rating systems. The paper presents new insights into how current and future trends influence the way in which consumers select hotels and how this influences the way that hotels are rated.

The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers.

Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms.

The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews.

The authors did not analyse data across demographic details because of access restriction policies of the websites.

Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously.

This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers.

This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

This study aims to develop a Sharīʿah-compliance rating mechanism for the Islamic financial services industry (IFSI), with a special focus on banking. The banking sector is taken as the area of focus due to its leadership role in the volume of global Sharīʿah-compliant assets.

The objectives of the Islamic financial system (IFS) are selected as the basis for ratings. A range of performance indicators (leading to achievement of the objectives) is grouped into four broader categories and used in the study to allocate scores with a sum total of 100. Special considerations – including the amount of resources required in performing an activity, suitability of prevailing business conditions, the degree of compulsion/discretion in performing a task and linkage with the essence of the IFS – were taken into account in the allocation of scores.

This study groups multiple performance measures into four categories, including portfolio construction (deposits mechanism, participatory and asset-based modes of financing), access to finance (service to the less-privileged and sector screening), reputation (disclosures and stakeholders’ survey) and Sharīʿah governance (Sharīʿah supervision and controls, charitable operations, human resources, product development and organization). The Portfolio, Audit, Reputation and System (PARS) rating system is then developed.

A Sharīʿah-compliance rating system is helpful in measuring the progress towards goal achievement of the IFS and in gaining stakeholders’ trust. It is also important for Sharīʿah boards and regulators in policy formulation, for management in addressing weaknesses and taking corrective measures and potentially for standard-setting bodies.

This study presents a comprehensive quantitative Sharīʿah-compliance rating mechanism, taking into consideration the objectives of the IFS – equitable distribution of wealth and financial stability, in addition to Sharīʿah-compliance in operations. Development of Sharīʿah-compliance quality ratings for Islamic banking is essential to gain customers’ trust; the suggested methodology is thus a contribution to the literature on Islamic finance.