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Studies in corporate social responsibility (CSR) disclosure were initially focused more on disclosure “Quantity” than “Quality” and while they have started to explore “Disclosure Quality”, their assessment mechanisms are found to be immature. Thus, while a number of papers have sought to assess the quality of CSR disclosure, this paper aims to suggest an approach tied closely to both expectations in assessing “quality” derived from the Conceptual Framework for Financial Reporting (revised 2018) and the global reporting initiative. The outcome is to offer a best practice approach to assessing CSR disclosure quality.

In this paper, prior literature is reviewed, qualitative characteristics from the Conceptual Framework for Financial Reporting (revised 2018) and globally recognised guidelines such as the GRI are reviewed. The framework for a “CSR disclosure quality index” as an assessment tool to assess CSR disclosure quality is developed from qualitative characteristics and criteria identified.

The proposed CSR disclosure quality index is developed in stages from the qualitative characteristics identified in the Conceptual Framework for Financial Reporting (revised 2018) and criteria identified from the guidelines discussed. A table was then developed linking the qualitative characteristics to criteria providing a Likert scale approach to assessing the disclosures made by companies to make an assessment of the quality of the companies’ reports. It is argued this provides a robust assessment, being a direct and comprehensive measure of disclosure quality.

As with most qualitative work, there are alternative approaches to establishing an index, but the authors believe this is an approach offering links (and, therefore, credibility) to globally recognised guidelines in the assessment of CSR disclosure quality. Future work could enhance the alignment of this index with the sustainable development goals (SDGs), building on the preliminary connections established in this study.

At a practical level this index offers an approach to reviewing the quality of CSR disclosures which could prove useful to policymakers and in the future development and expansion of this framework offering greater objectivity to assessments and justification for proposed improvement in reporting practice. Also, this index serves as a benchmarking tool for companies to meet the disclosure expectations of stakeholders.

This approach has the potential to substantially fulfil stakeholder expectations by addressing the growing demand for transparency in this area, while avoiding practices that could be perceived as superficial or misleading (greenwashing). Focusing on social issues enables stronger connections between companies and their stakeholders. Furthermore, the index helps companies link their CSR efforts with SDGs and show their commitment to long-term social value building in discussion of governance factors to show accountability expectations are being met.

This paper contributes to CSR disclosure quality literature and provides a reliable method of assessing the quality of CSR disclosures. Opportunities for further and broader developments can be envisaged while offering a credible and reliable approach.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

The purpose of this paper is to provide a systematic literature review on Shariah governance and Islamic banks.

The literature was searched from Scopus and Web of Science using various queries related to Shariah governance and Islamic banks. Through a screening process, 93 articles were considered fit for the systematic literature review.

The paper provides a systematic review based on different themes, including measurement of Shariah governance in Islamic banks, disclosure of Shariah governance and its determinants, the impact of Shariah governance on performance, risk management and other outcomes of Islamic banks. Finally, issues and challenges of Shariah governance in Islamic banks are discussed, followed by conclusions and recommendations related to future research.

This study is the first of its kind, to the authors’ knowledge, to provide a comprehensive systematic literature on Shariah governance and Islamic banks by exploring different themes and highlighting multiple future avenues of research.

Since 1960s it has been realized that the bilateral trade at international level cannot be explained solely by the classical and neoclassical models of trade based on inter-industry trade. There is an existence of export and import within the same industry among the trading partners. Intra-industry trade (IIT) for products and product groups has been empirically observed by several studies. However, there is not much literature available on IIT in services. So also, from country perspective many studies are based on IIT for advanced countries. There is not much empirical evidence available for IIT among the emerging economies. The study aims to analyze the IIT in tourism services for five major emerging economies constituting BRICS – Brazil, Russia, India, China, and South Africa. The group constitutes 41% of world population with 24% of world GDP and 16% share in world trade. The study used both static and dynamic approaches to measure the IIT between India and other BRICS nations between 2018 and 2020. To empirically estimate the IIT, the study employs Grubel and Lloyd index and Brülhart index (MIIT). The study reveals that India had a very high level of intra-tourism trade with Brazil and South Africa. While with China and Russian Federation it was moderate. Results denote a correlation between the theory of international trade and tourism. There is two-way trade in BRICS tourism flows.

This study was conducted to review the overview of green growth and examine the role of financial inclusion as well as economic integration and other variables on green growth in Association of Southeast Asian Nations (ASEAN) countries.

Principal component analysis (PCA) was used to construct financial inclusion variables and panel data regression analysis to examine the effect of financial inclusion and economic integration on green growth in 10 ASEAN countries from 2010 to 2021.

The results showed that financial inclusion had played a role in supporting green growth in ASEAN. The rapid development of green finance and green bonds promoted the implementation of better green growth. The variables of export diversification and trade openness had a significant effect on green growth. Therefore, there is a need for appropriate policies to prevent negative effects on the environment and the behavior of ASEAN countries.

The findings of this study suggest that policymakers in ASEAN countries not only focus on gaining economic benefits from financial inclusion and economic integration activities but also pay attention to environmental impacts. Moreover, the ASEAN region is actively developing strategic steps in providing easy access to capital and finance as well as expanding international trade activities through ASEAN Free Trade Area (AFTA). Therefore, it is hoped that apart from being able to establish sustainable policies, this region will also encourage and optimize previous policies to make them more environmentally friendly.

This study used a green growth approach with the Index by the Global Green Growth Institute. This index considered aspects of green economic opportunities and social inclusion that have not been applied in previous studies. In addition, this study contributed to review the activities of economic integration and financial inclusion and the sustainability of green growth in ASEAN countries. Until now, there has been no research focused on ASEAN; even though ASEAN has long carried out economic integration and encouraged financial inclusion policies, this region is vulnerable to environmental degradation issues.

In today’s knowledge-based economy, companies are hugely driven by intangible resources such as intellectual capital. However, whether corporate governance of a company drives intellectual capital is less explored in emerging economies. We examine the impact of intellectual capital efficiency on firm performance for Indian firms, considering the moderating role of board gender diversity.

We have created a framework for panel data analysis and conducted estimation using the dynamic panel data model to control for endogeneity and heteroskedasticity issues. We use alternate performance and gender diversity measures for our sample of top 500 listed companies for a period of six years, that is 2015–2020.

The results demonstrate a significant positive association between intellectual capital and performance. However, moderating impact of gender diversity on the relationship between intellectual capital and performance is not significant.

The findings indicate that IC plays a crucial role in a company’s performance, which may boost economic growth. Further, the findings reveal that despite the mandatory quota for women on boards in Indian companies, their impact on IC is subliminal. It may be because the critical mass is yet to be achieved, which should be considered by policy-makers while framing policies in this area.

Our study is one of the foremost studies to consider the impact of mandatory gender quotas while examining the association between tangible and intangible firm performance. It makes an incremental contribution to literature to enrich our understanding on the influence of gender diversity on intellectual capital-performance linkages.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This study aims to examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations.

Using the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence.

The inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market.

The paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

This study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.

To accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.

The empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.

This research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.