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This study aims to investigate whether CEOs who graduated from prestigious universities can provide a better-quality working environment.

Using a sample of 1,877 observations from all companies listed on the Indonesia Stock Exchange from 2019–2021, this research employs logistic OLS and coarsened exact matching (CEM) analyses to ensure robust results.

This study revealed that companies with CEOs who are alumni of a reputable university provide a high-quality working environment. These results are robust using the coarsened exact matching (CEM). Additional analyses exploring subindicators of working environment quality revealed that CEOs who have received an education from a reputable university have a better understanding of the importance of continuous education and training.

The findings of this study can provide guidance for managers and decision-makers in managing human resources and the work environment more effectively. By understanding the impact of high-quality education on leadership abilities in creating a supportive work environment, companies can be more strategic in recruiting and developing their leaders.

This study provides a unique contribution by providing empirical data on the quality of the working environment in Indonesia, specifically focusing on the role of CEOs from a reputable university as policy-makers, which has not been extensively explored in previous research.

The aim of this paper is the validation of a scale that has Emotional Intelligence (EI) and Internal Marketing (IM) as determinants of organizational success.

The survey (questionnaire) allows assessing the contribution of motivation and job satisfaction to organizational success and was disseminated on social networks and directly in some national institutions.

The results of this research suggest that the 58 items of the scale can be grouped into eight main dimensions and can be confidently applied to professionals from organizations and companies operating in Portugal.

Furthermore, this study can be considered as an innovative, effective and useful tool for entrepreneurs, managers and organizations, as it can help diagnose the perceptions of their employees and promote a healthy and appealing environment, moving towards an excellent organizational performance, greater profitability and corporate sustainability.

Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively designing and managing a single-supplier multi-retailer cold chain for fresh produce with deterministic demand to minimize the total cost, which includes cooling, loss of value and carbon emission costs.

The global stability index (GSI) method and the non-Arrhenius model are integrated to describe the behavior of food quality degradation. The power-of-two (PoT) policy is adopted in determining the coordinated replenishment policies for the suppliers and retailers, and an appropriate wholesale price structure that can achieve the coordination of the chain is presented.

The properties of the cold chain are uncovered, and an appropriate wholesale price scheme that achieves chain coordination with the optimal PoT decision is provided. In the numerical examples, different scenarios are investigated, and it is found that the cold chain parameters influence the optimal decisions in certain ways.

The PoT policy – an efficient policy to determine the replenishment strategy – has not been adopted in finding the solution of a single-supplier multi-retailer cold chain in the literature. Also, no study has compared the uncoordinated and coordinated cold chain. Moreover, in the existing literature, the wholesale price is usually a constant rather than having a coordinated scheme. This research aims to fill these research gaps.

This study investigates the association between board gender diversity and multiple directorships, two board characteristics representing human, social and relational capital and the extent to which corporate reporting (using the double materiality principle) explains value creation for the organization, environment, society and the economy, which we define as total value reporting.

This study uses a disclosure index developed based on the Integrated Reporting Framework and the Global Reporting Initiative (G4) guidelines to analyze disclosures made using the double materiality principle and reflect the value created by companies. The sample includes corporate reports of 102 Australian Securities Exchange (ASX) companies in the Health Care sector. Ordinary least squares regression analyses test the relationship between board gender diversity and multiple directorships and the quality of total value reporting (and its subcomponents) with appropriate control variables.

Findings reveal that human, social and relational capital formed through multiple directorships and gender-diverse boards is positively related to the quality of total value reporting. Results hold for alternative measures and sensitivity tests of gender diversity and multiple directorships.

Our study reveals that (1) the <IR> Framework, when combined with the GRI Framework, effectively measures connected information quality under a double materiality perspective for total value reporting; (2) enhancing board effectiveness for total value reporting is achievable by increasing female directors and those with multiple directorships; (3) limitations in accessing experienced directors, particularly women, do not disadvantage countries like Australia and (4) directors holding multiple board positions are pivotal in disseminating best practices in corporate governance and reporting across various companies and industries.

Our research reveals that gender diversity on corporate boards transcends mere representation, significantly enhancing how firms articulate their value to stakeholders. This finding underscores the urgency for public policies to advocate for increased female board representation. Additionally, our findings indicate that board diversity, encompassing gender, experience, industry background and cultural perspectives, can elevate transparency in reporting, crucial for attracting global investors, particularly in emerging markets.

Our study is an early attempt to examine total value reporting – underpinned by double materiality – which reports on how companies create value for themselves, the environment and society. It is one of the first to identify drivers of reporting based on double materiality.

The aim of this chapter is to develop a conceptual model for the analysis of sustainable development and the ranking of cities based on selected standard criteria and metrics of smart cities. The conceptual framework contains standard and measurable indicators that influence the creation and survival of smart cities that could be self-sustaining, Green Resilient. We can measure the level of smartness of cities from two perspectives, first from the point of view of the degree of automation of services, infrastructure, buildings, transport, etc. and second from the point of view of planning the further development of the city in order to raise the quality of life of its citizens. Indicators should satisfy the principles of specificity, measurability, availability, relevance and timeliness (Schomaker, 1997). Researchers in the field of smart cities define different sets of characteristics, on which they construct a system of indicators that together describe the degree of development of a smart city. It must be taken into account the fact that there is no single set of indicators that would refer to the level of smartness of the city. It is a complex phenomenon, which occurs differently depending on the conceptual framework and the goal of classifying cities according to the complex characteristics of smartness, especially if you take into account the fact that the general well-being and quality of life of citizens are more important than only indicators of the quality of city services.

The purpose of this paper is to investigate the impact of size, asset quality, asset management, financial risk, gross domestic product and inflation rate on the financial performance of companies listed on the Jakarta Islamic Index of 30 industrial firms.

Based on the selected criteria, this study analysed an unbalanced panel of data from 30 industrial companies on the Indonesian capital market that are members of the Jakarta Islamic index. Profitability is measured using the dependent variables return on assets (ROA), return on equity (ROE) and stock prices. The influence of explanatory variables of internal factors, namely, size, asset quality, asset management, financial risk, gross domestic product and inflation is investigated using pooled OLS, fixed and random effect estimation.

The empirical findings indicate that the scale of a company has a significant impact on its performance, asset quality, asset management and financial risk. GDP has a substantial impact on financial performance, particularly as measured by ROA and ROE. This study’s ramifications have substantial effects on a broad spectrum of stakeholders. The results of this study provide the general public and investors with a greater understanding of the factors that influence a company’s performance on the Jakarta Islamic Index 30.

The implication of this research is that a deeper comprehension of the factors that influence the financial performance of companies within industrial sectors that follow Islamic finance principles can help design more effective strategies and policies.

This research has significant practical implications in a number of crucial areas. First, it provides a comprehensive comprehension of the company’s financial performance in the industrial sector in accordance with Islamic finance principles. Second, the research findings provide more precise guidance on how company size, asset quality and macroeconomic variables influence the performance of Indonesia's financial market.

The study’s authenticity and value hold considerable importance. This study introduces novel perspectives on the assessment of corporate financial performance within industrial sectors through the lens of Islamic finance principles. It offers valuable insights that have not yet been extensively investigated by scholars in the field.

This research aims to examine the relations between Shariah compliance and earnings quality.

The authors study three Shariah features: Shariah compliance status, level of Shariah compliance (H-Score) and Shariah compliance persistence. The sample consists of 463 firms from the Middle East and North Africa from 2011 to 2018. A variable determining the level of Shariah compliance was created in accordance with the methodology of S&P 500 Shariah and its underlying index, S&P 500. Then, a probate relapse study was created to identify the link between Shariah compliance and earnings quality.

Results show that Shariah-compliant firms engage in lower earnings management compared to their Shariah-non-compliant counterparts. This paper reveals that Shariah compliance status and high level of Shariah compliance have significant positive association with earnings quality. The authors also find novel evidence that persistence of the Shariah-compliant status has a significant negative association with earnings quality.

This study only examines firms listed on MENA stock markets. It is recommended to further study different markets in addition to the emerging Arab markets in order to compare and contrast the results. Further, larger sample observations from a greater date range can be used.

Few studies have examined the earnings management behavior of Shariah-compliant firms vs Shariah-non-compliant ones in emerging markets; however, no study has focused on Shariah-compliant firms and their level of Shariah compliance. To the best of our knowledge, this is the first study which uses all four proxies for earnings quality in association with Shariah compliance and used new Shariah variables such as Level of Shariah Compliance and Persistent Shariah Compliance status.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.