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As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.

To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.

This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.

The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.

A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.

The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.

In Structural Equation Modelling (SEM) cases, a number of steps to ensure that the measurement of the latent constructs, variables, and indicators have been appropriate, reliable, and meet the rules of quantitative research that must be passed by researchers. One of them is the criteria for determining the presence (or not) of a discriminant validity violation, which is still a fierce debate among researchers today. The last recommended method is the Heterotrait–Monotrait ratio of correlation (HTMT) which seeks to revise the previously existing discriminant validity criteria such as the Fornell–Larcker and Cross-loadings criteria. This chapter discusses the implementation of HTMT in the case of manufacturing small and medium enterprises (SMEs) in Indonesia with the aim of providing an illustration of how the HTMT is capable of detecting the violation of discriminant validity and the solutions that can be carried out following the recommendations given by the originators.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

The main purpose of this study is to examine the impact of different dimensions of institutional quality indices on the economic growth of Sub-Saharan African (SSA) countries.

The study uses a panel data set of 31 SSA countries from 1991 to 2015 and employs a two-step system-GMM (Generalized Method of Moments) estimation technique.

The study's empirical results indicate that investment-promoting and democratic and regulatory institutions have a significant positive effect on economic growth; however, once these institutions are taken into account, conflict-preventing institutions do not have a significant impact on growth.

The study's findings suggest that countries in the region should continue their institutional reforms to enhance the region's economic growth. Specifically, institutions promoting investment, democracy and regulatory quality are crucial.

Unlike previous studies that use either composite measures of institutions or a single intuitional indicator in isolation, the present study has employed principal component analysis (PCA) to extract fewer institutional indicators from multivariate institutional indices. Thus, this paper provides important insights into the distinct role of different clusters of institutions in economic growth.

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

The tightening of environmental measures and policies in various countries around the world is forcing manufacturing companies, particularly those that make up the automotive industry, to improve their production processes, through the implementation of approaches such as lean production (LP) and Industry 4.0 (I4.0) technologies, to reduce industrial waste. However, the literature indicates that the implementation of LP and I4.0 does not always lead to an improvement in the level of operational performance (OP). Therefore, this study analyzes the effects of the implementation of LP practices and I4.0 on a green supply chain (GSC) and the operational performance of manufacturing companies in the Mexican automotive industry.

A theoretical research framework consisting of six hypotheses was developed and validated by applying partial least squares structural equation modeling (PLS-SEM) and using a sample of 460 companies from the Mexican automotive industry.

The results show that the level of OP of manufacturing companies increases substantially with the implementation of LP and I4.0 practices, as well as a GSC.

Managers of manufacturing companies will be able to use the results of this study to improve their production systems and to demonstrate the effects of these practices on OP.

This study contributes to the literature on LP and I4.0 by providing robust empirical evidence of the positive effects of implementing these approaches on the GSC and OP of manufacturing companies.

The objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.

The use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.

In the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.

The description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.

本文旨在探討在歐洲、創新與人工智能和數字技術的發展之間的關係。研究人員透過一個綜合指數、去探討歐洲公司之間數字技術的使用狀況。至於創新與人工智能之間的關係, 則以對數線性回歸模型來進行研究。從模型所得的結果, 為我們提供了建議、去訂定適切的經濟和產業政策。

研究人員透過一個人工智能和資訊科技的綜合指數, 去探討歐洲企業之間數字技術的使用狀況 (研究人員使用了公平和可持續福利方法論), 其目標為測量領土差距, 以及確定哪些歐洲國家、大體上傾向於使用數字技術;至於創新與人工智能之間的關係, 則以對數性回歸模型來進行研究。

本文使用了兩個不同的方法、去探討在歐洲、創新與數字技術發展之間的關係。有關的合成指標, 使研究人員可製定一個不同國家間的分類法;而有關的對數線性模型, 則讓研究人員可確立並說明創新的決定因素。

本文使用了合成指標和對數線性模型、去探討創新與人工智能之間的一對一的關係, 這是時下受到關注和適宜的課題;就研究法而言, 本研究確是新穎獨創的。

Infrastructures become critical with the emerging threats triggering through disasters. Sri Lanka is a country with a higher risk of disaster impacts, in which the eye-opening has widened towards mitigating the damages towards critical infrastructures. Based on this, the purpose of this paper is to develop an index that identifies the significance of critical infrastructure resilience.

From the initial literature survey, disaster resilience is defined as capacity of three stages, absorptive, adaptive and restorative along with ten indicators to measure capacities. Selected indicators were then checked for suitability for scope of the research based on opinions of seven experts. Subsequently, the critical infrastructure resilience index (CIRI) was introduced such that the numerical values for each indicator are aggregated using the Z score method. Statistical relations between the actual impact against disasters and CIRI calculated for administrative regions in Sri Lanka were used as the final step to validate the developed index.

Resilience index development is presented in this paper with a comprehensive methodology of developing and validation. Further, the case study results imply the weakness and strengths in each resilience capacities, which are important in decision-making.

Unavailability of disaster impact data and centralized data repository were main constrains in the validation process of this research. Hence proxy data was used to validate resilience index in this research.

This research identified and validated a novel approach of defining disaster resilience index for regional decision-making.

This study investigates the impact of corporate social responsibility (CSR) on corporate innovation. We selected the listed nonfinancial firms of South Asian Economies. The sample of the study comprised a total of 426 listed manufacturing firms of South Asian Countries for period spans 10 years from 2012 to 2021. In this study, descriptive statistics, multicollinearity diagnostic tests, correlation analysis and two-step dynamic panel system generalized method of moments (GMM) were applied to analyze the data. CSR measured with three proxies' social indicators, environmental indicators, and CSR composite index of social and environmental indicators. However, corporate innovation is captured with number of citations received in a year and number of patents filed in the year. Overall, findings of the study using all measures of CSR shows that CSR significantly and positively related with corporate innovation. Our results find support for CSR-innovation view with all measures of CSR. The findings suggest that the current study is helpful for managers, regulators, policymakers, and researchers. For managers, the study helps them to make the CSR and innovation decision. The policymakers should take appropriate innovative decision while considering factors such as CSR. This study can also be extended by considering this study for developed and emerging economies sample.

This study aimed at exploring the differential effects of different corporate governance (CG) indicators on risk management practices in Islamic financial institutions (IFIs) and conventional financial institutions (CFIs) of Pakistan. It also investigated the moderating role of institutional quality (IQ) in shaping the effects of CG practices on financial institutions of Pakistan.

A sample of 57 financial institutions including commercial banks, insurance companies and Modarba companies over the period 2006–2017 is used to carry out the empirical analysis. The authors applied the robust two-step system-generalized method of moments estimator, which is also called the dynamic panel data estimator. They also built the PCA-based composite index of CG and IQ by using different indicators to investigate the moderating role of IQ. They used three proxies for risk taking, five for CG and one for Shari’ah governance. To test the validity of the instruments, they applied the Arellano and Bond’s (1991) AR (1) and AR (2) tests and the J-statistic of Hansen (1982).

The results provided strong evidence that several individual characteristics of CG and the composite index are significantly related to the operational risk, the liquidity risk and the Z-score (a proxy for solvency risk). The results also revealed that IQ significantly and substantially contributes in reducing the level of risks. Finally, the estimation results indicated that the effects of CG on risk management are significantly different at IFIs and CFIs. This differential impact is mainly attributed to the fundamental differences in business models, operational strategies and contractual obligations of both types of institutions.

The findings of this study are important for enhancing our understanding of how CG relates to risk taking in Islamic and conventional financial services industries and how good quality institutions are important for formulating the governance effects on the risk-taking behavior of financial institutions. The findings suggest that a suitable size of board should be chosen to manage the risk effectively. As the findings show that the risk-taking behavior of IFIs differs from that of CFIs, the regulators and international standard setting bodies should tailor the regulatory frameworks accordingly.

This paper is different from the existing studies in four aspects. First, to the best of the authors’ knowledge, this is the first empirical investigation in Pakistan, which does the comparison of IFIs and CFIs while examining the impacts of CG on risk management. Second, the paper constructs the composite index of CG by considering several different indicators of governance and examines the combined effect of governance indicators on risk management process. Third, this paper adds to the growing literature on the role of IQ by investigating whether it acts as a moderator between CG structures and risk management and if yes, then whether this moderating role is different for IFIs and CFIs. Finally, the paper builds upon the existing research work on the CG effects for different types of financial institutions by proposing a single regression based analytical framework for comparing the effects across two different types of institutions, harvesting the benefits of higher degrees of freedom and avoiding/minimizing the measurement error.