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This paper examines the time-varying efficiency of nine major Middle East and North Africa (MENA) stock markets namely Egypt, Bahrain, UAE, Jordan, Saudi Arabia, Oman, Qatar, Morocco and Tunisia during times of COVID-19 pandemic outbreak and vaccines.

The authors use two econometric approaches: (1) autocorrelation tests including the wild bootstrap automatic variance ratio test, the automatic portmanteau test and the Generalized spectral test, and (2) a non-Bayesian generalized least squares-based time-varying model with statistical inferences.

The results show that the degree of stock market efficiency of Egyptian, Bahraini, Saudi, Moroccan and Tunisian stock markets is influenced by the COVID-19 pandemic crisis. Furthermore, the authors find a tendency toward efficiency in most of the MENA markets after the announcement of the COVID-19's vaccine approval. Finally, the Jordanian, Omani, Qatari and UAE stock markets remain globally efficient during the three sub-periods of the COVID-19 pandemic outbreak.

The results have important implications for asset allocations and financial risk management. Portfolio managers may maximize the benefit of arbitrage opportunities by taking strategic long and short positions in these markets during downward trend periods. Policymakers should implement the action plans and reforms to protect the stock markets from global shocks and ensure the stability of the stock markets.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

The study aims to test the success of university-industry (U-I) collaboration in terms of innovation process efficiency. Then, this study explores the moderating role of a set of organizational routines in the U-I relationship, which can help in overcoming the issues undermining the collaboration success.

The study is based on an international Open Innovation (OI) survey. The survey investigated the items to build the main variables of the conceptual framework, measured through seven-point Likert scales. Steps to ensure the reliability and validity of the variables were conducted. Then, hypotheses were tested with an ordinary least squares regression.

Results show that the higher the collaboration intensity (depth) with universities, the higher the innovation process efficiency. Furthermore, organizational routines aimed at improving firms' assimilation absorptive capacity further strengthen the positive effects of intensive collaboration on innovation process efficiency.

Findings indicate that R&D managers should strive to build deep collaborations with universities to enhance process efficiency and invest in the quality of these relationships. Managers should create and maintain an internal environment that further enhances the positive effects of intensive collaboration on innovation process efficiency.

The OI literature has not reached a shared view on the positive contribution of universities toward industrial firms' innovation performance. The study adopts a process-efficiency view, rarely used by other OI studies usually focused on output indicators; this study unpacks, respectively, the role of the intensity of collaboration and the organizational routines, thus disclosing the benefit of U-I collaboration on innovation efficiency.

This study aims to provide a comparative insight into the level of informational efficiency and irregularities of Shariah-compliant stocks and conventional stocks in three emerging markets, namely, China, Malaysia and Pakistan. The empirical evidence is provided for pre-crisis and crisis periods caused by the Covid-19 pandemic.

Informational efficiency is measured using the variance ratio (VR) Test developed by Kim (2006). The Approximate Entropy (ApEn) Metrics is used to investigate the level of irregularities in stock prices caused by the pandemic.

All the three emerging markets in the sample are not immune to the crisis caused by Covid-19 pandemic. The level of informational efficiency of both the Shariah-compliant and conventional stock is affected by the crisis. However, the former exhibits relatively high level of informational efficiency and stability in returns as compared to more volatility of conventional stocks.

This study provides market agents and policy makers with a robust assessment of the impact of the Covid-19 pandemic on informational efficiency of Shariah-compliant and conventional stocks. Relatively high informational efficiency of Shariah-compliant stocks indicates that they are more transparent and that investors can trust the Shariah-compliant stocks more. This higher level of transparency and trust leads to more steady returns and lower levels of risk even during turbulent time like Covid-19. Investors can gain superior returns by conducting fundamental analysis and investing in index funds.

To the best of the authors’ knowledge, this is the first study that highlights the difference in informational efficiency of conventional stocks and Shariah-compliant stocks in the crisis period caused by Covid-19. Unlike previous studies, this study uses firm level data which enables firm-wise assessment of informational efficiency.

The main purpose of this paper is to predicate financial distress using the worst-practice-frontier data envelopment analysis (WPF-DEA) model and artificial neural network.

In this study, a neural network technique was used to forecast inputs and outputs in the future time-period. Using a WPF-DEA model, financially distressed companies were identified based on the worst performance, and an improvement solution was provided for those decision-making units.

This study’s findings show that dynamic WPF-DEA has high predictability in corporate financial distress, and it can be used with high confidence. Based on the future time-period results, JOUSH & OXYGEN was predicted to be a financially distressed company in the two future time-periods.

In recent decades, globalization, technological changes and a competitive space have increased uncertainty in the economic environment. In such circumstances, economic growth certainly depends on correct decision-making and optimal allocation of resources. It can be done by introducing appropriate tools and models for assessing corporate financial conditions, including financial distress and bankruptcy.

The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

This study aims to benchmark the operational efficiency of fifty-eight public hospitals across Mexico between 2015 and 2018 and identifies the most critical inputs affecting their efficiency. In doing so, the study analyzes the impact of policy changes in the Mexican healthcare system introduced in recent years.

To measure the operational efficiency of Mexican public hospitals, data envelopment analysis (DEA) window analysis variable returns to scale (VRS) methodology using longitudinal data collected from the National Institute for Transparency and Access to Information (IFAI). Hospital groups are developed and compared using a categorization approach according to their average and most recent efficiency.

Results show that most of the hospitals in the study fall in the moving ahead category. The hospitals in the losing momentum or falling behind categories are mostly large units. Hospitals with initially low efficiency scores have either increased their efficiency or at least maintained a steady improvement. Finally, the findings indicate that most hospitals classified as moving ahead focused on a single care area (cancer, orthopedic care, child care and trauma).

This study examined the technical efficiency of the Mexican healthcare system over a four-year period. Contrary to conventional belief, results indicate that most public Mexican hospitals are managed efficiently. However, recent changes in public and economic policies that came into effect in the current administration (2018) will likely have long-lasting effects on the hospitals' operational efficiency, which could impact the results of this study.

To the best of authors’ knowledge, this is the first study that examines the efficiency of the complex Mexican healthcare system using longitudinal data.

Most economic growth is concentrated in the eastern and coastal provinces of China, while the western and central provinces have not yet experienced the expected economic growth. This study aims to address the following crucial research questions: Do the central and western provinces achieved potential efficiency in economic growth? Have China’s provinces used their resources effectively in implementing economic growth strategies?

The research design concerns the use of a panel dataset on province-specific economic growth in China over the years to 2000–2020. The methodology used was a stochastic frontier gross domestic product (GDP) model with time-varying technical efficiency over time. The approach uses the existing literature to identify the important variables influencing economic growth at the provincial level to model the stochastic frontier GDP model for empirical analysis.

This study concludes that the central provinces show the highest rate of efficiency in economic growth, though not 100%, followed by the Eastern and Western provinces. By increasing and improving skilled education institutes and intensifying supply chain opportunities through foreign direct investment (FDI), the central provinces achieving 100% growth efficiency may not be ruled out.

The modes of economic governance and policies to improve GDP growth have been rapidly changing from increasing incentives to improving competition. Thus, more unique avenues and expansion of the horizon for impending research on provincial, national and international macroeconomics would emerge that would make current methodologies of the growth analysis outdated.

The empirical analysis highlights the importance of improving skilled education institutes and intensifying supply chain opportunities through FDI for achieving sustained economic growth.

The empirical analysis facilitates finding ways to reduce income inequality across provinces in China.

To the authors' knowledge empirical analysis examining the Chinese province-specific economic growth efficiency explicitly has not been carried out using the recent Chinese panel dataset.

The purpose of this paper is to understand if and how industrialized house building (IHB) could support productivity developments for housebuilding on project and industry levels. The take is that fragmentation of construction is one explanation for the lack of productivity growth, and that IHB could be an integrating method of overcoming horizontal and vertical fragmentation.

Singe-factor productivity measures are calculated based on data reported by IHB companies and compared to official produced and published research data. The survey covers the years 2013–2020 for IHB companies building multi-storey houses in timber. Generalization is sought through descriptive statistics by contrasting the data samples to the used means to control vertical and horizontal fragmentation formulated as three theoretical propositions.

According to the results, IHB in timber is on average more productive than conventional housebuilding at the company level, project level, in absolute and in growth terms over the eight-year period. On the company level, the labour productivity was on average 10% higher for IHB compared to general construction and positioned between general construction and general manufacturing. On the project level, IHB displayed an average cost productivity growth of 19% for an employed prefabrication degree of about 45%.

Empirical evidence is presented quantifying so far perceived advantages of IHB. By providing analysis of actual cost and project data derived from IHB companies, the article quantifies previous research that IHB is not only about prefabrication. The observed positive productivity growth in relation to the employed prefabrication degree indicates that off-site production is not a sufficient mean for reaching high productivity and productivity growth. Instead, the capabilities to integrate the operative logic of conventional housebuilding together with logic of IHB platform development and use is a probable explanation of the observed positive productivity growth.

The aim of the research is to determine the influence of photovoltaic (PV) installation and the share of façade glazing on the energy profile of nursery buildings in the Baltic Sea region, as well as defining the most favorable configuration in terms of energy efficiency.

The article provides comparative calculations of energy performance indicators (Ep, Ed, Eu) and CO₂ emissions (mCO₂) made for the defined model of the nursery. It includes calculations concerning energy performance of the building, depending on its PV power (0–60 kWp), PV efficiency (100 and 85%) and façade glazing ratio (GR = 25%, 50% and 75%).

The results of the research indicate that an increase in the PV power exerts proportional impact on the reduction of the Ep and Ed indicators, as well as on the CO₂ emissions. Only low GR values (25%) reduce the Eu indicator significantly. Decrease in high range of GR values (over 50%) does not provide proportional effects. In the variant: 60 kWp (100% efficiency) with GR = 25%, the biggest share (99.5%) of RES was obtained. This proves that the concept of energy independent nursery buildings is feasible and reasonable in the examined location.

Designing buildings towards environmental neutrality requires laborious pre-design conceptual work before developing the right solutions. The set of results of the relationship between the variables of the building's envelope, energy performance indicators and the required involvement of active RES installations to achieve high energy performance of a building presented in the article is valuable. It allows for a preliminary decision of the direction of the design solutions selection in the design process of public utility buildings, such as nurseries. Thus, it may significantly shorten the pre-design analysis process for the location of the southern part of the Baltic Sea region.

The novelty of the paper relies on examining the dependences between PV power and façade glazing ratio in terms of their influence on energy profile of nursery buildings.