COVID-19 and business renewal: Lessons and insights from the global airline industry

The emergence of the COVID-19 pandemic has adversely affected the fortunes of multiple companies around the globe. Accordingly, questions are increasingly being asked about how organizations can revitalize during and after a crisis. Yet, we have limited understanding of how organizations renew themselves during crises over time. We explore this question through the lens and examination of two South-Asian airlines: Pakistan International Airlines and Sri Lankan Airlines. The cases offer important insights into the reasons behind underperformance of state-controlled enterprises and renewal activities. We shed light on strategic renewal (SR) in the wake of increasing liberalization and deregulations in the global airline industry. To this end, we propose a four-stage approach towards renewing such underperforming organizations to respond effectively to black swan events and external shocks.     

Dynamic linkages among equity markets in the Middle East and North African countries

The relaxation of security laws and regulations in emerging markets in the Middle East and North Africa (MENA) provides abundant opportunities for foreign investors. These markets exhibit high-expected returns and substantial volatility. In this paper, we investigate the lead/lag relationship between the MENA countries and regions. We find no market causality or spillover from one country to another in the North Africa region. Our results for the Levant region reveal that there are linkages between stock markets in this region. The results for the Gulf Cooperation Council (GCC) region show that there is more interaction and linkage in the GCC region than in the North Africa and Levant regions. An unexpected result is that UAE's stock market leads all the markets in this region. Finally, we investigate linkages among the three regions. We find that GCC influences the other two regions.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Sustainable resource use,economic development,and public regulation

The role of production technology for sustainable economic growth and resource management in the multispecies renewable resources industries is a neglected issue, particularly in complex tropical ecosystems. Given the still rudimentary understanding of biological interactions among species, even in most temperate ecosystems, the importance of under-standing the technological and economic interactions is heightened for sustainable economic growth and public regulation. This paper evaluates these interactions for the multiproduct gill net fisheries of Peninsular Malaysia. Standard price and quantity controls may have little promise. Gear regulations, a policy of constant escapement, and managing the entire mix of species as a single stock for economic rather than biomass yield appear the most promising management tools given the limited regulatory options.     

Market based price support program: an alternative approach to large scale food procurement and distribution system

In most developing countries of the world, large scale public food procurement and distribution systems (PFDS) have become too expensive for the country governments to support from their own resources. Despite high financial and administrative costs of the programs, the degree of seasonal price stabilization and price support achieved through the activities remain quite low. Using the Bangladesh PFDS as a case study, this research indicates that considerable improvements in price support can be achieved by providing credit to the farmers immediately after the harvest. If the government procurement is reduced by 50 per cent in Bangladesh, and providing 150 per cent of the cost of running PFDS as credit, Bangladesh can improve the farmers' income and achieve better stability of cereal prices at a cost less than one-third of the current costs of the PFDS.     

A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.     

Vicarious warfare and dynamic efficiency of companies in the aerospace and defence industry

This study explores the economic performance that vicarious warfare can bring for the aerospace and defence industry. First, this study measures the performance of 22 companies using a nonradial dynamic data envelopment analysis model from 2011 to 2017. Second, this study evaluates whether vicarious warfare can influence the performance. The efficiency analysis suggests rooms for improvements meanwhile, the projection analysis suggests that market value should be significantly increased, and the number of employees should be reduced significantly. The regression analysis suggests that the number of times a country takes a side in wars would positively affect the efficiency of companies.     

The relationship between laissez-faire leadership and burnout: Mediation through work alienation and the moderating role of political skill

We tested the relationship between laissez-faire leadership and job burnout and the mediating role of work alienation in this relationship. We also examined the moderating role of political skill in the relationship between laissez-faire leadership and burnout. Based on time-lagged (three waves, two months apart) survey data collected from 272 employees in 92 firms operating in China, our results showed that laissez-faire leadership was positively related to burnout both directly and via work alienation. Moreover, the positive relationship between laissez-faire leadership and burnout was contingent on political skill, such that the relationship was weak when political skill was high. The study provides useful suggestions to help managers curb employees' feelings of burnout and work alienation.     

Corporate commitment to climate change action,carbon risk exposure,and a firm's debt financing policy

Motivated by the rising consensus that corporate engagement in climate change actions holds the key for society's transition into environmentally resilient economy, the study examines whether a firm's commitment to climate change action and its carbon risk exposure shape the firm's debt financing policy. Based on insights drawn from signaling, corporate reputation, and agency theories, we develop models that link corporate commitment to climate change actions and a firm's carbon risk exposure with its debt financing decisions. Using data drawn from S&P 500 companies, for years 2015 to 2019, we find a robust evidence that firms that engage in higher levels of commitment to climate change actions issue a higher proportion of debt with longer terms to maturity, even after controlling for their carbon risk exposure. However, we do not find a robust evidence corroborating an association between firms' carbon risk exposure and their debt financing policy. These findings are consistent with arguments that high-commitment firms enjoy positive reputation, better credit rating, and reduced agency and information asymmetry costs, allowing them to gain easier access to long-term debt markets.