In this paper, we conduct an empirical study on the impact of CEOs’ environmental awareness on technological innovation. To this end, we obtain a large sample with 7615 observations from Chinese A-share listed firms between the years of 2003 and 2014. Our empirical results show that a CEO’s environmental awareness has a significant positive impact on technological innovation of his/her enterprise. Environmentally conscious CEOs will invest more in R&D and obtain more patents. This will help their enterprises achieve higher efficiency of technological innovation. Furthermore, the environmental awareness of a CEO has a more significant impact on technological innovation if his/her enterprise is subject to a higher level of monitoring. We also conduct robustness check of our findings and provide managerial insights and proactive government policies to raise the environmental awareness of CEOs and improve the innovation vitality of enterprises.

This paper analyzes the impact of the COVID-19 pandemic on the mental health of the teachers, specifically the techno stress arising in them as a result of issues faced by them in the use of technology when they conduct the online academic activities. It aims to assess the major factors related to the online teaching that specifically adds to techno stress on the teachers during the COVID-19 outbreak. Finally, the study aims to provide suggestions to the policymakers and the management of the universities so that the effect of the COVID-19's on teachers' mental health and the related techno stress can be reduced. This paper is a literature review of the articles on the notion of techno stress on teachers and their mental health by searching the related articles with these terminologies using the renowned search engines of Google Scholar and Web of Science. A combination of the terms such as Coronavirus, COVID-19, mental health, psychological distress, techno stress, and online teaching were used in the article search for the review. The literature has suggested that the COVID-19 outbreak has significantly affected the mental health of the employees in general and specifically, the teachers who are engaged in online academic activities and teaching in the universities. The paper has identified a few factors that are the cause of the techno stress and provides recommendations for the university management and the policy makers for minimizing their negative impact on the teachers, in terms of the techno stress and their mental health. Coronavirus is a new strain of the viruses that has badly engulfed the entire population of the world. It is even now badly rising and causing deaths while this article is in the writing phase. The article has addressed the mental health concerns of the university teachers as they are now working from home using ICT for delivering the lectures and conducting the online teaching and learning activities for the students at their universities. This is a matter of grave importance now and requires immediate attention. Hence, this article broadens the scope of the research on the corona virus and its impact on the university teachers.

The green vehicle routing problem is a variation of the classic vehicle routing problem in which the transportation fleet is composed of electric vehicles with limited autonomy in need of recharge during their duties. As an NP-hard problem, this problem is very difficult to solve. In this paper, we first propose a memetic algorithm (MA)—a population-based algorithm—to tackle this problem. To be more specific, we incorporate an adaptive local search procedure based on a reward and punishment mechanism inspired by reinforcement learning to effectively manage the multiple neighborhood moves and guide the search, an effective backbone-based crossover operator to generate the feasible child solutions to obtain a better trade-off between intensification and diversification of the search, and a longest common subsequence-based population updating strategy to effectively manage the population. The purpose of this research is to propose a highly effective heuristic for solving the green vehicle routing problem and bring new ideas for this type of problem. Experimental results show that our algorithm is highly effective in comparison with the current state-of-the-art algorithms. In particular, our algorithm is able to find the best solutions for 84 out of the 92 instances. Key component of the approach is analyzed to evaluate its impact on the proposed algorithm and to identify the appropriate search mechanism for this type of problem.

In the study of the “Porter Hypothesis”, scholars explored the impact of different forms of innovation on the firms’ competitivity, but did not distinguish between innovations on the difference in patent quality. In addition, relevant research only regards innovation as a mediator between environmental regulation and competitivity, and doesn’t take into account innovation induced by environmental regulation, can only promote competitivity under the constraints of environmental regulation. That is to say, environmental regulation not only induces innovation, but also moderates innovation to promote competitivity. In view of this, we use panel data of A-share listed firms in China from 2006 to 2016, and adopt propensity score matching and different in different (PSM-DID) model to empirically test the inductive effect and moderating effect. The results show that CETS cannot only improve the quantity and quality, but also significantly enhance the firms’ market value; innovation itself cannot enhance the firms’ market value, but the interaction with CETS can promote the firms’ market value. In addition, the CETS has a stronger inductive effect on innovation of state-owned shares firms, but the positive moderating effect on high-quality innovation and competitivity only exists in non-state-owned shares firms.

The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.