International Journal of Industrial Engineering & Production Research

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Drawing lessons from the Covid-19 pandemic according to literature, this contribution aims to show that greening the United Nations System with stronger environmental considerations, can help to shift the global economy from fossil energy to renewable energy with public-health resilient systems. This contribution starts with highlighting the fact that past economic crises and the implementation of the Sustainable Development Global Agenda have not been able to generate strong institutional arrangements for sustainable development including climate resilience building and public health resilient systems. This allows us to apprehend the possibility that the Covid-19 pandemic crisis may face the same incapacity. In response to these statements, this contribution shares the opinion that institutional reforms within the United Nations System may lead to perennial normative provisions and institutional arrangements able to make sustainable development happen with resilient public-health systems. This note highlights the fall of GHZ emissions during the Covid-19 pandemic. It shows, however, based on the history of the past crisis, that the huge investment being mobilized to recover from the pandemic can quickly absorb GHZ emissions fall. The way out suggested is that both the Global Economy and the Global Public Health agendas can be revisited to be strengthened by stronger environmental considerations. One of our findings is that multilateralism can adopt suitable institutional arrangements in Global Environmental Governance throughout the current global agenda on International Environmental Governance Reform within the United Nations System.

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To respond to the urgent call for preventive action against COVID-19 pandemic implications for societies, this research is carried out. The main aim of our research is providing a new insight for the effects of the newly emerged restrictions by COVID-19 on the SD Goals (SDGs). This research applied a qualitative approach for supporting the SDGs achievement post-COVID in Iran, as a developing country in the Middle East, in two phases. In the first phase, using a fuzzy Delphi method, the SDGs affected by COVID-19 were identified. In the next phase, a fuzzy cognitive map, as a qualitative system dynamics modeling, was conducted to specify the key interconnections among the SDGs post COVID-19. Finally, three strategies including focus on people in vulnerable situation, support for industrial units and small and medium-sized enterprises, and national aggregation to Fight COVID-19 were examined. As a result, different scenarios associated with the three proposed strategies were tested based on the identified interconnections among the SDGs to reduce the potential negative effects of COVID-19 crisis on the achievement of the SDGs. The results provide a decision support for stakeholders and policy makers involved in SD action plan.

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In today's world, COVID-19 pandemic has affected many organizations. Pandemic issues have created financial and social problems for businesses. Crisis and risk management have a significant impact on reducing consequences of pandemics. Rapid response to risk enhances the performance of organizations in times of crisis. Therefore, a framework to provide risk treatment in a pandemic crisis seems essential. To do this, this paper presents a framework to identify risk factors posed by pandemics. In this regard comprehensive risk factors by considering sustainability concept are illustrated for university. Then, identified risk factors are evaluated by best–worst methodology (BWM) and then the important risks are recognized. Using the importance of risk and the strengths and weaknesses of the business, solutions to reduce the impact of risk are suggested to managers. The results of this paper can be used in order to enhance resiliency of the organization in front of the pandemics from social and financial viewpoints.
 

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This research paper aims to examine the impact of the COVID-19 pandemic on consumer behaviour and the strategic adjustment implemented by small to medium-size businesses. Consumer behaviour has been altered. It has made organizations react to survive. To understand emerging consumer behaviour, and how organizations mitigate the changes in the environment, a qualitative study on small to medium size business owners was conducted in October-November 2020. An intensive 60-minute, semi-structured interview was conducted with 23 business owners in Jakarta and its surrounding cities. The findings revealed that there are positive and negative impacts of the COVID-19 pandemic on business depending on the industry type. The type of industry also influenced the scale of the effect. Regardless of the impact, most business owners were optimistic about their businesses surviving. Consumer behaviour changed to involving less human interaction, for example going online, and people became more cost-conscious. Business owners mitigated the change with a change in the type of products offered, offering promotions or price reductions and online access. From the business owners' perspective, some of the new behaviour will remain after the pandemic, whilst others will revert to the old behaviour. Those that offer convenience and simplicity will stay.

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The Coronavirus Disease 2019 (COVID-19) epidemic in China has been controlled periodically. However, we are now in a period of rapid outbreaks worldwide, the situation of epidemic prevention and control in all countries is still tense. Due to the COVID-19 outbreak, objectively, international trade has a higher risk of infection. At this stage, the prevention and control of the epidemic have become a responsibility for the countries worldwide. This study aims to measure the potential economic impacts of COVID-19 on trade volume between China and One Belt One Road countries (OBOR). The economic impacts assessments of (COVID-19) on trade are based on a Gravity model and speed of convergence (SC) method by changes in trading behavior and cost of (COVID -19) outbreak by in affected countries. The results reveal that potential trade values between China and European Union (EU) will drop by 11.5%, China and East Asia and Pacific (EAP) by 6,7%, China and the Middle East and North Africa (MENA) by 8.9%, China and South Asia (SAR) by15%, China and Europe and Central Asia (ECA) by 9%.

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Floating markets are not only a unique type of market but also sustainable tourist attractions. The literature focuses on both of floating market Covid-19 preventive measures and tourist’ satisfaction dimensions. The study is using quantitative research by concentrated on the tourist’s satisfaction of an anonymous Floating Market in Nakhon Pathom province. The research concentrated on the floating market Covid-19 preventive measures and the tourists’ satisfaction. The visitors certainly got great enjoyment from the floating market and this resulted in overall good experience for them better than most of them expected. The most important of Covid-19 preventive measures factors for the tourists were the provide clear entry, exit routes and screening point, merchants and customers always wear masks and provide hand washing points. The tourism component clearly overshadowed the destination shopping experience. The close proximity of the market to Bangkok contributes to the success of this market and the perceived satisfaction of the tourists
 

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The COVID-19 pandemic forced Malaysian Higher Education Institutions to pursue online and distance learning. This study aimed to gain insight into the pre-university students’ acceptance and intention to use the Microsoft Teams (MS Teams) application for online learning platforms during the pandemic. This group of students was chosen because they had just finished high school and their transition from the school system to the university system with online learning will pose many difficulties. The theoretical framework for this study was developed using the Technology Acceptance Model (TAM) with additional facilitating conditions and computer self-efficacy as the external elements. The participants were 180 pre-university students from Universiti Kuala Lumpur Malaysian Institute of Information Technology who had experience using MS Teams during their first semester. With SPSS, the predictive factors on the acceptance of students toward online learning have been explained. The findings also indicate that the proposed TAM-based scale successfully explained the factors predicting intention to use MS Teams during the pandemic. The findings assist researchers and practitioners in developing a more comprehensive view of pre-university students’ acceptance and intention to use MS Teams. Finally, several recommendations have been made, including the implications and limitations of the study at the end of this paper to reference future research.
 

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This paper proposes a data-driven method, using Artificial Neural Networks, to price financial options and compute volatilities, which speeds up the corresponding numerical methods. Prospects of the Stock Market are priced by the Black Scholes model, with the difference that the volatility is considered stochastic. So, we propose an innovative hybrid method to forecast the volatility and returns in Stock Market indices, which declare a model with a generalized autoregressive conditional heteroscedasticity framework. In addition, this research analyzes the impact of COVID-19 on the option, return, and volatility of the stock market indices. It also incorporates the long short-term memory network with a traditional artificial neural network and COVID-19 to generate better volatility and option pricing forecasts. We appraise the models' performance using the root second-order quadratic function means of the out-of-sample returns powers. The results illustrate that the autoregressive conditional heteroscedasticity forecasts can serve as informative features to significantly increase the predictive power of the neural network model. Integrating the long short-term memory and COVID-19 is an effective approach to construct proper neural network structures to boost prediction performance. Finally, we interpret the sensitivity of option prices concerning the market or model parameters, which are essential in practice.

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