Scientific publications

The Belt and Road Initiative (BRI) is expected to boost the economic and technological cooperation among the participating countries. In this paper, we argue that the economic and environmental efficiency can be used as measures identifying the best practice in the BRI. However, the results of the analysis may be affected by perturbations in the data and outlying observations. The outliers may lead to biased policy implications. Unlike previous research, this paper compares economic and environmental performance in developing countries using both convex and nonconvex production technologies based on a nonparametric framework.

The outbreak of the COVID-19 pandemic has exposed the power of social media in the dissemination of information. The current pandemic has hurt not only social media users but also on state's sustainable development. As a result, the present study seeks to understand the reasons for using social media during the COVID 19 pandemic by screening various topics and assessing the impact of misinformation on social media, primarily psychological and mental effects. The study utilized a quantitative research design. Participants were individuals between the age of twenty and fifty. Data was collected using a questionnaire shared online to the 360 participants.

Improving green innovation efficiency (GIE) is crucial for attaining sustainability in China’s stage of high-quality development. However, there is a paucity of research on the roles of and links among the government and market in GIE. This study bridges this research gap by unifying marketization, local government competition, and GIE into one empirical framework. First, we extend a super-efficiency Ray slacks-based measure model to evaluate provincial GIE in China during 1997-2018 and then analyze its evolution of spatial-temporal dynamics. Subsequently, marketization, local government competition, and GIE are incorporated into a nest of spatial panel models to address the endogeneity concerns resulting from model misspecification and omitted variables.

The purpose of this study is to analyze the influence of Corporate Social Responsibility (CSR) on a firms’ sales growth and to assess the mediating role of competitive advantage and the moderating role of the employee’s individual belief of social responsibility (SR) on the relationship between CSR and sales growth of small and medium enterprises. A survey of 107 small and medium enterprises (SMEs) in the consumption and manufacturing industry of a developing country was performed.

Productivity analysis has been an important avenue for economic research. Therefore, medleys of quantitative techniques have been proposed to operationalize productivity analysis. In this article, an extended by‐production model is discussed and applied to ensure a link between the production and the pollution‐generating subtechnologies.

Farmers operate in a changing market, policy and social environment so questions arise as to how they experience these changes and react in their business orientation. This topic was examined in the period 2011 to 2016 in a strongly fluctuating product market and food policy environment, e.g., abolition of milk quotas in Europe. The study was based on unique panel data for 290 dairy farms in Poland, Slovenia, Lithuania and The Netherlands, questioned up to three times in 2011, 2013 and 2016. The conceptual framework was composed of Farmer goals, Resources, Opportunities and Threats (O&T), and Future expectations (performance) as continuous variables, and countries and strategy farmer groups as categorical variables.

The goal of the current study is to highlight the factors that could affect retail food prices and develop an econometrical model for estimating the level of the impact of the identified factors. The research covers the period from 2016 to 2018. Multiple regression modelling is used for model creation. The outcomes mad available evidence that the factors mostly affecting the prices are the monthly average price of food product and yield of the agricultural subsector providing main stock for the food product.

Decarbonization of heating sector is an important part of the global low carbon energy transition, and an essential step towards implementing climate change mitigation commitments as this sector accounts for 40-50 % of global energy consumption and is one of the main sources of greenhouse gas (GHG) emissions. In addition, this sector is sensitive in terms of energy vulnerability and energy poverty. The aim of this paper is to develop a set of indicators and evaluation tool for assessing sustainability of the heating sector at national level and to apply developed methodology for comparative assessment in selected North European countries.

The objective of this research was to forecast the sectorial energy consumption of Pakistan for five fiscal years, i.e., from FY18 to FY23 using two different time series techniques and explore the causal relationship between total energy consumption and its sectorial components, and Gross Domestic Product (GDP). The study further analyzed the efficiency of two different time series models, such as the Autoregressive model (AR with seasonal dummies) and Autoregressive Integrated Moving Average model (ARIMA/ARMA). In any economy, forecasting energy consumption and its relationship with GDP is paramount to ensure the economic development and fiscal policies.

Bioenergy is a kind of renewable energy that can potentially contribute to a broad spectrum of economic, environmental, and societal objectives and aid sustainable development. The assessment, management, and monitoring of the diverse bioenergy production technology alternatives are complex in nature and deliver different benefits due to the lack of precise and comprehensive data. Selection of an optimal bioenergy production technology (BPT) alternative is considered a complex multi-criteria decision-making (MCDM) problem that involves many incompatible tangible and intangible as well as qualitative and quantitative criteria. The procedure of defining and evaluating the weights of the criteria is an important concern for decision experts because the assessment and the final selection of the BPT alternative are carried out on the basis of the defined set of criteria. Intuitionistic fuzzy sets (IFSs) have received considerable attention due to their ability to handle the imprecision and vagueness that can arise in real-life situations.