ABSTRACT
The paper presents the results of forecasts made for the volume of steel production in Poland based on actual data for the period from 2006 to 2021 with forecasting until 2026. The actual data used for the forecasts included annual steel production volumes in Poland (crude steel) in millions of tons. Basic adaptive methods were used to forecast the volume of steel production for the next five years. When selecting the methods, the course of the trend of the studied phenomenon was taken into account. In order to estimate the level of admissibility of the adopted forecasting methods, as well as to select the best forecasts, the errors of apparent forecasts (ex post) were calculated. Errors were calculated in the work: RMSE Root Mean Square Error being the square root of the mean square error of the ex-post forecasts yt for the period 2006-2021;? as the mean value of the relative error of expired forecasts y*t (2006-2021) - this error informs about the part of the absolute error per unit of the real value of the variable yt. Optimization of the forecast values was based on the search for the minimum value of one of the above-mentioned errors, treated as an optimization criterion. In addition, the value of the point forecast (for 2022) obtained on the basis of the models used was compared with the steel production volume obtained for 3 quarters of 2022 in Poland with the forecast for the last quarter. Forecasting results obtained on the basis of the forecasting methods used, taking into account the permissible forecast errors, were considered as the basis for determining steel production scenarios for Poland until 2026. To determine the scenarios, forecast aggregation was used, and so the central forecasts were determined separately for decreasing trends and for increasing trends, based on the average values of the forecasts obtained for the period 2022-2026. The central forecasts were considered the baseline scenarios for steel production in Poland in 2022-2026 and the projected production volumes above the baseline forecasts with upward trends were considered an optimistic scenario, while the forecasted production volumes below the central scenario for downward trends were considered a pessimistic scenario for the Polish steel industry.
ABSTRACT
The transition to sustainable food systems is one of the main challenges facing national and international action plans. It is estimated that food services and lodging accommodation activities are under pressure in terms of resource consumption and waste generation, and several tools are required to monitor their ecological transition. The present research adopts a semi-systematic and critical review of the current trends in the food service and lodging accommodation industries on a global scale and investigates the real current environmental indicators adopted internationally that can help to assess ecological transition. This research tries to answer the subsequent questions: (i) how has the ecological transition in the food service industry been monitored? and (ii) how has the ecological transition in the lodging accommodation industry been monitored? Our study reviews 66 peer-reviewed articles and conference proceedings included in Web of Science between 2015 and 2021. The results were analyzed according to content analysis and co-word analysis. Additionally, we provide a multidimensional measurement dashboard of empirical and theoretical indicators and distinguish between air, water, energy, waste, health, and economic scopes. In light of the co-word analysis, five research clusters were identified in the literature: “food cluster”, “water cluster”, “consumers cluster”, “corporate cluster”, and “energy cluster”. Overall, it emerges that food, water, and energy are the most impacted natural resources in tourism, and users and managers are the stakeholders who must be involved in active monitoring.
ABSTRACT
Supply chain sustainability, which takes environmental, economic, and social factors into account, was recently recognized as a critical component of the supply chain (SC) management evaluation process and known as a multi-criteria decision-making problem (MCDM) that is heavily influenced by the decision-makers. While some criteria can be analyzed numerically, a large number of qualitative criteria require expert review in linguistic terms. This study proposes an integration of Data Envelopment Analysis (DEA), spherical fuzzy analytic hierarchy process (SF-AHP), and spherical fuzzy weighted aggregated sum product assessment (SF-WASPAS) to identify a sustainable supplier for the steel manufacturing industry in Vietnam. In this study, both quantitative and qualitative factors are considered through a comprehensive literature review and expert interviews. The first step employs DEA to validate high-efficiency suppliers based on a variety of quantifiable criteria. The second step evaluates these suppliers further on qualitative criteria, such as economic, environmental, and social factors. The SF-AHP was applied to obtain the criteria’s significance, whereas the SF-WASPAS was adopted to identify sustainable suppliers. The sensitivity analysis and comparative results demonstrate that the decision framework is feasible and robust. The findings of this study can assist steel industry executives in resolving the macrolevel supplier selection problem. Moreover, the proposed method can assist managers in selecting and evaluating suppliers more successfully in other industries.
ABSTRACT
The purpose of this study is to analyze the economic ripple effects caused by the supply-side reforms on China’s steel industry. To this end, using the 2012 and the 2017 China Input–Output Tables, this study analyzes the economic ripple effect of the Chinese steel industry caused by its supply-side reform. In this study, the influence coefficients (rear-linked effect) and the sensitivity coefficients (forward-linked effect), conceptualized by Leontief, are used as research tools to analyze the ripple effects of the Chinese steel industry. The analysis results are as follows. First, the fact that 2012 ranked high in professional equipment and meter manufacturing shows that the Chinese government’s supply-side reforms are effective and creating the required shift from traditional manufacturing to qualitative growth. Second, in terms of the sensitivity coefficient, in 2012, most of the top industries contributed significantly to the development of the Chinese economy. The originality of this study is as follows. The input production analysis used in this paper is a methodology mainly used in the steel, coal, automobile, and petrochemical industries, which clearly distinguishes the front and rear industries. Additionally, this study is a novel attempt at comparative research on the Chinese steel industry between 2012 and 2017.