Sustainable Industrial Development Research Articles

Green supply chain for steel raw materials under price and demand uncertainty

The scientific formulation of procurement and inventory plans is an important topic in the steel industry, when considering both economic and environmental impacts in an uncertain market environment. Robust optimization methods offer an effective solution to this problem. This study has investigated a multi-echelon and multi-period front-end supply chain centered on a steel enterprise under uncertain purchase prices and demand. The goal is to minimize the costs associated with mining, processing, transportation, procurement, and inventory along with the corresponding carbon emission costs. To address this issue, we present a robust rolling horizon model (RRHM) that considers the inventory capacity constraints of steel enterprise and incorporates ore grade requirements. Subsequently, the RRHM was reformulated into a solvable mixed-integer linear programming model, and the relationship between the robust model and a specific deterministic model was established. Finally, the model was validated by generating instances based on real scenarios. The results demonstrate that the robust rolling horizon model proposed in this paper outperforms both the Sample Average Approximation (SAA) strategy and the (s, S) strategy in terms of cost and robustness. In addition, a sensitivity analysis of the key parameters was conducted. The findings reveal that the unit inventory, mining, and carbon emission costs have a limited impact on the total cost, highlighting the robustness of the model. These findings provide valuable insights into the green and sustainable development of the steel industry, enabling the formulation of effective strategies to mitigate the impacts of uncertainties.

Integrating Environmental Sustainability into Macroeconomic Frameworks: The Eco-Keynesian Cross

The ecological transition hinges on ecological structural change, necessitating smart macroeconomic policies. Incorporating ecological considerations into macroeconomic modelling constitutes a pivotal area of inquiry that examines the nexus between environmental sustainability and economic expansion. This article proposes a macroeconomic modelling to establish a foundational analytical framework to address this challenge. Incorporating ecological considerations into macroeconomic modelling constitutes a pivotal area of inquiry that examines the nexus between environmental sustainability and economic expansion. Contributing to the post-Keynesian Ecological Macroeconomics field, this paper proposes an eco-Keynesian cross due to its simplicity and widespreadness for teaching macroeconomics to illustrate the macroeconomic perspective of green targets strategies in a closed economy. Green public and private investments have the potential to enhance output through the multiplier effect and improve environmental efficiency. However, these investments may also induce rebound effects, resulting in a net increase in pollution intensity within the economy. The model underscores the potential trade-off between social and environmental objectives, which an ecological perspective seeks to surmount by advocating for sustainable and inclusive industrial development.

Development of a novel sustainable concrete from waste coconut shell with alccofine supplements

The infrastructure of a country depends significantly on cement concrete as the primary construction material. The aggregate comprises a significant proportion of the overall volume of concrete. However, the ongoing extraction of granite rock to obtain coarse aggregate contributes to the escalating need for natural resources among future generations. Due to its high carbon dioxide (CO2) footprint, the cement industry is a significant contributor to global warming. An appropriate reduction in the amount of cement in concrete without affecting its key properties can result in economical and sustainable development of the construction industry. In this investigation, agricultural waste coconut shell is considered as a substitute for conventional aggregate in concrete to produce lightweight coconut shell concrete. The alccofine-1203 contains ultrafine particles with a distinctive composition that enhances the pozzolanic and hydration process in concrete. Alccofine ranging from 5 % to 15 % were added to cement. The results demonstrated that the 10 % alccofine enhanced the fresh and mechanical properties of the lightweight coconut shell concrete. Using a combination of coconut shell and alccofine in concrete would be the most environmentally sustainable option in the construction industry.

The Impact of Offshore Photovoltaic Utilization on Resources and Environment Using Spatial Information Technology

In recent years, the rapid development of the photovoltaic (PV) industry has resulted in a saturation of research on onshore PV power plant construction. However, current studies on the impact of marine PVs on the marine environment remain limited and scarce. In order to facilitate the implementation of carbon reduction goals and promote the sustainable development of the offshore PV industry, this study analyzes the environmental impact of PV sea-use resources based on spatial information technology in the western part of Gaotang Island. The findings show that the MIKE21FM model provides relatively accurate simulations of tidal flow and tide level in the marine PV area. Flow velocity in the marine PV area exhibits a decreasing trend, with an average decrease ranging from 0.03 to 0.07 m/s. This decrease minimally affects surrounding navigational channels and large-scale flow fields. The resulting siltation is also deemed less significant, with an annual deposition from 0.03 to 0.06 m/a. Moreover, offshore PV construction resulted in a total intertidal biological loss of 123.45 t. The suspension of sediment during cofferdam construction and removal has a potential effect on zooplankton and fishery resources. Overall, it is proposed that careful planning, prudent site selection, and the execution of countermeasures during marine PV construction will combine to minimize the impact on the marine environment.

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

The extensive carbon emissions produced throughout the life cycle of buildings have significant impacts on environmental sustainability. Addressing the Carbon Emissions from China’s Construction Industry (CECI), this study uses panel data from seven coastal areas (2005–2020) and the Bayesian Optimization Extreme Gradient Boosting (BO-XGBoost) model to accurately predict carbon emissions. Initially, the carbon emission coefficient method is utilized to calculate the CECI. Subsequently, adopting the concept of a fixed-effects model to transform provincial differences into influencing factors, we employ a method combining Spearman rank correlation coefficients to filter out these influencing factors. Finally, the performance of the prediction model is validated using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R2) and Mean Absolute Percentage Error (MAPE). The results indicate that the total CECI for the seven provinces and cities increased from 3.1 billion tons in 2005 to 17.2 billion tons in 2020, with Shandong Province having the highest CECI and Hainan Province having the lowest. The total population, Gross Domestic Product (GDP) and floor space of the buildings completed passed the significance test, among a total of eight factors. These factors can be considered explanatory variables for the CECI prediction model. The BO-XGBoost algorithm demonstrates outstanding predictive performance, achieving an R2 of 0.91. The proposed model enables potential decisions to quantitatively target the prominent factors contributing to the CECI. Its application can guide policymakers and decision makers toward implementing effective strategies for reducing carbon emissions, thereby fostering sustainable development in the construction industry.

Evaluating Competitiveness of Container Shipping Operators in the Sustainability and Digitalization Era

This study aims to comprehensively analyze the operational status and international competitiveness of global container shipping enterprises in the era of sustainability and digitalization within the field of international container transportation. Utilizing the entropy method, this study quantitatively evaluates the direct operational strength of 14 leading container shipping enterprises while considering multiple factors including environmental protection, service quality, company scale, customer satisfaction, research and development level, and brand influence. The contributions of this study to the existing knowledge are primarily manifested in several aspects: firstly, by constructing a comprehensive evaluation framework, it offers a new perspective for assessing the international competitiveness of container shipping enterprises, facilitating a more comprehensive understanding of their strengths and weaknesses. Secondly, this study emphasizes the crucial roles of environmental protection and customer service in the competitiveness of shipping enterprises, providing new strategic directions for the industry’s sustainable development and digital transformation. Lastly, through detailed analysis of the operational performance of different companies, this study provides specific improvement suggestions for shipping enterprises, aiding them in achieving more precise management and more efficient development. The research findings demonstrate that companies exhibit varied performance in different aspects, showcasing their respective strengths and challenges. Particularly, this study identifies leading enterprises that have made significant progress in environmental technology innovation and customer service, while also highlighting deficiencies in some companies regarding scale expansion and brand building. These findings not only offer valuable insights for the development of the shipping industry but also serve as a window for policymakers, investors, and consumers to gain a deeper understanding of the shipping market. Through the thorough analysis conducted in this study, we aim to contribute to the sustainable development and digital transformation of the global container shipping industry.

What Role Does Simulation Play in Sustainable Industrial Development?

Sustainability as a concept is present in most aspects of our everyday life, and industry is no exception. Likewise, there is no doubt that the necessity to produce goods in a sustainable way and to ensure that products are sustainable is gaining more and more attention from producers, customers, governments, and various organizations. Understandably, there are several ways to increase the sustainable development of industrial production. One effective tool is simulation, which can have a significant impact on improving environmental, economic, and social sustainability. This paper explores the role of simulation as a powerful scientific and engineering solution in advancing sustainability within industrial ecosystems. Its main scope is to map the existing literature on the usage of simulation as a supportive tool for achieving this goal. For this purpose, a bibliometric analysis was conducted, allowing for tailored insights into the use of simulation in sustainable production.

Does industrial sustainable development policy act as a booster for urban economic growth? Evidence from China's eco‐industrial parks

AbstractEco‐industrial parks (EIPs), which reduce pollution and transform the industrial sector to be more environmentally benign, represent the industrial sustainable development policy. However, little research has concentrated on its economic effects. We explore the impacts of 93 national demonstration EIPs on urban economic development using time‐varying difference‐in‐difference, based on panel data from 330 Chinese cities from 1995 to 2018. We show that EIPs have contributed to an economic growth range between 7.47% and 7.61% in pilot cities, with robustness considering price deflators and alternative satellite data on night lights. Structure, technological, and scale effects help explain the mechanisms. Further estimates show that EIPs have had mixed success in addressing the resource curse, where they only alleviate the curse for growing resource‐based cities. We argue that the industrial sustainable development policy not only conveys significant economic benefits but also holds the potential to address the resource curse.

Analysis on Lean Management of Real Estate Projects Oriented by Target Cost Management

At present, the state has more and more regulatory policies for the real estate industry, and the regulatory intensity is also greater. With the introduction of national policies and the impact of the downturn in the real estate market, industry competition has become increasingly fierce. Under this situation, if real estate companies want to avoid being eliminated by the market, they must rely on their own efficiency levels and management capabilities. Therefore, strengthening cost control on projects is an inevitable choice and important means for real estate companies. In recent years, with the slowdown of economic growth and the state's regulation of the real estate industry, the sustainable development of the real estate industry has faced increasing challenges. This article is oriented by target cost management and focuses on the lean process of real estate development projects. The key points of management and its management strategies are discussed to provide industry reference.

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

The Impact and Spatial Spillover Effects of Tourism Development on Urban Welfare: Empirical Evidence from the Yangtze River Delta in China

The ultimate goal of China’s tourism industry is to create a flourishing sector that brings happiness. It is of immense theoretical and practical importance to investigate the impact of tourism development (TD) on urban welfare (UW) and uncover its spatial spillover characteristics from a macro perspective. Utilizing panel data from 41 cities in the Yangtze River Delta region from 2000 to 2021, this study applies the spatial panel Durbin model to explore the direct and spillover effects of TD on UW. The results show that TD significantly boosts UW in both local and neighboring areas, with the spillover effects taking a dominant position in the total effects. Examining the sub-dimensions of UW, the local welfare effects of TD primarily stem from economic welfare, whereas the spillover effects are characterized by the “three-wheel drive” of economic, social, and environmental welfare. This study can provide practical insights into the coordinated and sustainable development of the regional tourism industry.

Flexural Behaviour of RC Beam with Pond Flyash and ESP FlyAsh

The use of Supplementary Cementitious Materials (SCM) such as Fly ash, Granulated Slag and Silica fume as a replacement for Portland cement in concrete presents one viable solution with multiple benefits for the sustainable development of the construction industry. Out of various supplementary materials, Fly ash is the most widely used material worldwide. Fly ash has excellent structural and durability characteristics. The pore filling effect and pozzolanic properties of Flyash improves the properties of fresh and hardened concrete. In addition to the cost saving bythe replacement amount of cement; it reduces co2emission during the manufacture of Portland cement. In the present investigation, a controlled beam and six number of ESP flyash and Pond flyash beams of size 200 x 100 x 1700 mm were cast. This paper deals with the investigation on the flexural behaviour of beam with pond flyash and ESP (Electro static precipitated) flyash at various cement replacement levels of 4%, 6%, and 8% and the results are compared with controlled beam. The flexural test was conducted to determine the ultimate load carrying capacity of the beams and their corresponding mid span deflection, load point deflection, crack pattern, Stress vs strain are measured. The flexural strength of ESP flyash is increased 24.76% for 8% replacement level and pond flyash is increased 10.97 % for 6% replacement level than controlled beam respectively. This study revealed that the replacement of cement by flyash concrete provides higher compressive strength & flexural strength compared with controlled concrete.

Review on Dust Control Technologies in Coal Mines of China

China faces a challenge in the sustainable development of the coal industry due to pneumoconiosis problems. Dust control technologies are crucial for safe production and miners’ health, ensuring the industry’s longevity. This article reviews the development process of dust prevention and control in underground coal mines in China, summarizes various technologies, and divides them into dust suppression, open-space dust reduction, and mine dust collectors according to different stages and environments of use. In dust suppression technologies, coal-seam water injection can reduce total dust generation by 60%, wet rock drilling can reduce drilling dust in the presence of stable water sources and high-pressure bearing equipment, and water-seal blasting can reduce blasting dust by 50–70%. In open-space dust reduction technologies, spray dust suppression can remove total dust by 50–95% and the removal efficiencies of foam dedusting for total and respirable dust are reported to reach 95% and 85% under the right conditions, respectively. In dust collector technologies, dry collectors can remove 80–95% of total dust. Wet collectors achieve up to 90% efficiency, dependent on water supply and waste processing. This article also discusses vapor heterogeneous condensation technology as a promising method for improving respirable dust removal in humid mine environments.

An exploratory diagnosis and proposed index of technological change and sustainable industrial development in selected OECD member countries

Industrial development has resulted in economic progress and the well-being of the society. At the same time, the impact of the industrial complex has disrupted the environment and resulted in climate change related impacts. The purpose of this study was to carry out an exploratory diagnosis and propose a technological change and sustainable industrial development index at the international level. Therefore, a network study was conducted to identify the main nodes and thematic clusters associated with cleaner production. A patent analysis was applied to technologies related three selected/relevant areas of cleaner production, i.e. carbon footprint, wastewater treatment, and renewable energy. Additionally, based on factor analysis, an index including different indicators related to scientific, technological, economic, environmental, and social issues was developed and proposed in this study.

Examining nonlinear effects of socioecological drivers on urban solar energy development in China using machine learning and high-dimensional data

In the context of carbon neutrality target, renewable energy sources have been transforming from “supplementary energy” to “main energy”, which have promoted the green and low-carbon transition of global energy supply system. In-depth analyzing the spatial patterns and driving mechanisms of renewable energy expansion are of significance for optimizing the spatial layout of clean power, and avoiding the phenomenon of wind and solar power curtailment. In this paper, we proposed an ensemble learning model to examine the nonlinear effects of physical geography, resource endowment, and socio-economic factors on solar photovoltaic (PV) capacity at the prefecture-level city scale in China. Using the city-level multi-sources geospatial big data, we extensively collected a total of 175 related explanatory variables and cumulative installed capacity of solar PV power for 295 prefecture-level cities of China. The recursive feature elimination algorithm (SVM-REF) is firstly used to extract the optimal feature subset of urban PV capacity from multi-dimensional features variables. Furthermore, three advanced machine learning models (random forest, decision tree, extreme gradient boosting) are developed to identify the key influencing factors and nonlinear driving effect of urban solar PV power expansion in China. The results show that China's PV installation capacity is highly concentrated in Northern and Northwest parts of China, with the occupancy over 70% in 2019. Moreover, the XGBoost model has the best prediction accuracy (R2 = 0.97) among three methods. We also found that total amount of urban water resources, average solar radiation, and population density are the most important controlling factors for urban solar PV capacity expansion in China, with contribution of 35.6%, 17.7%, and 13.3%, respectively. We suggested that urban solar PV layout mode in China is recommended to gradually shift from resource orientation to the “resource-environment-demand” comprehensive orientation. The paper provides a replicable, scalable machine learning models for simulating solar PV power capacity at the prefecture-level city scale, and serves as a motivation for decision-making reference of the macro siting optimization and sustainable development of China's green power industry.

Insurance Risk Assessment Model based on Game Theory-Combined Weighting-TOPSIS

With the increasingly severe climate change and intensifying severity of weather events and natural disasters, ensuring the sustainable development of the property insurance industry becomes particularly important. The policy distribution of insurance companies has become a key issue. This paper proposes a novel Game Theory-Combined Weighting-TOPSIS model, which weights indicators using The Entropy Weight Method and the CRITIC method, combines the weights of the former two through game-based combined weighting, and leverages the advantages of the TOPSIS method in handling multi-criteria decision-making problems. Among them, taking China as an example and applying the model, it is found that southeastern China and coastal areas have higher scores and are suitable for insurance. Through this approach, we can scientifically and reasonably assess the risk levels in different regions, provide decision support for property insurance companies to optimize policy distribution, and promote the healthy development of the insurance industry.

Research on Marketing Strategy of Social E-commerce Platform Based on 4R Marketing Theory-Taking Pinduoduo as an Example

As a representative enterprise of domestic social e-commerce platform, Pinduoduo has successfully opened up a blue ocean with social as its main profit, and in just a few years, it has jumped into the top three e-commerce companies and become the top three e-commerce companies in China alongside JD.COM and Ali. Unique marketing strategy is the key to its success. Therefore, based on 4R marketing theory, this paper makes an in-depth study on Pinduoduo's marketing strategy, aiming at digging the key factors behind its success, providing reference for other social e-commerce platforms and ensuring the stable and sustainable development of the e-commerce industry in the future.

Evaluation of combined disinfection methods of infectious myonecrosis virus (IMNV) in seawater using Pacific white shrimp (Penaeus vannamei)

The global spread of infectious myonecrosis virus (IMNV) poses a serious threat to the shrimp aquaculture industry and urgent actions are needed to control its transmission and prevalence. Aquaculture water serves as an important route of IMN transmission, and disinfection of aquaculture water is crucial to ensure the health and stable production of shrimp. In this study, we introduced the purified IMNV into seawater and then subjected the seawater to different disinfection treatments (PMS, PMS + PVP-I and ClO2 + PVP-I) before culturing shrimp. By performing RT-qPCR tests on both the seawater and Pacific white shrimp (Penaeus vannamei) samples, we evaluated the effectiveness of the different disinfection methods in eradicating IMNV from the seawater. The results showed that peroxymonosulfate (PMS) could effectively reduce the viral load of IMNV in seawater samples. The combined disinfection approach (10 ppm) of PMS disinfection (combined with povidone‑iodine) followed by a standing time of at least 2 days, or 10 ppm chlorine dioxide disinfection (combined with povidone‑iodine) followed by a standing time of at least 4 days, were found to be successful in the efficient disinfection of IMNV. This research provides a method to effectively remove IMNV from marine aquaculture water, thereby contributing to reducing the risk of IMN disease transmission and providing a sound basis for the sustainable and healthy development of the shrimp aquaculture industry.

Evaluation of Ergonomic Risks for Construction Workers based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method

Ergonomic risks critically impact workers’ occupational health, safety, and productivity, and thereby the sustainability of a workforce. In the construction industry, the physical demands and dynamic environment exposes workers to various ergonomic hazards. While previous research has mainly focused on postural risks, there is a need to broaden the scope to include more relevant factors and assess them systematically. This study introduces a multi-criteria decision framework integrating the Spherical Fuzzy Sets (SFSs) and Alternative Queuing Method (AQM) to evaluate and prioritize ergonomic hazards. First, SFSs are employed to quantify the linguistic expressions of experts, addressing the inherent vagueness and uncertainty. Then, an entropy-based objective weighting method is adopted to determine the criteria weights. Finally, AQM is utilized to generate the risk priority. The proposed method has been implemented in a real-life construction project, where “overexertion due to unreasonable task organization”, “hypertension and heart diseases”, and “existing WMSD record” are identified as the top three ergonomic hazards. Then, a thorough discussion of intervention strategies regarding different risk categories is presented to facilitate ergonomic interventions. This proposed decision support system can promote effective ergonomic risk management, benefiting workers’ health and well-being and contributing to the sustainable workforce development of the construction industry.

Explore the Transformation and Application of Paper Cutting Art in Modern Brand Visual Design

As a treasure of Chinese traditional folk art, paper-cut art has been inherited for thousands of years. Its unique hollow out effect and profound cultural connotation make it glow with new glory in the modern brand visual design. In the modern brand visual design, the transformation and application of paper-cut art not only enrich the design forms, but also endow the brand with unique cultural connotation and visual impact. Therefore, this paper explores the transformation and application of paper-cut art in the modern brand visual design, aiming to provide some reference value for the sustainable development of the modern brand visual design industry, and make the best contribution.