International Journal of Environment and Sustainable Development (4 papers in press)

Special Issue on: OA Green Supply Chain Management Innovations in Sustainable Business Environment and Digital Transformation

• Open Access

  Evaluation on the impact of digital transformation on the economic eco-environmental benefits of enterprises under the background of sustainable development ( Free Full-text Access )

  by Yue Wu, Yin Ma 
  Abstract: Digital transformation (DT), as a key driving force for enterprise innovation and development, has been widely applied in various fields such as agriculture, industry, and services. Although DT has achieved significant results in improving operational efficiency, optimising resource allocation, and reducing costs, its potential negative impact on the ecological environment is gradually becoming apparent, especially in terms of increased energy consumption, intensified resource waste, and rising pollutant emissions. This study investigates the economic and ecological impacts of digital transformation (DT) under a sustainable framework, based on surveys and performance data from agricultural, industrial, and service enterprises. Results show improved revenue and reduced costs across sectors, with agricultural firms reporting a 13.87% revenue increase and 5.69% cost reduction in the third quarter, and industrial firms showing an 8.73% revenue increase and 5.89% cost reduction in the fourth quarter. Service firms demonstrated slower yet positive changes. However, 96.13% of employees perceived negative environmental consequences, particularly in air pollution, water shortages, and reduced forest coverage. Findings indicate that while DT enhances economic performance, it imposes environmental pressures. Aligning digital strategies with ecological goals is essential for achieving sustainable enterprise development.
  Keywords: sustainable development; digital transformation; enterprise economic benefit; enterprise ecological environmental benefits.
  DOI: 10.1504/IJESD.2026.10076924
   
  

• Open Access

  Coordinated development of rural green industry planning based on ecological sustainable model and the internet of things ( Free Full-text Access )

  by Chong Meng 
  Abstract: Although industrial factories can rapidly promote economic development, they have caused significant damage to rural ecosystems. Based on the principle of ecological sustainable development, this paper analyses the characteristics of rural resources and combines IoT sensor technology to develop green industries such as tourism and e-commerce, in order to solve the problems of rural ecological balance and industrial development. This paper compares the situation before and after the implementation of rural green industry planning in Wuyuan County and Haifeng County, respectively. The experimental results show that in Wuyuan County, the average economic growth rate of traditional rural enterprises is 34.08%, while after the implementation of rural green industry planning, this growth rate has increased to 72.04%. In Haifeng County, the average economic growth rate of traditional rural enterprises is 42.04%, but after implementing the rural green industry plan, the growth rate increases to 64.64%.
  Keywords: rural green industry; coordinated development; ecological sustainability; internet of things; IoT.
  DOI: 10.1504/IJESD.2026.10076925
   
  

Regular Issues

• Prediction of domestic waste removal volume using GM (1, N, r, ) model: a case study of Shanghai City  
  by Afi Laeticia Awaga, Yan Yan, Hongyao Zhang, Wei Xu, Lu Zhang 
  Abstract: This paper aims to address domestic waste generation issues in urban planning by enhancing the accuracy of domestic waste removal forecasts through the development of an optimised grey prediction model. Focusing on optimising the cumulative order and background coefficient value of the GM (1, N) model, the analysis of Shanghais domestic waste data reveals that the optimised model achieves a markedly reduced mean absolute percentage error (MAPE) of 8.1%, mean absolute error (MAE) of 59.89, and the root mean squared error (RMSE) of 78.00, conversely to the unoptimised model (10.09%, 73.01, and 93.29, respectively) and the partially optimised model (9.49%, 70.16, and 94.36, respectively). These results validate the efficiency of the parameter optimisation method, and the model predicts that Shanghais domestic waste removal volume will reach 11.666 million tons by 2030, offering essential insights for sustainable urban waste management.
  Keywords: domestic waste removal; waste forecasting; parameter optimisation; grey models; GM(1; N; r; ξ) model; urban waste management; Shanghai.
  DOI: 10.1504/IJESD.2026.10077100
   
  

Special Issue on: Joint Implications of Circular Economy and Digital Transformation for Resilient Business Ecosystems

• Redefining EU competitiveness: unlocking the power of digitalisation, institutional quality, environmental factors and human capital in shaping a sustainable future  
  by Bernard Vaníček, Tomáš Fišera, Jan Stejskal 
  Abstract: In todays turbulent times, understanding sustainable competitiveness is crucial. This study fills important gaps in existing research by examining the integrated relationship between digitalisation, environmental factors, institutional quality and human capital in 24 EU countries, and using stepwise regression to identify significant factors influencing the Global Sustainable Competitiveness Index (GSCI). This study contributes by developing a holistic framework that integrates drivers of sustainable competitiveness, addressing the limitations of prior research that examined these factors in isolation. Practically, it offers policy recommendations tailored to different EU country groups based on their sustainability and economic performance. Findings reveal that government effectiveness negatively impacts low-GSCI-growth countries (Bulgaria, Croatia, Poland and Romania), while environmental factors, particularly circular economy material flows, drive high-GSCI-growth nations (France, Italy, Netherlands, Portugal and Spain). These insights emphasise the need for targeted policies, including digital infrastructure improvements, circular economy support, and institutional reforms, particularly for lower-performing countries, to enhance sustainable competitiveness.
  Keywords: sustainable competitiveness; digitalisation; institutional quality; environmental factors; human capital.
  DOI: 10.1504/IJESD.2025.10072648