International Journal of Environment and Sustainable Development (7 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
   
  

• Open Access

  From smart facilities to smart services: building a new ecosystem integrating tourism and smart cities ( Free Full-text Access )

  by Guanxi Chen, Jiajun Chen 
  Abstract: The lack of integration between the tourism industry and smart cities affects the tourist experience and the efficiency of urban management. This paper collects data on tourist behaviour and urban operations through IoT sensors and mobile Internet data. It uses support vector machines and random forest algorithms to perform demand forecasting and behaviour analysis. Then, convolutional neural networks and long short-term memory networks are used to optimise personalised service recommendations for tourists and to schedule urban resources. The experimental results show that average tourist satisfaction has increased by 8 points, and the average urban management response time has been reduced by 102 seconds. Through this intelligent, collaborative approach, this paper has achieved deep integration between tourism and smart cities, providing a feasible solution for future smart city development.
  Keywords: smart city; tourism industry; big data; artificial intelligence; convolutional neural network; CNN.
  DOI: 10.1504/IJESD.2026.10077679
   
  

• Open Access

  Environmental variable regulation and optimisation strategy in forest seedling cultivation based on reinforcement learning ( Free Full-text Access )

  by Xianghong Liu 
  Abstract: Addressing reinforcement learning's failure to model high-dimensional dynamic interactions in seedling cultivation, this paper proposes an intelligent regulation strategy integrating species embedding and proximal policy optimisation (PPO) for precise, dynamic environmental management of diverse seedlings. The study constructs a 12-dimensional state space encompassing initial biological traits, real-time environmental parameters, and species encoding, designs a 243-dimensional discrete action space encompassing temperature, humidity, light, water, and CO2, and introduces a multi-objective reward function to co-optimise growth rate, survival rate, resource efficiency, and stress avoidance. The strategy improves the average daily growth rate, with a final survival rate of 95.2%, an average reduction in electricity consumption per unit biomass of approximately 0.4 kWh/g, and an average reduction in stress events of 19.86. Furthermore, a transfer learning mechanism enables fine-tuning for new tree species in just seven days. This study provides a generalisable, efficient, and personalised regulation paradigm for intelligent seedling cultivation.
  Keywords: reinforcement learning; forest tree seedling cultivation; environmental variable regulation; environmental optimisation strategies; proximal strategy optimisation.
  DOI: 10.1504/IJESD.2026.10077680
   
  

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
   
  
• The impact of institutional quality on environmental sustainability: evidence from ASEAN countries  
  by Lien Do Thi Hoa, Phuong Hoang Vo Hang 
  Abstract: The article evaluates the influence of national institutional quality, as represented by the Worldwide Governance Indicators (WGI), on the load capacity factor (LCF), which serves as an indicator of environmental sustainability. Employing panel data regression methodologies, the study analyses data from nine developing ASEAN countries (Cambodia, Brunei Darussalam, Indonesia, Lao PDR, Malaysia, Myanmar, the Philippines, Thailand and Vietnam) spanning the years 2002 to 2021. The PCA method was utilised to synthesise multiple representative factors of institutional quality into a single institutional quality index. The research data was analysed using pooled OLS, FEM, REM and FGLS techniques. The findings demonstrate significant relationships among the variables under investigation. Notably, the variable representing institutional quality exerts a negative and statistically significant effect on environmental sustainability within the ASEAN region. Based on these results, the article articulates various policy implications aimed at enhancing institutional quality across multiple dimensions, thus striving to improve environmental outcomes in the context of economic growth and foreign direct investment within developing ASEAN countries.
  Keywords: institutional quality; environmental sustainability; ASEAN.
  DOI: 10.1504/IJESD.2026.10077678