Digital technologies applied to the monitoring and sustainable management of natural resources

Digital Technology as an Enabler for Sustainable Natural Resource Management Policies in Indonesia

This study investigates the role of digital technologies in supporting sustainable natural resource management in Indonesia. The research aims to identify dominant technologies and clarify their contributions to policy-oriented sustainability frameworks. A mixed-methods approach was applied, combining a systematic review of Scopus-indexed journals, thematic coding of sustainability elements, AI-assisted clustering of architectural technology usage, and quantitative frequency mapping. The results highlight the prominence of the Internet of Things (IoT, 45.88%) and Building Information Modelling (BIM, 30.63%) in enabling real-time monitoring and integrated infrastructure planning. Complementary tools such as ArcGIS, Google Earth Engine, Blockchain, and VR/AR further support transparency, spatial analysis, and eco-friendly design. By synthesising these contributions, the study demonstrates how digital technologies enable sustainable resource management strategies in Indonesia and provides a foundation for future research and implementation

SUSTAINABLE FARM MANAGEMENT IN THE CONTEXT OF THE SOCIETY 5.0 CONCEPT – CHALLENGES AND DEVELOPMENT PERSPECTIVES

Purpose: The purpose of this article is to demonstrate how the ideas of Society 5.0 can be translated into the everyday management of a crop farm and what real benefits and limitations accompany this transformation. The focus is on linking digital tools with the environmental, economic, and social objectives of sustainable development, viewed from the perspective of on-farm practice. Design/methodology/approach: The study adopts a qualitative–quantitative approach in the form of a case study of a single anonymous crop farm located in the Kujawsko-pomorskie Province of Poland. The analysis is based on the farm’s operational data (crop structure, yields, records of purchases and usage of production means) as well as a structured interview with the farm owner. The research is complemented by a review of the literature and reports on digital agriculture, Society 5.0, and data governance. Findings: The case study shows that the gradual implementation of digital tools, which is focused on areas generating the greatest losses, makes it possible to achieve measurable environmental and cost-related effects without full farm automation. The greatest benefits resulted from the organization of treatment records (FMIS), the reduction of overlapping passes through the use of GNSS, and better adjustment of fertilization and crop protection to field conditions. Key barriers included costs, user competencies, and the integration and accessibility of data from machines and systems, including the risk of dependence on a single provider. Research limitations/implications: The findings relate to a single farm and are not representative of the entire sector. The observed effects may have been influenced by external factors such as weather conditions, changes in crop structure, or production means prices. The value of the study lies in illustrating a practical chain: data – decision – implementation – result, which is relevant for further research on the digitalization of agriculture. Practical implications: The most important solutions are those that shorten decision-making time and reduce losses that are difficult to detect in the short term, such as overlapping passes, repeated treatments, or incomplete records of field operations. In practice, the key issue is not “more technology” but better control of the production process. Social implications: Within the logic of Society 5.0, technology is intended to serve people by facilitating work, reducing time pressure and the risk of errors, and ordering documentation. The social dimension of sustainability thus translates into greater predictability of work and a reduced administrative burden.Originality/value: The article links the concept of Society 5.0 with the practice of crop farm management, demonstrating an implementation pathway from data, through decision-making, to measurable environmental, economic, and organizational effects.

Digitalization, AI and ESG: adoption of the environmental management information system for marketing and sustainability performance

Artificial intelligence (AI)-enabled environmental management information systems (EMISs) are designed to collect environmental data, facilitate informed interpretation of environmental issues and enable effective reporting and management of environmental information. As their relevance grows, more scholarly attention should be paid to the role of AI-enabled EMIS in marketing contexts, their adoption and their effectiveness in enhancing firms’ performance in meeting Sustainable Development Goals (SDGs). Against this backdrop, this study aims to examine the antecedents and outcomes of AI-enabled EMIS adoption, with particular emphasis on digitalization, sustainability performance and alignment with SDGs. Furthermore, this study explores leadership support as moderator and firm-level sustainability performance as mediator in these relationships. Drawing on the resource-based view (RBV), the dynamic capability view (DCV) and stakeholder theory, this study proposes an integrative conceptual framework. The proposed model was subsequently empirically tested using structural equation modelling based on survey data collected from respondents in India. This study shows that the SDGs, firm capability and stakeholders’ willingness positively influence AI-enabled EMIS adoption within the firm. Also, this study shows that government policies and regulations on adopting an AI-enabled EMIS in firms are weak. This study also finds that leadership support has a considerable moderating effect on the relationship between AI-enabled EMIS adoption and the firm’s sustainability performance. The SDGs were established by the United Nations General Assembly to achieve a better, more sustainable future for all. There is growing interest among researchers, academicians and practitioners in understanding the antecedents of AI-enabled EMIS adoption and its consequences for sustainability, SDGs and the firm’s overall performance.

Innovative Strategies for Sustainable Resource Management: Balancing Ecosystem Integrity and Human Development

With the increased pressure on natural resources in the world, sustainable management of resources that resonates with both the integrity of ecosystem maintenance with the development of humankind has been a burning issue of concern. This review discusses new approaches, including the ecological protection in the framework of the developmental aims, when systemic approaches are used, instead of an individual intervention. The paper discusses some of the major directions towards sustainability, such as technological solutions (e.g., precision agriculture, digital monitoring), nature-based solutions (e.g., restoration, agroecology), circular economy, financial mechanisms (e.g., payments to ecosystem services, green bonds), and governance innovations (e.g., adaptive management, polycentric governance). It highlights the importance of multi-sectoral approaches that realize both ecological and social aspects of sustainability, and specifically equity and inclusiveness. The review also gives much attention to the role of measurements and monitoring, which is very critical and identifies the necessity to monitor not only the results of ecological integrity but also the results of human development. It also talks about the issue of balancing trade-offs between trade and conservation and provides advice on the reduction of risks of the leakage effect, rebound effects, and unfair allocation of benefits. Finally, the article also introduces the need to replace the concept of balancing with the co-optimizing of human development and ecosystem health, and its future agenda of research, policies, and practices will be to construct a resilient, just, and sustainable future of both people and nature.

The role of intelligent technologies in ensuring sustainable organizational development and management: Analysis and prospects

Blending innovative technologies such as artificial intelligence, big data, and the Internet of Things has become a key driver of sustainable organizational development (SOD) worldwide. These technologies support resource optimization, informed decision- making, and environmentally sustainable growth. However, in Ukraine, the post-war context and energy challenges have both facilitated and constrained the adoption of technology-driven sustainability practices. This study employs a convergent parallel mixed-methods design, in which quantitative and qualitative data were collected simultaneously, to examine the role of intelligent technologies in promoting SOD in Ukrainian organizations. Quantitative data were collected through structured questionnaires from 250 organizational respondents; however, regression and ANOVA analyses were conducted on 89 complete cases using a complete-case approach, while qualitative insights were obtained through interviews with 18 experts. Quantitative data were analyzed using descriptive statistics, regression analysis, and ANOVA in SPSS, whereas qualitative data were examined through thematic analysis using NVivo. The findings reveal several enabling factors, including EU integration initiatives and national digitalization strategies, alongside key barriers such as skill shortages and cybersecurity concerns. The study provides practical policy recommendations to strengthen digital resilience and promote sustainable organizational development in Ukraine.

Eco-Friendly Environmental Management: Synergy of Policy, Technology, and Community Behavior