Search results

The circular economy (CE) has been endorsed as representing a model that is able to achieve environmental protection through decreased use of raw materials, together with changing economic values and social inclusion thanks to its demand for a wide variety of skill profiles. This has motivated many policy initiatives to support the implementation of the CE. The purpose of this study is to follow such policy initiatives in three geographically anchored industry-specific networks.

The study contributes to the research debate on the CE through a spatial approach with a focus on how the implementation of the CE is conditioned by spatial and regional contexts. The authors investigate three different networks in Sweden for CE with different locations and industrial profiles.

The findings reveal the difficulty that exist in relation to the implementation of the CE. The network and support functions in combination with private industry are vital. The risk of sustaining an uneven regional economic development is evident.

Although research on the development of the CE has proliferated, geographical approaches to this development are comparably rare to date. The authors seek to contextualise the strategy development and policy implementation of a CE policy.

The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.

This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.

This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.

This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.

This study aims to investigate the application of red cabbage extract in biodegradable composite-based edible film and evaluate its physicochemical characteristics and ability to be used in steamed chicken packaging.

Cassava starch, gelatin and glycerol were used as basic materials for edible film. Red cabbage extract was infused, and eggshell powder was also incorporated. The smart edible film formulation consists of six treatments which are C (control: cassava starch + gelatin + glycerol), CE (control + 0.1% eggshell powder), CRA (control + red cabbage A ratio), CERA (control + 0.1% eggshell powder + red cabbage A ratio), CERB (control + 0.1% eggshell powder + red cabbage B ratio) and CERC (control + 0.1% eggshell powder + red cabbage C ratio).

The different ratios of red cabbage extract in the formulation of the edible film affected its physicochemical properties (p < 0.05). The range of anthocyanin content were 0.39–11.53 mg cy-3-glu-eq/100 g and phenolic content were 19.87–369.68 mg GAE/100 g. Meanwhile, the antioxidant activity was 12.35%–51.09%. The tensile strength in all treatments was lower than control and adding red cabbage extract decreased the tensile strength. On the other hand, the elongation increased. The water vapor transmission rate was ranged from 158.09 to 191.19 g/m²/24 h. Morphological changes can be observed from scanning electron microscopy and optical data. Furthermore, using steamed chicken as a model, the edible film can show a response through the changes in edible film color, as confirmed by the pH value, total plate count and sensory quality of the stored steamed chicken.

There is no report available on the infusion of red cabbage extract on the bio composite edible film materials. The result shows a promising packaging material that can be used as an alternative to plastic packaging.

Drawing on panarchy theory and adaptive cycles, this study aims to investigate the role of reorganisation capabilities on firms’ supply chain resilience. The conceptual model underpinned by panarchy theory is tested in the agrifood supply chains disrupted by a geopolitical crisis and faced with material shortage. The study considers circularity as a core reorganisational capability and measures its interplay with two other capabilities: new product development and resource reconfiguration capabilities to achieve supply chain resilience.

A quantitative research design is followed to test the relationships between circularity capabilities, resource reconfiguration capabilities, new product development capabilities and supply chain resilience. A cross-sectional survey is applied to a sample drawn from food manufacturers who are dependent on wheat and sunflower oil as raw material and who are faced with material shortages in the aftermath of a geopolitical crisis. Measurement models and hypotheses are tested with the partial least squared structural equation modelling (PLS-SEM) based on 324 responses.

The results show that new product development and resource reconfiguration capabilities fully mediate the relationship between circularity capabilities and supply chain resilience. In other words, the food producers achieved supply chain resilience in response to agrifood supply chain disruption when they mobilised circularity capabilities in combination with new product development and resource reconfiguration capabilities.

The findings suggest that producers in the agrifood industry and even those in other industries need to develop circularity capabilities in combination with new product development and resource reconfiguration capabilities to tackle supply chain disruptions. In a world that is challenged by geopolitical and climate-related crises, this means leveraging 3R practices as well as resource substitution and reconfiguration in new product development processes.

The study explores the release and reorganisation phases of adaptive cycles in a panarchy by analysing the interplay between different capabilities for building supply chain resilience in response to disruptions challenging supply chains from higher levels of the panarchy. The results extend the theoretical debate between circularity and supply chain resilience to an empirical setting and suggest the introduction of new variables to this relationship.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.