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Using a soft-hard continuum of drivers and barriers, this research seeks to explain wood companies' adoption of circular economy (CE) practices.

Multiple interviews, complemented by secondary documents and site observations were used to investigate three wood-based companies that have adopted CE practices. The 10R framework and soft-hard continuum are used to guide data analysis.

The adoption of 10R practices were explained by soft-factor incentives of leaders' values and vision and openness for innovation, all within a regulatory void, and eventually overcome hard-factor barriers of process development, supply chain capability and customer behaviours at product end-of-life.

Crucial for CE model adoption are leaders' positive attitudes, subsequently grown across the companies. The 10Rs are a prompt for CE practice adoption to capture and retain value and generate revenue. Collaboration across the supply chain, including customers and other value capture companies (e.g. repurposing companies), is essential to maximise value retention. Government should play an increased soft-factor incentive regulatory role and support CE practices to overcome hard-factor barriers.

This study contributes an explanation of CE adoption within a relatively unsupported context. Despite the regulatory void, CE practice adoption was driven by leader values. To achieve their vision and overcome the numerous barriers, suppliers and customers required a large investment in education. Indeed, customer behaviour, previously thought to be an incentive for CE adoption, is also identified as a barrier.

The study aims to compare and analyze the impact of the commonly used pallets (wooden pallet and plastic pallets), using life cycle assessment (LCA), then provide certain suggestions for the development of green packaging.

In this study, software Simapro was used to calculate and analyze the whole life cycle of pallets from the stage of raw materials and production to processing and waste disposal.

A total of 12 environmental categories were used to quantitatively analyze the environmental impact of the four different pallets. The results showed that, regardless of raw material, processing, or waste stage, the environmental impact of wooden pallet was lower than that of plastic pallet. Wooden pallet was better than plastic pallets.

This study compared and analyzed the pallet of 1 × 1.2m with different materials.

Green packaging is the development trend of the future packaging, which follows the principle of 3R1D. According to the calculation results, corresponding suggestions can be put forward from production, processing, using, wasting and other aspects, and make corresponding contributions to the development of green packaging.

The contribution and impact of each stage of the product on the environment can be studied. The environmental impact, such as global warming potential, water scarcity, can be reduced through different solutions such as the use of green materials, good processing techniques and higher recycling rates.

The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably.

A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment.

The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation.

Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent.

The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases’ influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies’ effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers.

To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes.

Pallets ensure efficient processes in logistics and are exchanged between the different actors, while passing through various supply chains several times. In common practice, the exchange is often not directly carried out on site, e.g. due to a lack of time, so that additional trips and new pallet purchases become necessary. To reduce these negative effects, a digital cross-actor platform is designed, and its potential is investigated.

The authors developed an agent-based simulation model with mathematical optimization. Using experience from practitioners, as well as real-world datasets which were analyzed, the authors ensure a realistic model of the pallet exchange system in Germany.

The authors demonstrated that, with the help of this platform concept, transport routes can be shortened, debts and receivables can partly be equaled out through balancing, and the quantity of pallets in the overall system can be reduced.

The results are not directly transferable to pallet exchange systems in other countries without considering their general settings.

Digital networking increases the efficiency of the existing pallet exchange system. Even small collaborations prove to be reasonable.

The authors developed new mechanisms for a digital pallet exchange platform, which takes on the role of a central planning instance, in addition to recording pallet receivables and debts. It enables the planning of the commodity flow of empty pallets, which are transported by the forwarders on regular routes, and distributed between the platform participants.

This study aims to explore how green supply chain management (GSCM) strategies can be effectively implemented for business supply chain operations, relationship management and product design to gain green competitive advantages.

An exploratory in-depth case study was conducted with one of the largest Chinese electronics manufacturers that is considered a leading GSCM adopter in the industry, to understand how the company adopts green supply chain practices across its multiple product lines.

The findings show that businesses can build different green focuses across GSCM elements of green operation, green relationship management and green product design to form diverse hybrid strategic solutions. They include green control, lean, leagile, agile and clean innovation while taking consideration of supply chain type and product lifespan. A taxonomy of four key GSCM strategic combinations is proposed based on the findings. The strategies align with green demand and supply chain characteristics balancing a series of business competitive objectives in terms of reducing pollution and waste, improving green cost efficiency, enhancing green demand innovation and building green service effectiveness.

This study lends insight into the strategic alignment relationships between product supply chain types and approaches to GSCM.

The findings of this study can support industry practitioners in formulating aligned GSCM strategies based on product types to achieve optimal results.

Optimised green supply chain design, operations and relationship management incorporating product attributes can help further minimise negative impacts of business activities on the environment.

This research provides a systematic understanding of how product supply chain types can influence GSCM strategy formulation. It gives a holistic picture of how hybrid choices of strategies with green supply chain operations, relationship management and product design can be formulated based on product and supply chain characteristics.

Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to be examined. Such findings can be cumulated using smart assessment like life cycle analysis. The ecological impact category, supply chain, and climate-changing factors were considered for the necessary assessment.

This paper applies the Life Cycle Assessment technique in the textile and yarn industry to estimate critical environmental potentials. The critical input for the fabric and yarn industry was put in the GaBi software model to estimate various environmental potentials.

Global warming potential, electricity, and raw cotton consumption in the fabric and yarn industry were critical concerns where attention should be focused on minimizing environmental potentials from cradle to gate assessment.

This qualitative study is made via the industry case-wise inputs and outputs, which can vary with demographic conditions. Some machine and human constraints have not been implemented in modelling life cycle model for smart simulation. Smart simulation helps in linking different parameters and simulates their combined effects on the product life cycle.

This modelling approach will help access pollution constituents in different supply chain production processes and optimize them simultaneously.

The raw data used in this analysis are collected from an Indian small scale textile industry. In the textile fabrication industry, earlier assessments were carried out in cotton generation, impact of PET, cradle to grave assessment of textile products and garment processing only. In this research the smart model is drawn to consider each input parameter of yarn and textile fabric to determine the criticality of each input in this assessment. This article mainly talks about life cycle and circular supply assessment applied to first time for both cotton to yarn processing and yarn to fabric industry for necessary estimation of environment potentials.

Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

This study aims to explore the critical application areas of radio frequency identification (RFID) technology for sustainable buildings.

The quantitative research approach was adopted through a structured questionnaire administered to relevant stakeholders of construction projects. The data collected were analysed with the exploratory factor analysis, relative importance index (RII) and fuzzy synthetic evaluation (FSE).

The study’s results have categorised the crucial areas of application where construction industry stakeholders should focus their attention. These areas are divided into four categories: management technologies, production technologies, sensing technologies and monitoring technologies. The findings from the FSE indicate that monitoring technologies represent the most significant category, whereas management technologies rank as the least significant. Moreover, the RII analysis highlights that tools management stands out as the most important application of RFID, while dispute resolution emerges as the least significant RFID application.

The study establishes the core areas of RFID application and their benefits to sustainable buildings. Consequently, it helps stakeholders (consultants, clients and contractors) to examine the RFID application areas and make informed decision on sustainable construction. Furthermore, it provides systematic proof that can aid the implementation of RFID in developing countries.

The study provides an insight into the possible application areas and benefits of RFID technology in the construction industry of developing countries. It also developed a conceptual frame for the critical application areas of RFID technology in the construction industry of developing countries.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.