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This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions.

The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties.

The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type.

The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry.

The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively designing and managing a single-supplier multi-retailer cold chain for fresh produce with deterministic demand to minimize the total cost, which includes cooling, loss of value and carbon emission costs.

The global stability index (GSI) method and the non-Arrhenius model are integrated to describe the behavior of food quality degradation. The power-of-two (PoT) policy is adopted in determining the coordinated replenishment policies for the suppliers and retailers, and an appropriate wholesale price structure that can achieve the coordination of the chain is presented.

The properties of the cold chain are uncovered, and an appropriate wholesale price scheme that achieves chain coordination with the optimal PoT decision is provided. In the numerical examples, different scenarios are investigated, and it is found that the cold chain parameters influence the optimal decisions in certain ways.

The PoT policy – an efficient policy to determine the replenishment strategy – has not been adopted in finding the solution of a single-supplier multi-retailer cold chain in the literature. Also, no study has compared the uncoordinated and coordinated cold chain. Moreover, in the existing literature, the wholesale price is usually a constant rather than having a coordinated scheme. This research aims to fill these research gaps.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

The purpose of this paper is to present a case study the application of lean six sigma combined with mining transportation overall vehicle effectiveness (MTOVE) to improve mining transportation performance. MTOVE is a newly developed model to measure the overall effectiveness of mining transportation.

The method used is case study combines the MTOVE and LSS methodologies. Data were collected from the hauling operation during a three-month period. Various lean six-sigma tools, such as the Pareto chart, ANOVA, two sample t-tests, one sample t-test, cause-and-effect analysis and time study, have been used.

The case study resulted in improvement of vehicle overall effectiveness; a 35% increase in MTOVE value, a 17% improvement in productivity and a 9% increment in truck utilization. Statistical tests confirmed the significance of reducing the mean and variation in the hauling process cycle time, which led to productivity improvement.

This study provides practitioners with additional quantitative evidence of the potential benefits of LSS methods in the coal mining industry.

This paper practically and unquestionably has contributed to the LSS body of knowledge focused on the mining sector, which is recently still far behind the manufacturing sector. The study has demonstrated that some challenges in the mining environment can be solved through the effective implementation of LSS tools. Hence, this paper could be used as a reference for both researchers and practitioners.

The study contributes in the field of LSS spread in mining industries using a case study. This study shows practical evidence of improving overall vehicle effectiveness using LSS. Practitioners can refer to this study to understand the benefits of LSS in mining sector. Since the mining industry should also adopt the LSS principle into the mining business process due to its ability to improve business performance (Valente et al., 2020; Tupamahu et al., 2019; Zanon et al., 2021).

There has been little scientific study of the LSS implementation in the mining industry. This research provides detailed evidence of LSS implementation in the mining sector. The main contribution is the implementation framework, which shows the combination of newly developed indicators (MTOVE and LSS) to enhance hauling operation effectiveness. This paper demonstrates how LSS tools and methods can be applied in the mining transportation industry.

Cold supply chain technology is critical for extending the shelf life of perishable leafy green vegetables. This study aims to investigate the concept of managing leafy green products using cold supply chain technology and visualise the findings.

Using expert interviews and data visualisation approaches, this study examines how organisations deal with the complexity of cold supply chain processes and networks. Thematic data analysis was conducted. Two types of software were used to accomplish the research objectives. The first software used AntConc version 3.5.8 with word frequency (N-gram) analysis, whereas the second software, VOSViewer offered co-occurrence network visualisation and cluster analysis.

The findings show that the appropriate design of cold chain technology is critical in ensuring the freshness and quality of leafy green vegetables. The primary goal of managing the complexity of the cold supply chain is to achieve product freshness and energy efficiency. Regardless of the importance of energy efficiency, cold supply chains require warehouse management solutions for transportation and storage.

This study found that proper design and selection of appropriate technology in the cold supply chain have driven the companies to improve the firms’ competitive advantage while delivering the best quality of perishable leafy green food products. In addition, the freshness, quality, safety, and health of leafy green vegetables will be determined by the company’s capacity to handle long-distance transportation and select the appropriate distribution channels and storage. Warehouse management system technology was found to be secondary compared to cold chain technology, although distribution and warehousing practices are critical for supply chain performance.

This study has established the conceptual indicators based on best practices and outcomes for the cold supply chain. This study argued that cold supply chain management and performance should be monitored independently. Furthermore, the theory of technological adoption can be expanded to include product nature as a driver. Finally, this study has established cold chain best practices based on a perishable supply chain perspective. The findings of this study can promote healthy foods to solve zero hunger and achieve sustainable development goals. Although this study demonstrates that technology improves supply chain practises, cold storage and logistics benefit the most from technological advancements. In contrast, non-cold supply chains benefit from technology-driven improvements in performance.

Food quality and safety issues have always been imperative topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality. How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

The paper aims to analyze the differences in product quality levels and market participants’ profits before and after the use of blockchain-driven traceability technology in the food agricultural product supply chain (SC) in the dynamic game frameworks of supplier-led and retailer-led modes, respectively, and explores the willingness, social welfare and consumer surplus of each member of the agricultural product SC to participate in the blockchain. Besides, We investigate the SC performance improvement with the mechanism of central centralized decision-making and revenue-sharing contract, compared to the SC performance in dynamic games.

The results are obtained as follow: The adoption of blockchain traceability technology can help improve the quality of food agricultural products, consumer surplus and social welfare, but the application and popularization of technology is hindered by traceability technology installment costs. Compared with the supplier leadership model, retailer-led food quality level, customer surplus and social welfare are higher.

How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

Food quality and safety issues have always been hot topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality.

The research results enrich the theories related to food safety and quality, and provide a valuable reference for food enterprises involved in the decision-making exploration of blockchain technology.

Based on the characteristics of blockchain technology, the demand function is adjusted and the product loss risk of channel members is transferred through a Stackelberg game SC composed of agricultural products suppliers and retailers.

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  We introduce two features of blockchain: quality trust and product information tracking.

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  The willingness of each member of the supply chain to use blockchain for product traceability was explored.

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  The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

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  The cost of blockchain technology is a barrier to its adoption.

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  Blockchain brings higher consumer surplus and social welfare.

We introduce two features of blockchain: quality trust and product information tracking.

The willingness of each member of the supply chain to use blockchain for product traceability was explored.

The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

The cost of blockchain technology is a barrier to its adoption.

Blockchain brings higher consumer surplus and social welfare.

This study aims to characterize the experiences of health professionals participating in an exploratory randomized controlled trial designed to improve hearing and vision among older adults without dementia receiving the in-home health services provided by Norwegian municipalities.

Semistructured individual and paired interviews were conducted by nine health professionals from five municipalities to explore health professionals’ experiences with the intervention. The data were analyzed using content analysis.

Three main categories of experiences were identified: (1) participating in the intervention, (2) emerging new knowledge and (3) developing in-home health services. The mutual collaboration between health professionals and service recipients during the screening process led to a more-thorough understanding of the service recipients’ needs and resources, enabling personalized advice and guidance.

In-home interventions have the potential to improve the quality of life of older adults with hearing and vision impairments. Given the promising outcomes of such interventions, future research should (1) investigate their effects on changes in behaviors and attitudes, (2) integrate technological advancements and (3) explore environmental modifications to further enhance the quality of life of older adults in various settings.

The health professionals in this study enjoyed assisting the service recipients in receiving in-home health services by screening their hearing, vision and indoor lighting conditions. The trial enabled the health professionals to provide personalized advice, and to motivate and guide the service recipients toward actions to remedy their impairments.

The health professionals recommended hearing, vision and indoor lighting screening to be a routine municipal service because it would safeguard independence, prevent falling and maintain the quality of life of service recipients. However, additional resources are needed to implement these recommendations.

In-home interventions have the potential to improve the quality of life of older adults with hearing and vision impairments.

The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.

This research investigates the distinct characteristics of blockchain technology to safeguard against the deterioration of handover information quality in the post-construction phase. The significance of effective management of handover information is highlighted by global building failures, such as the Grenfell Tower fire in London, UK. Despite existing technological interventions, there remains a paucity of understanding regarding the factors contributing to the decline in the quality of handover information during the post-construction phase.

This study employed a multi-case studies approach across five higher education institutions. It involved conducting semi-structured interviews with 52 asset management professionals, uncovering the underlying reasons for the decline in handover information quality. Building on these insights, the study performed a mapping exercise to align these identified factors with blockchain technology features and information quality dimensions, aiming to evaluate blockchain’s potential in managing quality handover information.

The study findings suggest that blockchain technology offers advantages but has limitations in addressing all the identified quality issues of managing handover information. Due to the lack of an automated process and file-based information exchange, updating handover information still requires an error-prone manual process, leading to potential information loss. Additionally, no solutions are available for encoding drawings for updates and validation.

This study proposes a framework integrating blockchain to enhance the information management process and improve handover information quality.