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Master information delivery plan (MIDP) is a key requirement for building information modelling (BIM) execution plan (BEP) that enlists all information deliverables in BIM-based project, containing information about what would be prepared, when, by who, as well as the procedures and protocols to be used. In a well-conceived BEP, the MIDP facilitates collaboration among stakeholders. However, current approaches to generating MIDP are manual, making it tedious, error-prone and inconsistent, thereby limiting some expected benefits of BIM implementation. The purpose of this study is to automate the MIDP and demonstrate a collaborative BIM system that overcomes the problems associated with the traditional approach.

A BIM cloud-based system (named Auto-BIMApp) involving naming that automated MIDP generation is presented. A participatory action research methodology involving academia and industry stakeholders is followed to design and validate the Auto-BIMApp.

A mixed-method experiment is conducted to compare the proposed automated generation of MIDP using Auto-BIMApp with the traditional practice of using spreadsheets. The quantitative results show over 500% increased work efficiency, with improved and error-free collaboration among team members through Auto-BIMApp. Moreover, the responses from the participants using Auto-BIMApp during the experiment shows positive feedback in term of ease of use and automated functionalities of the Auto-BIMApp.

The replacement of traditional practices to a complete automated collaborative system for the generation of MIDP, with substantial productivity improvement, brings novelty to the present research. The Auto-BIMApp involve multidimensional information, multiple platforms, multiple types and levels of users, and generates three different representations of MIDP.

Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.

A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.

The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.

This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.

This paper aims to explore the issue of product counterfeiting in Türkiye and assess Türkiye’s role in the global supply chain of counterfeit goods. It sheds light on the supply-side dynamics of counterfeiting in the Turkish context.

Interviews were conducted with 46 key experts, including police officers, customs officers and trademark attorneys. The study also incorporated data from a documentary analysis of counterfeit products seized by the Bulgarian Customs.

The findings of this study highlight the significant role of Türkiye in international supply chains, serving as both a manufacturing hub for a wide array of counterfeit products and a crucial transit point for goods bound for European markets. This study suggests that counterfeiting serves as a source of livelihood for many individuals in Türkiye, with counterfeiters often justifying their activities by claiming they contribute to the country’s economy through job creation and the influx of foreign currency.

While qualitative research is essential for exploring nuanced aspects and gaining in-depth insights, it may not provide the statistical robustness and generalizability associated with larger quantitative studies.

This paper is an original contribution to the understanding of product counterfeiting in Türkiye, a major counterfeit-producing country, with potential implications for the future of consumer protection and market integrity.

Asymmetric cost information exists between a supplier and a manufacturer regarding the manufacturer's process innovation for remanufacturing (PIR), which may hurt the supplier's profit. The authors therefore seek to develop a menu of nonlinear pricing contracts for channel information sharing.

Based on principal–agent theory, the supplier, acting as a Stackelberg leader, designs a menu of nonlinear pricing contracts to impel the manufacturer to disclose its private cost information on PIR (i.e. PIR efficiency). In addition, the authors compare the equilibrium outcomes under asymmetric and symmetric information to examine the effects of asymmetric PIR information on the production policies and profits of the supplier and the manufacturer.

The proposed contract menu encourages th4e manufacturer to spontaneously share PIR efficiency information with the supplier. Asymmetric PIR information may distort the output of new products upward or downward, but the output of remanufactured products may only be distorted downward. In addition, the manufacturer with high PIR efficiency gains information rent, and interestingly, the increase in the probability of low PIR efficiency amplifies its information rent. Finally, an asymmetric information environment may increase the threshold for the manufacturer to enter remanufacturing.

The authors probe the issue of the supplier's contract design by jointly considering remanufacturing, process innovation and information asymmetry. The paper expands the influencing mechanism of process innovation information in the remanufacturing field. The authors also observe new results that may offer guidance to decision makers.

Industry 4.0 has received significant attention in today's competitive business market, necessitating a restructuring of functional domains in nearly every manufacturing organization. A comprehensive strategy to improve performance in preparation for Industry 4.0 implementation necessitates several steps, one of which is the establishment of performance outcomes (POs). The aim of this paper is to identify and rank the POs realized due to the adoption of Industry 4.0 enablers.

Based on an extensive literature review and inputs received from experts, a comprehensive list of enablers and the POs was prepared and finalized. This paper proposes a framework based on hybrid solution methodology, namely Neutrosophic Analytical Hierarchy Process (N-AHP) and Neutrosophic Combined Compromise Solution (N-CoCoSo), to rank the POs realized due to the adoption of Industry 4.0 enablers. The N-AHP methodology has been adopted to calculate the relative weights of the Industry 4.0 enablers. In comparison, the N-CoCoSo method has been adopted to rank the POs of Industry 4.0.

The proposed framework is applied to an Indian manufacturing organization to test the organization's practical applicability. Additionally, sensitivity analysis is also carried out to check the steadiness of the proposed framework. The findings of this study revealed that “Improved responsiveness to market conditions in today's competitive business environment” is the top-ranked PO of Industry 4.0, followed by “Enhanced competitiveness and better market share”, “Better product quality, through smart management of production process” and “Reduction in manufacturing waste and environmental sustainability” which could be realized due to adoption of its enablers.

This research would aid practitioners by enhancing the practitioners' capacity to understand and prioritize the various POs resulting from implementing Industry 4.0 enablers. Embracing a clear strategic plan will further assist practitioners in improving the efficiency of Industry 4.0 implementation.

Previous literature has only addressed the relationship between Industry 4.0 enablers and POs in a limited way. This paper attempts to compile a comprehensive list of Industry 4.0 enablers relevant to manufacturing organizations in order to fill this knowledge and research gap.

Industry 4.0 is recognised as a competitive strategy that helps implementers optimise their value chain. However, its adoption poses several challenges. This study investigates and ranks the drivers and barriers to implementing Industry 4.0 in the Thai sugar industry, the world's second-largest sugar exporter. It also evaluates the industry's readiness for Industry 4.0.

The drivers and impediments were identified based on a systematic literature review (SLR) and further investigated using a questionnaire, expert interviews, Pearson's correlation and nonparametric statistical analyses. The IMPULS model was used to assess the industry's readiness.

Most companies expect to minimise costs, develop employees and improve various elements of operational performance and data tracking capability. Thai sugar producers are still at a low readiness level to deploy Industry 4.0. High investment is the major challenge. Small businesses struggle to hire competent employees, collaborate with a highly credible technology provider and adapt to new solutions.

The findings can serve as a benchmark or guide for sugar manufacturers and companies in other sectors, where Industry 4.0 technologies are not yet widely utilised, to overcome existing roadblocks and make strategic decisions. They can also assist governments in developing policies that foster digital transformation and increase national competitiveness.

There is a scarcity of research on Industry 4.0 execution in the sugar industry. This study addresses this gap by investigating the reasons for the hesitancy of sugar producers to pursue Industry 4.0 and proposing solutions.

The purpose of this paper is to realize the lightweight of connecting rod and meet the requirements of low energy consumption and vibration. Based on the structural design of the original connecting rod, the finite element analysis was conducted to reduce the weight and increase the natural frequencies, so as to reduce materials consumption and improve the energy efficiency of internal combustion engine.

The finite element analysis, structural optimization design and topology optimization of the connecting rod are applied. Efficient hybrid method is deployed: static and modal analysis; and structure re-design of the connecting rod based on topology optimization.

After the optimization of the connecting rod, the weight is reduced from 1.7907 to 1.4875 kg, with a reduction of 16.93%. The maximum equivalent stress of the optimized connecting rod is 183.97 MPa and that of the original structure is 217.18 MPa, with the reduction of 15.62%. The first, second and third natural frequencies of the optimized connecting rod are increased by 8.89%, 8.85% and 11.09%, respectively. Through the finite element analysis and based on the lightweight, the maximum equivalent stress is reduced and the low-order natural frequency is increased.

This paper presents an optimization method on the connecting rod structure. Based on the statics and modal analysis of the connecting rod and combined with the topology optimization, the size of the connecting rod is improved, and the static and dynamic characteristics of the optimized connecting rod are improved.

The study aims to develop and test a supply chain wide green product development framework of focal firms and their major suppliers, in the context of the Chinese automotive industry.

An in-depth case studies approach is adopted for this study. Three automotive sector upstream supply chains involving 17 firms and 51 experts as respondents were interviewed on the importance and implementation effectiveness of 6Rs (reduce, redesign, recover, remanufacture, reuse and recycle) across the manufacturer and their respective tier 1 and tier 2 suppliers.

The results indicate that the Chinese automotive sector supply chains are mainly focused on “reduce” practices with immediate environmental and economic benefits. The investigated firms however had future implementation plans for “redesign” and “recovery” practices to become comprehensive in green product development (GPD).

The study facilitates automotive firms, industry policymakers and researchers the understanding of incorporating comprehensive GSCM practices across the upstream supply chain to achieve circularity. The study focused on upstream supply chain due to the concentration of major production practices in this section of the supply chain. However, the downstream supply chain equally deserve attention as well as the need to understand the mediating and moderating roles of the different Rs to tease out the pros and cons of achieving overall environmental sustainability.

There are very limited studies on comprehensive GPD for achieving optimal GSCM and sustainability. By simultaneous looking at a focal firm and its upstream supply chains GSCM practices, this study addresses a system-wide comprehensive GPD issues from implementation of 6Rs perspectives in the supply chain.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

The purpose of this study is to examine how the quality management of small and medium-sized enterprises (SMEs) impacts their supply chain financing performance (SCFP). This study also investigates the mediating roles of organisational dependence between quality management and the SCFP of SMEs, as well as the moderating role of environmental dynamics.

Questionnaires were administered to 248 financial managers responsible for supply chain finance (SCF) in SMEs in China. Data analysis techniques used include necessary condition analysis and multiple regression analysis.

Research findings show that, in SCF, the quality management of SMEs positively predicts their SCFP through the mediation of the organisational dependence of the focal enterprises in the supply chain network. Environmental dynamics are also found to moderate the relationship between quality management and SCFP through the organisational dependence of capital providers.

To the best of our knowledge, this is the first study to explore the relationships between SMEs' quality management and their SCFP. Also, this study provides a new theoretical lens through which to study SCF by introducing signalling theory.