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This study aims to propose a framework for the development of implementation guidelines (IGs) that can help consultants mitigate not-invented-here (NIH) syndrome during a consultant intervention as a specific type of knowledge transfer.

The authors adopted a design science research approach for proposing an NIH-mitigating IG development framework. Inspired by findings and rich primary data from two consultant interventions, the authors, through theory building, ground five core principles in the general theory of NIH attitude functions. Finally, the authors revisit two consultant interventions to identify and describe mechanisms that led to the enactment of the principles.

The proposed framework provides five principles for developing NIH-mitigating IGs. The present research proposes that successful knowledge transfer and the mitigation of NIH syndrome as a prerequisite for this success are conditioned by adequately developed IGs.

The originality and value of the present research lie in the proposed NIH-mitigating IG development framework containing a set of principles for IG development as a proactive rather than reactive approach to NIH mitigation. To the best of the authors’ knowledge, this is the first research to address the problematics of mitigating NIH syndrome in consultant knowledge transfer by focusing on developing appropriate IGs. By developing and implementing IGs based on the proposed framework, a more successful transfer of knowledge from consultants to clients should take place, thus, increasing the value that clients receive from consultancy.

Building information modelling (BIM) claims to be spearheading the modern technological revolution in the global construction industry. While scholars have emphasised the cruciality of BIM, associated costs have been identified as one of the major barriers to successful BIM implementation, as is the case in Sri Lanka. Besides, lean principles (LPs) are known for increasing efficiency, quality and eliminating waste, thereby reducing overall costs. Hence, this research aims at addressing the BIM implementation barrier associated with costs by applying suitable LP, enhancing overall value by minimising value-insignificant activities.

The study adopted a qualitative research approach. 10 experts with expertise in both BIM and LP were targeted for the primary data collection through semi-structured interviews. The collected data were analysed using manual content analysis.

Research findings discovered the cost centres that can be applied to the LPs and the effective LPs that can be applied with the cost centres of BIM implementation. The theoretical implication of the study is to provide insights into a potential application of LP for BIM cost centres, whereas practical consequences include the identification of LP's potential to minimise BIM cost centres, ergo, achieving a successful BIM implementation.

This study will be the first of its kind in the Sri Lankan construction industry, intending to apply LP with BIM implementation cost centres to achieve a successful implementation. This research also has paved the way forward for further research on the application of both the BIM and LP concepts for similar construction industries in developing countries across the world and in addressing other BIM implementation barriers.

This paper aims to explore the intellectual structure shaping the circular economy (CE) discourse within the built environment in Africa.

The study adopted a bibliometric analysis approach to explore the intellectual structure of CE in the built environment in Africa. The authors collected 31 papers published between 2005 and 2021 from the Scopus database and used VOSviewer for data analysis.

The findings show that there are six clusters shaping the intellectual structure: demolition, material recovery and reuse; waste as a resource; cellulose and agro-based materials; resilience and low-carbon footprint; recycling materials; and the fourth industrial revolution. The two most cited scholars had three publications each, while the top journal was Resources, Conservation and Recycling. The dominant concepts included CE, sustainability, alternative materials, waste management, lifecycle, demolition and climate change. The study concludes that there is low CE research output in Africa, which implies that the concept is either novel or facing resistance.

The data were drawn from one database, Scopus; hence, adoption of alternative databases such as Web of Science, Google Scholar and Dimensions could potentially have yielded a higher number of articles for analysis which potentially would result in different conclusions on the subject understudy.

This study made a significant contribution by articulating the CE intellectual structure in the built environment, identified prominent scholars and academic platforms responsible for promoting circularity in Africa.

This research aims to investigate how adaptability potential analysis in collaborative manufacturing networks can be used to enhance resilience when addressing innovative production challenges that require change initiatives.

A literature review on collaborative adaptive systems showed a lack of solutions to adapt production to an unpredicted product within a network. A framework is proposed for evaluating the adaptability of collaborative networks and providing inter-system adaptation recommendations. We demonstrate the applicability of this approach through an illustrative experimentation involving a cosmetic company seeking to produce a new product, hydroalcoholic gels in the context of collaborative networks.

The experimentation demonstrates that the adaptability analysis based on ontology can help different manufacturing systems make decisions based on their state and limits of capabilities. Also, our adaptation recommendations may help understand the economic impacts of collaboration for different scenarios before launching.

The research scope does not extend to the consideration of quantity and operational aspects. Additionally, the reconfigurability aspects within each manufacturing system, such as the reordering of layout sequences, have not been addressed yet.

The results allow organizations to compare resilience states from an individual and collaborative perspective, enabling them to make informed decisions about new production opportunities and effectively navigate the changing manufacturing landscape.

This research combines capability-based analysis and a collaborative network perspective to streamline decision-making for systems facing new production demands. It provides new insights into effectual decision-making, empowering organizations to skilfully manage unexpected challenges and identify suitable partners accordingly.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

This paper aims to analyze the importance of big data analytics (BDA) and supply chain analytics for sustainable supply chain management in all types of enterprises in the footwear industry. The importance and implementation of BDA in supply chain management have been discussed in this research paper, and a conceptual framework is proposed for the implementation.

The previous research indicates that the application of BDA and supply chain analytics is the key point to establishing sustainable supply chain management. Even though there are several types of research on the implications of BDA, there is still a gap in practical implications in organizations. For a better understanding, comparison of frameworks has been done for literature support. Further, 11 in-depth, semi-structured interviews have been conducted with four organizations from the footwear industry, and a conceptual framework has been proposed.

This research demonstrates an important gap in the literature through a thorough investigation of how firms can improve operational efficiency and productivity through the framework application and whether it is feasible to apply this within the global footwear industry or not. In conclusion, the research has denoted that despite lack of understanding related to sustainability agendas and not having proper ERP or BDA systems, the organizations operating in Pakistan still met some standards of sustainability and are moving toward achieving more.

The research has pointed out the importance of the integration of all stakeholders in the supply chain through a proposed framework that aligns and guides the stakeholders so that the policies and other constraints may be taken into consideration while revising sustainable supply chain strategies.

This study will help increase sustainability through the application of BDA technology, which will benefit various stakeholders, particularly those in the footwear industry.

This study has proposed a framework based on three stages of the implementation of BDA in the existing supply chain to maintain and achieve sustainability in the organization in the footwear industry. This three-stage framework covers many aspects that were not covered in the literature before.

We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

This chapter discusses the empirical data analysis that will form the basis of the early pricing framework. It focusses on the complexity of furniture production and describes the historical production data collected from companies, along with the potential applications of machine learning for knowledge management purposes. The chapter then presents the results of machine learning for early cost estimation as part of a lean innovation that is affordable and accessible for small and medium-sized enterprises (SMEs). Finally, the chapter describes an experiment on the structured expert evaluation methodology, which shows that a well-formed panel of experts can increase the predictive power of machine learning solutions, particularly at extreme points.

Despite endeavors to alleviate construction and demolition waste and the indications that the process of deconstruction has the potential to steer waste reduction initiatives, there has not been a progressive increase in the adoption of Design for Deconstruction (DfD) in the global south, especially Ghana. This paper aims to identify and analyze the barriers to implementing DfD in developing countries.

A structured questionnaire survey was used to solicit the views of 240 design professionals in the Ghanaian construction industry (GCI). The questionnaire was developed by reviewing pertinent literature and complemented with a pilot review. Data were analyzed using descriptive and nonparametric statistics.

The findings revealed ten (10) significant impediments to implementing DfD within the construction industries in developing economies. These impediments revolve around cost, legal matters, storage, incentive and design-related matters. Key among these barriers is “For recovered materials, there are little performance guarantees,” “The absence of strict regulations regarding design for deconstruction,” “Lack of a large market enough for components that have been recovered,” “The need for building codes that address how to design with reused materials” and “Lack of effective design for deconstruction tools.”

The results of this research shed light on a relatively unexplored area within the construction sector, particularly in a developing country like Ghana. Furthermore, to the best of the authors’ knowledge, the study contributes fresh and supplementary knowledge and perspectives regarding the challenges in implementing DfD practices.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.