Applications of blockchain technology in sustainable manufacturing and supply chain management: A systematic review

Developing sustainable products and processes is essential for the survival of manufacturers in the current competitive market and the industry 4.0 era. The activities of manufacturers and their supply chain partners should be aligned with sustainable development goals. Manufacturers have faced many barriers and challenges in implementing sustainable practices along the entire supply chain due to globalisation, outsourcing, and offshoring. Blockchain technology has the potential to address the challenges of sustainability. This study aims to explain the applications of blockchain technology to sustainable manufacturing. We conducted a systematic literature review and explained the potential contributions of blockchain technology to the economic, environmental, and social performances of manufacturers and their supply chains. The findings of the study extend our understanding of the blockchain applications in sustainable manufacturing and sustainable supply chains. Furthermore, the study explains how blockchain can influence the sustainable performance of manufacturers by creating transparency, traceability, real-time information sharing, and security of the data capabilities

Cross-docking: A systematic literature review

This paper identifies the major research concepts, techniques, and models covered in the cross-docking literature. A systematic literature review is conducted using the BibExcel bibliometric analysis and Gephi network analysis tools. A research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis are used to identify the primary research themes. The RFPN results suggest that vehicle routing, inventory control, scheduling, warehousing, and distribution are most studied. Of the optimization and simulation techniques applied in cross-docking, linear and integer programming has received much attention. The paper informs researchers interested in investigating cross-docking through an integrated perspective of the research gaps in this domain. This paper systematically reviews the literature on cross-docking, identifies the major research areas, and provides a survey of the techniques and models adopted by researchers in the areas related to cross-docking

Forecasting failure of information technology projects using an adaptive neuro-fuzzy inference system

The role of information technology (IT) applications has become critical for organisations in various sectors such as education, health, finance, logistics, manufacturing and project management. IT applications provide many advantages at strategic, management and operational levels, and the investment in IT applications is therefore growing; however, the failure rate of IT projects is still high, despite the development of theories, methodologies and frameworks for IT project management in recent decades. The consequences of failure of an IT project can be devastating, and can threaten the existence of an organisation. There are many different factors that impact on the performance of a project; these factors are varied and interrelated, and can impact project performance throughout the different phases of the project life cycle. The aims of this research are to (i) identify the critical failure factors (CFFs) of IT projects; (ii) categorise these CFFs; (iii) identify the relationships between CFFs; and (iv) develop a model using an adaptive neuro-fuzzy inference system (ANFIS) to forecast the failure of IT projects in the early stages. The primary data collection tool is a questionnaire, and the analysis is carried out with the ANFIS technique. ANFIS is a hybrid model that combines an artificial neural network (ANN) with learning algorithms and techniques, and uses fuzzy logic to extract fuzzy rules based on prior knowledge of past data. In this research, we develop 266 rules and then test the performance of the developed model using training data and checking data. In this way, the role structure of the ANFIS model is obtained, which can be used to forecast the failure of IT projects. The findings suggest that there are many failure factors that can impact negatively on the performance of IT projects. These factors can be categorised into organisational, project management, planning, project manager, project team, user/customer, technological and technical, and legal factors. The results show that CFFs related to the project team, planning and organisation have the highest impact on the failure of IT projects. The ANFIS model constructed here can help IT project managers to effectively address the risk associated with projects in the early phases and to forecast the failure percentage of IT projects. This research can enable managers and decision makers to predict failure early in the project, allowing them to take suitable decisions, and can provide policy makers with an innovative approach to enhance decision-making processe

Prioritizing critical failure factors of IT projects with fuzzy analytic hierarchy process

The role of Information Technology (IT) systems is critical for organizations in different sectors to increase their performance and profitability, hence, to achieve the strategic goals. However, failure rate of IT projects is still high despite the development of theories, methodologies and frameworks of IT project management in past decades. The aim of this paper is to (1) identify critical failure factors (CFFs) for IT projects, (2) classify CFFs based on their original source, and (3) prioritize CFFs using fuzzy analytic hierarchy process (FAHP). Findings provide project managers and practitioners with a framework that contributes in proper planning the project from the start. Trying to diagnose and solve the highly ranked CFFs minimizes the possibility of IT project failure. Results show that the main factors of project team and planning are the highest impact factors on IT projects performance, and critical failure factors (CFFs) of unstable organization environment and poor communication and reporting between project stakeholders are the most CFFs among all CFFs that impact significantly on IT projects and lead to projects’ failure

Industry 4.0 digital transformation and opportunities for supply chain resilience:a comprehensive review and a strategic roadmap

Despite interest in opportunities that Industry 4.0 offers for Supply Chain Resilience (SCR), little is known about the underlying mechanisms for such contributions. The study develops a roadmap that explains how supply chains can capitalize on Industry 4.0 SCR functions. The study conducted a content-centric literature review and identified 16 functions through which Industry 4.0 enhances SCR. Results reveal that the Industry 4.0 SCR functions identified are highly interrelated, and supply chain members should align their digitalization strategies with the sequence in which Industry 4.0 delivers these functions. Industry 4.0 contribution to SCR first involves delivering data-centric functions such as supply chain automation, information and communication quality, process monitoring, and visibility. Industry 4.0 further allows supply chain partners to collaborate better on improving supply chain mapping, complexity management, and innovation capabilities. Through these functions and by increasing transparency, flexibility, and agility of supply chain operations, Industry 4.0 delivers more dependent but consequential resilience functions such as supply chain responsiveness, adaptive capability, and continuity management. The roadmap further explains how each pair of Industry 4.0 SCR functions mutually interact while contributing to the overall resilience of the supply chain. The study discusses possible implications and outlines important avenues for future research

Blockchain technology as an enabler for sustainable business ecosystems: A comprehensive roadmap for socioenvironmental and economic sustainability

Blockchain technology is a core technology expected to play a highly instrumental role in competing with socioenvironmental challenges. The literature hypothesizes various blockchain functions for building a sustainable business ecosystem. This study unifies these diverse perspectives into an interpretive strategy roadmap that provides a holistic overview of how blockchain should be leveraged to deliver sustainability functions optimally. The study first identified the sustainability functions of blockchain through a content‐centric literature review. The study applied interpretive structural modeling (ISM) and drew on experts' opinions to model how and in which order blockchain delivers these sustainability functions. The study further drew on the ISM output and interpretive logic‐knowledge base to develop the promised roadmap. Results revealed that blockchain promotes a decentralized decision system that facilitates automation and real‐time information sharing (RIS) across supply chains. Blockchain introduces traceability and transparency into supply chain operations. These conditions offer monitoring of business operations and the development of trust across value‐chain stakeholders. These driver functions lead to value chain optimization and circularity integration into business and supply chain operations. When these necessary functional conditions are met, businesses can further draw on blockchain to promote economic and environmental aspects of sustainability through more complex functions enabling resource efficiency, cost reduction, pollution prevention, and higher profit margins. The order in which businesses can leverage these functions would define blockchain sustainability performance. Each function is uniquely valuable to sustainability, and none of them can be overlooked

Blockchain technology as an enabler for sustainable business ecosystems: A comprehensive roadmap for socioenvironmental and economic sustainability

Blockchain technology is a core technology expected to play a highly instrumental role in competing with socioenvironmental challenges. The literature hypothesizes various blockchain functions for building a sustainable business ecosystem. This study unifies these diverse perspectives into an interpretive strategy roadmap that provides a holistic overview of how blockchain should be leveraged to deliver sustainability functions optimally. The study first identified the sustainability functions of blockchain through a content‐centric literature review. The study applied interpretive structural modeling (ISM) and drew on experts' opinions to model how and in which order blockchain delivers these sustainability functions. The study further drew on the ISM output and interpretive logic‐knowledge base to develop the promised roadmap. Results revealed that blockchain promotes a decentralized decision system that facilitates automation and real‐time information sharing (RIS) across supply chains. Blockchain introduces traceability and transparency into supply chain operations. These conditions offer monitoring of business operations and the development of trust across value‐chain stakeholders. These driver functions lead to value chain optimization and circularity integration into business and supply chain operations. When these necessary functional conditions are met, businesses can further draw on blockchain to promote economic and environmental aspects of sustainability through more complex functions enabling resource efficiency, cost reduction, pollution prevention, and higher profit margins. The order in which businesses can leverage these functions would define blockchain sustainability performance. Each function is uniquely valuable to sustainability, and none of them can be overlooked