Purpose: Over the last few decades, more emphasis has been placed on those innovations that can reconcile economic, social and environmental goals in order to achieve a “win-win-win” situation. This paper aims to systematise the scientific literature on Sustainable Innovation as a broad field in order to identify the most relevant scholars and their significant contributions as well as existing lines of research. Finally, future research directions are suggested.Design/methodology/approach: A novel methodology, the Systematic Literature Network Analysis, has been applied. By using a dynamic approach to the traditional Systematic Literature Review, the present review investigates the creation, transfer, and development of knowledge throughout the epistemic community of Sustainable Innovation.Findings: Starting from a sample of 1,108 articles, the critical assessment of the results detected five main themes: (1) “the role of Regulation, Market and Technology”; (2) “Eco-Innovation determinants and firm specific factors and the debate between corporate environmental performance and corporate financial performance”; (3) “Green innovation and internal and external drivers”; (4) “The strategic determinants of green (non-green) innovation”; (5) “The interplay between policy, regulations and the green innovation”.Practical implications: From a practitioner's perspective, this study provides an objective view on the current internal, external drivers and strategic determinants of sustainability-oriented innovations and relevant studies that can guide managers in their decision-making processes and enhance sustainable innovation performance.Originality/value: This study is a first attempt to unveil the evolution of knowledge in the field of sustainable innovation by utilizing bibliometric tools.

The purpose of this review is to describe the landscape of scientific literature enriched by an author’s keyword analysis to develop and test blockchain’s capabilities for enhancing supply chain resilience in times of increased risk and uncertainty. This review adopts a dynamic quantitative bibliometric method called systematic literature network analysis (SLNA) to extract and analyze the papers. The procedure consists of two methods: a systematic literature review (SLR) and bibliometric network analysis (BNA). This paper provides an important contribution to the literature in applying blockchain as a key component of cyber supply chain risk management (CSRM), manage and predict disruption risks that lead to resilience and robustness of the supply chain. This systematic review also sheds light on different research areas such as the potential of blockchain for privacy and security challenges, security of smart contracts, monitoring counterfeiting, and traceability database systems to ensure food safety and security.

The debate about Circular Economy (CE) has been increasingly enriched by academics through a vast array of contributions, based on several theoretical perspectives and emanating from several research domains. However, current research still falls short of providing a holistic and broader view of CE, one that combines existing themes and emerging research trends. Accordingly, based on a Systematic Literature Network Analysis, this paper tackles this gap. First, a Citation Network Analysis is used to unearth the development of the CE literature based on papers’ references, whilst the Main Path is traced to detect the seminal papers in the field through time. Second, to consider the literature in its broader extent, a Keywords Co-Occurrence Network Analysis is conducted based on papers’ keywords, whereby all papers in the dataset, including the non-cited papers, are assessed. Additionally, a Global Citation Score analysis is conducted to uncover the recent breakthrough research, in addition to the Burst Analysis used to detect the dynamic development of CE literature over time. By doing so, the paper explores the development of the CE body of knowledge, reveals its dynamic evolution over time, detects its main theoretical perspectives and research domains, and highlights its emerging topics. Our findings unfold the evidence of eight main trends of research about CE, unearth the path through which the CE concept emerged and has been growing, and concludes with promising avenues for future research.

Over the last few years, the increasing level of cyber risks derived from the growing connectedness of Industry 4.0 has led to the emergence of blockchain technology as a major innovation in supply chain cybersecurity. The main purpose of this study is to identify and rank the significant barriers affecting the implementation of blockchain technology as a key component of cyber supply chain risk management (CSCRM). This research relied on the “interpretive structural modeling (ISM)” technique in the structure of a hierarchical model to investigate the contextual relationships of identified challenges for blockchain adoption in CSCRM; it also classifies the influential challenges based on their driving and dependence powers. The results highlight that “cryptocurrency volatility” is the challenge at the top level of the hierarchy, implying weak driving power but it is strongly dependent on the other challenges. “Poor regulatory provisions”, “technology immaturity”, “dependent on input information from external oracles”, “scalability and bandwidth issues”, and “smart contract issues” are significant challenges for the adoption of blockchain in cyber supply chain risk management and are located at the bottom level of the hierarchy with higher driving power. The implications for theory and practice of the research are also highlighted.

This work examines the bullwhip effect generated and suffered by each level of a four-stage beer game supply chain when different demand scenarios are considered. The paper shows that the actors who generate lower bullwhip are those who suffer more from its effects. Moreover, a new definition of an inventory oscillations measure based on bullwhip definition is introduced. Finally the paper verifies that the new measure of inventory oscillations provides more information on supply chain performance than the bullwhip measure.

The aim of this study is to investigate the body of literature on digital twins, exploring, in particular, their role in enabling smart industrial systems. This review adopts a dynamic and quantitative bibliometric method including works citations, keywords co-occurrence networks, and keywords burst detection with the aim of clarifying the main contributions to this research area and highlighting prevalent topics and trends over time. The analysis performed on citations traces the backbone of contributions to the topic, visible within the main path. Keywords co-occurrence networks depict the prevalent issues addressed, tools implemented, and application areas. The burst detection completes the analysis identifying the trends and most recent research areas characterizing research on the digital twin topic. Decision-making, process design, and life cycle as well as the enabling role in the adoption of the latest industrial paradigms emerge as the prevalent issues addressed by the body of literature on digital twins. In particular, the up-to-date issues of real-time systems and industry 4.0 technologies, closely related to the concept of smart industrial systems, characterize the latest research trajectories identified in the literature on digital twins. In this context, the digital twin can find new opportunities for application in manufacturing, control, and services.