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The competitiveness of mining regions largely depends on the performance of the regional supply chains that provide services to mining companies. These local supply chains are often highly intertwined and represent a regional supply network for the industry. Individual companies often use supply chain strategies that are sub-optimal to overall supply network performance. To effectively respond to an uncertain business environment, policy-makers and supply chain participants would benefit by a governance framework that would allow to incentivise the formation of supply networks structures enabling effective operations. The purpose of this paper is to offer an empirically grounded conceptual framework based on Complex Adaptive Systems (CASs) governance principles, which links network governance mechanisms with supply network structure and operational performance to incentivise the formation of adaptive and resilient supply networks in the mining industry.

A mixed method research design and a case study of the South Australian mining sector were used to collect empirical data. Qualitative interviews and network analysis of the SA mining industry regional supply network structure were conducted. The relationships between network parameters were interpreted using CAS theory.

An empirically grounded conceptual framework based on CAS governance principles is developed. The case study revealed that supply chain strategies and governance mechanisms in the SA mining industry have led to the formation of a hierarchical, scale-free structure with insufficient horizontal connectivity which limits the adaptability, responsiveness and resilience of the regional supply network.

The findings are drawn from a single case study. This limits generalisability of the findings and the proposed framework.

The proposed framework draws the attention of the policy-makers and supply chain participants towards the need for utilising CAS governance principles to facilitate the formation of adaptive, responsive and resilient regional supply networks in the mining industry.

The proposed conceptual framework is an attempt to parameterise the governance of the regional supply networks in the mining industry.

Megaprojects present an intricated pattern of leadership activities, which evolve over their planning and delivery and comprises several stakeholders. A framework is useful to navigate this complexity; it allows to identify and cluster the key elements. This paper aims to introduce a novel framework based on boundary spanners to describe the structural pattern of shared leadership in megaprojects.

A systematic literature review about boundary spanning and shared leadership is used to identify and cluster the key elements of shared leadership in megaprojects. The systematic literature review provides a rich theoretical background to develop the novel shared leadership framework based on boundary spanners.

There are three key dimensions characterizing shared leadership topology in megaprojects: stakeholders, boundary spanning leadership roles and project phases. The novel framework shows how project leadership dynamically transfers among different stakeholders, showing the importance of shared leadership as a leadership paradigm in megaprojects.

The novel framework epitomizes shared leadership in megaprojects by exploring its antecedents with social network metrics. This paper stresses that shared leadership is the envisaged form of leadership in megaprojects. By modeling complex project leadership in a simple, yet effective way, the framework fosters critical thinking for future research. The modeling introduced by this framework would also benefit practitioners in charge of megaprojects.

The paper moves the project leadership research to the network-level by taking boundary spanners as shared leadership roles in megaprojects. It shows how shared leadership is a valuable management tool for planning and delivery megaprojects.

This paper aims to propose an empirically grounded governance framework based on complex adaptive systems (CAS) principles to facilitate formation of well-connected regional supply chains that foster economic development, adaptability and resilience of mining regions.

This study is an exploratory case study of the South Australian (SA) mining industry that includes 38 semi-structured interviews with the key stakeholders and structural analysis of the regional supply network (RSN).

Findings demonstrate the applicability of the CAS framework as a structured approach to the governance of the mining industry regional supply chains. In particular, the findings exemplify the relationship between RSN governance, its structure and interconnectivity and their combined impact on the adaptability and resilience of mining regions.

The data set analysed in the current study is static. Longitudinal data would permit a deeper insight into the evolution of the RSN structure and connectivity. The validity of the proposed framework could be further strengthened by being applied to other industrial domains and geographical contexts.

The proposed framework offers a novel insight for regional policy-makers striving to create an environment that facilitates the formation of well-integrated regional supply chains in mining regions through more focussed policy and strategies.

The proposed framework is one of the first attempts to offer a holistic structured approach to governance of the regional supply chains based on CAS principles. With the current transformative changes in the global mining industry, policy-makers and supply chain practitioners have an urgent need to embrace CAS and network paradigms to remain competitive in the twenty-first century.

Based on the emerging view of supply chains as complex adaptive systems, this paper aims to build and test an analytical model for resilience assessment surrounding supply chain risks at the level of the supply chain system and its individual tiers.

To address the purpose of this study, a multimethod research approach is adopted as follows: first, data envelopment analysis (DEA) modelling and fuzzy set theory are used to build a fuzzy network DEA model to assess risk resilience of the overall supply chains and their individual tiers; next, the proposed model is tested using a survey of 150 middle- and top-level managers representing nine industry sectors in Iran.

The survey results show a substantial variation in resilience ratings between the overall supply chains characterizing nine industry sectors in Iran and their individual tiers (upstream, downstream and organizational processes). The findings indicate that the system-wide characteristic of resilience of the overall supply chain is not necessarily indicative of the resilience of its individual tiers.

High efficiency scores of a number of tiers forming a supply chain are shown to have only a limited effect on the overall efficiency score of the resulting supply chain. Overall, our research findings confirm the necessity of adopting both the system-wide and tier-specific approach by analysts and decision makers when assessing supply chain resilience. Integrated as part of risk response and mitigation process, the information obtained through such analytical approach ensures timely identification and mitigation of major sources of risk in the supply chains.

Supply chain resilience assessment models rarely consider resilience to risks at the level of individual supply chain tiers, focusing instead on the system-wide characteristics of supply chain resilience. The proposed analytical model allows for the assessment of supply chain resilience among individual tiers for a wide range of supply chain risks categorized as upstream, downstream, organizational, network and external.

The study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely, vulnerabilities, capabilities, strategies and performance metrics. The analysis also revealed various influential authors, journals, institutions and trending articles, across SCRES literature.

This study performs a bibliometric analysis of 771 articles published over the 32 years from 1988 to 2020, and network analysis in combination with content analysis of 90 most cited articles published in research fronts of SCRES.

The results demonstrate the underlying research areas within the SCRES, which are clustered into nine research themes: (1) conceptual development of SCRES, (2) recent developments of designing resilient supply chain (SC) networks, (3) focus on identifying drivers of SC vulnerability and risks, (4) impact of risks on network resilience, (5) risk assessment to avoid breakdowns/disruptions, (6) measuring resilience approaches/drivers to improve SC performance, (7) building resilient capabilities by integrating other SC dimensions, (8) quantification of SC network and (9) emphasis on developing robustness in SC networks.

This research offers implications for classifying the works in literature based on bibliometric information and network analysis techniques. This can help researchers and practitioners to understand the prominent areas in SCRES and provide guidelines for future research in this area.

This study provides an overview of the evolution of SCRES over time in the domain of supply chain management and also outlines a future research agenda claimed by the trending articles to encourage further investigations in the field of SCRES.

The purpose of this paper is to promote social network analysis (SNA) methodology within the humanitarian research community, surveying its current state of the art and demonstrating its utility in analyzing humanitarian operations.

A comprehensive survey of the related literature motivates a proposed agenda for interested researchers. Analysis of two humanitarian networks in Afghanistan demonstrates the use and utility of SNA, based on secondary data. In the second case study, the use of random graphs to detect network motifs is demonstrated using Monte Carlo simulation to create the benchmark null sets.

SNA is an adaptable and highly useful methodology in humanitarian research, quantifying patterns of community structure and collaboration among humanitarian organizations. Network motifs suggesting distinct affinity between particular agencies within humanitarian clusters are observed.

The authors summarize common challenges of using SNA in humanitarian research and discuss ways to alleviate them.

Practitioners can use SNA as readily as researchers, to visualize existing networks, identify areas of concern and better communicate observations.

By making SNA more accessible to a humanitarian research audience, the authors hope its ability to capture complex, dynamic relationships will advance understanding of effective humanitarian relief systems.

To the best of knowledge, it is the first study to conduct a systematic analysis of the application of SNA in empirical humanitarian research and outline a concrete SNA-based research agenda. This is also a currently rare instance of a humanitarian study using random graphs to assess observed SNA measures.

Benefits of modularity are being limited by the lack of agreement over terminology. Neither researchers nor managers use the same typology, complicating comparisons of modular strategies.

Presents existing problem, then develops comprehensive and necessary typology. Examples illustrate practical use of the typology, and help reader understand implications on product design and future research.

Development of modularity typologies, including their characteristics and implications for product design and production systems, has been minimal. A well‐defined typology for soft modules exists, but literature on categorization of hard modules is limited. Most existing definitions of modularity are related to a common type called manufacturing modularity.

Each type of modularity is characterized by a different set of design attributes. For example, appearance, durability, and ergonomics are important for product‐use modularity, while accessibility, recycling and cost are key considerations for limited life modularity. Designers must understand these different characteristics in order to design products that address relevant customer needs such as cost, customization, serviceability and upgradeability that can give product a competitive edge in the marketplace. When developing individual modules, focus on core characteristics of that module type. When developing a multiple module type product, balance characteristics of the interdependent module types in order to ensure that the product meets customer needs.

Four types of modularity are defined: manufacturing, product‐use, limited life and data access. New products often incorporate all four types in order to address both the needs of the customers as well as the manufacturer.

The objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.

The research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.

The synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.

The two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single region

New Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.

The use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

The purpose of this paper is twofold. First, the author aims to explore if there is a curvilinear relationship between the network rent, generated as a combination of the relational performance of two dyads and the network profile of the triadic supply chains. Second, the author seek to recognize the ideal network profile, consisting of the properties at the node and relationship level, that provides the highest network rents, and thus enables to increase the competitive advantage of supply chains.

The paper opted for an exploratory study using a survey of triads forming supply chains. In order to reveal the capability of yielding the network rent in the examined triads, multiple regression analysis with interaction effects was employed. Having confirmed the existence of supernormal profit, the author investigated the relationship between the network rent and the network index. Finally, a cluster analysis was conducted to compare the network profile in the group of triads generating higher network rents with the cluster yielding relatively lower network rents.

The obtained findings show that a combination of the relational performance of two dyads contributes to generating the network rent, and thus ensures a more favorable competitive position of supply chains. The results of the study also indicate that there is a significant curvilinear, inverted U-shaped relationship between the network profile and the competitive advantage of triadic supply chains. In addition, the following network properties appear to be particularly important for yielding higher network rents: network centrality, betweenness, network density and network size.

The study contributes to the theory by testing if the network rent can be yielded as a combination of the relational performance of two dyads in the triadic supply chains. The research also indicates that there is a curvilinear relationship between the network rent and the network profile of examined supply chains. Moreover, the study also addresses the link between the network profile, consisting of the multiple network properties simultaneously, in relation to the competitive advantage of supply chains.

The purpose of this paper is to systematically review, synthesize and critically evaluate the current research status on the role of collaborative interorganizational relationships (CIRs) in supply chain risks (SCRs) from a social capital perspective and provide an organizing lens for future scholarship in this area.

This study adopts a systematic literature review approach to investigate 126 articles from 27 peer-reviewed journals between 1995 and 2020.

This paper investigates supply chain CIRs using a social capital perspective to explain the role of structural, relational and cognitive capital that resides in these relationships in various SCRs (i.e. environmental, supply, manufacturing, demand, information, financial and transportation). The review reveals that the three social capital dimensions uniquely and both positively and negatively affect different SCRs. The findings further suggest that the perceived SCRs can influence the structural and relational capital.

This study calls for practitioners to consider the cognitive alignment with their supply network partners, their relational investments, as well as the interorganizational processes and systems in managing and alleviating SCRs.

This review offers a theoretical articulation of how various aspects of CIRs affect SCRs. Specifically, this study extends the existing understanding of the role of social capital in SCRs through offering a synthesis of dominant findings and discourses, and avenues for future research.