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The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

While the literature on multitier supply chain management traditionally assumes that first-tier suppliers belong to the visible proportion of the supply base, intermediaries might limit focal firms' visible horizon already at this stage. High power asymmetries promoting centrality and complexity in the supply network are seen as a particular root cause that limits the impact of governance mechanisms for sustainability. To map the space for governance mechanisms in a network-sensitive context more comprehensively, the study analyzes supply network characteristics from a power perspective.

This research is conceptual. To better understand power imbalances and mutual dependencies from network centrality and complexity, network configurations were constructed drawing on resource dependence theory. These configurations allow deducing the impact of (non-)mediated governance mechanisms for a sustainable development in the supply network. An agenda to stimulate future empirical and model-based research is accordingly presented.

The research shows that those networks with densely interconnected first-tier suppliers promote network centrality and complexity, leading to an inverted U-shape relationship between the focal firm's exertion of coercive power and the sustainability performance in the supply network. The findings allow a more comprehensive theoretical grounding for mapping governance approaches in a network-sensitive context and provide insights on how to avoid negative effects from power asymmetries.

The findings suggest the need for accompanying, indirect governance mechanisms already at the stage of first-tier suppliers based on non-mediated forms of power, such as referent power, also promoting disintermediation. Purchasing companies may also consider using digital platform technologies that foster disintermediation, such as blockchain technology.

By studying intermediaries from a power and network perspective, the conceptualization adds to the discussion on governance in multitier sustainable supply chain networks in various industries. Furthermore, it contributes to the increasing efforts of middle-range theorizing in logistics and supply chain management. The results partially challenge previous assumptions on the moderating role of specific network characteristics.

Catastrophic supply chain disruptions can significantly damage the operational and financial performance of firms. While a growing body of literature on supply network structures has studied what influences supply networks' vulnerability to supply chain disruptions and capability to recover from them, it remains unclear how supply network structures change after major supply chain disruptions. We aim to provide an understanding of how these changes occur.

Using a natural experiment approach and supply network data from Factset, this study investigates how firms' supply network structures change after experiencing the catastrophic supply chain disruptions caused by the 2011 Tohoku earthquake and tsunami in Japan. We capture post-earthquake supply network changes using the measures of degree centrality and ego network density.

The results of the analysis suggest that compared to unaffected firms, the affected firms experience changes in their supply network structures tending toward lower complexity measured by in-degree centrality, out-degree centrality and ego network density.

This study contributes to social network theory and the complex adaptive supply network literature by providing empirical evidence of structural changes in supply networks after catastrophic supply chain disruptions. A managerial contribution is made by providing a reflection on why these changes might be occurring and alert firms to the challenges of managing complexity in their supply networks.

This paper considers supply chain management organizations with the aid of 'chaotic systems theory' developed originally in physics and mathematics. Since innovations in supply chain management are vital for organizational survival 'complex systems theory' may assist in fine-tuning managerial philosophies that provide stability in supply chain management because it is on the boundary of chaos that the greatest innovational creativity occurs. Neither 'management by rigid objectives' (MBO) nor 'management by instruction' (MBI) will be suitable for the information society of the twenty-first century because chaotic social systems will no longer be effectively managed. However, the capacity for self-organization will be derived essentially from how supply chain management members accept a shared set of values or principles for action-'management by values' (MBV). Complex systems theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organizes is attributable to the appearance of the 'strange attractor' and provides the ideal basis for creativity and innovation in the twenty-first century. In the self-organized state of chaos, social members are not confined to narrow roles and gradually develop their capacity for differentiation and relationships, growing progressively towards their maximum potential contribution to the efficiency of the organization. In this meaning, values act as organizers of 'attractors' of disorder, which, in the theory of chaos, are systems represented by usually regular geometric configurations that predict the long-term behavior of complex systems. In supply chain management organizations (as in all kinds of social systems) the initial principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of the system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is heading based on its rules of motion. In supply chain management organizations that cultivate or shares values of autonomy, responsibility, independence, innovation, creativity, and proactivity, the risk of short-term chaos is mitigated by external complexities that organizations are currently confronting. The strategy is to alter the supply chain management's surroundings so that they can benefit from management by values (MBV).

The purpose of this research work is to examine the financial effect of supply chain disruptions (SCDs) caused by coronavirus disease 2019 (COVID-19) and how the magnitude of such effects depends on event time and space that may moderate the signaling environment for shareholder behaviors during the pandemic.

This study analyses a sample of 206 SCD events attributed to COVID-19 made by 145 publicly traded firms headquartered in 21 countries for a period between 2020 and 2021. Change in shareholder value is estimated by employing a multi-country event study, followed by estimating the differential effect of SCDs due to the pandemic by event time and space.

On average, SCDs due to pandemic decrease shareholder value by −2.16%, which is similar to that of pre-pandemic SCDs (88 events for 2018–2019). This negative market reaction remains unchanged regardless of whether stringency measures of the firm's country become more severe. Supply-side disruptions like shutdowns result in a more negative stock market reaction than demand-side disruptions like price hikes. To shareholder value, firm's upstream or downstream position does not matter, but supply chain complexity serves as a positive signal.

This study provides the first empirical evidence on the financial impact of SCDs induced by COVID-19. Combining with signaling theory and event system theory, this study provides a new boundary condition that explains the impact mechanism of SCDs caused by the pandemic.

A low-carbon economy is the pressing need of the hour. Despite several efforts taken by the government and large corporations, there is still research to be conducted exploring the role of top management commitment in translating external pressures into responses that help to build low-carbon emissions in supply chains.

The authors have grounded their framework in institutional theory, agency theory and contingency theory. On the basis of existing literature, four hypotheses were drawn. To test these hypotheses, a questionnaire was developed and pre-tested. Finally, statistical analyses were performed to test the research hypotheses using 176 samples gathered using a pre-tested questionnaire following Dillman’s (2007) total design test method.

The results suggest that coercive pressures and mimetic pressures under the mediating effect of top management commitment have a significant influence on organizational response to low-carbon emissions. The authors further note that supply base complexity has moderating effects on the link between top management commitment and organizational response towards low-carbon emissions.

This study offers valuable insights to those managers and environmental consultants who view supply base complexity as a limitation. However, the results indicate that supply base complexity may help to enhance the effectiveness of the top management commitment on organizational response towards low-carbon emissions.

The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.

The purpose of this paper is to elaborate on how perspectives and assumptions embedded in the complexity paradigm contribute to make logistics management research better aligned with real-life logistics. This is necessary, due to increasing supply chain complexity caused by an increasing request for sustainable development (SD).

The research is exploratory and based on a narrative literature review of logistics and supply chain management (SCM) from a complexity science perspective. Qualitative research interviews have been conducted with 12 logistics and supply chain managers in international companies and have focussed on their daily experiences and the underlying assumptions related to their actual work.

Logistics and SCM research is embedded in the functionalistic paradigm with reductionistic assumptions as the dominant logic. These do not sufficiently align with the complexity related, for example, to the daily work of SD in logistics management practice.

It is proposed that the inclusion of complexity-based assumptions in logistics management research can increase realism in the advancement of the discipline. A key result is that the recognition of logistics as complex means inclusion of human and social aspects – which is apparent in any logistics process or phenomenon – in logistics knowledge creation processes.

Increased realism in logistics management research by addressing complexity, instead of merely reducing it, will provide logistics and supply chain managers with increased understanding and appropriate knowledge when they deal with emerging challenges such as SD.

Based on Boulding’s levels of complexity, this paper challenges the underlying assumptions of logistics management in research and practice, and provides reflective frameworks for advancing the discipline and aligning it to the complexity of contemporary challenges in logistics management.

The coronavirus disease (COVID-19) pandemic has emerged as an unprecedented health crisis worldwide and heavily disrupted the healthcare supply chain. This study focuses on analysing the different types of disruptions occurring in personal protective equipment (PPE) supply chains during the COVID-19 pandemic and on proposing mitigation strategies that are fit to the global scale and many interdependencies that are characteristic for this pandemic. The authors construct a conceptual system dynamics model (SD) based on the literature and adjusted with the use of empirical data (interviews) to capture the complexity of a global supply chain and identify leverage points (mitigation strategies).

This research follows a mix-methods approach. First, the authors developed a conceptual framework based on four types of disruptions that usually occur during health emergencies (direct effect, policy, supply chain strategy, and behaviourally induced disruptions). Second, the authors collected and analysed data from interviews with experts in the PPE supply chain. Based on the interviews data, the authors developed a conceptual system dynamics (SD) model that allows to capture the complex and dynamic interplay between the elements of the global supply chain system, by highlighting key feedback loops, delays, and the way the mitigation strategies can impact on them. From this analysis, the authors developed four propositions for supply chain risk management (SCRM) in global health emergencies and four recommendations for the policy and decision makers.

The SD model highlights that without a combination of mitigation measures, it is impossible to overcome all disruptions. As such, a co-ordinated effort across the different countries and sectors that experience the disruptions is needed. The SD model also shows that there are important feedback loops, by which initial disruptions create delays and shortages that propagate through the supply chain network. If the co-ordinated mitigation measures are not implemented early at the onset of the pandemic, these disruptions will be persistent, creating potential shortages of PPE and other critical equipment at the onset of a pandemic – when they are most urgently needed.

This research enriches the understanding of the disruptions of PPE supply chains on the systems level and proposes mitigation strategies based on empirical data and the existing literature.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.