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As an effective mode to help small and medium enterprises (SMEs) raise working capital, supply chain finance has recently gained extensive attention. The purpose of this paper is to explore the intrinsic mechanism of how both weak and strong ties in the supply chain network impact the supply chain financing performance (SCFP) of SMEs from the perspective of the supply chain network.

Based on the extended resource-based perspective, this paper proposes a theoretical model to explain the mode in which strong ties and weak ties of SMEs in the supply chain network influence SCFP through both physical distribution flexibility and demand management flexibility. Based on data from 182 manufacturing firms in China, this paper uses multiple regression analysis to test hypotheses.

The results of this paper indicate that weak ties improve SCFP more effectively than strong ties. Furthermore, both physical distribution flexibility and demand management flexibility exert different mediating roles either between strong ties and SCFP or between weak ties and SCFP. Moreover, the effect of physical distribution flexibility and demand management flexibility on SCFP of SMEs is not reinforced.

This paper highlights the importance to expand supply chain finance research from the perspective of the supply chain network. In particular, this paper explores the poorly understood mediating effect both physical distribution flexibility and demand management flexibility exert on the relationship between network ties and the SCFP of SMEs.

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.

To explore the mechanism that shapes firms' supply chain learning (SCL) practices, this study examines the relationship between firms' knowledge network embeddedness and their SCL practice in a supply chain network, as well as the moderating role of supply chain network cohesion in this relationship.

Using patent application data and supply chain partner information from 869 listed firms between 2011 and 2020 in China, this study uses fixed-effect regression models to reduce endogeneity problems by controlling for individual heterogeneity effects that cannot be observed over time.

Firms' knowledge network embeddedness has an inverted U-shaped effect on their SCL, and this non-linear relationship is conditional on supply chain network cohesion, which strengthens (weakens) the positive (negative) effect of knowledge network embeddedness on SCL.

The findings show that managers can reconcile the downsides of knowledge network embeddedness on SCL by fostering greater supply chain network cohesion.

Drawing from the network pluralism perspective, this study contributes to supply chain literature by extending the research context of the antecedents of SCL from a single-network setting to a dual-network setting. It extends the network pluralism perspective by showing that not only positive effects but also negative effects of network embeddedness can transfer from one network to another.

The purpose of this research is to investigate the R&D investment (RDI) of manufacturing firms from the perspective of supply chain network, especially the effect of firms' supply chain network structures (network power and network cohesion) on its RDI, and further to explore the contingency conditions of this effect within the context of Chinese manufacturing supply chains.

The authors collect a large sample of Chinese manufacturing firms over the period 2014–2019 and construct a large-scale supply chain network, and finally obtain 2,390 firms from 20,483 observations. Ordinary least squares regression was adopted to analyse how supply chain network structures affect RDI in manufacturing firms.

It is surprising that firm's supply chain network structures have a negative effect on RDI. In addition, knowledge and technology intensity (KTI) positively moderate the relationship between network cohesion and RDI.

This study contributes to the innovation stream from the perspectives of supply chain network, and provides the empirical findings that the negative role of a firm's supply chain network structure on its RDI for the first time. The rationale for these negative effects is straightforward according to the social capital theory that manufacturing firms with a high level of social capital that are possibly to accept established patterns of thinking and behaviour, causing them to decrease the enthusiasm of RDI.

This research is aimed at understanding how inter-organizational team members' ability to encode, interpret, retain and recall knowledge can lead to effective supply chain collaboration, resulting in improved firm performance. Using the lens of transactive memory systems (TMS), this research demonstrates the value of knowing who knows what (specialization), is it trustworthy (credibility) and how to retrieve it (coordination) on supply chain firm performance through network collaboration.

The authors used a multi-method approach that includes quantitative survey methodology and a qualitative methodology using semi-structured interviews. In total, 207 survey responses and six semi-structured interviews provided valuable insights into the use of TMS in supply chain relationships.

This study shows that TMS can enable firms to exploit potential benefits of collaboration on network optimization, thus improving the overall efficiency and process innovations.

To maintain the efficient use of a firm's assets while suppliers get added or removed from the network, this study’s findings suggest that managers should be more knowledgeable of supply chain partners carrying codified knowledge, which can contribute to superior firm performance. Recognizing that when two or more firms collaborate, there are multiple supply chains affected by each decision, it is important that managers carefully assign the specific role of each firm within the supply chain.

This research takes a new approach to network optimization by specifically considering how firms work together to share information about their changing networks to allow firms throughout the supply chain to gain greater levels of asset efficiency and process improvement.

The purpose of this paper is to explore whether brokered network governance, run by the manufacturer, affects relational embeddedness and thus contributes to yielding the Coleman rent in the triadic supply chains.

Building upon the theoretical tenets of transaction cost analysis, complemented by the underpinnings of social capital theory, this study involves an empirical investigation that uses survey data collected from the triadic supply chains in Europe. The research covers a two-step analysis. In the first step, the Coleman rent was estimated through the regression analysis with the interaction effects. Then, partial least squares–structural equation modeling was used to estimate the reflective-formative nature of higher component model and test the research hypotheses.

The results of the study demonstrate that the distribution of three mechanisms in network governance is relatively even; however, market and hierarchy still emerge as the most impactful dimensions. Interestingly, though, this study shows that social capital can actually coexist with market and hierarchy in the triadic supply chains with the structural hole. Likewise, the research indicates that the impact of brokered network governance on the strength of network relational embeddedness is significant, but relatively weak, whereas network relational embeddedness has a strong and positive effect on the Coleman rent.

This study makes three major contributions. First, this study is one of very few that explicitly considers brokered network governance, run by the manufacturer positioned on the structural hole in its triadic supply chain. Second, as the triadic perspective is still uncommon in the supply chain studies, this research investigates a triad with the structural hole within the manufacturing setting. Third, the paper seeks to investigate the ability to yield the Coleman rent in the triadic supply chains with the structural hole, although this type of rent is typically linked to another arrangement called closure.

Given the increasing attention paid to the role of social capital within supply chains, this study investigates how relational embeddedness can be used by the manufacturer, sitting on the structural hole and running the network governance mechanism, to yield the Coleman rent in the triadic supply chain.

The purpose of this paper is to systematically review and assess the current status of research on supply chain sustainability from a network structural perspective and provide an organising framework for future scholarship in this area.

By adopting an evidence-based approach, this study conducts a systematic review of 73 articles from 18 peer-reviewed journals published between 2000 and 2020.

Adopting a social network analysis approach, the review identifies specific node-level (i.e. degree centrality, closeness centrality and betweenness centrality) and network-level (i.e. network density, network sub-groups and network diversity) structural properties that play a role in supply chain sustainability. The results reveal that structural properties determine the extent of perception of sustainability risks, the diffusion of sustainability targets, introduction of sustainable innovations, development of sustainability capabilities, adoption of sustainability initiatives and the monitoring of sustainability performance throughout the supply chain.

By distinguishing between supply network and sustainable supply network types, this study extends the existing understandings of the role of network connectivity patterns in supply chain sustainability through synthesising and evaluating the extant literature. This study further clarifies the role of these network structural properties in supply chain sustainability by describing their impact on a set of sustainable supply chain management practices through which firms achieve sustainability goals across their supply chains.

The purpose of this paper is to develop a novel network and dynamic data envelopment analysis (DEA) model for evaluating sustainability of supply chains. In the proposed model, all links can be considered in calculation of efficiency score.

A dynamic DEA model to evaluate sustainable supply chains in which networks have series structure is proposed. Nature of free links is defined and subsequently applied in calculating relative efficiency of supply chains. An additive network DEA model is developed to evaluate sustainability of supply chains in several periods. A case study demonstrates applicability of proposed approach.

This paper assists managers to identify inefficient supply chains and take proper remedial actions for performance optimization. Besides, overall efficiency scores of supply chains have less fluctuation. By utilizing the proposed model and determining dual-role factors, managers can plan their supply chains properly and more accurately.

In real world, managers face with big data. Therefore, we need to develop an approach to deal with big data.

The proposed model offers useful managerial implications along with means for managers to monitor and measure efficiency of their production processes. The proposed model can be applied in real world problems in which decision makers are faced with multi-stage processes such as supply chains, production systems, etc.

For the first time, the authors present additive model of network-dynamic DEA. For the first time, the authors outline the links in a way that carry-overs of networks are connected in different periods and not in different stages.

The purpose of this paper is to conduct a large-sample empirical examination of how intangible supply chain complexity impacts firm performance in light of a firm's organizational structure.

The study uses panel data from 2,580 Indian manufacturing firms and constructs empirical proxy for intangible supply chain complexity, i.e. CHQ distance from major cities. The proposed conceptual model is grounded in the dynamic capability view (DCV) and social network theory (SNT). Multivariate regression analyses are performed to investigate the effect of intangible complexity on firm performance.

Results show that intangible supply chain complexity, as proxied by “CHQ distance from major cities”, negatively affects firm performance and a firm's organizational structure plays an important role in conceiving CHQ locational strategies. Firms with interconnected supply chain and social network (e.g. business group firms) have a higher propensity to locate their CHQs farther away from major cities, and business group firms that have more distantly located CHQs experience better financial performance compared to independent firms (with less network resources).

In light of the supply chain literature and relevant theories, the study conceptualizes intangible supply chain complexity as “CHQ distance from major cities” and deepens our understanding of the relationship between intangible complexity and firm performance in light of organizational structure. Further, it develops an objective understanding of intangible supply chain complexity by relying on secondary panel data.

The purpose of this paper is to examine how over-reliance on buyer-supplier relational capital (created through the interconnected supply chain and social network) impacts firm performance in the context of the emerging market, i.e. India.

The study uses the Prowess database (on Indian firms) to identify the firms that rely heavily on relational capital and employs panel data regression analyses to test the effect of relational capital on firm performance (supply chain performance and financial performance).

The results show that over-reliance on relational capital leads to lower supply chain performance (proxied by supply chain cycle) and financial performance (proxied by Tobin's Q). The results also reveal that supply chain performance mediates the relationship between over-reliance on relational capital and financial performance. Together, these results indicate that over-reliance on relational capital created through the interconnected supply chain and social network for supply chain management may negatively affect a firm's competitive advantage, which in turn can significantly impede its financial performance.

In light of the supply chain literature and relevant theories, the study develops an objective understanding of over-reliance relational capital created through the interconnected supply chain and social network, by relying on a large panel dataset of manufacturing firms and hence contributes to the supply chain literature. Also, it presents a novel idea to operationalize the measure for relational capital using the Prowess database.