Murat Kristal

A large body of literature has studied supply chain integration (SCI) at the macro (firm or dyad) level. However, the micro-foundations of SCI that highlight the range of different activities and choices firms have in implementing integration have not been studied. This paper identifies and analyzes integrative activities or practices that form the micro-units of firm-level SCI. Qualitative analysis yields nine elements of integration that emerge from the large number of integrative practices. In doing so, the paper maps out the structure of the broad SCI construct and discusses the theoretical repercussions of this new approach. New theoretical insights and research directions are identified based on this new micro-level activity-based view of SCI. This paper shifts the focus from where integration is done (customer vs. supplier integration) to what integration entails. SCI has become a very broad construct over time. This paper is a significant and systematic step in unraveling the structure of this broad conceptual domain. It improves nascent ideas about the multiple dimensions of integration by identifying elements based on a comprehensive list of different integrative activities that firms undertake.

Purpose
The purpose of this paper is to explore how different forms of integration interact with environmental dynamism to influence the outcomes of a buyer–supplier relationship (BSR). Specifically, the authors assess the impact of communication, operational process integration (OPI) and joint knowledge exploration (JKE) on the economic value and competitive differentiation generated by the BSR. Furthermore, the authors assess the moderating role of environmental dynamism in changing the performance implications of these different forms of integration.

Design/methodology/approach
The authors empirically test the theoretical model using survey data collected from North America. The authors apply techniques such as confirmatory factor analysis, regression and a variety of robustness checks to ensure the validity of the findings.

Findings
The results indicate that OPI and JKE are useful in generating higher value from key supply chain relationships. However, communication does not directly influence performance outcomes, rather it assists in the implementation of other forms of integration. In stable environments, better returns can be obtained from focusing on OPI, while in dynamic environments JKE becomes far more important.

Originality/value
This study shows that different aspects of integration have very different performance implications and that selective integration can outperform broad-based integration in some conditions. More importantly, the performance implications depend on environmental dynamism in unique ways, where greater integration is not always the best response to dynamic business conditions. The results allow managers to make better decisions regarding what forms of integration to establish in key supply chain relationships.

The maritime transport industry continues to draw international attention on significant Greenhouse Gas emissions. The introduction of emissions taxes aims to control and reduce emissions. The uncertainty of carbon tax policy affects shipping companies’ fleet planning and increases costs. We formulate the fleet planning problem under carbon tax policy uncertainty a multi-stage stochastic integer-programming model for the liner shipping companies. We develop a scenario tree to represent the structure of the carbon tax stochastic dynamics, and seek the optimal planning, which is adaptive to the policy uncertainty. Non-anticipativity constraint is applied to ensure the feasibility of the decisions in the dynamic environment. For the sake of comparison, the Perfect Information (PI) model is introduced as well. Based on a liner shipping application of our model, we find that under the policy uncertainty, companies charter more ships when exposed to high carbon tax risk, and spend more on fleet operation; meanwhile the CO2 emission volume will be reduced.

Purpose
This paper studies buyer–supplier relationships (BSRs) by taking a routine-based approach and develops a taxonomy of BSRs. Recent advances in the BSR literature have shown that firms implement a host of diverse routines, called integrative practices, with their supply chain partners. Relationships differ based on what integrative practices are present in them. This paper aims to develop a taxonomy of supply chain relationships based on integrative practices measured at the relationship level.

Design/methodology/approach
The authors use survey data collected from North American manufacturers to establish the measurement properties of new relationship level constructs that represent different aspects of integration. Cluster analysis is used with these new constructs to develop a taxonomy of supply chain relationships. Regression and bootstrapping techniques are used to establish the predictive validity and stability of the taxonomy.

Findings
The results show four distinct types of relationships. On comparison, the authors find salient differences between their results and past classifications. As a result of taking a routine-based multidimensional view of integration, the authors find two types of relationships that have not been discovered by past taxonomies.

Originality/value
The new relationship level constructs will allow academics to have greater precision in their research questions on BSRs, as not all aspects of integration behave in the same manner. The four types of relationships identified by this study provide a useful framework to manage supply chain relationships for practitioners.

Supply networks are becoming increasingly complex with multiple overlapping relationships between firms that may span across industries. Consequently, inventory management is becoming more difficult as managers have to cope with variability in the supply flows that originate from different parts of the network. Managers that quickly sense abnormal flows may intervene and adapt their inventory policies in response to system changes. In this article, we present a framework for sensing abnormal flows originating within the upstream supply network of a focal organization. Our framework combines time series modeling with process charts to identify abnormal flow patterns in the incoming supply streams. It is a flexible framework that uses off‐the‐shelf technology to provide managers with a process that can be employed for monitoring multiple individual or aggregated data streams originating within any complex system such as complex adaptive supply networks. We illustrate our framework on four years of longitudinal supply data from the second largest food bank in the United States. We identify multiple instances of abnormal supply flows and validate our results through rigorous inventory analysis as well as field‐based expert interviews. We discuss the implications of our findings for inventory management in complex supply networks, both from academic and practitioner points of view.