Search results

Complexity has been called the 21st-century supply chain (SC) challenge. Most SC managers view it as a necessary evil, ever-present, costly and tough to manage, and few prioritize it. Still, anecdotes suggest some leverage it to drive operational excellence. This study aims to explore how they do it, delving into the development of a complexity management capability, under what circumstances it emerges and its effect on competitiveness.

To better understand why, and how, companies develop (or not) a distinctive SC complexity management capability, this study employed an inductive study of 10 leading European companies, each operating a complex SC.

Although SC complexity raises costs, increases disruptions and makes decision-making difficult, few companies have made complexity management a priority. Among those, most focus on reducing or absorbing complexity to improve operational excellence. A few invest to develop a distinctive SC complexity management capability. They manage complexity for market success. The interaction among competitive pressures, managerial attitudes and investments delineate a dynamic capability development process.

Despite extensive research on complexity drivers, the tools used to manage SC complexity and the impact of SC complexity on performance, the interplay among factors that promote, or hinder, the development of an SC complexity capability continues to be poorly understood. By mapping the complexity capability development process, this study explicates a more nuanced approach to managing SC complexity that can yield a competitive edge.

SC complexity prevails because the dynamic, iterative complexity capability development process is overlooked. Managers can use the complexity capability roadmap to assess the cost/benefits of pursuing a distinctive complexity management capability more accurately.

This study demystifies the development of a complexity management capability, showing how some companies develop the capability to distinguish between value-added and value-dissipating complexity and thus become empowered to leverage SC complexity for competitive advantage.

The purpose of this paper is to understand and measure empirically the objective and perceived dimensions of supplier-induced complexity in supply chains.

An equal-weight, complementary mixed-method approach is used to investigate supplier-induced complexity and understand its impact on outcomes. Initial qualitative research and extant literature review allowed the identification of supplier characteristics that add complexity to supply chains and development of four research hypotheses. Subsequently, quantitative analysis was used for testing the hypotheses.

The results suggest that supplier-induced complexity is related to adverse outcomes, and both perceived and objective dimensions of complexity are valuable in understanding and measuring supplier-induced complexity.

This study employs a mixed-method approach to establish and test relationships among perceived and objective supplier-induced complexity, and their outcomes. The unit of analysis is the first-tier suppliers of one farm equipment manufacturing firm. This limits the generalizability of the results to similar industrial manufacturing firms.

This paper presents an approach to identify suppliers that add the highest levels of complexity to a supply chain and, thus, require closer monitoring. Specific supplier characteristics are identified for individual suppliers. Developing specific complexity-related measures helps better identify critical suppliers compared to traditional approaches (e.g. ABC analysis).

This paper contributes to supply chain management literature by comprehensively exploring supplier-induced complexity, incorporating the often-ignored perceived complexity dimension, and providing a managerially useful framework.

Increasing environmental uncertainty, more demanding customers, rapid technological growth and rising capital costs have all forced firms to evolve from collaborating with buyers and suppliers to collaborating with their competitors and that is called coopetition. The purpose of this paper is to better understand the antecedents and outcomes associated with coopetition.

Building from the existing literature and three theoretical foundations, resource-based theory, resource dependence theory and game theory, the authors develop a model showing the antecedents and outcomes of coopetition and associated propositions of coopetition. Using a semi-structured interview process of 21 industry executives, the authors offer empirical support for the proposed coopetition model and propositions.

Firms are increasingly dependent on the knowledge and expertise in external organizations to innovate, solve problems and improve supply chain performance. This research suggests that there is a value for firms to consider coopetition as a part of their inter-firm strategies.

The semi-structured interview process used in this research provided a wealth of information and executive experiences in coopetition. The interviews, however, only provide a single perspective of collaborative engagements with competitors. Multiple perspectives of each project would add value to this research.

Collaboration among buyers and suppliers have been well researched; however, there has not been as much research on coopetition. This research provides a new area for future research for academics and offers suggestions for managers to improve the effectiveness and efficiency of their coopetition projects.

This case focuses on supplier management through quantitative and qualitative analysis of data from a real company. In the process of solving the case, students determine and operationalize what constitutes a critical supplier, analyse the data provided, and identify the most critical suppliers.

Steel Corp has a large production capacity but a shrinking steel market in Europe. Reaching growing markets like China and U.A.E will be important to sustaining and growing revenue but is tough due to higher transportation costs. In this case, users must identify and use logistics data; logistics customer segmentation and related cost analysis.

The purpose of this paper is to further advance an existing supplier evaluation model for the purpose of identifying those supplier relations which predominantly threaten or worsen a company's performance. A defined basic set of parameters to determine complexity facilitates the identification of critical locations within a supply network (SN) under certain business conditions.

This paper is based on a structured literature review in scientific periodicals in logistics/supply chain management between 2000 and 2009. Articles are analysed based on a structured framework and the identified complexity parameters are operationalised using quantitative and summable measures. The conceptual model is applied within a multiple case study in the Austrian agricultural industry.

This paper illustrates how complexity in SNs can be operationalised in a company‐specific configuration in order to achieve concrete managerial recommendations. Hence, the model allows evaluating SN‐partners based on selected parameters to determine the contribution of a single partner to the overall complexity.

Due to the literature review executed and the case study approach chosen, the research may lack generalisability. Therefore, continued validation by means of implementing a greater amount of use cases in other companies and industries is advisable.

Applying the model, a company is able to determine tier‐1 to tier‐n suppliers which are predominantly affecting its business from a complexity perspective.

Unlike typical current complexity evaluation approaches, the proposed model respects rapid and continuous applicability, profound conceptualisation and practical feasibility.

The purpose of this paper is to conceptualize archetypes of engineer-to-order (ETO) to support companies in determining the appropriate degree of design standardization and automation, and as a result achieve superior performance. Products of ETO manufacturers are classified in a 2×2 matrix using annual units sold and engineering complexity as dimensions.

This research adopted a theory refining approach based on multiple case studies. Seven ETO manufacturers from different industry sectors participated in the study. Data collection was primarily based on a series of in-depth interviews supported by observations and archival sources.

The paper proposes four distinct archetypes of ETO (complex, basic, repeatable, and non-competitive) and empirically validates three of them. The organizational structures and processes most suitable for the different archetypes are described, and standardization and automation strategies are linked to the quadrants of the matrix. The matrix can support practitioners in making strategic choices and provides a framework for benchmarking their ETO products and processes.

Existing conceptualizations of ETO consider the company as the primary object of investigation, rather than the product or product family. However, companies often have different product families demanding different strategies. Also, there is little or no focus on the engineering perspective. The authors move the engineering perspective to the center of investigation and identify a set of standardization and automation strategies for different types of ETO products.

The purpose of this paper is to illustrate how centralization and decentralization of supply chains (SCs) play a major role in creating organizational resilience.

Starting with the basic tenets of contingency theory and applying a grounded theory approach, results from exploratory qualitative and quantitative studies are combined to investigate the impact of (de)centralization on SC resilience capabilities.

The findings from a comprehensive literature review combined with two empirical surveys indicate that four important organizational capabilities are needed in order to cope with internal and external disruptions: fast reactions to unforeseen disturbances, reducing the number of negative external forces, reducing the impact of negative external forces and the quick return to normal operating processes. Furthermore, it is illustrated how (de)centralization activities can support these capabilities and thus maximize the SC resilience.

This paper presents 12 measures for (de)centralization and shows how they can support the four major capabilities of resilient companies. The results from qualitative and quantitative surveys allow for a holistic understanding of the organization and provide a basis for future SC resilience research.