S. Sivadasan, J. Efstathiou, G. Frizelle, R. Shirazi and A. Calinescu
In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to…
Abstract
In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to exhibit operational complexity. The operational complexity of supplier‐customer systems is primarily characterised by the uncertainty of the system. As the operational complexity of a system increases there is an associated increase in the amount of information required to monitor and manage that system. Based on this understanding, a novel information‐theoretic entropy‐based methodology for measuring and analysing the operational complexity of supplier‐customer systems has been developed. This paper makes contributions in the theoretical, conceptual and practical developments of the methodology. The methodology can quantitatively detect and prioritise operational complexity hotspots. At the interface, the framework can identify and quantify the transfer of operational complexity. Within the internal manufacturing system, the framework provides a comparative operational complexity measure across sub‐systems such as flows and products. This entropy‐based methodology provides a tool for identifying and measuring four classes of operational complexity transfer corresponding to the extent to which organisations generate, absorb, export and import operational complexity.
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One of the difficulties in developing a coherent operationalstrategy is to know how the various elements of a manufacturing systeminteract and to assess the relevant importance of…
Abstract
One of the difficulties in developing a coherent operational strategy is to know how the various elements of a manufacturing system interact and to assess the relevant importance of each. Looks at the manufacturing systems and how complex they are. A measure which calculates the systems′ complexity and the contribution from each operational source has been developed. It thus provides a tool that can assist in a strategy development exercise by quantifying the problem areas on a common basis. The approach has been used at three manufacturing sites. The resulting analysis allowed the local management, in each case, to identify the key areas of weakness, in both the short and medium term. As such it gave each of them a possible starting‐point from which to formulate an operational strategy.
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Markus Gerschberger, Ila Manuj and Patrick Freinberger
The purpose of this paper is to understand and measure empirically the objective and perceived dimensions of supplier-induced complexity in supply chains.
Abstract
Purpose
The purpose of this paper is to understand and measure empirically the objective and perceived dimensions of supplier-induced complexity in supply chains.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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).
Originality/value
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.
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Li Zhao, Baofeng Huo, Linyan Sun and Xiande Zhao
The purpose of this paper is to empirically explore the relationships among supply chain risks (SCRs), supply chain integration (SCI), and company performance in a global context.
Abstract
Purpose
The purpose of this paper is to empirically explore the relationships among supply chain risks (SCRs), supply chain integration (SCI), and company performance in a global context.
Design/methodology/approach
This study is based on the High Performance Manufacturing (HPM) project database collected from 317 manufacturing plants in ten countries and three representative industries (machinery, electronics and transportation components), using structural equation modeling (SEM) methods.
Findings
Results show that SCRs, especially supply delivery risk (SDR), are negatively related to SCI. There is a contingent relationship between SCI and performance. Different types of SCI play different roles in improving different types of company performance. Supplier, internal, and customer integration are the most important drivers for schedule attainment, competitive performance, and customer satisfaction, respectively.
Originality/value
This study is one of the first empirical studies to explore how SCRs affect SCI. It also expands current SCI research by linking three dimensions of SCI with three dimensions of company performance, using the global database collected from HPM companies in ten countries.
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Sander de Leeuw, Ruud Grotenhuis and Ad R. van Goor
The purpose of this paper is to discuss complexity assessment in supply chains, to describe a methodology for measuring supply chain complexity in distributive trade and to…
Abstract
Purpose
The purpose of this paper is to discuss complexity assessment in supply chains, to describe a methodology for measuring supply chain complexity in distributive trade and to illustrate the measurement of supply chain complexity and mechanisms to cope with supply chain complexity in distributive trade.
Design/methodology/approach
The paper discusses literature on measuring supply chain complexity and uses five case studies among wholesale companies to illustrate a methodology to measure supply chain complexity and to discuss strategies to cope with supply chain complexity.
Findings
The study confirms the multifaceted nature of supply chain complexity. The paper identifies eight drivers of supply chain complexity and uses these to illustrate the measurement of supply chain complexity in a wholesale environment. The paper identifies six strategies used by wholesalers for coping with supply chain complexity and identifies interrelations between supply chain complexity drivers and these strategies.
Research limitations/implications
The research is based on case studies in wholesale companies; future research may include survey research, including other sectors to analyze industry differences but may also focus on other parts of the supply chain.
Practical implications
The study provides insights into how to identify and measure complexity in a supply chain and what can be done to manage supply chain complexity.
Originality/value
The measurement approach is new to supply chain management and is based on multiple drivers of supply chain complexity. The research is focused on wholesalers, which is a segment that has received limited academic attention in supply chain research to date.
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Gerry Frizelle and Ivian Casali
The purpose of this paper is to look at how novel measures of supply chain performance can be used to identify unnecessary waste in terms of under-loaded vehicles and extended…
Abstract
Purpose
The purpose of this paper is to look at how novel measures of supply chain performance can be used to identify unnecessary waste in terms of under-loaded vehicles and extended delivery times, along with their causes. In particular it focuses on problems that can be tackled without the need for capital expenditure. The measures go under the collective name of “turbulence”. This represents the chain deviating from its goals. Quantifying unnecessary waste then allows unnecessary carbon emissions to be estimated while pointing to what changes will have the biggest impact. The measures have been used by three companies and some early results are provided.
Design/methodology/approach
The approach was first to use evidence from the literature to show the value of having a new measure. Next the creation of one specific new measure, called relative turbulence, a relative measure for the more general concept of turbulence. Third testing it in the field with data from companies. Then showing how carbon emissions can be derived.
Findings
The first finding is that the analysis can pinpoint sources of unnecessary emissions. Second the results suggest excessive emissions arise both though poor planning and poor practice. Third that there is a need for two models – from the users’ viewpoint and the carriers’ viewpoint. Finally the approach can be used with field data that is currently available, thus avoiding expensive one-off studies.
Research limitations/implications
The main research implication is that entropic measures are useful and can provide fresh insights. Being generic they may be applicable in other contexts. However, they can be mathematically tricky to use.
Practical implications
The analysis has been tested in companies and findings are included in the paper. They provide an insight that is not available solely from current measures. Businesses cannot only measure emissions but start to pinpoint causes.
Originality/value
The main areas of original contributions are in the introduction of a new measure, based on entropic principles, particularly the one called relative turbulence. The second is juxtaposing this measure with standard measures to gain new insights. Finally the idea that supply networks can be built from, what is called the irreducible chain.
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Enayon Sunday Taiwo, Farzad Zaerpour, Mozart B.C. Menezes and Zhankun Sun
Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further…
Abstract
Purpose
Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further escalating the situation worldwide. One of the most critical questions is how to adequately quantify what constitutes overcrowding and determine implications for operations management in improving service efficiency. This paper aims to discuss the aforementioned.
Design/methodology/approach
The authors propose the time and class complexity measures for ED service systems, taking into account important patient-level and system characteristics. Using an extensive data set from a Canadian ED, the authors investigate the performance of complexity-based measures in predicting service delays.
Findings
The authors find that the complexity measure is potentially more important than some well-known crowding metrics. In particular, EDs can improve service efficiency by managing the level of complexity within a desirable interval. Furthermore, complexity exposes how the interplay between demand-side behavioral changes and supply-side responses affects operational performance. Moreover, the results suggest that arrival patterns—the number of patients of each class arriving per time and times between events (arrivals and service completions)—increase the risk of service delays more than the demand volume.
Originality/value
This paper is the first to provide an extensive investigation into the application of the complexity-based measure for ED crowding. The study demonstrates potential values to be gained in ED service systems if complexity measure is incorporated into their operations management decisions.
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John Mills, Johannes Schmitz and Gerry Frizelle
This review aims to provide researchers and managers interested in supply networks with a strategic review of this rapidly expanding field. It does not attempt a comprehensive…
Abstract
This review aims to provide researchers and managers interested in supply networks with a strategic review of this rapidly expanding field. It does not attempt a comprehensive review of the enormous and fast growing literature but does present the breadth and depth of research and practice in the area. The central aspect of the paper is to suggest that the field can be viewed from four perspectives which all researchers and managers implicitly or explicitly use: upstream, as purchaser; downstream, as supplier; static network, as an auditor of position within its supply network, typically comprising several supply chains, providing a static and comparative view; and dynamic network, as strategist, seeking opportunities to improve the firm's position in an existing network or creating a new network, providing a strategic, dynamic and long‐term view.
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A methodology for implementing CAPM systems is described. Theresearch was motivated by evidence of dissatisfaction with theperformance of current systems, and the existence of no…
Abstract
A methodology for implementing CAPM systems is described. The research was motivated by evidence of dissatisfaction with the performance of current systems, and the existence of no generic methodology. A superposition process was employed. Areas of functional management were explored for sources of implementation methodologies and yielded a number of attributes for successful implementation. The emergent structure was then validated against field studies. The result, a methodology for improving control, is a three‐level hierarchy. The first level assesses the ability of the organisation to absorb change. The next considers the options for better control. The lowest level is concerned with implementation.
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Pushpesh Pant, Shantanu Dutta and S.P. Sarmah
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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).
Originality/value
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.