A study on the cost of operational complexity in customer–supplier systems

Wu, Yue; Frizelle, G.; Efstathiou, Janet

doi:10.1016/j.ijpe.2006.06.004

Cited by 79 publications

(56 citation statements)

References 16 publications

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“…In order to better understand the complexity, one must be able to measure it. Complexity index measures the complexity of the system based on the types of the products, "the uncertainty in the running system", and the materials and resources used [7]. In addition, there must be analysis on the cost of the complexity in order to help the organizations to reduce the amount of the complexity.…”

Section: The Complexity Theorymentioning

confidence: 99%

Information System Complexity and Business Value

Alamoudi¹,

Kumar²

2017

Int J Econ Manag Sci

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Section: The Complexity Theorymentioning

confidence: 99%

Information System Complexity and Business Value

Alamoudi¹,

Kumar²

2017

Int J Econ Manag Sci

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“…Two-echelon supply chain games and their information characteristics, in particular, are discussed in [27]. Finally, the papers [28][29][30] are concerned with measuring the operational complexity of supplier-customer systems, and initiated our serious interest in the field.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In general, we are able to define a lot of variables which are denoted systematically (a,b)Qi and (a,b)Ti, i = 1, ..., n, where a stands for a side (s-supplier, i-interface, c-customer) and b denotes a type of production in particular, i.e., scheduled (s), actual (p), forecast (f), order (o), and delivery (d), thus generalizing the scheme presented in [29].…”

Section: Definition Of Variablesmentioning

confidence: 99%

Operational Complexity of Supplier-Customer Systems Measured by Entropy—Case Studies

Lukáš

Hofman

2016

Entropy

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This paper discusses a unified entropy-based approach for the quantitative measurement of operational complexity of company supplier-customer relations. Classical Shannon entropy is utilized. Beside this quantification tool, we also explore the relations between Shannon entropy and (c,d)-entropy in more details. An analytic description of so called iso-quant curves is given, too. We present five case studies, albeit in an anonymous setting, describing various details of general procedures for measuring the operational complexity of supplier-customer systems. In general, we assume a problem-oriented database exists, which contains detailed records of all product forecasts, orders and deliveries both in quantity and time, scheduled and realized, too. Data processing detects important flow variations both in volumes and times, e.g., order-forecast, delivery-order, and actual production-scheduled one. The unifying quantity used for entropy computation is the time gap between actual delivery time and order issue time, which is nothing else but a lead time in inventory control models. After data consistency checks, histograms and empirical distribution functions are constructed. Finally, the entropy, information-theoretic measure of supplier-customer operational complexity, is calculated. Basic steps of the algorithm are mentioned briefly, too. Results of supplier-customer system analysis from selected Czech small and medium-sized enterprises (SMEs) are presented in various computational and managerial decision making details. An enterprise is ranked as SME one, if it has at most 250 employees and its turnover does not exceed 50 million USD per year, or its balance sheet total does not exceed 43 million USD per year, alternatively.

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“…An analytical model for measuring system complexity was presented based on information entropy and probability distribution of resource allocations (Cho et al 2009). Operational complexity was measured as a function of cost through supply chain management systems (Wu et al 2007). They indicated that inventory costs are associated with operational complexity.…”

Section: Literature Reviewmentioning

confidence: 99%

Complexity Analysis of Industrial Organizations Based on a Perspective of Systems Engineering Analysts

Garbie

Shikdar

2011

Jou. Eng. Res.

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Complexity in industrial organizations became more difficult and complex to be solved and it needs more attention from academicians and technicians. For these reasons, complexity in industrial organizations represents a new challenge in the next decades. Until now, analysis of industrial organizations complexity is still remaining a research topic of immense international interest and they require reduction in their complexity. In this paper, analysis of complexity in industrial organizations is shown based on the perspective of systems engineering analyst. In this perspective, analysis of complexity was divided into different levels and these levels were defined as complexity levels. A framework of analyzing these levels was proposed and suggested based on the complexity in industrial organizations. This analysis was divided into four main issues: industrial system vision, industrial system structure, industrial system operating, and industrial system evaluating. This analysis shows that the complexity of industrial organizations is still an ill-structured and a multi-dimensional problem.

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A study on the cost of operational complexity in customer–supplier systems

Cited by 79 publications

References 16 publications

Information System Complexity and Business Value

Information System Complexity and Business Value

Operational Complexity of Supplier-Customer Systems Measured by Entropy—Case Studies

Complexity Analysis of Industrial Organizations Based on a Perspective of Systems Engineering Analysts

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