A review of supply chain complexity drivers

Serdarasan, Şeyda

doi:10.1016/j.cie.2012.12.008

Cited by 213 publications

(246 citation statements)

References 42 publications

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“…Entropy represents the most known quantitative measure of expected amount of information required to describe the state of a system, and builds a basic framework for the development of complexity theory [9,10]. Entropy is used for measuring the complexity of supply chains [11][12][13][14][15][16][17]. These papers bring manifold topics and approaches, and show also more or less connections with inventory control theory, in general.…”

Section: Theoretical Backgroundmentioning

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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Section: Theoretical Backgroundmentioning

confidence: 99%

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

Lukáš

Hofman

2016

Entropy

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“…Effort reduction (making products easily available for search) as well as use and risk reduction through functionality improvement and provision of warranties adds complexity to SCM. Variety of target customers and their different demands [15], [24] and differentiation in distribution channels [25] are obvious complexity drivers for SCM. Geographical market segments necessitate a variety of relationship management strategies adding complexity to SCM [13].…”

Section: Bmc and Scm Orientationmentioning

confidence: 99%

“…A formal definition says that SCM orientation is "the recognition of systemic, strategic implications of the tactical activities involved in managing the various flows in a supply chain" [29]. Theories, propositions related to complexity management (especially in SCM) stress that addressing each type of complexity based on its origin and level of impact through different tailored approaches is mandatory [15]. Thus, to manage the complexity created by a value network"s BM, it is necessary to give different levels of focus (priorities) to different areas of SCM.…”

Section: Bmc and Scm Orientationmentioning

confidence: 99%

“…Static/ structural (complexity) (driven by number and variety of elements) and dynamic/ operational (complexity) (driven by uncertainty and variability) are two prominent dimensions focusing on the nature of complexity [15], [16]. Internal (complexity) and external (complexity) are the other prominent dimensions in SCM literature which consider the origin of complexity [15]. Number of variables/ elements and the ties between them are the consideration of TIM literature on complexity [8].…”

Section: B Measuring Complexitymentioning

confidence: 99%

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Effect of Business Model Complexity on Supply Chain Management: A Case Study of Apparel Value Networks

Gunawardhana¹,

Suzuki²,

Enkawa³

2015

JOEBM

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Abstract-Focusing on the impact of business model (BM) on supply chain management (SCM), the paper takes a case study approach with six global apparel value networks to quantify the complexity created by the BM of a value network and to assess how SCM orientations differ among value networks owing to internal and external BM complexities. Results reveal a clear distinction among value networks in terms of BM complexities. Further, there are significant differences in areas of focus in SCM between high complex and less complex group proving that BM complexity matters significantly to SCM.Index Terms-Business model complexity, supply chain, apparel case study, value networks.

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“…[6] Writing the implementation of supply chain management on aviation manufacturing, [7] Researching the collaboration between supply chain networks, while [8] Writing about the optimal delivery time to minimize tardiness and shipping costs. [9] Write about drivers that affect supply chain complexity, while [10] Wrote a key success factor determination to implement reverse logistics using fuzzytopsis.…”

Section: Introductionmentioning

confidence: 99%

Implementation of supply chain management in supplier performance assessment using Analytical Hierarchy Process (AHP) Objective Matrix (OMAX) and Traffic Light System

Sukendar

Hidayati

2018

MATEC Web Conf.

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Abstract. This study focuses on researching the implementation of supply chain management in supplier performance measurement using Analytical Hierarchy Process (AHP) Objective Matrix (OMAX) and Traffic Light System. The method used consisted of several stages: Identification stage of criteria variable and subcriteria variable, designing hierarchy AHP structure, calculating the weight of each criterion and subcriteria, supplier performance appraisal using OMAX method, calculating the total value of each supplier perfomance and identifying the performance of each supplier Using color indicator from Traffic Light System. Based on the results of the research, it can be seen that 9 out of 10 suppliers that are considered have a good performance while 1 supplier has a performance under the target.

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A review of supply chain complexity drivers

Cited by 213 publications

References 42 publications

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

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

Effect of Business Model Complexity on Supply Chain Management: A Case Study of Apparel Value Networks

Implementation of supply chain management in supplier performance assessment using Analytical Hierarchy Process (AHP) Objective Matrix (OMAX) and Traffic Light System

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