A conceptual model of performance measurement for supply chains

Theeranuphattana, Adisak; Tang, John C.S.

doi:10.1108/17410380810843480

Cited by 86 publications

(61 citation statements)

References 33 publications

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“…The actual level of s CO is determined by conjoining their performance and importance. The subsequent approach is applied to the fuzzy performance measurement method for supply chains, introduced by and improved by Theeranuphattana and Tang (2008). The specific importance weights of the service factors are determined by a fuzzy AHP (Analytical Hierarchy Process) introduced by Kwong and Bai (2002).…”

Section: A Fuzzy Approach For Quantifying the Lcs-revenue Curvementioning

confidence: 99%

Determining the revenue contribution of logistics customer service improvements: a multi criteria decision making approach

Wessely¹,

Hofmann

2014

Decis. Anal.

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In operations and service management generating revenues is as important as reducing costs. Although logistics customer service is an important measure for executives, little research has been conducted to quantify the extent to which improvements of service levels contribute to a company's revenues. The paper applies existing fuzzy-based methods to monetarily determine the revenue contribution of logistics customer service. A logistics customer service-revenue curve and its influencing parameters are derived to obtain a quantitative relation. The method of the analytical hierarchy process is evolved dynamically by involving competitors and customer reactions. A case study from the consumer goods industry illustrates the main findings.

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Section: A Fuzzy Approach For Quantifying the Lcs-revenue Curvementioning

confidence: 99%

Determining the revenue contribution of logistics customer service improvements: a multi criteria decision making approach

Wessely¹,

Hofmann

2014

Decis. Anal.

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Section: Introductionmentioning

confidence: 99%

“…Good supply chain management integrates user expectations, commercial requirements, and the flow of purchased materials and services: it rewards shareholders by enhancing profitability and providing better returns (Beamon and Bermudo, 2000;Hausman, 2002). However,the measurement of "good" supply chain management needs to be reflected in performance metrics that address the resources involved, outputs created and overall system flexibility (Beamon, 1999;Chan et al 2003;Chan & Qi, 2003;Power, 2005;Theeranuphattana & Tang, 2008).Underlying an industry supply chain, are the individual business"s internal supply chains. These can be defined as the flow of raw product through various internal sections of the business to create the final saleable product that is passed onto the customer -normally the next component in the industry supply chain (Krajewski and Ritzman, 1993;Shah and Singh, 2001).…”

mentioning

confidence: 99%

Alignment of performance metrics in a multi‐enterprise agribusiness

Bryceson

Slaughter²

2010

International Journal of Productivity and Performance Management

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Purpose -To examine the disconnect that can develop between corporate goals and those of individual intra-organisational business units arranged as an internal supply chain within a large vertically integrated agribusiness. To explore and discuss the development of a holistic performance metrics system that facilitates internal supply chain coordination and cohesion while allowing synergies to develop across the company.Design/methodology/approach -A case study approach involving a participative action research component was used to examine the disconnect between internal business unit (operational) goals and overall corporate (strategic) goals and to develop a conceptual performance assessment model addressing both operational and strategic contexts.Findings -The findings show that appropriate performance indicators and measures can be created that relate directly to logical operational outcomes thus encouraging a more tightly integrated internal supply chain, a stronger coherence among the components and a better aligned set of operational and corporate goals.Research limitations/implications -Only financial information and data obtained from a participative managerial decision making simulation were used to explore performance goal incongruence between operational and corporate managers, compared to the need for multiple contextual performance measurement metrics that the literature suggest provides a best practice system.Originality/value -The rapidly developing corporate agribusiness sector provides a unique operating environment in that these companies deal primarily in self regenerating assets such as livestock. Additionally we explore for the first time the development of performance metrics for 2 improving the coordinated integration of autonomous business units and suggest the concept of "Integrated Autonomy" as a way to describe the resulting situation.Keywords: Case study; Agribusiness; Internal Supply Chain; Performance Measurement; Goal Alignment, Integrated Autonomy. 3 BackgroundPerformance measurement is the process of developing measurable indicators that can be systematically tracked to assess progress made in achieving predetermined goals (GAO). Measures are a quantifiable metric of results (i.e. number of dollars saved, number of days saved in a business process, or recorded improvement in customer satisfaction) and have traditionally centred on the main performance areas of a company -financial, operational, or functional efficiency (Otley, 1999, Hongren, Foster andDatar, 1999). Such metrics have been used for many years in business (Govindarajan and Gupta, 1985;Scott and Tiessen, 1999;Abernethy, Bouwens and van Lent, 2003;Davis and Albright, 2004;Simons, 2005), and tend to be derived from operational accounting and information systems.From a supply chain perspective, given that such chains are recognised as multiagent complex systems which require a large number of performance measures to accurately characterise the system (Swaminithan et al., 1998, Beamon, 1999 functional metrics...

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“…For example, M2 is further divided into activities, for example, schedule the respective production activities (M2.1), issue sourced/in-process product (M2.2), produce and test (M2.3), etc. (Theeranuphattana and Tang, 2008).…”

Section: Scor Modelmentioning

confidence: 99%

Building a comprehensive service supply chain conceptual framework: a step ahead, based on comparative analysis of previous frameworks

Ramish

Azhar

Rasheed

2017

IJSOM

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Abstract:The purpose of the study is to build a comprehensive supply chain framework for service industry including the ones engaging in purchasing of services, making of services and delivering the services, through the comparative analysis of models and conceptual frameworks previously existing in the literature of services supply chains. The findings of this paper also present a fresh outlook of how the service organisations can strategise while implementing proposed framework in their firms and all along their service supply chains. This comparative analysis and conceptual framework will enable the detection of the problems that surround result estimation within and across single supply chains and expand existing knowledge in the performance measurement in the service supply chain. In addition, this study should offer 98A. Ramish et al. fundamental insights as to how service business can develop their performance systems to be converted into more effective supply chains by focusing on new dimensions.

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A conceptual model of performance measurement for supply chains

Cited by 86 publications

References 33 publications

Determining the revenue contribution of logistics customer service improvements: a multi criteria decision making approach

Determining the revenue contribution of logistics customer service improvements: a multi criteria decision making approach

Alignment of performance metrics in a multi‐enterprise agribusiness

Building a comprehensive service supply chain conceptual framework: a step ahead, based on comparative analysis of previous frameworks

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