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An optimisational model of benchmarking

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PurposeThe purpose of this paper is to develop a quantitative methodology for benchmarking process which is simple, effective and efficient as a rejoinder to benchmarking detractors who debate benchmarking is just a catch‐up process.Design/methodology/approachThe methodology developed for benchmarking here consists of three phases; define, analyze and results. Define phase concentrates on what to benchmark, whereas analyze and results concentrate on how to benchmark. Analyze phase is developed based on two popular mathematical programming techniques which are called technique for order preference by similarity to ideal solution (TOPSIS) and goal programming.FindingsThe developed benchmarking methodology is deployed in the case of business schools and results show its efficiency and effectiveness as well as its applicability to various business environments in implementation.Research limitations/implicationsThe main limitation here is necessity of collecting data about all the peers involved in benchmarking which indirectly restricts the number of peers in the benchmarking process.Practical implicationsBased on the TOPSIS that addresses the benchmark (what to benchmark) and the GP model that addresses the way to reach the benchmark, this methodology may be implemented as a solution procedure for business benchmarking process.Originality/valueThe novelty in this approach is that TOPSIS and GP are being used as a benchmarking techniques in a simple methodology which choose a non‐real benchmark that is more than all the peers involved. In that sense, this research work may be the first, where quantitative methodology for benchmarking is developed and rejoined to the benchmarking old criticize that debates benchmarking is just a catch‐up play.
Title: An optimisational model of benchmarking
Description:
PurposeThe purpose of this paper is to develop a quantitative methodology for benchmarking process which is simple, effective and efficient as a rejoinder to benchmarking detractors who debate benchmarking is just a catch‐up process.
Design/methodology/approachThe methodology developed for benchmarking here consists of three phases; define, analyze and results.
Define phase concentrates on what to benchmark, whereas analyze and results concentrate on how to benchmark.
Analyze phase is developed based on two popular mathematical programming techniques which are called technique for order preference by similarity to ideal solution (TOPSIS) and goal programming.
FindingsThe developed benchmarking methodology is deployed in the case of business schools and results show its efficiency and effectiveness as well as its applicability to various business environments in implementation.
Research limitations/implicationsThe main limitation here is necessity of collecting data about all the peers involved in benchmarking which indirectly restricts the number of peers in the benchmarking process.
Practical implicationsBased on the TOPSIS that addresses the benchmark (what to benchmark) and the GP model that addresses the way to reach the benchmark, this methodology may be implemented as a solution procedure for business benchmarking process.
Originality/valueThe novelty in this approach is that TOPSIS and GP are being used as a benchmarking techniques in a simple methodology which choose a non‐real benchmark that is more than all the peers involved.
In that sense, this research work may be the first, where quantitative methodology for benchmarking is developed and rejoined to the benchmarking old criticize that debates benchmarking is just a catch‐up play.

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