A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain

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Abstract

This paper aims to develop a benchmarking framework that evaluates the cold chain performance of a company, reveals its strengths and weaknesses and finally identifies and prioritizes potential alternatives for continuous improvement. A Delphi-AHP-TOPSIS based methodology has divided the whole benchmarking into three stages. The first stage is Delphi method, where identification, synthesis and prioritization of key performance factors and sub-factors are done and a novel consistent measurement scale is developed. The second stage is Analytic Hierarchy Process (AHP) based cold chain performance evaluation of a selected company against its competitors, so as to observe cold chain performance of individual factors and sub-factors, as well as overall performance index. And, the third stage is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based assessment of possible alternatives for the continuous improvement of the company’s cold chain performance. Finally a demonstration of proposed methodology in a retail industry is presented for better understanding. The proposed framework can assist managers to comprehend the present strengths and weaknesses of their cold. They can identify good practices from the market leader and can benchmark them for improving weaknesses keeping in view the current operational conditions and strategies of the company. This framework also facilitates the decision makers to better understand the complex relationships of the relevant cold chain performance factors in decision-making.

Highlights

► This paper aims to develop a benchmarking framework that evaluates the cold chain performance of a company, reveals its strengths and weaknesses and finally identifies and prioritizes potential alternatives for continuous improvement. A Delphi-AHP-TOPSIS based methodology has divided the whole benchmarking into three stages. The first stage is Delphi method, where identification, synthesis and prioritization of key performance factors and sub factors are done and a novel consistent measurement scale is developed. The second stage is Analytic Hierarchy Process (AHP) based cold chain performance evaluation of a selected company against its competitors, so as to observe cold chain performance of individual factors and sub factors, as well as overall performance index. And, the third stage is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based assessment of possible alternatives for the continuous improvement of the company’s cold chain performance. Finally a demonstration of proposed methodology in a retail industry is presented for better understanding. The proposed framework explains the complex relationship among relevant cold chain attributes, and could assist managers to quantify the performance of each individual attribute as well as assess the overall performance index of a company. It also encourages managers to understand the present strengths and weaknesses of their cold chain vis-à-vis the competition. That in turn, could facilitate them in identifying ‘better processes’, which could be benchmarked for improving the identified weaknesses.

Introduction

A ‘cold chain’ is comprises of equipments and processes that keeps perishable products under conditioned environment. These perishable products can be categorized into two types: living products (fruits, vegetables, live seafood, flowers, etc.) and non-living products (meat, dairy products, processed food products, medicines, blood, frozen products, etc.), which all require appropriate atmosphere to defy microbial spoilage (Donselaar, Woensel, Broekmeulen, & Fransoo, 2006). In today’s competitive environment, perishable products are one of the main drivers through which retailers are attaching additional customers to increase profitability. Heller has stated that the quality of perishable goods assortment is becoming the core reason many customers choose one retailer over another (as cited in Thron, Nagy, & Wassan, 2007). The global market for perishable goods such as cooled products and processed foods is growing due to changing lifestyles and overall declining prices.

Retailers who are in the business of perishables can find a direct correlation between the cold chain performance and the quality delivered to the customer. Any disorder in time–distance or temperature in the cold chain could hamper the net present value of the activities and adversely influence the over all performance (Bogataj, Bogataj, & Vodopivec, 2005). Since long time, the cold chain data has been under utilized and used solely for the purposes of evaluating the integrity of individual shipments (i.e. facilitating the accept or reject decisions). These data can be gathered to measure performance of the cold chain, which in turn can identify flaws and weaknesses in the processes.

Benchmarking is a well-defined tool for improving these weaknesses through improvement processes in which a company measures its performance against that of market leaders, finds how market leaders have achieved their performance levels, and prudently uses this knowledge to improve its own performance (Saunders, Mann, & Smith, 2007). A well defined performance measurement system (PMS) aims to support the setting of objectives, evaluating performance, and determining future courses of action on a strategic, tactical and operational level (Gunasekaran, Patel, & Tirtiroglu, 2001). PMS allows comparison of planned and actual parameter values and taking certain reactive measures in order to improve performance or re-align the monitored value to the defined value (Beamon, 1999).

In India it is estimated that around 35–40% of the total production of fresh fruits and vegetables, is wasted only because of inadequate cold storage, poor logistics, ineffective cold chain facilities and lack of other infrastructure supports (Viswanadham, 2006). Although, India is the second largest producer of fruits and vegetables in the world, but at the current level of production, the farm produce valued at Rs 70,000 million ($1400 M) is lost in wastages which is tantamount to the total production of the Great Britain (Khan, 2005). The high margin of product losses offers a significant opportunity for the improvement and advocates for technology and research advancement with in this domain. As one cannot improve what one cannot measure, the necessity of the hour is to measure the current status of Indian cold chain performance.

In light of above, this research paper delves into the performance improvement of the cold chain in Indian context. Here, a framework is proposed for performance evaluation of the cold chain and its improvement through effective benchmarking. This framework is suitable for the actual situations of the cold chains in the Indian retail market. The relevant information was collected from the field visits to various retail stores in India followed by an extensive literature review and consultation with the experts.

This research mainly discusses the Key Performance Factors (KPF) of Indian cold chain, so as to provide a consistent measuring system to establish the basis of an evaluation reference. Based on this consistent measuring system the cold chain performance index of the chosen company can be measured against its competitors’. Subsequently the strengths and weaknesses of the company can be identified and their competitive gains and losses can be examined. These identified weaknesses can be considered as the performance gap or an opportunity for improvement. Further, for improving the weaknesses, the best practices learnt from the market leader are then short-listed and examined against current operational conditions of the selected company to choose the preferred one for bridging the performance gap. This should be a continuous improvement process as the company can improve its weaknesses one after another.

The companies trading in perishable products like fruit and vegetable, flowers, milk and milk product, meat and meat products, etc. are focused upon. The research scope is the cold chain operations of the companies that provide direct link between grower/producers and consumer. Authors specifically targeted on cooperatives governed by Government of India and privately owned supermarket chains offering fresh and processed vegetable and fruits under the same roof.

Section snippets

Literature review

Measuring the performance of a cold chain is difficult, because it has many characteristics that set them apart from other types of supply chains like shelf life constraints, seasonality in production, physical product features like appearance, taste, odor, color, size and image, long production throughput time, refrigerated transportation and storage requirement, traceability, product quality and safety, etc. (Aramyan et al., 2007, Mangina and Vlachos, 2005).

Many researchers (Ghobadian et al.,

Research method

The research methods used in this article are introduced as follows.

Delphi method

In the first phase, an initial visit to the selected retail stores was undertaken to understand their use of cold chain operations. Six experts, two from each three retail stores, holding position of manger and above had been identified. Three experts from academia and Five Government officials working in departments related to perishables were also identified for getting better insight into the problem. Further using semi-structured questionnaire technique, interviews were conducted. The

An application of proposed methodology in retail industry

In this section, a stepwise demonstration of methodology is given to exemplify how Delphi-AHP-TOPSIS approach can be employed for the evaluation and improvement assessment of the cols chain performance of the retail industry. This example uses actual cold chain situations in Indian market. At this stage it is taken that first stage of Delphi research technique is done as discussed in earlier section. The deliverables of this stage are the identified Key Performance Factors (KPF), sub-factors,

Discussion and conclusion

Measuring performance of a cold chain is difficult, because it has many characteristics that set it apart from other types of supply-chains. This paper has attempted to present a benchmarking framework that simplifies and reduces the complexities of cold chain evaluation with a view to helping focus the practicing mangers’ efforts towards improvement. The evaluator can judge the performance of the cold chain in a better way, as data collection is relatively easy and accessible due to the

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