A multi-objective approach to design strategic supply chains and develop responsiveness- efficiency frontiers

• Date: 12 February 2018
• Published date: 12 February 2018
• Pages: 365-386
• DOI: https://doi.org/10.1108/IJLM-12-2016-0292
• Author: Raed AlHusain,Reza Khorramshahgol
• Subject Matter: Management science & operations,Logistics

A multi-objective approach to

design strategic supply chains

and develop responsiveness-

efficiency frontiers

Raed AlHusain

Kuwait University, Shuwaikh, Kuwait, and

Reza Khorramshahgol

Department of Quantitative Methods and Information Systems,

Kuwait University, Shuwaikh, Kuwait

Abstract

Purpose –The purposeof this paper is twofold.Initially, a multi-objectivebinary integer programmingmodel

is proposed for designing an appropriate supply chain that takes into consideration both responsiveness

and efficiency.Then, a responsiveness-cost efficient frontier is generatedfor the supply chain design that can

help organizationsfind the right balance betweenresponsiveness and efficiency, and hence achievea strategic

fit between organizational strategyand supply chain capabilities.

Design/methodology/approach –The proposed SC design model used both cross-functional and logistical

SC drivers to build a binary integer programming model. To this end, various alternative solutions that

correspond to different SC design portfolios were generated and a responsiveness-cost efficient frontier

was constructed.

Findings –Various alternative solutions that correspond to different SC designs were generated and a

responsiveness-cost efficient frontier was constructed to help the decision makers to design SC portfolios to

achieve a strategic fit between organizational strategy and SC capabilities.

Practical implications –The proposed methodology enables the decision makers to incorporate both

qualitative and quantitative judgements in SC design. The methodology is easy to use and it can be readily

implemented by a software.

Originality/value –The proposed methodology allows for subjective value judgements of the decision

makers to be considered in SC design and the efficiency-responsiveness frontier generated by the

methodology provides a trade-off to be used when choosing between speed and cost efficiency in SC design.

Keywords Decision making, Strategic planning, Supply chain management, Modelling,

Distribution management, Inventory decisions, North America, Supply chain design, Response time,

Binary integer programming, Responsiveness-efficiency frontier

Paper type Research paper

1. Introduction

Supply chain design or strategy can be defined as the process of managing organizational

resources in a way that best fits its SC capability and meets its competitive strategy by

exploiting the right balance between efficiency and responsiveness. SC design basically

involves decisions about the overall structure of SC network and what each stage of SC will

perform. Typical decisions in SC design are, which products to produce, facility location/

capacity, transportation mode, inventory level and tradeoffs among them.

The effectiveness of a SC design is determined by how well it is aligned with the

overall organizational objectives and competitive strategy to satisfy customer needs

(e.g. see Khan et al., 2012; Qi et al., 2011; Hofmann, 2010; Ivanov and Sokolov, 2009; The International Journal of

Logistics Management

Vol. 29 No. 1, 2018

pp. 365-386

© Emerald PublishingLimited

0957-4093

DOI 10.1108/IJLM-12-2016-0292

Received 11 December 2016

Revised 8 March 2017

7 May 2017

2 June 2017

Accepted 29 June 2017

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/0957-4093.htm

The authors are most grateful to three anonymous reviewers for their constructive comments that

helped to improve the quality of the paper considerably. The authors are also indebted to

Dr Britta Gammelgaard, Chief Editor, IJLM, for expediting the review process.

365

Strategic

supply chains

Chopra and Meindl, 2013). For example, Walmart and Amazon.com are two companies that

have achieved continuous success by their optimal SC design and superb SC management

(Chopra and Meindl, 2013). As leaders in providing low price, large variety and high

availability of numerous products, Walmart’s efficient SC and Amazon’s responsive SC

enables them to surpass their competitors in business performance (Chopra 2003; Lee, 2004;

Natto, 2014; Xu et al., 2014). Chiles and Dau (2005) use Amazon and Walmart as an example

of companies that are industry leaders due to their SC practices that reinforces their

competitive business strategy.

In order for an organization to successfully achieve a strategic fit and align its SC design

with competitive strategy, decision makers must determine the right balance between SC

efficiency and responsiveness. Such a balance can be achieved by the right mixture of SC

decisions in each SC driver component that would work in synergy toward achieving and

maintaining this balance (Manuj, 2011; Chopra and Meindl, 2013). Responsiveness is mainly

concerned with issues such as quantity and variety, time, innovation and service level

whereas efficiency deals with lowering cost and minimizing waste (Taylor et al., 2003). Often

the objective is for the firm to strive to be as responsive as required by the market while

attempting to be as efficient as possible.

The balance between efficiency and responsiveness depends on the nature of the

products and services offered (Fisher, 1997). Based on Fisher (1997), functional type

products should use efficient SC strategy while innovative type products should employ

responsive SC strategy. The determination of the right SC decisions in each SC driver,

however, is a complex process that involves a “holistic”approach to SC design, one that

considers the simultaneous influence of all SC drivers toward achieving an appropriate

balance between efficiency and responsiveness. SC drivers are classified into logistical

(composed of facilities, inventory, transportation) and cross-functional (which includes

information, sourcing, and pricing). These six drivers are interrelated and interact with one

another to provide the desired efficiency and responsiveness (Shahzadi et al., 2013; Chopra

and Meindl, 2013). This concept is presented in a pictorial view in Figure 1.

Ideally, finding the optimal SC design that would lead to a strategic fit can benefit

significantly from the responsiveness-efficiency frontier. This is a non-trivial task since the

effect of SC decisions in each SC driver on the overall performance in terms of efficiency and

responsiveness must be estimated. Moreover, efficiency and responsiveness are not

necessarily negatively correlated. In other words, some SC decisions in each SC driver could

work in synergy and offer both.

This paper, using both logistical and cross-functional SC drivers, applies binary integer

programming to determine the optimal combination of the related decision variables to

properly tune SC design towards a desired balance between efficiency and responsiveness.

Subsequently, a responsiveness-efficiency frontier is generated to help organizations

to find the optimum balance between efficiency and responsiveness. The frontier helps

to determine, for a given level of responsiveness, what would be the lowest cost?

Or, alternatively, for a given level of cost, what would be the best responsiveness level that

can be achieved? If the frontier is drawn such that it represents the responsiveness-

efficiency of the best supply chains for an industry, then, not all firms in that industry are

situated on the frontier. In this case, frontier provide vital information for those firms that

lag behind in terms of managing their supply chains, and how to use their SC drivers and

capabilities to operate on the frontier, rather than on an interior point. Of course, the frontier

can be pushed upward by using, as an example, a new technology or a new strategy that

helps improving efficiency, responsiveness or both.

The following sections provide a review of the literature, followed by a detailed

discussion of the proposed methodology. Lastly, an illustrative example demonstrates the

applicability of the proposed model.

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