Optimal divestment time in supply chain redesign under oligopoly: evidence from shale oil production plants

• DOI: http://doi.org/10.1111/itor.12651
• Date: 01 September 2020
• Published date: 01 September 2020

Intl. Trans. in Op. Res. 27 (2020) 2559–2583

DOI: 10.1111/itor.12651

INTERNATIONAL

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IN OPERATIONAL

RESEARCH

Optimal divestment time in supply chain redesign under

oligopoly: evidence from shale oil production plants

Farzad Alavifarda,∗, Dmitry IvanovbandJianHe

c

aAustralian Center of Quantitative Research, Harrington Street, Sydney, NSW 2000, Australia

bThe Berlin School of Economics and Law, Badensche Straße 52, 10825 Berlin,Germany

cSchool of Economics and Finance, RMIT University, Swanston Street,Melbourne, 3000, Australia

E-mail: f.alavifard@gmail.com [Alavifard]; dmitry.ivanov@hwr-berlin.de[Ivanov]; jian.he@rmit.edu.au [He]

Received 4 November2018; received in revised form 12 February 2019; accepted 16 February 2019

Abstract

This paper investigates the optimal timing for the closure of production plants in the context of supply chain

redesign. We consider producers operating under oligopoly and analyze their optimal decisions with the aid

of real options. We contextualize this study in the energy supplychain, where revenue is heavily influenced by

the Organization of the Petroleum Exporting Countries (OPEC). It is optimal to divest from a production if

certain values pass below the liquidation cost. The optimal time to divestis, then, the optimal time to exercise

a perpetual American put option on the total value of the project, where the strike price is the liquidation

value and expenses. The OPEC oligpolistic power is modeled with the aid of a hidden market in a Hidden

Markov Model, since the state of the Markov chain is not directly visible to the production manager. The

reported results can be used by supply chain managers in decision making on production network redesign

in the oligopolistic environment considering present value of plants and cash flows in the supply chain. The

advantage of the modeling approach proposed is its analytical tractability, especially for project valuation

and real-option problems.

Keywords: operations research; supply chain; finance; energy; real option; hidden Markov model; oligopoly; oil shale

extraction

1. Introduction

Supply chain redesign has been an influential research avenue over the last decades (cf. Choi et al.,

2016; Dolgui et al., 2018; Ivanov et al., 2019). Production plant openings and closures belong to the

determinants in this research area. Recent studies (Choi et al., 2016) call for the development of new

methodologies in the given domain byattracting analytical tools from different disciplines,including

finance. In this study, we propose for the first time the use of a real-option approach to the optimal

divestment time in supply chain redesign in terms of production plant closure. There is a substantial

∗Corresponding author.

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International Transactionsin Operational Research C

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Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA02148,

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2560 F. Alavifardet al. / Intl. Trans. in Op. Res. 27 (2020) 2559–2583

body of work on the applications of real options in corporate finance, operational research, and

supply chain management literature (cf. Mun, 2002; He et al., 2018; Ivanov et al., 2018; Jahani

et al., 2018; and the references therein). In this paper, we extend this work to determine the optimal

liquidation strategy for production plants operating in oligopolistic markets. Due to the significant

economical and financial importance of oil production on global markets, we contextualize our

study for shale extraction.

In recent years, shale extraction has emerged as an alternative source of oil production, signif-

icantly disrupting the traditional petroleum supply chain apparatus. Nonetheless, as a developing

fuel source, the production and processing costs for oil shale are high, given the small nature and

the specialist technology involved. A full-scale project to develop oil shale would require heavy

investment and could potentially leave businesses vulnerable should the oil price drop. The recent

plunge in oil and gas prices have presented many challenges to producers fracking (i.e., hydrologic

fracturing) for shale oil. Many producers have borrowed heavily for capital expenditures, following

a shale oil boom in the United States and low interest rates in the wake of the global financial crisis.

These companies typically pay interest at 10% higher than treasury rates, which puts them at the

verge of bankruptcy, if the low prices continue. On the other hand, in an uncertain world predict-

ing the profitability of production and the returns accrued from investment projects undertaken

is difficult. In an oligopolistic market, such as the oil industry, investment decisions of firms are

directly dependent on the estimated size of production bythe large players. Even a small unexpected

increase in uncertainty may have a strong impact on both market value of firm and expected value

of its future cash flows. For example, between July 2015 and March 2016, the political competition

between Iran and Saudi Arabia, twolarge players in the market, led to an excess supply of crude oil,

which in turn resulted in a drop in value of over 55%. Under these conditions, if a firm overestimates

future demand, then it may be subjected to considerable losses generated by excess supply when

operating revenues fall below production costs.

The oil industry is unique, in that 73% of the world’s proven oil reserves is controlled by the

Organization of the PetroleumExporting Countries (OPEC), an intergovernmental organization of

13 petroleum-exporting nations. Many believe that OPEC acts as a cartel when it sets production

quotas to maintain price (cf. G¨

ulen, 1996). However, others point out that widespread cheating

and political rivalry between members largely neutralizes OPEC’s collective ability to influence

pricing (cf. Colgan, 2013). Therefore, we proposethat the analysis of profitability and, subsequently,

investment (or divestment) decisions must be made considering two states of the market: (a) a

“consensus” state, where the OPEC members can collude and agree on the production level. In

this scenario, members are able to collect monopoly rent by tightening the production level and

increasing oil and gas prices. (b) the “gridlock” state, where the OPEC members cannot reach a

consensus (e.g., November 2015 to March 2016) and oversupply the market, which results in the

low oil prices.

The remainder of this paper is structured as follows. Section 2 provides a comprehensive analysis

of the literature. The modeling setup is outlined in Section 3. In Section 4, we entail our model

for OPEC’s oligopoly using a hidden Markov model (HMM), including elaborate derivations

for robust filtration and parameter estimations. Section 5 constructs the real-option model and

provides analytical tools for the decision-making process. Section 6 provides a thorough numerical

analysis to highlight the practical importance of our model. Section 7 concludes the paper with a

managerial remark.

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2019 The Authors.

International Transactionsin Operational Research C

2019 International Federation ofOperational Research Societies