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Measuring the financial effects of mitigating
commodity price volatility in supply chains
Barbara Gaudenzi
Department of Business Administration, University of Verona, Verona, Italy
George A. Zsidisin
Department of Supply Chain and Analytics, College of Business Administration,
University of Missouri – St. Louis, Saint Louis, Missouri, USA, and
Roberta Pellegrino
Department of Mechanics Mathematics and Management – Polytechnic University of Bari, Bari, Italy
Abstract
Purpose – Firms can choose from an array of approaches for reducing the detrimental financial effects caused by unfavorable fluctuations in
commodity prices. The purpose of this paper is to provide guidance for effectively estimating the financial effects of mitigating commodity price risk
volatility (CPV) in supply chain management decisions.
Design/methodology/approach – This paper adopts two prominent and complementary methodologies, namely, total cost of ownership (TCO and
real options valuation (ROV), to illustrate how commodity price risk mitigation strategies can be analyzed with respect to their effect on costs and
performance. The paper provides insights through a case study to demonstrate the application of these methods together and establish the benefits
and challenges associated with their implementation.
Findings – The paper illustrates advantages and disadvantages of TCO and ROV and how these approaches can be adopted together to contribute
to effective purchasing decisions. Supply chain flexibility is a key capability but requires investments. Holistically measuring the financial effects of
flexibility investments is imperative for gaining executive management support in mitigating commodity price volatility.
Research limitations/implications – This study can provide supply chain professionals with useful guidance for measuring the costs and benefits
related to developing strategies for mitigating commodity price volatility. TCO provides a focus on the costs associated with the commodity
purchasing process, and ROV enables the aggregation of all the costs and benefits associated with the use of the strategy and synthesizes them into
the net value estimate.
Originality/value – The paper provides a comparison of different but complementary approaches, specifically TCO and ROV, for analyzing the
effectiveness of CPV risk mitigation decisions. In addition, these two methods allow supply chain professionals to evaluate and control the financial
effects of CPV risk, particularly the impact of mitigation on firm’s cash flows.
Keywords Purchasing, Supply chain risk, Commodity price volatility, Risk mitigation, Total cost of ownership, Real options valuation,
Risk management, Supply risk, Commodities
Paper type Research paper
airline industry are just a few examples. When an extensive
portion of the firm’s overall purchases consists of price-volatile
commodities, a key concern is commodity prices changing
sharply, putting the company’s economic viability at risk
(Fischl et al., 2014; Bandaly et al., 2014). If not effectively
managed, commodity price volatility (CPV) may severely
undermine the ability to meet customer requirements, creating
challenges for product pricing decisions, budget planning and
net cash flow management (Kaufmann et al., 2017; Finley and
Pettit, 2011; Matook et al., 2009).
From a supply chain risk management (SCRM) perspective,
CPV has been considered as a subcategory of supply chain risk
(Fischl et al., 2014). During the past years, different approaches
1. Introduction
Most organizations purchase commodities in some form as part
of its firm’s operations. Commodities, such as metals (e.g. steel,
aluminum, copper, silver, gold), energy (e.g. natural gas, oil)
and agricultural products (e.g. wheat, corn, soybeans) can be
acquired directly as raw material inputs to a firm’s products,
indirectly as components of purchased items from a firm’s
suppliers, and/or as part of a firm’s operations and overhead
expenses (Zsidisin et al., 2013). Commodities are a significant
input affecting many industries: steel for automotive or
electronics companies, lead for battery manufacturing,
agricultural commodities for food companies and jet fuel in the
The current issue and full text archive of this journal is available on Emerald
Insight at: https://www.emerald.com/insight/1359-8546.htm
We would like to thank Dr Florian Schupp for helping motive this study
and his insights, an anonymous contributor for providing the context and
data used in this research, and the reviewers for improving the manuscript.
Received 1 February 2020
Revised 16 June 2020
22 June 2020
Accepted 27 June 2020
Supply Chain Management: An International Journal
26/1 (2021) 17–31
© Emerald Publishing Limited [ISSN 1359-8546]
[DOI 10.1108/SCM-02-2020-0047]
17
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
have been discussed for mitigating CPV. In particular, Bandaly
et al. (2014) highlighted the key role of cross-functional
collaboration between operations and finance to minimize the
expected total opportunity cost related to upstream commodity
price fluctuations and downstream demand variability. Several
risk mitigation strategies have been identified from the financial
perspective, namely, financial hedging (Sun et al., 2017;
Caniato et al., 2016), and from the SCRM perspective,
specifically sourcing approaches (forward buying, switching
supplier, substituting commodities, vertical integration)
(Manikas and Kroes, 2016) and contracting strategies
(escalator clauses, staggering contracts, passing price increase
to customers) (Gaudenzi et al., 2018; Zsidisin et al., 2013;
Wakolbinger and Cruz, 2011). All of these strategies are
characterized by different thresholds between costs and
benefits, which need to be carefully evaluated by supply
management professionals before implementing measures to
mitigate this form of risk. Hence, companies should calculate
how risk mitigation strategies reduce the negative effects of
CPV. Despite this practical need, the existing SCRM literature
on CPV and its mitigation has mainly focused on analyzing how
firms perceive CPV and how CPV affects profitability along its
supply chain (Zsidisin and Hartley, 2012). Others have
analyzed the range of possible mitigation strategies available to
supply chain managers for mitigating CPV (Liu and Wang,
2019; Zsidisin et al., 2015), which are the main factors
influencing the choice of CPV mitigation strategies (Gaudenzi
et al., 2018) and how the concept of flexibility may be leveraged
for building the mitigation capability of specific SCRM
strategies in dealing with CPV (Pellegrino et al., 2019;
Costantino et al., 2016).
There is a lack of structured tools benchmarking commodity
price risk mitigation strategies for understanding which
approaches are more effective and efficient in mitigating
commodity price risk and the conditions under which some
strategies perform better than others. In addition, both
practitioners and academics highlight the need to further
investigate how to mitigate emerging risks, such as CPV,
affecting supply chains (Kumar and Park, 2019; Manikas and
Kroes, 2016; Bandaly et al., 2014). This paper aims to fill the
abovementioned gaps, from both practical and theoretical
perspectives, and develops an approach for better measuring
the financial and operational performance effects from
implementing risk mitigation strategies. The measures are
based upon two prominent approaches, namely, total cost of
ownership (TCO) and real options valuation (ROV). The
rationale for using these two approaches is twofold. First, they
both assess the financial effects of mitigating CPV, namely, the
impact that strategy adoption has on firm cash flows
(Carmichael, 2016). The different risk mitigation strategies
(financial hedging, sourcing approaches and contracting
strategies) have different features which often are noncomparable. TCO can potentially support decision-makers
through the monetary quantification and aggregation of these
features. Specifically, features that are not naturally expressed
as a financial unit of measure are “translated” into financial
numbers (Morssinkhof et al., 2011). Further, several CPV
mitigation strategies build their mitigation capability on
creating flexibility, whose value may be well captured in
financial terms by ROV approach rather than pure discounted
cash flow (DCF)-based tools (Pellegrino et al., 2019;
Carmichael, 2016; Carmichael, 2015). The second reason for
combining these two approaches is their practicality, which fits
to the aim of the paper to provide guidance for effectively
estimating the financial effects of mitigating CPV in supply
chain management decisions, as discussed in the following
sections.
2. Total cost of ownership
2.1 Overview
TCO is a methodology and philosophy which goes beyond the
purchase price to include several other purchase-related costs
(Bhutta and Huq, 2002). It is the term used to describe costs
associated with the acquisition, use and maintenance of a good
or service (Ellram and Siferd, 1993). TCO examines the cost
associated with purchased goods and services throughout the
entire supply chain, including the costs from the idea of the
product/service (e.g. cost of working with a supplier to develop
a new or improved part, in relationship with production and/or
assembly systems) (Brad et al., 2018; Heilala et al., 2006),
through warranty claims because of that part once the final
product is used by the customer (Ellram, 1993).
According to the TCO approach, the buying firm needs to
base sourcing decisions not just on adopting a “price only”
focus, as found in the traditional approaches to supplier
selection under supply chain risk conditions (Dupont et al.,
2018; Yoon et al., 2018). Rather, firms need to determine
which costs they consider most important or significant in the
acquisition, possession, use and subsequent disposition of a
good or service. Hence, in addition to the price paid for the
item, a TCO approach may include other elements such as
order placement, research and qualification of suppliers,
transportation, receiving, inspection, rejection, replacement,
downtime caused by failure and disposal costs, among many
others (Ferrin and Plank, 2002).
The two primary conceptual insights provided by a TCO
approach can be summarized as follows:
1 the evaluation of a broader spectrum of all the costs
related to a ‘TCO’ perspective, considering acquisition
costs, all the costs related to suppliers, and generally all
internal costs; and
2 the evaluation of life cycle costs, which consider all the
costs associated with using a given item from a given
supplier during the entire life of the item, including costs
incurred when the item is in use.
2.2 Total cost of ownership for measuring commodity
price risk mitigation
Several models have been suggested for understanding TCO
associated with purchasing a product or service. Ellram and
Siferd (1993) suggest grouping purchasing activities into six
categories:
quality,
management,
delivery,
service,
communications and price. Another approach consists in
looking at costs based upon the order in which the cost
elements are incurred, following the transaction sequence: pretransaction, transaction and post-transaction (LaLonde and
Zinszer, 1976).
In TCO, the quoted price of the commodity is the starting
point. Then, other factors considered important in the
18
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
purchasing of a commodity are considered and replaced by a
cost factor. Each issue is translated into a cost component that
is added into a price adder formula (Bhutta and Huq, 2002).
Finally, the total cost of each purchasing option is calculated:
the best option is the one with the lowest total cost. Following
the TCO approach, Table 1 reports some costs elements
associated with the commodity purchase under different
commodity price risk mitigation strategies, classified as pretransaction, transaction and post-transaction.
The analysis of the cost components related to the risk
mitigation strategies – conducted through a TCO approach of
commodity purchases – reveals many additional costs arise
beyond the purchase price. These cost elements highlight the
need to carefully revise the decision-making processes
regarding risk mitigation strategies based on purchase price.
When organizations create their commodity purchasing
strategy, there is a risk of paying limited attention to a detailed
ex ante analysis of the consequences and benefits stemming
after its implementation. A purchase price comparison is often
the key criteria driving the purchasing strategy, although the
practice may highlight additional expenses might occur, such as
negotiating price adjustments, qualifying new suppliers and
personnel travelling costs, for example. Furthermore,
uncertainties and risks might increase, such as the risk of supply
chain disruptions because of suppliers cancelling orders
because they cannot offset price increases from their
commodity purchases. For these reasons, the commodity
purchasing strategy should holistically consider the costs
related to the purchasing process, the risks generated by CPV
and the total costs related to implementing commodity price
risk mitigation strategies. Table 1 highlights examples of
possible cost elements in a TCO model when selecting a
commodity price risk mitigation strategy.
option to defer production, temporarily shut down production,
hold or abandon a project, decide the timing of investment,
choose the production technology, inputs and outputs and to
change a project’s output mix (Amram and Kulatilaka, 1999;
Trigeorgis, 1998; Majd and Pindyck, 1987; McDonald and
Siegel, 1986).
Two key insights underlie the application of ROV. First,
ROV builds upon the assumption that opportunity costs are
associated with irreversible investments under uncertainty.
This implies the possibility to defer committing resources
under uncertainty is worthwhile (Trigeorgis, 1998). Second,
ROV recognizes many investments create valuable follow-on
investment opportunities (Amram and Kulatilaka, 1999).
These insights suggest that certain up-front investments enable
management to capitalize on favorable opportunities and
mitigate negative events by proactively managing uncertainty
over time in a flexible way (Kogut, 1991) rather than by
attempting to avoid uncertainty. This managerial flexibility
may be exploited, for example, when new information
regarding market demand, competitive conditions or the
viability of new processes technologies is available (Leiblein,
2003).
3.2 Real options valuation for commodity price risk
mitigation approaches
Among different risk treatment strategies, risk transfer means
passing the financial consequences of a risk to a third party
(supplier, subcontractor, service, distributor, customer, etc.),
whereas risk sharing means dividing it among different actors.
Conversely, risk taking is a single-handed strategy that is
characterized by the use of only internal risk management
techniques (Lavastre et al., 2012; Hallikas et al., 2004; Harland
et al., 2003). While risk transfer and risk sharing consist of
passing some parts of risks and sharing it with others, risk taking
is a decision made within the organization, thereby requiring
the identification of appropriate and feasible approaches for its
management.
The literature on SCRM has recognized the combination of
redundancy and operational and strategic flexibility as effective
practices for mitigating supply chain risk (Namdar et al., 2018;
Daultani et al., 2015; Ho et al., 2015; Yu et al., 2015).
Strategies that prioritize their mitigation capability on
redundancy essentially maintain excess resources such as
inventory and capacity. Among commodity price risk
mitigation approaches, this is the case of forward buying and
vertically integrating. Investments in creating supply chain
flexibility can serve as an approach for mitigating the
detrimental effects of commodity price volatility. We define
flexibility in terms of the firm’s ability to proactively react to
environmental changes with little or negligible penalty and
sacrifice in terms of time, operational efforts, cost or
performance (Lu et al., 2017; Pérez et al., 2016; Upton, 1994).
The choice of the mitigation strategies requires not only a deep
understanding of all the costs associated with the strategies
itself, beyond the purchase price, but also the assessment of the
value created by the flexibility itself.
Firms can also create operational and strategic flexibility for
mitigating CPV risk (Pellegrino et al., 2019). For instance,
among flexible sourcing approaches, Switching Suppliers and
Substituting Commodities are two flexibility-based commodity
3. Real options valuation
3.1 Overview
ROV has been introduced in the literature as an approach that
overcomes the limits of traditional methodologies for
evaluating investment opportunities under uncertain
environments. Traditional methods, such as those based on
DCF – net present value, internal rate of return and discounted
pay back period – implicitly assume investment benefits and,
therefore, the “expected scenario” of cash flows are known and
presume management’s passive commitment to a certain
operating strategy (Zhao et al., 2015; Wei and Tang, 2015;
Boute et al., 2004). During project management and
operations, especially in highly uncertain and dynamic
environments, managers may make different choices about
operating actions when new information from the market is
available. The right, but not the obligation, to do something in
the future represents a (real) option (Dixit and Pindyck, 1995).
This concept emphasizes the manner in which investments
create economic value through operating flexibility. Having a
real option in a project means being able to react to unexpected
market changes, assuring the capability to mitigate project risk,
therefore improving project value (Chiara et al., 2007). This
possible additional value needs to be considered during the
decision-making process. A broad variety of real options have
been studied in the literature including – for example – the
19
20
Delivery/
transportation
Tariffs/duties
Inspection
Return of noncompliant
materials
Follow-up and
corrections
Transaction Purchase price
components
Order placement
Build up (extra)
storage capacity
and handling
capability
Order placement
Order placement
Supplier switching Commodity
(change
switching (change
management):
management):
(1) set up adjustments (1) set up adjustments
for the production
for the production
equipment
equipment
(2) handling costs to (2) handling costs to
operate and clean
operate and clean
equipment and load equipment and load
the new material
the new material
Delivery/
transportation
Tariffs/duties
Inspection
Return of noncompliant materials
Purchase price
Educating new
supplier in firm’s
strategies and
operations
Purchase price
Delivery/
transportation
Tariffs/duties
Inspection
Return of noncompliant materials
Commodity (longterm) validation
Supplier
qualification
Innovative design
with multiple
materials (R&D
involvement)
Testing facilities
Substituting
Switching supplier commodity
Sourcing approaches
Supplier search
Assessing the
Pretransaction feasibility of using
componentsthe commodity (e.
g. perishability)
Continuous price Supplier evaluation
monitoring
Cost
component Forward buying
Strategy
Passing price
increase to
customers
Assessing vertical
integration
alternatives
Follow-up and corrections
Tariffs/duties
Inspection
Return of non-compliant
materials
Delivery/transportation
Order placement
Purchase price
Maintaining
margin in
account
Monitoring
Maintaining
margin in
account
Monitoring
Purchase pricePurchase price
Cross-hedging
Financial
hedging
Financing approaches
Supply Chain Management: An International Journal
Volume 26 · Number 1 · 2021 · 17–31
(continued)
Order
Order placement Short term
Short- term
placement
cash outlay cash outlay
Delivery/
Delivery/
Broker fees Broker fees
transportationtransportation
Tariffs/duties Tariffs/duties
Inspection
Inspection
Inspection
Return of non- Return of non- Follow-up and Follow-up and
corrections corrections
compliant
compliant
material s
materials
Follow-up and Follow-up and
corrections corrections
Purchase pricePurchase price
Negotiating the contractual Negotiating Customer
terms (e.g. frequency of price the (multiple) approval for
adjustment, base cost/price, contract termsusing a different
commodity
price corridor)
Negotiating the
(Multiple)
Integrating the
contracting contract terms
distribution channel
(i.e. relationshipspecific investments)
Obtaining customer Adding new supplier to
internal systems (e.g. ERP
approval for using
different commodity platform)
Staggering
contracts
Contracting approaches
Vertically integrating Inserting escalation clauses
Table 1 Cost elements associated with commodity purchases using various commodity price risk mitigation approaches
Mitigating commodity price volatility
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Substituting
Switching supplier commodity
Sourcing approaches
21
Risk/cost of scrap
(obsolescence)
Inventory capital
costs
Communication/
maintaining a (long
term) relationship
with suppliers
Administrative activities of
maki ng price changes
Passing price
increase to
customers
Damage to
customer
relationships and
reputation of
firm
Contract
management
Administrative
(Multiple)
activities of
contract
management making price
changes
Staggering
contracts
Contracting approaches
Vertically integrating Inserting escalation clauses
(3) extra warehousing (3) extra warehousing
space to store the
space to store the
second material
second material
Damages to supplier Customer goodwill/ Managing the
Monitoring
Postreputation of firm integrated channel
transaction increased inventory relationships
componentslevels
Cost
component Forward buying
Strategy
Table 1
Foregone
profit from
favorable
price
fluctuations
Monitoring
Financial
hedging
Foregone
profit from
favorable
price
fluctuations
Monitoring
Cross-hedging
Financing approaches
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
price risk mitigation approaches: the decision-maker will decide
whether substituting commodities or switching suppliers is
appropriate on the basis of the commodity prices and the cost of
enabling such flexibilities. Inserting escalation clauses or financial
hedging are examples of flexibility-based commodity price risk
mitigation approaches among contracting and financial ones.
Operationalizing and assessing these mitigation strategies
requires modeling the managerial flexibility of the decisionmaker, considering both the price of commodities and the cost
of flexibility itself. Any attempt to quantify this flexibility leads
almost naturally to the concept of options. Hence, these
approaches are analyzed in this paper by operationalizing them
from an ROV perspective.
Although most of the commodity price risk mitigation
approaches summarized in Table 1 provide firms flexibility in
responding to commodity price changes, the four we will
highlight with respect to ROV are switching suppliers and
substituting commodities among the sourcing approaches, inserting
escalation clauses among the contracting ones and financial
hedging among the financial ones. Switching Suppliers provides a
firm the ability, but not the obligation, to reconsider its cost
structure in response to commodity price changes. The
company will switch suppliers when the cost efficiency gains
outweigh the aggregate transaction costs of setting up
operational flexibility. Similarly, substituting commodities gives a
firm an option to react to CPV by making the commodity
substitution when there are favorable conditions, such as when
the financial benefits gained through the substitution are greater
than its costs. At the same time, however, to open an option,
such as making a substitution technically and commercially
viable, there is the need for upfront investments in R&D, market
research and material/supplier qualification, as well as the need
for sustaining on-going supply chain costs to manage such
flexibility. Inserting escalation clauses in contractual agreements
with commodity suppliers allows the organization to define how
often the commodity prices are reviewed and changed, the base
“price” from which adjustments will be made, and if past or
future prices will be changed. The company has the right, but
not the obligation, to demand price adjustment when the actual
prevailing price in spot market is above a base (predefined)
target price. To have such a flexibility, administrative costs
which depend on the frequency of review (monitoring) and
price adjustment have to be sustained. Financial hedging gives
companies needing to buy significant quantities of commodity
the possibility to hedge against rising commodity price by taking
up a position in the commodity futures market. In this way, the
company secures a purchase price for a supply of commodity
that it will require sometime in the future. If the commodity
price increases, the company has the possibility to offset it by the
gains in the futures market (i.e. the difference between the
actual price of commodity and the price locked with the
futures). To build this mitigation ability, the company has to
pay the cost for entering into future contracts and monitoring
the commodity spot price.
Figure 1 describes the discussed strategies from the
perspective of ROV. It shows how an ROV model provides an
approach for integrating and comparing seemingly
incomparable issues (either qualitative or quantitative, either
cost- or benefit-related), thus guiding the purchasing manager
to select the commodity price risk mitigation strategy which
ensures the required trade-off among such issues.
4. Advantages and disadvantages of total cost of
ownership and real options valuation
TCO and ROV have their respective advantages and
disadvantages with regard to measuring the financial effects
from implementing commodity price risk mitigation strategies.
Figure 1 Flexibility-driven commodity price risk mitigation strategies from a real options valuation perspective
Strategy
Source of managerial
flexibility
Real Option parameters
Real
Option
modelling
Sourcing approaches
Contracting approaches
Financing approaches
Inserting escalation clauses
Financial hedging
Switching supplier
Substituting commodity
Option Cost
The cost of acquiring flexibility: Multiple
sourcing arrangements involve higher costs
than those of single sourcing (due to the need
for managing more than one contract/supplier
and the loss of scale economies).
It is the (sunk) cost needed to “implement the flexible Administrative costs which depend The sunk cost needed to enter into the
on the frequency of price review and contract and to monitor the commodity price.
system”, namely, the upfront
adjustment.
investment in R&D, market research and material
qualification for having flexible products or processes
and being able to change commodity. It is given by
the sum of: (1) cost to
produce test products with the alternative material
(mainly personnel cost for people that work on the
qualification), and (2) the cost of the material itself
for the test.”
Exercise Price
Transaction costs when exercising the
switching option.
Cost of making the switch from one commodity to the Targeted commodity price: Base
other one and vice versa (e.g., tooling, process
price of the commodity, from which
modifications, inventory costs):
adjustments are made.
(1) set up adjustments for the production equipment
(2) handling costs to operate and clean equipment and
load the new material
(3) extra warehousing space to store the second
material since the two commodities cannot be
physically mixed
It is the price of commodity futures: To
hedge against a rise in commodity price, the
company has to lock in a future purchase
price by taking a long position in an
appropriate number of futures contracts (in
order to cover the commodity quantity
needed by the company).
Expected cost efficiency gains from flexibility:
savings from switching the commodity source
At t, the company will substitue the commodity
whether the savings gained by the alternative
commodity with lowest price are higher than the cost
of making the switch.
The prevailing spot price for commodity.
Underlying asset Expected cost efficiency gains from
flexibility: savings from switching the
Decision at each t At t, the company will switch the commodity
supplier whether the savings gained by
purchasing from the alternative supplier
charcing a lowest price are higher than the
cost of making the switch.
Value created by the flexibility
Expected payoff from option exercise at t:
max (Underlying asset – Exercise price; 0)
Value of the flexibility:
22
Actual commodity price paid for the
supply
At t, the company will demand
commodity price adjustment only if
the actual commodity price is above
the base (predefined) price (exercise
price), otherwise the option will be
worthless.
At t, with the increase in commodity price,
the company will offset the increased
purchase price by the gains in the futures
market; with the prevailing spot price of
commodity having fallen, the company will
offset the loss in the commodity futures
market by the savings realised from the
reduced purchase price for the commodity.
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
A summary of these advantages/disadvantages is proposed in
Table 2 and is discussed below.
the short as well as long term. By understanding costs beyond
those associated with the commodity prices themselves, such as
its effects on supplier performance and internal costs, purchasing
professionals can be better prepared to negotiate with suppliers,
both for those with direct spend on commodities, as well as
“value chain” purchases of suppliers acquiring commodities and
the potential “cascading” effects of those commodity prices in the
supply chain.
Although there are many reported benefits of TCO (Bhutta
and Huq, 2002; Ellram, 1995), there are also various
drawbacks associated with implementing this measurement
approach for assessing commodity price risk mitigation
strategies. The first consists of its complexity to implement and
time it takes to collect the data and derive calculations, many of
which are difficult to estimate and understand. Second, it is a
static approach, where changes in the internal/external
environment, such as changes in technology affecting cost
structures and additional maintenance and operating costs, can
influence the outcomes of the model. Being a deterministic
model, TCO relies mostly on uncertain data, making it difficult
to forecast the future expense or income for a specific purchase.
Another challenge with TCO models is potentially ignoring
cost elements beyond mathematical measurement. For instance,
in case of forward buying strategy, the model ignores the intrinsic
value of the strategy that consists in eliminating the price volatility
at an unknown cost, because there is no way to account for the
risk of fixed prices being higher or lower than the fluctuating
price. The essential TCO metric focuses only on cost, and
because of this insight might select a mitigation strategy
minimizing expenditures, rather than a strategy maximizing the
return for the company. Finally, TCO ignores the benefits of
flexibility in the supply chain because it is a static model.
4.1 Total cost of ownership advantages and
disadvantages
One advantage of the TCO approach concerns the potential
thoroughness of incorporating many different cost elements
associated with implementing a commodity price risk
mitigation strategy. These can include, for example, investment
(pre-transaction) costs in qualifying alternate supply sources,
costs in creating flexibility in product design to facilitate
substituting commodities, negotiating contracts with suppliers
and/or customers for inserting escalation clauses and building
inventory capacity in preparing for forward buys, among
others. Further, additional cost elements (transaction costs)
can likewise be incorporated, such as switching supply sources,
changing production processes to use different commodities,
adjusting payment amounts at specific time intervals from
escalation clause agreements and transporting larger quantities
from forward buys, for example. Other potential future (posttransaction) costs from implementing commodity price risk
mitigation strategies can also be incorporated such as carrying
additional inventory, losing customer confidence and goodwill
from changing product materials, creating additional scrap and
waste and experiencing unforeseen product failures and quality
issues. These costs elements can be aggregated for better
gauging the actual cost of implementing these strategies,
beyond solely looking at the potential commodity price savings
accruing from mitigating commodity price risk. However, some
of these costs, especially post-transaction costs, can be very
difficult to accurately assess.
Using TCO as a measurement approach provides supply
management professionals, as well as other key organizational
stakeholders, greater insight to supply chain processes, including
those of their suppliers (Ellram, 1993). This information is
critical for better preparing negotiations with suppliers (and even
sometimes customers) in determining how best to address “what
if” scenarios of significant commodity price movements, both in
4.2 Real options valuation advantages and
disadvantages
The ROV as an analytic tool for measuring the effects of
implementing a commodity price risk mitigation strategy has
several benefits. First, an ROV model assesses the value created
Table 2 TCO and ROV advantages and disadvantages
TCO
Advantages
Disadvantages
Incorporates numerous cost elements associated with a given strategy into consideration
Considers costs beyond acquisition price (purchase price comparison)
Allows for the identification of costs that otherwise may remain hidden
Complex and time consuming
Static system
Deterministic model relying mostly on
uncertain data
Great effort in tracking and maintaining
cost data
Often focuses on costs and not revenues
Often situation-specific
Ignores flexibility benefits
Need for estimating uncertain elements
Computational complexity
Provides a tool for negotiating with suppliers
ROV
Assesses the value created by the flexibility embedded in some strategies
Ability to model the decision-making process of the manager, even when quantitative and
qualitative factors need to be considered
Focuses on cash flow and profit, not just cost minimization
Helps in comparing strategy performance (benchmark) against other approaches and self over
time
Opportunity to understand the impact of changes in the environment
23
Non-standardized calculation methods
for option values
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
from the flexibility embedded in a strategy by estimating the
potential benefits of investing in specific approaches for
mitigating commodity price risk given changing valuations.
Further, these models provide managers insights to the
decision-making process for adopting and implementing a given
strategy, going beyond the cost elements themselves. Therefore,
this approach can lead to a more holistic understanding of the
strategy, considering both the costs (as TCO does), as well as its
associated risks.
Another advantage of the ROV model is its analysis measuring
the effectiveness of commodity risk mitigation strategies on
maximizing cash flow and profit rather than minimizing cost.
While a TCO model can provide significant insights on the cost
of the approach, the ROV model will also analyze those costs, but
as well provide estimates how the price of the commodity
influences cash flow expenditures and profits from considering
investments a priori. This analysis provides an opportunity to
understand the impact of changes in both the internal and
external environment on the effectiveness of the selected strategy.
However, the ROV also has several drawbacks associated
with its use. Similar to TCO models, and maybe even more
significant, there is computational complexity in deriving these
models. This is because of the challenges of framing inputs to
the model, as well as the mathematics involved. ROV requires
using software programs such as Oracle Crystal Ball Decision
Optimizer and Real Option SLS, which are often beyond the
training of many purchasing professionals. An additional
drawback is the lack of standardized models. There are
different calculation methods for option values and their
necessary assumptions and simplifications. The lack of
standardization can yield significantly different results,
depending on the calculation methods.
Although TCO and ROV have their respective advantages and
disadvantages, they are complementary tools, which are able –
respectively – to fill the gaps and limitations of each other,
contributing to a holistic management of cost, risk and mitigation
strategies, as summarized in Table 3. The adoption of both the
tools can provide insight to the effectiveness of implementing
flexibility strategies for mitigating the detrimental financial effects
of commodity price volatility. The next section provides a
grounded example of how these approaches are applied.
establish the benefits and challenges associated with their
implementation. To provide a practical example, we selected a
company listed in the Fortune ranking of the 100 best
companies, which is one of the leaders in the fast-moving
consumer goods industry. It is a multinational company
offering a broad range of products across the world. The
identity of this firm is concealed for confidentiality reasons. In
this example, the company was exposed to commodity price
volatility in the region including Europe, Middle East and
Africa, where the company buys surfactants used in personal
care and detergent, cosmetics, cleaning agents and detergents.
In this example we considered realistic operational conditions
and market values, adjusted by a specific coefficient for reason
of confidentiality.
For mitigating commodity price risk, the company is
interested in exploring the opportunity for substituting the
commodity by using a natural surfactant – Commodity A (i.e.
made with organic ingredients) or a synthetic one –
Commodity B (i.e. petroleum derived raw materials). The base
case considers a total volume of 10 K tons of surfactants, a total
investment of $0.1m (option cost) to implement the flexible
system for switching from one material to the other and a
switching cost (exercise price) from natural surfactant to
synthetic one and vice versa of $0.2m. After applying TCO and
ROV approaches to the case, we revised the results with one of
the managers involved in the case to get his perspective about
the two approaches.
5.1 Applying the total cost of ownership approach
The analysis of the costs adopting the substituting commodity
strategy according to the TCO approach has been carried out
following Table 1. First, the possibility to switch the
commodity depends on the ability of the final products/
materials to be obtained by using a different mix of
commodities without changing its quality requirements. In
other words, switching commodities is possible when a flexible
formulation of the final product/material exists. To build such a
flexible formulation, the R&D department needs to search for
the proper mix of commodities which produces commercially
acceptable outputs. Hence, the company has to invest in the
R&D activity to create a flexible formulation using different
commodities. In this case, because such flexibility produces
commercially acceptable outputs (with the same
requirements), it is not required to obtain customer approval
for using a different commodity. However, there are costs for
testing alternative materials and validating the new commodity.
The sum of all these (pre-transaction) cost elements to
5. Measuring the cost of mitigating commodity
price risk: a case example
An aim of this paper is to provide insights through a case
example to demonstrate the application of TCO and ROV and
Table 3 How total cost ownership and real options valuation contribute to effective purchasing decisions
Contribution of the tools
Key elements of effective purchasing decisions
Holistic cost structure assessment (Purchasing price & total cost consideration)
Assessment of risk dimensions
Cash flow, revenue and profit considerations
Support the decision-making process
Optimize flexibility
Aid in negotiating with suppliers
Measurement of commodity risk mitigation strategy effectiveness
24
TCO
ROV
x
x
x
x
x
x
x
x
x
x
Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
implement the flexible system able to switch from one material
to the other is the material qualification cost and accounts for
$0.1m (option cost).
Once the flexibility has been enabled in the system, the buyer
will compare the purchase price of the alternative commodities
A and B, which have been estimated averaging the historical
data of commodity prices paid by the company for the two
sources. Contrary to what could be concluded with a rough
assessment, the choice of the commodity to be used will not be
based only on the lowest price, but will necessarily have to take
into account if the lowest price commodity is not being
currently used, the company will incur additional switching
costs because of set up adjustments for the production
equipment and handling costs to operate and clean the
equipment, for example. In our specific case, these are the
switching costs (exercise price) from a natural surfactant to a
synthetic one and vice versa, which account for $0.2m.
The transportation cost also needs to be considered as an
additional transaction cost. In this scenario, because
the commodities are purchased from the same country and
have similar physical characteristics, the transportation cost is
the same and does not affect the price comparison. Finally,
there are some post-transaction cost components associated to
substituting commodity strategy, which are the loss of economies
of scale incurred because very often contracts have a minimum
volume, thus causing a loss of some discounts as company
leverages a different commodity; higher scrap rate and market
share loss because of different performance of the new
commodity versus the other. Table 4 reports the main cost
elements associated with the substituting commodity strategy.
Three main insights may be drawn from the TCO
application for commodity price risk mitigation strategies.
First, as shown in Table 4, the TCO approach provides a
more holistic understanding of the costs associated with
adopting the substituting commodity strategy, beyond the pure
purchase price. In the specific case, this analysis is useful
because it improves the buyer’s understanding of the
purchasing process and the related cost structure and
therefore provides an excellent data source for negotiations.
This is particularly valuable because it allows us to
understand that an assessment based purely on the purchase
price would be misleading for two reasons. On one hand, a
choice based on the mere comparison of the average purchase
price would lead to the conclusion that the substituting
Table 4 Simplified total cost ownership model for substituting commodity
Strategy
Cost component
Substituting commodity
Pre-transaction components
Innovative design with multiple materials (R&D involvement) = 55.000$
A.
B
Testing facilities = 30.000 $
C
Commodity (long-term) validation = 15.000 $
Transaction components
Purchase price of commodity A = 1.105,82 $/unit (Tot. Volume 10.000 units)
Transportation cost (land freight) = 150 $/ton
Total material qualitification cost (A 1 B 1 C) = 100.000 $
D If company purchases commodity A:
If company purchases commodity B:
Purchase price of commodity B = 1.384,40 $/unit (Total volume 10.000
units)
Transportation cost (land freight) = 150 $/ton
E
Commodity switching (change management):
Post-transaction components
Loss of economies of scale (if one contract has a minimum volume, you may
lose some discounts as you leverage a different commodity)
(1) Set up adjustments for the production equipment
(2) Handling costs to operate and clean equipment and load
the new material
(3) Extra warehousing space to store the second material
Commodity switching (change management) = 200.000 $
F
G
Higher scrap rate (i.e. if the new commodity has different performance vs
the other)
H
Market share loss (e.g. if the new commodity offers low performance vs the
other)
TCO = A 1 B 1 C 1 D 1 E 1 F 1 G 1 H
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Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
commodity strategy is not appropriate because the
commodity has a lower price (in this case Commodity A
having a lower price than Commodity B). On the other hand,
if instead we consider the real uncertainty of prices, we would
choose the lowest-priced commodity from time to time, thus
defining for the company a purchase cost given, time by time,
by the lower price commodity (Figure 2). This would be a
deceptive conclusion if we do not consider this choice having
other costs. A more holistic evaluation of all cost components
makes it possible to understand that switching costs arise
beyond those under the direct purview of the purchasing
department. The flexibility of the substituting commodity
strategy involves business functions including, but going
beyond, the purchasing department and therefore entails
additional costs that must be considered. The perspective is
that organizations need to align TCO as the KPI across all the
functions involved in the sourcing process.
As a second insight, as other costs associated with the
strategy are considered and assessed, the total cost of the
strategy cannot be calculated by simply summing up all the cost
elements associated with the strategy itself, as shown in the
Table 4. Looking at each cost element, we can conclude they
are not homogeneous. Specifically, the pre-transaction
component represents a sunk cost (one-off cost for
implementing the flexible system), while, contrarily, the
transaction component is actually recurrent (this cost is
charged anytime there is a commodity substitution). From
additional discussions with this firm’s management, more
complex analyses require the need for the involvement of the
finance function in determining how exactly these models
should look like, which costs/benefits have to be included and
how the cost elements should be calculated. This is a call to
action for companies to involve the finance function to a greater
extent in creating these models and validating measures and
calculations.
Third, the TCO approach does not provide any information
about the benefits created by using the substituting commodity
strategy for the company. The TCO approach shows its limits
in assessing the net value of flexibility-driven strategies, such as
the commodity substitution strategy provided in this example.
In this sense, TCO provides a full understanding of costs and
benefits (in terms of saving opportunities) associated to the
single purchasing option rather than a full assessment of the
strategy as a commodity price risk mitigation approach.
The ROV model provides some solutions to these
limitations. While TCO is still the primary approach at this
firm, it requires a calculation of all costs involved. The
challenge becomes that when there is uncertainty, such as
including volatility commodity prices into the equation, the
“risk” needs to be added as a cost in the TCO model. ROV is a
way to quantify and embed those uncertainties into TCO.
5.2 Application of real options valuation in the case
study
Using an ROV, we simulated the forecasted values of the two
commodities prices (Commodity A and B) for a timeframe of
12 months based on the historical data of commodity prices
paid by the company. In running this simulation, coherently
with the literature (Pellegrino et al., 2019), we assume price to
vary stochastically in time following a mean reverting process.
In particular, the key parameters related to long run mean,
annual volatility, mean reversion rate and the initial values are
reported in Table 5. The outcome of the mathematical model
in terms of total value of the flexibility, computed as the sum of
expected payoffs over the strategy lifetime – option cost as
described in Figure 1 – is shown in Figure 3. Because the model
inputs are uncertain, specifically the price of the two
commodities, and because the decision taken at each time t is
dependent on the evolution of such values along the strategy
lifetime, the value created by the flexibility is not a determinist
value, but rather a probability distribution. Looking at the
statistics of the distribution, it is possible to observe that
the value created by the flexibility ranges between a negative
value equal to –$0.138m up to a positive value equal to
Figure 2 Historical data on commodities prices: Commodity A, Commodity B and lowest price between A and B
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Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
Table 5 Parameters of commodities prices
Commodity A
Commodity B
Long run mean
Annual volatility
Mean reversion rate (in %)
Initial value S0
$1,021.88
$1,171.58
0.0555
0.0513
7.17
3.06
$923.54
$1,094.21
As the findings highlight, the mean value of the flexibility passes
from being negative (a loss of $0.0085m when Switching costs
are $0.2m) to positive (a gain of $0.19m when switching costs
are $0.05m). This implies that the substituting commodity
strategy becomes more effective in mitigating CPV (i.e. it
delivers higher value), as expected, when the switching cost
decreases. In other words, the impact of the strategy adoption
on the firm’s profit becomes more positive when the switching
cost is lower. At the same time, the risk that the substituting
commodity strategy results in a loss for the company, decreases
from 83% to 43%.
Three main insights may be drawn from the ROV application
for commodity price risk mitigation strategies. First, it is
interesting to observe the net benefit associated with these
strategies (NPV of the flexibility) is positive with a certain risk
level (measured by the probability that the value of flexibility is
lower than 0). Beyond the specific numbers found for the value
of flexibility in the discussed case, the findings show flexibilitydriven strategies may be effective in mitigating CPV because
they positively contribute to the firm’s cash flow and profits.
Second, the findings highlight that it is crucial for companies
to carefully assess the value of these strategies before their
implementation, because they are characterized by high
implementation costs that need to be justified by
the materialized cost savings. In fact, there is still a chance the
value of the flexibility is less than 0. It is essential to consider the
value of the managerial flexibility to decide whether it is logical
to pursue switch sourcing option when properly assessing their
value. This shows the importance of adopting ROV to model
such managerial flexibility and account for its value.
Finally, the sensitivity analysis of the value of flexibility to the
variation of the switching costs shows how the value of such
strategies is not just dependent on the CPV but also on the
structural characteristics of such strategies and on the costs
needed to develop flexibility. The effectiveness of the strategy in
mitigating CPV increases when the switching cost decreases.
Figure 3 Probability distribution of the value of flexibility
$2.160m. This means that against the initial price to develop
the flexible system, the net benefits associated with the
substituting commodity strategy are positive with a certain risk
level (measured by the probability that the value of the
flexibility is lower than 0). In particular, given the initial
parameters considered as inputs of the model, we found that
there is a chance of about 17% that this strategy positively
impacts on the firm’s profit delivering a value up to $2.160m.
In the remaining 83% of cases, the strategy produces a loss for
the firm up to –$0.138m.
We also carried out a sensitivity analysis on the switching cost
(i.e. the exercise price of the option). The findings are depicted
in Figure 4 which shows the probability distributions of the
value of flexibility when switching costs change, whereas the
statistics of the distributions are summarized in Table 6.
Figure 4 Results of sensitivity analysis: probability distribution of the value of flexibility when Switching costs change
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Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
Table 6 Results of sensitivity analysis: summary of statistics
Base case
Investment MM$
Switching MM$
Volume kt
Mean value of the flexibility:
Prob (Flexibility Value > 0)
Range of flexibility value (Min–Max)
0.1
0.2
10
$0.0085MM
0.17
0.138 MM$
2.160 MM$
Switching – 50%
Switching – 25%
0.1
0.1
10
$0.128MM
0.45
0.354 MM$
2.124 MM$
0.1
0.05
10
$0.19MM
0.57
0.256 MM$
2.320 MM$
does not provide a full assessment of the strategy itself and its
mitigation capability. On the other side, ROV enables the
aggregation of all the costs and benefits associated with the use
of the strategy, including the value of flexibility as a mitigation
capability, and synthesizes them into a single (economic) value
which is the net value of the strategy. This helps in comparing
strategy performance (benchmark) against other approaches
and itself over time. Such characteristics makes ROV a
powerful tool that can be used by purchasing managers not only
to understand the effectiveness of the selected strategy in terms
of its impact on firm’s profit, but also to understand the impact
of changes in both the internal and external environment on the
effectiveness of the selected strategy (as the sensitivity analysis
demonstrates). This will guide the manager in the selection of
the appropriate strategy given actual conditions and future
expectations.
The review of the case results with the company
management also highlight interesting insights of what
managers perceive about the two approaches:

the importance of cross-functional collaboration for
obtaining all the inputs needed for a proper application of
TCO and ROV approaches;

the need for scorecards to be aligned/synchronized across
functions;

the need for finance to have greater involvement;

the ROV as a complement to TCO to embed risk into the
equation;

the need to understand who owns and leads the
implementation of these capabilities in a company; and

the need to run these analyses on a case-by-case basis
because of the need to incorporate many factors, making it
difficult to generalize the effectiveness of a certain
strategy.
Reviewing the application of ROV to the case with
management from the case company, the main insight we
discovered was that there is not a general framework that can
simplify these decisions: inputs need to be collected (hence, the
importance of a cross-functional approach, with multiple
inputs required from multiple functions) and a specific person
or business function needs to own these calculations (which can
be the finance function, purchasing, or another function
determined by the firm).
6. Implications and conclusions
Creating a portfolio of flexible commodity price risk
mitigation strategies may provide supply management
professionals the capability to select the most effective
option given CPV financial and operational risk exposure.
This paper analyzes commodity price risk mitigation
strategies under the perspective of their costs and
performance by adopting two measurement approaches: the
TCO and ROV. The case provides an example of the
analysis by showing how such approaches can be used to
address the effective and efficient selection of commodity
price risk mitigation strategies. The findings and their
discussion highlight how the two approaches do not seem to
be alternative or mutually exclusive, but instead we
discovered that ROV can serve as an extension of TCO
because of its ability to calculate the net value of the strategy
and its impact on the firm’s bottom line. ROV considers not
only costs associated with the strategy at various times in its
life cycle and with different recurrence but also its benefits.
Findings from this paper provides contributions to both the
business and academic literatures. With regard to contributions
to practice, we believe this study can provide supply chain
professionals useful guidance for measuring the costs and
benefits related to developing strategies for mitigating
commodity price volatility. Supply chain flexibility is a key
organizational and supply chain capability but requires
investment. Holistically measuring the financial effects of
flexibility investments is imperative for gaining executive
management support in mitigating commodity price volatility.
Using TCO and ROV for measuring the effectiveness of
commodity price risk mitigation approaches ex ante is a step
toward this direction. The application to the case and the
discussion of findings show that TCO provides a focus on the
costs associated with the commodity purchasing process, sets
priorities regarding the areas in which it is needed to intervene
to obtain benefits (i.e. saving opportunities) and provides
excellent data for negotiations with suppliers. However, TCO
Finally, according to their management, the value of this
approach is for sourcing organizations to be smarter on how to
embed risk into calculations so that the correct resource
allocations are made.
As for contributions to the academic community, this work
begins to address an existing gap regarding the use of structured
tools for analyzing the effectiveness of commodity price risk
mitigation approaches. Prior research provides insight for
comparing the benefits and drawbacks of TCO in the supply
chain as a whole (Brad et al., 2018; Heilala et al., 2006) and in
relation with other measurement approaches such as the
analytic hierarchy process (Bhutta and Huq, 2002;
Ramanathan, 2007) and data envelopment analysis (Garfamy,
2006; Ramanathan, 2007). TCO models have often been used
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Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
References
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2005), outsourcing (Ellram and Maltz, 1995), purchasing
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with specific services such as cloud computing (Han, 2011;
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We believe our paper extends current understanding of the
benefits and drawbacks of TCO, and how other measurement
approaches such as ROV can be used to complement the
analysis of purchasing processes, especially those associated
with creating flexibility in the supply chain.
Commodity price volatility directly affects the financial
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significant commodity price shifts. Analyzing the effects on
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The study has several limitations, which also offers
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methods adopted, the case example serves to highlight,
beyond the specific numbers, interesting managerial
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Commodity price volatility and risk have and will continue
to present challenges to supply chain management
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of risk through creating supply chain flexibility may provide
financial benefits for firms in the long run. This paper
provided insight as to how TCO and ROV can be
implemented as decision analytic approaches for determining
how organizations can make investments for better mitigating
this form of risk in the supply chain and contribute to firm
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Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
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Mitigating commodity price volatility
Supply Chain Management: An International Journal
Barbara Gaudenzi, George A. Zsidisin and Roberta Pellegrino
Volume 26 · Number 1 · 2021 · 17–31
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interests focus on supply chain management, B2B
management and supply chain risk management. She has
published in international journals such as International
Journal of Production Economics, Journal of Purchasing and
Supply Management, Industrial Marketing Management,
International Journal of Logistics Management, Journal of
Logistics: Research and Applications, Corporate Reputation
Review and others. Barbara Gaudenzi is the corresponding
author and can be contacted at: barbara.gaudenzi@univr.it
George A. Zsidisin, PhD (Arizona State University),
CPSM, is the John W. Barriger III Professor and Director of
the Supply Chain Risk and Resilience Research (SCR3)
Institute at the University of Missouri – St. Louis. Professor
Zsidisin’s research focuses on how firms assess and manage
risk associated with supply disruptions and price volatility in
their supply chains. He has published over 80 research and
practitioner articles and seven books, including Supply
Chain Risk: A Handbook on Assessment, Management and
Performance; Managing Commodity Price Volatility: A Supply
Chain Management Perspective; Handbook for Supply Chain
Risk Management: Case Studies, Effective Practices, and
Emerging Trends; and Revisiting Supply Chain Risk. His
research on supply chain risk has been funded by the AT&T
Foundation and IBM, and he has received numerous
awards, such as from the Institute for Supply Management,
Deutsche Post, Council of Supply Chain Management
Professionals, and the Decision Sciences Institute. Further,
he is one of the founding members of the International
Supply Chain Risk Management (ISCRiM) network, teaches
and leads discussions on supply chain management and risk
with various Executive Education Programs and numerous
companies in the US and Europe, is co-Editor Emeritus of
the Journal of Purchasing & Supply Management and serves
on the Editorial Review Board for several academic supply
chain journals.
Roberta Pellegrino, PhD, is Assistant Professor of
Management Engineering in the Department of Mechanics
Mathematics and Management – Polytechnic University of
Bari, Italy. Her main research interests are on public–private
partnership/project financing, supply chain risk management,
real options theory and other topics in the area of
organizational process management (economic-management
engineering). She obtained PhD in Advanced Production
Systems from the Polytechnic University of Bari, in 2010. She
is has authored and co-authored several publications in
international journals and books and has presented more than
50 papers at national and international conferences.
About the authors
Barbara Gaudenzi, PhD, is Associate Professor at the
Department of Business Administration at the University of
Verona, Italy. She is Director of the Master in Supply Chain
Management (LogiMaster) and Risk Management
(RiskMaster) at the University of Verona. Her research
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