Risk MGMT

Vol. 30, No. 2, February 2021, pp. 355–389 DOI 10.1111/poms.
13269
ISSN 1059-1478|EISSN 1937-5956|21|3002|0355 © 2020 Production and Operations Management Society
Operations–Finance Interface in Risk Management:

Research Evolution and Opportunities
Jiao Wang
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China,
jiaowang@scu.edu.cn
Lima Zhao
Ningbo China Institute for Supply Chain Innovation, MIT Global SCALE Network, No.169 Qixing South Road, Ningbo 315832, China
Center for Transportation and Logistics, Massachusetts Institute of Technology, 1 Amherst Street E40, Cambridge, Massachusetts 02142,
USA, limazhao@mit.edu
Arnd Huchzermeier
WHU–Otto Beisheim School of Management, Burgplatz 2, Vallendar 56179, Germany, Arnd.Huchzermeier@whu.edu
he operations–finance interface (OFI) jointly optimizes material, monetary, and information flows under intricate
T sources of uncertainty. To sketch the broad landscape in this emerging and interdisciplinary field, this study synthe-
sizes literature across diverse themes and dispersed methodologies, screens systematically the research progression from
original foundations to recent contributions in each major research stream, and thereby advocates future research innova-
tions on prospective topics in light of the interconnections and potential reciprocity between operations and finance from
risk management aspects.
Key words: operations–finance interface; supply chain finance; supply chain management; corporate finance
History: Received: April 2019; Accepted: August 2020 by Sridhar Seshadri, after one revision.
reality, markets imperfections (e.g., tax, bankruptcy

1. Introduction cost, information asymmetry) lead to inevitable oper-
Operations and finance are two key functions that ations-finance interactions. Hence, omitting such
jointly drive business success. Operations manage- interactions could distort both functions and result in
ment optimizes the supply and processing of material potential losses to a firm or a supply chain (Birge
flows to ensure the efficient and effective resource uti- 2015). This provides an important starting point for
lization in meeting customer demand, that is, physical subsequent research on operations–finance interface
supply chain management. Corporate finance primar- (OFI) in the next decades.
ily adjusts capital structure using various instruments In an accelerated business environment under intri-
to allocate monetary resources over space and time, cate risk exposures, both researchers and practitioners
that is, financial supply chain management. Opera- believe an in-depth understanding of the trade-offs
tions management on the one hand is supported by between operational and financial metrics and
financial activities, and on the other hand drives the thereby integrating both functions if necessary can be
financial performance of enterprises or supply chains of substantial importance (Protopappa-Sieke and Sei-
(BAFT 2016). fert 2010), especially after the financial crisis rippled
Firms operating in global supply chain are exposed across global markets in 2008-2009 (McShane et al.
to a sheer variety of risks, for example, technological 2011). This financial crisis has been referred to as a
risks, economic risks, financial risks, performance “failure of conventional risk management in financial
risk, and legal/regulatory risks (Triantis 2005). The institutions” (Fraser and Simkins 2010, p.27), and thus
interface between operations and finance has long brought risk management to the forefront once again,
been examined in risk management. According to not only among top executives within firms but
Modigliani–Miller (MM) theorem, the separation also among members of congress and government
property between operations and finance holds under regulators.
the assumptions of symmetric information and per- Recently, the pandemic of COVID-19 and global
fect capital markets (Modigliani and Miller 1958). In trade conflicts have significantly affected global
355
Wang, Zhao, and Huchzermeier: Operations–Finance Interface in Risk Management
356 Production and Operations Management 30(2), pp. 355–389, © 2020 Production and Operations Management Society
supply chains, from upstream supply, inbound and management in a special issue of Management Science.
outbound logistics, to demand planning and forecast- Similarly, Babich and Kouvelis (2015) make another
ing (Kapadia 2020), and consequently casts a dark call for paper in a special issue of Manufacturing & Ser-
shadow on the global economy. The former IMF chief vice Operations Management to disseminate novel,
economists believe the pandemic outbreak and the insightful, and relevant research that unifies concepts
global actions to limit its spread are leading the world from finance, operations, and risk management.
economy into the next recession (Financial Times Given the wide range of topics and methodologies in
2020). Driven by the intense flurry of government and the vast literature on OFI, it might be challenging for
stock exchange activities related to risk management scholars to develop a grasp of various research
within corporations, trade and business publications streams. Despite the high visibility of several fre-
directed at top management are full of articles related quently cited articles, the overall research landscape
to risk management. may remain ambiguous. Hence, we attempt to pro-
Moreover, small- and medium-sized enterprises vide a holistic view of the existing research on OFI as
(SMEs) might face tremendous working capital pres- a navigation for researchers and practitioners.
sure under credit risk (especially in economic down- Literature overviews on OFI are related to our
turns) with regard to the exploitation issue owing to research, as summarized in Table 1. While Seifert
powerful supply chain partners and the credit rating et al. (2013) and Paul and Boden (2014) concentrate
issue arising from information asymmetry between on trade credit, Drover et al. (2017) review the litera-
SMEs and financial institutions (de Korte 2016, Paul ture on entrepreneurial equity financing with
and Boden 2014). This could lead to underinvestment emphases on venture capital, corporate venture capi-
in capital budgeting and thereby negative repercus- tal, and angel investment. Furthermore, Gelsomino
sions along a supply chain. To mitigate the impact of et al. (2016), Xu et al. (2018b), and Bals (2018) focus
financial frictions on SMEs, innovative supply chain on supply chain finance in various scopes. Closest to
finance (SCF) schemes—service clusters relying on our paper are three research syntheses on OFI. Birge
the collaboration between operations and finance (2015) provides an overview on the interactions
functions among supply chain players (Gelsomino between operations and finance adopting both analyt-
et al. 2016)—have prospered with the maturing of ical and empirical approaches without reviewing the
technology in recent years (BAFT 2016). According to literature. Zhao and Huchzermeier (2015) introduce a
2018 World Supply Chain Finance Report, global SCF “closed-loop” view and propose a framework for inte-
market size has reached $447.8bn in 2016—an incre- grated risk management on OFI by primarily review-
ment of 36% over 2015. Besides, more than half of the ing analytical models in this field. Moreover, Babich
corresponding firms have plans or are investigating and Kouvelis (2017) summarize the papers in a spe-
options to improve supply chain finance techniques cial issue on interface of finance, operations, and risk
(Bickers 2018). management and propose future research directions
In sum, there is growing recognition that risk man- mainly for analytical explorations.
agement should be conducted in a broader scope of The primary contributions of this study incorporate
financial assets and operational activities. On the one the following aspects. First, we review a broader scope
hand, CFOs across industries are going through liq- of research themes adopting multiple methodologies
uidity exercises to ensure their organizations have on OFI in risk management. Owing to the vast and
cash to survive the downturn, while they are also relatively divergent research streams, most previous
modeling scenarios of when stay-in-place restrictions reviews either envelop a subset of research topics in
start to lift (Freedman 2020). On the other hand, the this field or focus disparately on literature streams
COVID-19 pandemic brings more supply chain exec- primarily employing analytical, conceptual, or empir-
utives into the C-suite as sourcing diversification ical methods, as shown in Table 1. Therefore, synthe-
becomes a key supply chain strategy according to a sizing research streams spanning across various
recent PwC report (Cosgrove 2020). topics and dispersed methodologies could not only
Relative to the prevalence of risk management on provide a more comprehensive overview of this field,
OFI in practice, academic research in this field is but also help in revealing potential research opportu-
emerging rapidly yet still features great unleashed nities through a synopsis of topical mapping, data- or
potential. For instance, Seshadri and Subrahmanyam evidence-driven modeling, and the testing of extant
(2005) first introduce a special issue of Production & theoretical framework. Second, a systematic review
Operation Management to bridge the gap between the with an in-depth screening to draw the research evo-
worlds of finance and operations by combining and lution from original foundations to recent develop-
modifying concepts from finance to model risk in ments of each research stream on OFI in risk
operations. Moreover, Birge et al. (2007) call for management is presented to navigate through the
papers at the interface of finance and operations extensive landscape of research articles and to unveil
Production and Operations Management 30(2), pp. 355–389, © 2020 Production and Operations Management Society 357
Table 1 Overview of Research Syntheses on Operations–Finance Interface and New Contributions
Focal methodology of reviewed

papers
References Research scope Review methods Analytical Conceptual Empirical Concentration

Seifert et al. Trade credit Qualitative review √ √ Trade credit motives, order quantity decisions, credit
(2013) term decisions, and settlement period decisions
Paul and Trade credit Qualitative review √ √ Strategic advantages to well-managed trade credit and
Boden (2014) its impact on the wider economy & market failures in
trade credit supply chains & improving the operation
of trade credit
Birge (2015) Operations– Analytical √ √ The interactions between operations and finance with
finance interface examples and respect to the implications of the absence of
empirical arbitrage, the differences between systematic and
evidence idiosyncratic risk, the valuation of limited production
resources, and the inclusion of imperfect market
assumptions
Zhao and Operations– Qualitative review √ Integrated risk management framework for
Huchzermeier finance interface multidimensional integration of operations-finance
(2015) interface models by introducing a “closed-loop” view
Gelsomino Supply chain Qualitative review √ √ √ Concept and definitions of SCF & expected benefits &
et al. (2016) finance SCF initiatives
Babich and Operations– Qualitative review √ Main research themes of the recent iFORM research,
Kouvelis finance interface for example, supply chain finance, integrated risk
(2017) management, start-ups, entrepreneurship and
financing, asset pricing with supply chains
Drover et al. Entrepreneurial Qualitative review √ √ √ Integration of the large and disparate literature on
(2017) equity financing venture financing, and identify key considerations
relevant for the domain of venture financing moving
forward
Bals (2018) Supply chain Deductive and √ √ SCF ecosystem with seven dimensions and one
finance inductive data contextual perspective
analysis
Xu et al. Supply chain Bibliometric/ √ √ Research topics on deteriorating inventory models
(2018b) finance network analysis under trade credit policy based on the EOQ/EPQ
& qualitative model & inventory decisions with trade credit policy
review under more complex situations & interaction between
replenishment decisions and delay payment strategies
in the supply chain & roles of financing service in the
supply chain
This study Operations– Qualitative review √ √ √ Research evolution and opportunities in currency risk
finance interface management & commodity risk management &
supply chain finance & integrated operations and
finance in non-supply chain settings
disparity in literature as future directions. Third, this future research opportunities in (i) currency risk man-
study concentrates on the risk management perspec- agement, (ii) commodity risk management, (iii) sup-
tives of the interactions between operations and ply chain finance, and (iv) integrated operations
finance, and thereby categorize literature and identify and financing in non-supply chain settings. While
research gaps from sources of uncertainty, the linkage research streams (i) and (ii) address, respectively,
between operational and financial risks, and the integrated risk management via operational strate-
approaches to synchronize and explore the relation- gies and financial instruments to mitigate exogenous
ships among innovative operational strategies and financial risks (i.e., exchange rate risk and commod-
financial instruments in diverse settings. ity price volatility), research streams (iii) and (iv)
The remainder of this study is organized as follows. examine the management of endogenous financial
In section 2, we present the fundamentals to compre- risks (i.e., capital market imperfections) through
hend the evolution of OFI in risk management. Sec- joint operations and financing optimization in sup-
tions 3–6 paint the natural progression of research in ply chain and non-supply chain settings, respec-
this field through an detailed overview of four major tively. Section 7 concludes with a summary and an
research streams with respect to focal underlying overview of potential research directions on OFI in
sources of uncertainty, research evolvement, and risk management.
and financial flexibility are adopted (Trigeorgis 1993),

2. Evolution of Operations–Finance their interactions highlight the importance of coordi-
Interface in Risk Management nating financial and real risk management to build a
According to the MM theorem, financial risk manage- well-integrated risk management strategy (Triantis
ment could be independent from operational deci- 2005). For instance, financial hedging can mitigate
sions under strong assumptions of perfect capital inventory risk for a seasonal product through market
markets and information symmetry (Modigliani and instruments when its demand is correlated with the
Miller 1958). In the capital asset pricing model price of a financial asset (Gaur and Seshadri 2005). A
(CAPM), firms should not engage in any effort to risk-averse firm can dynamically hedge the profit by
manage firm-specific risk because investors can elimi- simultaneously optimizing operating policy and
nate firm idiosyncratic risks through diversification. hedging strategy when the profits are correlated with
Early research provides implications for the design of returns in financial markets (Caldentey and Haugh
capital structure and financial hedging strategies and 2006). Flexible contracts can be adopted with or with-
explores the reasons why firms hedge risk as justifica- out hedging in a supply chain of a producer and a
tions for the link between risk management and firm budget-constrained retailer facing stochastic clearance
value. The relationship between optimal hedging and price (Caldentey and Haugh 2009). Moreover, pro-
capital structure is studied in light of tax advantage of duct flexibility and financial hedging can be comple-
debt financing (Modigliani and Miller 1958, 1963) and ments (or substitutes) depending on whether product
agency costs of asset substitution (Jensen and Meck- demands are positively (or negatively) correlated,
ling 1976). The benefit of hedging could be greater while postponement flexibility and financial hedging
when agency costs are low (Leland 1998). are substitutes (Chod et al. 2010).
However, managers have become increasingly
aware of how their organizations can be buffeted by 3. Currency Risk Management
risks beyond their control in practice. In many cases,
fluctuations in economic and financial variables have In a risk management survey of 500 global company
destabilizing effects on corporate strategies and per- executives (The Economist Team 2009), exchange rate
formance, causing financial distress or making a firm uncertainty was ranked as the second most important
unable to carry out its investment strategy. Therefore, risk factor next to demand uncertainty due to the eco-
a value-maximizing firm can hedge for taxes, cost of nomic recession in 2009. Besides, the executives
financial distress, managerial risk aversion, the inter- ranked foreign exchange risk as their number one
nal supply of fund to ensure value-enhancing invest- concern for the subsequent year. While the majority
ments, or the elimination of costly lower-tail of multinational firms employ financial hedging
outcomes (Froot et al. 1994, Smith and Stulz 1985, instruments to mitigate the exchange rate risk, many
Stulz 1996). Meanwhile, shareholders and other stake- global companies have adopted operational hedging
holders start to realize they may need to manage sig- strategies by diversification in more than one low-cost
nificant risks for firms to be successful. Therefore, country (Chen et al. 2014). In this section, we first
there have been a dramatic change in the role of risk examine operational hedging and flexibility strategies
management in the past decades. To overcome the to manage exchange rate uncertainty, and then move
limitations of traditional silo-based risk management forward to the interaction between financial hedging
(i.e., risk management is compartmentalized and and operational flexibility.
uncoordinated in autonomous units of an enterprise),
managing risks across operational and financial func- 3.1. Operational Flexibility and Hedging
tions in a firm and across supply chain partners leads 3.1.1. Capacity Investment and Facility
to integrated risk management (Zhao and Huchzer- Location. Exchange rate uncertainty is first incorpo-
meier 2015, 2018). Thereafter, risk management has rated into an uncapacitated plant-location problem in
commanded a great deal of attention from researchers a mean-variance framework by Jucker and Carlson
in OM and finance, and a series of seminal papers laid (1976), in which currency risk is embedded in price
down the foundations of integrated risk management uncertainty and random demands are independent.
on OFI. While operational hedging utilizes real (com- A series of subsequent papers extend this model
pound) options that can be exercised contingent on using a mean-variance framework in quantity setting
demand, price and exchange rates in global supply firms (Hodder and Dincer 1986, Hodder and Jucker
chain networks (Huchzermeier and Cohen 1996), 1985a,b). In particular, Hodder and Jucker (1985a)
financial flexibility provides “the ability of a firm to study international plant location under correlated
access and restructure its financing at a low cost” exchange rate and price risks. Analogously, Hodder
(Gamba and Triantis 2013). When both real options and Jucker (1985b) examine a plant-location problem
for quantity-setting firms under correlated price risks contracts in the presence of exchange rate uncertainty,
across markets, where the mixed-integer quadratic order quantity flexibility, supplier-switching options,
programming problem can be solved using existing and profit sharing. Incentives for the producer and
branch-and-bound techniques. Moreover, Hodder suppliers to adopt flexibility are analyzed and its
and Dincer (1986) analyze simultaneous international impact on contract value is presented. Kazaz et al.
plant location and financing decisions in a mean-var- (2005) examine the impact of exchange-rate uncer-
iance model for quantity setting firms, which can be tainty on the optimal production strategies when the
readily solved using a multifactor approach. Hodder allocation decisions can be deferred until the realiza-
(1984) presents substantial computation advantages tion of exchange rates.
of a CAPM approach that measures risk by covariance The optimal production hedging (i.e., producing
as an alternative for a mean-variance objective for strategically less than total demand) and allocation
facility location models. hedging strategies are complementary as integral and
The valuation of “operating flexibility” to mitigate robust parts of an optimal global production-planning
currency risk in global manufacturing network con- strategy. Kouvelis and Gutierrez (1997) consider the
figuration has been well studied. For instance, Kogut production management of “style goods” sold in pri-
and Kulatilaka (1994) present a stylized model to mary and secondary markets with nonoverlapping
show the option value of production shifting in a selling seasons when demand and exchange rates are
multinational network under exchange rate fluctua- uncertain. The centralized production control policies
tions. Huchzermeier and Cohen (1996) study global are more (or much more) profitable than the decen-
supply chain network configuration options with tralized ones for any transfer price. Park et al. (2016a)
switching costs under correlated exchange rates study the pricing and manufacturing decisions for a
adopting a compound option valuation approach. firm selling one product in one domestic and one for-
Overall, the firm trades off switching and fixed oper- eign market under exchange rate risk. Stochastic
ating costs with benefit from exploiting differentials exchange rate leads to a new rationale for a monopoly
in factor costs and corporate tax rates. In addition, to set a price below its cost under various conditions.
Lowe et al. (2002) propose a two-phase approach to
evaluate alternatives in sourcing/production network 3.2. Interactions between Operational Flexibility
design using multiple criteria in the presence of and Financial Hedging
uncertain exchange rates. It is shown that a firm In practice, many multinational enterprises (MNEs)
should evaluate various supply chain network employ both financial hedging and operational flexi-
designs in light of environmental uncertainties across bility to manage exchange rate volatility. Hence,
multiple time periods. Please refer to Schwartz and established on the aforementioned operational flexi-
Trigeorgis (2004) for a neatly bound collection of bility and hedging literature, this research substream
novel research on real options and capital investment focuses on the interaction between operational strate-
under uncertainty. gies in capacity investment, production sourcing, and
allocation options with financial hedging in currency
3.1.2. Global Production and Distribution derivatives market.
Network. The variety of operational strategies in glo- This research stream analyzes operational flexibility
bal production and distribution provides rich soil for starting from stylized two-country sourcing model to
the exploitation on currency risk mitigation. Rosen- sophisticated network design of global supply chains
field (1996) presents structural results on global man- and financial hedging instruments from linear con-
ufacturing and distribution polices and focuses on tracts of futures/forwards to non-linear options in a
how to tradeoff extra capacity and flexibility to handle comprehensive portfolio, while the risk measurement
the uncertainties. Dasu and Li (1997) optimize pro- has evolved from symmetric risk metric, for example,
duction quantities for a cost-minimizing firm operat- variance to downside risk measure, for example, con-
ing plants in different countries under exchange rate ditional value-at-risk (CVaR). For instance, Mello
variability and switch-over costs. It is shown that the et al. (1995) show that the optimality of a multina-
optimal strategy is a barrier policy when switch-over tional firm’s production sourcing flexibility is depen-
costs are linear or step functions. Moreover, Kouvelis dent on the extent to which it is aligned with financial
et al. (2001) study both analytically and empirically hedging and liability structure. Chowdhry and Howe
the effects of exchange rates on the long-term owner- (1999) argue that a risk-averse global firm could
ship strategies (i.e., exporting, joint venture, or owned mainly adopt financial hedging to manage short-term
subsidiary) of production facilities for firms entering exposure while utilize operational hedging to a
foreign markets in the presence of strategy switch- greater extent in mitigating long-term exposure to
over costs. Kamrad and Siddique (2004) consider sup- currency risk. Ding et al. (2007) study the impact of a
pliers’ reactions in the valuation of flexible supply global firm’s financial hedging strategy on optimal
capacity, postponed allocation option, and thereby horizon (Aabo and Simkins 2005). Moreover, opera-
global supply chain structure in a mean-variance tional hedging by acquisitions (that reduce opera-
model. Chen et al. (2014) examine how operational tional volatility) is a viable substitute for financial
and financial hedging interact strategically in hedging by derivatives (Hankins 2011). Besides, a
maximizing the mean-variance utility in a multi- positive relationship is evident between the extent of
country-supplier model. When two exchange rates cross-functional integration in risk management and
are positively correlated and risk-aversion level is foreign exchange speculation, and active speculation
very high, financial hedging could dominate opera- and selective hedging are positively related to firm
tional hedging. Park et al. (2017) find that production size and internationalization (Aabo et al. 2012).
hedging could be both a complement and a substitute
to financial hedging in a global manufacturing firm 3.3. Future Research Directions
that maximizes expected profit under a value-at-risk In light of the recent coronavirus outbreak and global
(VaR) constraint, where production hedging may trade conflicts, various factors in capacity investment
cause the firm to decrease the optimal price below and facility location under currency risk can be
riskless price to benefit from exchange rate fluctua- exploited in future research. For instance, the mea-
tions. Zhao and Huchzermeier (2017) demonstrate surement technique of currency risk exposure and the
that operational flexibility (capacity reshoring and relationship among exchange-rate stabilization poli-
production switching) maximizes expected profit sub- cies, capacity utilization, taxation, location decision
ject to a CVaR constraint whereas financial hedging (e.g., reshoring), and return rates can be revisited in
minimizes CVaR subject to a minimum expected global supply chain settings. The relative effective-
profit, and therefore efficient financial hedging inter- ness of extant solution methodologies in managing
acts with capacity portfolio to minimize their substi- exchange rate risk, for example, financial market
tution effects in risk reduction. approach, mean-variance utility, real options theory
In empirical investigations, the effectiveness of can be assessed by further analysis and field study,
operational and financial hedging in currency risk while additional innovative approaches to capacity
mitigation has likewise been tested. In this context, optimization and valuation could be proposed. More-
operational hedging features geographic dispersion over, capacity location and financing decisions could
of multinational corporations’ global subsidiary net- be considered simultaneously to test and enhance the
work (Allayannis et al. 2001, Kim et al. 2006), efficiency of the existing findings (Hodder and Dincer
expected changes in operational volatility due to 1986). Besides, how capacity strategies in global man-
acquisitions (Hankins 2011), and real options; the lat- ufacturing network influence firms’ competitive
ter include market entry and exit, production and advantage could be validated empirically (Huchzer-
sourcing switches, and the acquisition and sale of a meier and Cohen 1996).
subsidiary (Aabo and Simkins 2005). Financial hedg- As COVID-19 pandemic has exposed the potential
ing has been measured by the magnitude of foreign vulnerabilities of global production, firms could
currency derivatives or foreign debt, where this hedg- adopt Industry 4.0 technologies and partially reshor-
ing is used to manage exposure to factors such as the ing for security and cost considerations. Therefore,
interest rate, price, and currency risks (Aabo and Sim- the implications of automation and reshoring on sup-
kins 2005, Aabo et al. 2012, Allayannis et al. 2001, ply-demand matching and the mitigation of currency
Hankins 2011, Kim et al. 2006). The complementary risk in both the foreign outsourcing and the interac-
relationship between operational and financial hedg- tion between robots and labor are worth further
ing has been supported by the finding that opera- explorations (Seric and Winkler 2020). In global pro-
tional hedging does not effectively substitute financial duction under exchange rate uncertainty, many issues
hedging (Allayannis et al. 2001). Hence, firms that such as cost structure analysis, pricing, product dif-
engage in relatively more operational hedging are ferentiation, market uncertainty, competitive advan-
likely to adopt financial derivatives, and such joint tage, and coopetition strategy could be explored
operational and financial hedging is associated with further. Moreover, various utility formulations and
reduced risk exposure and enhanced firm value. risk attitudes can be employed to examine the effec-
Operational hedging is typically used to mitigate tiveness of operational strategies. Besides production
long-term economic exposure, whereas financial hedging, switching options, and firm ownership
hedging is more often employed to manage short- strategies (Kouvelis et al. 2001, Park et al. 2016a, Zhao
term transaction exposure (Kim et al. 2006). The claim and Huchzermeier 2017), other operational strategies
that operational and financial risk management can such as modularization, product line expansion,
be substitutes is supported by evidence that the use of price-setting strategies, and long-term contracting (in-
real options (respectively, financial hedging) increases ter alia) could likewise be analyzed in global produc-
(respectively, decreases) with the length of the time tion networks under currency risk. In addition, it
would be interesting to study the impact of the afore- alternative measures of operational and financial
mentioned operational strategies on the value of hedging (with a higher precision) and extended to a
firm’s global production network, while competing broader scope of geographic regions and sectors,
and innovative approaches for example, CAPM and while the relationship between speculation and hedg-
real options theory could be further explored in real ing of currency risk could be explored in future
asset (production network) valuation models. research. The COVID-19 pandemic and tariff uncer-
The complexity of global supply chain network and tainty has accelerated the trend of production reshor-
the evolving variety of operational risks leads to a ing (Seric and Winkler 2020), thus global supply chain
sustained research interest in currency risk manage- restructuring and financial hedging as joint effort to
ment. First, identification of major operational risks in mitigate the impact of disruption and currency risks
global supply chains could vary over time. For necessitates further analysis and investigation. More
instance, as the recent major source of uncertainty, research attention could be devoted to global firms’
coronavirus outbreak could lead to interrelated dis- risk appetite and assessment, the drivers and condi-
ruption risks and currency fluctuations in multi-tier tions of integrated operations-finance in currency risk
supply chains. Empirical explorations by testing the management, case study of best practices examining
relationship among sources of uncertainty, as well as the success factors and effectiveness of currency risk
the relationship among financial, operational, and management, a comprehensive implementation plan
strategic currency risk management in global supply for currency risk management tailored to specific set-
chains. In terms of risk measurement, the implemen- tings, for example, industry-specific currency hedging
tation of downside risk measures (e.g., VaR and strategies in COVID-19 pandemic.
CVaR) features a higher computational complexity
(Park et al. 2017, Zhao and Huchzermeier 2017), thus
simplification methodology (analogous to the approx-
4. Commodity Risk Management
imation between mean-variance approach and an Commodities represent a large building block of glo-
exponential expected utility coupled with a normal bal economy (Martınez-de Albeniz and Vendrell
distribution) can be proposed in application. To fur- Sim on 2017). In general, commodities can be divided
ther explore the interactions between operational flex- into three major categories: agriculture commodities,
ibility and financial hedging under exchange rate energy commodities, and metal-based commodities.
uncertainty, existing models could be extended from Specifically, agriculture commodities include food
objective formulation, operational, and financial per- crops such as corn, rice, wheat, soybeans, sugar,
spectives. To start with, more general utility functions cocoa, and coffee, livestocks such as cattle, hogs and
could be adopted, while risk aversion could be con- pork bellies, and industrial crops such as lumber, cot-
sidered through constraints (instead of risk-return ton, rubber, and wool. Energy commodities incorpo-
objective formulations). Besides, macroeconomic vari- rate petroleum products such as crude oil and
ables could be incorporated as demand signals, vari- gasoline, natural gas, heating oil, coal, ethanol (used
ous risk-sharing contracts, price-setting, and as a gasoline additive) as well as electricity. While
payment-timing scenarios could be examined, and metal-based commodities include mined precious
more securities from derivative market in financial metals such as gold, copper, silver, and platinum, and
hedging could be employed. Moreover, to capture base metals such as aluminum, nickel, steel, iron ore,
real-world settings, the analyses could be expanded tin, and zinc. Besides, intermediary or manufactured
(respectively) to more complex settings, for example, products such as chemicals or generic drugs
multi-product, multi-currency, multi-stage, or contin- (Martınez-de Albeniz and Vendrell Sim on 2017) and
uous-time models. Additional sources of uncertainty products such as carbon emissions, renewable energy
(including interest rate risk, credit risk, commodity certificates, and white certificates could also be com-
price risk) and correlations among them could be con- modities. Typically, commodities are traded in very
sidered besides currency and demand risks, and the active markets, such as Chicago Board of Trade
effectiveness of operational and financial hedging can (CBOT), New York Mercantile Exchange (NYMEX),
be analyzed and tested when mitigating competitive or London Metal Exchange (LME), to cite a few
exposure to exchange rate risk in global supply (Martınez-de Albeniz and Vendrell Sim on 2017).
chains. As the most salient feature of commodities, price
In addition, the adoption of various risk metrics in volatility has a multifold impact on commodity opera-
global operations and financial hedging under tions. From the perspective of commodity buyers,
exchange rate uncertainty advocates further empirical price fluctuation would directly influence the pro-
investigation. Field study on the operations-finance curement costs, and thus creates uncertainty in mar-
interactions in multinational firms under exchange gins. It might further affect the demand when pricing
rate uncertainty could be conducted adopting is cost-sensitive and demand is price-sensitive (Goel
and Tanrisever 2017). For commodity sellers, price 4.1. Agricultural Commodities
fluctuation is likewise a great risk with regard to its Processors in agricultural sector face potential chal-
potential impact on demand. For intermediary com- lenges inherent from unique characteristics. First,
modity traders, the impact can be more severe since there is typically uncertainty in production yield and
both input costs and output prices are uncertain. quality due to weather, floods, drought and a number
Hence, commodity price fluctuations create great of hazards, as well as storage, handling, and process-
challenges in making operational decisions for all the ing parameters, which production managers must
parties involved; and moreover, if handled improp- deal with to ensure a regular flow of output products.
erly, they might even cause significant negative cash Second, the input and output spot prices are closely
flows and expose firms to financial distress (Devalkar linked and exhibit considerable variability. Third,
et al. 2017). unlike manufacturing products, agricultural products
Commodity operations naturally involve financial such as olives are typically perishable and therefore
considerations in integrated risk management. To producers cannot carry inventory from one selling
start with, financial hedging can play a pivotal role in season to another. Hence, the research on agricultural
mitigating commodity price risk, smoothening the commodities typically addresses a single-period
distribution of cash flows across periods, and helping model (Kazaz 2004). Moreover, while airlines, for
the firm avoid significant negative cash flows and example, are able to hedge against the risk of fluctuat-
costs via financial derivatives on commodity prices ing fuel prices by investing in call options, such hedg-
(Devalkar et al. 2017, Kouvelis et al. 2013, Turcic et al. ing instruments are far less prevalent for agricultural
2015). These hedging strategies typically do not affect commodities, due to the limited liquidity of the
the day-to-day procurement of raw materials, which option markets (Federgruen et al. 2017). As a result,
must take the current price as well as its expected evo- there is limited research on financial hedging in this
lution into account. Hence, an optimal procurement field, except for cases where soybean and corn are
strategy could be derived by combining traditional involved.
inventory theory with financial price modeling (Ber- Primarily, there are four methods agricultural firms
ling and Martınez-de Albeniz 2011, Berling and Xie can adopt to manage the uncertainty in purchasing
2014). Second, operational strategies such as forward cost and supply quantity. First, forward market (typi-
contracting is frequently adopted by firms to mitigate cally called contract farming in agricultural industry)
price variation in spot market (Anderson and Philpott is frequently used by buyers and sellers to lock the
2019); while the existence of spot market offers certain price for a fixed amount of products that will be deliv-
flexibility in procurement (Inderfurth et al. 2018, ered in the future (Boyabatli et al. 2011). Depending
Kleindorfer and Wu 2003). Meanwhile, futures con- on terms and conditions, there are different types of
tracts can provide important price information not forward contracts, for example, fixed price contract
available for conventional goods (Goel and Gutierrez and a contract with a specified pricing formula. Sec-
2011). Furthermore, in addition to price risk, com- ond, firms can mitigate supply uncertainty by trading
modity processors face demand risk (Goel and Tanri- the agricultural commodity in the spot market after
sever 2017), and operational constraints such as yield uncertainty is realized. As both forward con-
limited procurement, storage and processing capaci- tracting and spot market transaction can be utilized
ties (Devalkar et al. 2017). Since price and demand for for sourcing, it is thus important to optimize decisions
various commodities are typically correlated and stor- when choosing between them or combining both
age capacity and inventory decisions are crucial in (Inderfurth et al. 2018). Besides, leasing farm space to
matching a commodity’s supply with its demand, this grow crops or fruits in anticipation of reducing the
could result in an interaction between hedging and future purchasing costs is another strategy specific in
operating policies (Goel and Tanrisever 2017). agricultural sector. Compared with purchasing cost
Besides, for commodities (e.g., agricultural goods) under supply uncertainty, the expected cost of grow-
whose local spot prices might be affected by both ing by the firm is typically less expensive due to fac-
firm-specific local market specific factors such as tors such as scale economy. Finally, firms can counter
quality, timing, and location of production (Devalkar the supply and price uncertainty by changing the
et al. 2017) and other market factors, financial hedg- price of the final product in response to the realized
ing alone may reduce, yet not eliminate, the risk. The yield (Kazaz and Webster 2015).
above practices advocate research on the integrated Research in this substream could adopt multiple
optimization of financial hedging with operational methods simultaneously, while production decisions
decisions to mitigate commodity price risks, as and the unique characteristics of agricultural com-
detailed in the following subsections by various types modities are taken into consideration. For instance,
of commodities. Kazaz (2004) studies the leasing, spot market
purchasing and production planning under yield and (inventory) and hedging policies for a firm who pro-
demand uncertainty in the olive oil industry and fur- cures an input commodity, that is, corn, from the spot
ther investigates the value of leasing and having a sec- market to produce an output commodity, that is, etha-
ond chance to obtain olives in the spot market. nol, to sell to the end retailer, through either a spot,
Boyabatli et al. (2011) analyze the optimal procure- forward, or an index-based contract (the price and
ment, processing, and production decisions of a meat- volume of the commodities is determined as a func-
packer in a beef supply chain, where the packer can tion of spot and futures prices, thus is different from
source fed cattle from both a contract market and a that in Devalkar et al. 2011 and Devalkar et al. 2017),
spot market and then produce two substitutable beef when input price, output price, and demand are cor-
products. It is demonstrated the value of using a win- related and the yield is uncertain. In particular, they
dow contract instead of a fixed forward contract, and demonstrate that selling through an index price, that
the value of long-term contracting as a complement to is, partial hedging, is optimal. Besides, Shao and Wu
spot sourcing. In addition to leasing and trading in (2018) further take competition into account and
the open market that are explored in Kazaz (2004), study the effects of yield risk and yield correlation on
Kazaz and Webster (2011) study the pricing strategy firm’s selling strategies, spot price volatility, and
for a firm that operates under supply uncertainty profit, as well as the role of the forward market in the
from both a risk-neutral and a risk-averse perspective. equilibrium outcomes, and reveals that firms tend to
It is found that pricing is effective only when the firm allocate more sales via forward contracts as the corre-
is not trading in the market, and in the meantime, lation increases.
although the risk-neutral firm does not benefit from By incorporating the unique characteristics of agri-
fruit futures, a sufficiently risk-averse firm can under cultural commodities and examining several opera-
yield-dependent trading costs. Moreover, Kazaz and tional decisions, these papers underline the
Webster (2015) further investigate a generalized significant benefit of coupling input through sourcing
price-setting newsvendor problem where the firm decisions and output risk management via pricing,
cannot trade after the yield uncertainty is realized, production, and product substitution decisions (Boya-
and reveal that, besides risk aversion, the source of batli et al. 2011) and the importance of understanding
uncertainty—demand and/or supply—are quite the relationship between procurement, processing,
important in making the quantity and price decisions. and trade decisions for multiple commodities as well
Analogously, for agricultural-related firms whose as coordinating decisions across commodities and
output product is subject to commodity price uncer- periods (Devalkar et al. 2011). Kazaz and Webster
tainty, risk management is crucial. As frequently (2011) show that incorporating the yield-dependent
adopted in practice, a good portion of research con- cost structure into the problem has a profound impact
siders advance selling/forward contract. For exam- on the optimal amount of the initial investment in the
ple, Devalkar et al. (2011) consider the integrated farm space and on expected profit as well as the value
optimization problem of procurement, processing, of fruit futures. The correlation between input and
and trade of commodities for a firm that procures output prices provides a natural hedge, resulting in a
input commodity, for example, soybeans from the decrease in reliance on financial hedging in contrast
spot market, and then sells the processed commodity to the classic economics literature optimizing only the
by using forward contracts (with the forward prices output end of the supply chain and concluding the
being equal to the futures prices) and trades the input optimal hedge ratio is one in the absence of yield
at the end of the horizon, under the constraints of uncertainty (Goel and Tanrisever 2017). Therefore,
storage and operational capacity. They find that the firms should understand the dynamics between input
optimal procurement and processing decisions are and output prices across the supply chain when
governed by price-dependent inventory thresholds, developing hedging policies (Goel and Tanrisever
and it is optimal for the firm to postpone the output 2017). Besides, by obtaining advanced demand infor-
trade to the last possible period. Furthermore, mation through the forward sale, firms can have a bet-
Devalkar et al. (2017) incorporate financial distress ter operational planning by reducing holding and
costs and partially complete market where there are backlog costs (Goel and Tanrisever 2017).
firm-specific factors that affect the spot price of the
input commodity and the firm’s objective is to maxi- 4.2. Energy Commodities
mize the market-based value of cash flows. It is Energy commodities can be divided into two cate-
shown that the firm’s risk management objective has gories: renewable energy that can be easily replen-
a significant impact on the parameters of the optimal ished, and non-renewable energy that cannot be
policy; and in the meantime, financial hedging can reproduced. Almost 90% of the energy consumed
provide significant benefit. Moreover, Goel and Tanri- worldwide derives from five non-renewable sources:
sever (2017) examine the optimal procurement petroleum products, hydrocarbon gas liquids, natural
gas, coal, and nuclear energy. The five main renew- Since approximations are typically adopted to
able energy sources are: solar, geothermal, wind, bio- heuristically solve such MDPs (Nadarajah et al. 2015),
mass, and hydropower, which account for the there are numerous papers on the development of
remaining 10% of overall energy consumption. Since heuristics and further improve their performances.
the most developed commodity trading markets are For instance, Secomandi (2010b) finds that a reopti-
in non-renewable energy resources, with the excep- mized deterministic model can perform well for natu-
tion of ethanol and some electricity generation, we ral gas storage valuation, but restricts to a one-factor
next review the papers on non-renewable energy mean-reverting spot price model. Using a multifactor
commodities and then present those on electricity. forward curve model, Lai et al. (2010) develop a novel
Different from agriculture commodities, most of the and tractable approximate dynamic programming
energy commodities are storable; thus firms have the (ADP) method that, coupled with Monte Carlo simu-
option to purchase and inject, store, and withdraw lation, computes lower and upper bounds on the
and sell commodities during a predetermined finite value of storage to benchmark a set of heuristics used
time horizon (Nadarajah et al. 2015). In the meantime, by practitioners. They show that these heuristics are
the financial market for energy commodities is quite not only very fast to compute but also are significantly
mature. Hence, most of the problems on energy com- suboptimal compared to the upper and lower bounds.
modities are studied in a multi-period time setting Nadarajah et al. (2015) further develop a novel ADP
considering the significance of intertemporal linkages, approach to derive approximate linear programming
and financial hedging is of great importance. (ALP) relaxations for the real option management of
Typically, the value chain for energy commodities commodity storage. By applying to existing natural
entails physical conversions through refineries, gas storage instances, it is demonstrated that the ALP
storage facilities, transportation, and other capital- relaxations significantly outperform their correspond-
intensive infrastructures (Secomandi et al. 2014). There ing approximate linear programs, with the best ALP
are many types of operating flexibility embedded relaxation matching or improving on the best lower
in contracts, for example, “swing” or “take-or-pay” and upper bounds available in the literature for these
options in natural gas and electricity markets , which instances. In line with Lai et al. (2010), Secomandi
permit the option holder to repeatedly exercise the (2015) provides additional theoretical basis for the
right to receive greater or smaller amounts of energy, observed benefit of reoptimization with various
subject to daily as well as periodic constraints heuristics such as rolling intrinsic (RI, based on the
(Devalkar et al. 2011, Jaillet et al. 2004). Meanwhile, sequential reoptimization) policy and rolling basket
pipeline capacity contracts give merchants the option of spread options (RSO, based on a deterministic
to ship natural gas contingent on price realization at dynamic program) policies that are used to value leas-
the two ends of the pipeline (Secomandi 2010a). ing contracts on storage facilities, and offer additional
An important issue that has received significant numerical evidence for the near optimal performance
attention within the energy trading community is the of the RI and RSO policies in several practical cases.
valuation of these options/contracts. For example, Different from Lai et al. (2010) and Nadarajah et al.
Jaillet et al. (2004) present and test a general valuation (2015) in which dual penalties are obtained from the
(or pricing) framework for swing options; Secomandi value functions of approximate dynamic programs
(2010a) studies the value of pipeline capacity by using (ADPs) and thereby necessitates solving auxiliary
location spread options in the natural gas industry. ADPs, the estimation of dual penalties are obtained
Besides, great research attention has been devoted to from the optimal value function of a simplified ver-
the valuation of storage assets (Lai et al. 2010, sion of the problem, that is, when there are no fric-
Nadarajah et al. 2015, Secomandi 2010b). However, tions. It is shown that the RI policy significantly
compared with the valuation of financial options, outperforms the RSO policy in some cases. These
valuing such an option is difficult since it requires results are important to energy commodity traders
dynamic optimization of inventory trading decisions because they provide scientific validation, support,
with capacity constraints in the face of uncertain and guidance for the use of heuristic valuation mod-
energy commodity price dynamics to achieve the els in practice and therefore support the trading activ-
maximum time market value (Lai et al. 2010, Seco- ity (Lai et al. 2010, Secomandi 2015).
mandi et al. 2014). Hence, research in this field typi- Overall, by investigating the valuation of these
cally focus on the determination of trading policy, options, these papers suggest how the merchant’s
which nevertheless generally gives rise to intractable operational and trading decisions are linked and the
Markov decision processes (MDPs) owing to the need significant value in adapting the trading policy to the
to include the high dimensional exogenous commod- stochastic price evolution. For example, Secomandi
ity forward curve information (Nadarajah et al. 2015, (2010b) reveals that the optimal inventory trading
Secomandi 2015). policy at each decision time depends on both the
realized spot price and inventory available for a such risk is impossible. Quadratic hedging, which is
price-taking commodity merchant facing both space based on forming a self-financing approximate repli-
and capacity limits. A computational analysis based cating portfolio that is dynamically adjusted to mini-
on natural gas data further shows that mismanaging mize the expected quadratic hedging error, is an
the interplay of the operational and trading decisions attractive approach in this case. Interested readers can
can yield significant value losses. Moreover, when refer to Secomandi et al. (2019) for a more detailed
the firm has market power, that is, when the trading formulation and derivation of quadratic hedging in
decisions may have an impact on future prices, incomplete markets.
Martınez-de Albeniz and Vendrell Sim on 2017 find Moreover, electricity and other types of environ-
that the optimal trading policy is similar to the classi- mental friendly energy can be crucial with the
cal case without market power by taking kerosene as increasing concern of sustainability. In addition to net
an example. In addition, by studying the optimal metering and peak pricing policies, governments
multiechelon procurement and distribution policies have provided various direct (e.g., tax credit) and
for a firm in the gasoline supply chain, Goel and indirect subsidies (e.g., carbon tax) to increase renew-
Gutierrez (2011) indicate that the presence of the able energy investments (K€ ok et al. 2016). Correspond-
commodity market may lead to significant reductions ingly, different from the papers on conventional
in inventory-related costs; therefore, it is important energy commodities reviewed above, the research in
to incorporate the spot procurement flexibility and this field is mostly on the impact of pricing and sub-
price information available on commodity markets in sidy policies on investment, production decisions and
designing operating policies. carbon emission as well. For example, Murphy and
Besides, for most nonrenewable energy commodi- Smeers (2010) examine the impact of long-term for-
ties, refining is indispensable in the supply chain to ward contracts on investments in an electricity market
transforms inputs with a wide range of quality char- subject to market power, and find that it depends on
acteristics into refined derivative products of precise whether the demand is known at the time the invest-
specifications for feedstocks (Dong et al. 2014). ment and forward positions are taken. Alizamir et al.
Refineries vary greatly in input and capacity effi- (2016) study the dynamic control of remuneration rates
ciency (Plambeck and Taylor 2013); in their abilities to (prices) of feed-in tariff policies, and demonstrate that
convert heavy fractions to light fractions, that is, con- the current practice of maintaining constant profitabil-
version flexibility; and in the range of raw materials ity is theoretically rarely optimal, which is quite inter-
they are capable of processing, that is, range flexibility esting. K€ ok et al. (2016) investigate the impact of
(Dong et al. 2014). Since commodity industries such pricing policies (either flat or peak pricing) on the
as petroleum oil refining face tremendous price capacity investment levels and carbon emission, and
uncertainties in both input and output markets, the reveals that the same pricing policy may lead to dis-
ability to maximally utilize the process flexibility of tinct outcomes for different renewable energy sources
refining facilities and to make prudent procurement (renewable and conventional) due to their generation
decisions thereby is of critical importance for refiners’ patterns. Meanwhile, both direct and indirect subsidies
survival and profitability in volatile marketplaces can lead to a lower emission level, yet indirect subsi-
(Dong et al. 2014). In particular, Plambeck and Taylor dies may result in lower renewable energy invest-
(2013) show that variability in the market prices for a ments. Besides, Zhou et al. (2016) and Zhou et al.
manufacturer’s input and output has substantial (2019) explore the impact of negative prices. In particu-
implications for whether the manufacturer should lar, Zhou et al. (2016) show that the impact of the pres-
focus on improving input efficiency or capacity effi- ence of negative prices on the storage policy structure
ciency. Furthermore, Dong et al. (2014) consider the depends on whether it is fast or more typical slow
value drivers of conversion flexibility for a refinery grid-level electricity storage; and moreover, ignoring
who purchases inputs from a spot market and sells negative prices could result in a considerable loss of
outputs to a spot market. value when negative prices occur more than 5% of the
In addition, there is one research substream on how time. Zhou et al. (2019) further examine the effect of
to mitigate the risk of volatile energy commodity such negative prices on the value added by and envi-
prices by employing financial hedging strategy. For ronmental benefit of storage in a wind-energy-produc-
instance, Connors et al. (2011) investigate the optimal tion system. Moreover, Sunar and Birge (2018) study
static fuel surcharge financial hedging strategy and how each renewable firm commits and sets its produc-
the potential benefit for a manufacturer shipping fin- tion strategy when there are multiple competing
ished goods at different locations world-wide when renewable firms and inflexible conventional firms. It is
faced with both uncertain total transportation vol- shown that in equilibrium, imposing or increasing a
umes and fuel prices as well as budget constraint. market-based undersupply penalty rate in a period
However, when markets are incomplete, eliminating can result in a strictly larger renewable energy
commitment at all prices in the associated day-ahead costs. It is shown that if left unmanaged, the stochastic
market. The above research demonstrates that increas- costs could reverberate through the supply chain; and
ing renewable energy investments and further reduc- moreover, the equilibrium hedging policy will in gen-
ing carbon emissions require careful attention to the eral be a partial hedging policy. Kouvelis et al.
pricing policy and market characteristics. In addition, (2018b) further explore both stochastic costs and
Anderson and Philpott (2019) consider how a buyer working capital constraints. In the presence of capital
and a seller of a commodity can agree on a forward constraints, it is demonstrated that besides index
contract, either through direct negotiation or through a prices and index penalties that has to be pegged to the
nonstrategic broker, and further the difference between prices commodities that the supply chain members
these two mechanisms when both have private infor- purchase for production in the absence of capital con-
mation on the future spot price. straints, the terms of the coordinating contract must
include capital commitments, which would be chal-
4.3. Metal-Based Commodities lenging to implement in practice.
Metals play important roles in various industries
including power, construction, and manufacturing 4.4. General Industrial Commodities
sectors. For instance, they are important components Provided the absence of financial derivative markets
in battery production and even play a vital role in the for industrial commodities, financial hedging is thus
creation of nuclear energy. Besides, coins and bars infeasible and the only alternative is to focus on oper-
made out of precious metals are collected by investors ational risk management. This means that, for firms
as an investment vehicle. Price volatility is the most dealing with industrial commodities, they can on the
prevalent economic risk faced by both precious metal one hand mitigate the risk by considering procure-
miners and firms involved with base metals such as ment and selling both in spot market and by using
steel. Similar to energy commodities, financial hedg- option/forward contracts, just like that for the firms
ing is frequently adopted to manage price risk. Differ- dealing with agricultural commodities; and on the
ent from other commodities, there are typically other hand, they should not simply maximize
various grades for the same metal, which adds both expected profits, but instead sign contracts taking risk
complexity and flexibility to operations management. into account. For instance, as for the former,
For instance, gold miners can manage risk financially Martınez-de Albeniz and Simchi-Levi (2005) develop
by committing to sell gold through forward contracts a general framework for the design of effective portfo-
and options, and operationally by varying the grade lio contracts and replenishment policy so as to maxi-
of gold they process. Markou et al. (2017) thus empiri- mize the buyer’s expected profit when there are both
cally explore how these two risk management strate- inventory and price risks. It is demonstrated that port-
gies affect inventory operations. It is found that gold folio contracts not only increase the expected profit,
commitments and variable grading have clear effects but also reduce financial risk. Martınez-de Albeniz
on gold inventory, and moreover, they could be and Simchi-Levi (2006) further take the risk into
viewed as complementary risk management strate- account, which is measured by the variance of profit
gies: the operational side of the strategy allows firms and is considered together with expected profit. This
to remain profitable, and the financial side counter- thus extends portfolio analysis to the area of opera-
acts the unfavorable increase in inventory. tions management. Besides, Mendelson and Tunca
Integrated risk management for steel by incorporat- (2007) explore how the procurement of industrial
ing both operational and financial hedging has like- commodities is allocated between spot trading and
wise been explored. For instance, Kouvelis et al. the fixed-price market that precedes it, when there is
(2013) study how to manage commodity risks (price a single supplier and multiple manufacturers and
and consumption volume) via physical inventory and more importantly, all of them have private informa-
financial hedge in a multiperiod problem (with an tion. It is found that although strategic spot trading
interperiod utility function) for a risk-averse firm improves supply chain profits and consumer surplus,
procuring a storable commodity, such as steel, from it cannot eliminate fixed-price contracts entirely. This
both a spot market and a long-term supplier. It is is because depending on the information structure of
found that, as long as futures are used in each period, the supply chain, spot trading may make either the
alone or not, the optimal inventory policy is myopic; supplier or the manufacturers worse off. Similarly,
however, the optimal hedging policy, is never myo- Pei et al. (2011) analyze the structure and pricing of
pic, yet depends on future optimal decisions. Turcic option contracts for an industrial good in the presence
et al. (2015) examine the merits of hedging stochastic of spot trading and asymmetric information about the
input costs by considering a generalized version of buyer’s valuation premium for the supplier’s product.
newsvendor model in which both the upstream and In addition, Popescu and Seshadri (2013) examine
the downstream firms face stochastic input (e.g., steel) how different characteristics of product demand and
market affect the relative sales volume in the forward Boyabatli et al. (2017) examine the optimal processing
and spot markets for a commodity such as flash mem- and output storage capacity investment decisions—in
ory. Once again, it is demonstrated that a combination addition to the periodic processing and inventory
of factors will determine whether a commodity will decisions—of a processor that uses a commodity
be sold mainly through forward contracts or in the input to produce both a commodity output and a by-
spot market. product in the context of palm industry, where the
input and output spot prices are correlated and the
4.5. Future Research Directions production yield is uncertain. In the meantime, insuf-
Derivative markets for commodities enable financial ficient capacity and infrastructure could have an
hedging, bring liquidity to the markets, and thereby impact on the futures price and spot market price of a
mitigate price volatility. First of all, the research on commodity as well as the operations. For instance, the
commodity risk management with financial deriva- scarcity of available pipeline and storage has wors-
tives is still limited, especially in the agricultural sec- ened the situation of the oil market during the out-
tor. Second, while futures prices historically have break of coronavirus (Clifford 2020, Lahiff 2020,
served as benchmark prices for forward contracting Stevens 2020). Moreover, since the derivative markets
in research and practice, the futures contract price for commodity products could encourage long-term
might fail to converge with the cash price toward the investment in capacity, infrastructure and technology,
expiration date of the futures contract (nearby futures it would be interesting to incorporate financial
price) according to the US Institute for Agriculture & hedging.
Trade Policy (Suppan 2019a). Hence, how to manage Besides, the shocks of one firm in global supply
these risks in an inefficient derivative market is a chal- chains can be easily transmitted to its suppliers and
lenging issue worth more investigation. Third, while customers through operational decisions such as
excessive speculation and extreme price volatility transfer prices and order quantities, which might lead
have undermined the ability of processors and pro- to significant financial losses, and even a supply chain
ducers to manage their price risks (Suppan 2019a), disruption (Turcic et al. 2015). Moreover, the opera-
most papers suggest that the fundamentals of tional and financial interdependencies between sup-
demand and supply are the dominant drivers of comply chain members could ease the transmission of
modities prices. It is shown that excessive speculation risks along the chain. Thus, each firm must consider
and extreme price volatility can be attributed to the not only its own direct risk exposures, but also the
absence of well-calibrated and enforced position lim- cash-flow risks of its supply chain partners and how
its. Therefore, more research is needed in order to their strategic interactions through operational deci-
assess the true impact of speculation and position lim- sions, which might create indirect risks for the firm’s
its on the trading of commodity contracts by financial cash flows, as well as the other parties’ hedging strat-
entities. egy. For example, Kouvelis et al. (2018a) and Kouvelis
In the meantime, more operational strategies could et al. (2019) examine how cash-flow risks and supply
be introduced to manage the commodity price fluctu- chain characteristics such as market size, cash-flow
ations, for example, Park et al. (2016b) study the value volatility, and correlation affect firms’ hedging deci-
of inventory sharing between two firms in the pres- sions via vertical interaction (i.e., its supply chain
ence of spot and forward markets in a multi-period partners’ decision). Hence, more research can be con-
setting, where the two firms process a common com- ducted along this line, that is, both empirically and
modity to meet stochastic demands. While inventory analytically studying the operational and financial
sharing is more frequently adopted in retailing sector, decisions of a firm dealing with commodities from a
it has received relatively less attention in commodity supply chain perspective by taking its partners’ price
operations. Hence, another future research direction risk and decisions into account.
could be the effectiveness of inventory sharing in mit- Moreover, the strong linkages among various com-
igating the commodity price risk and further intro- modity markets could attract more research attention.
ducing other innovative risk management strategies. On the one hand, agricultural commodities could
This is of great importance in the context of the cur- serve as both a source of food and an industrial ingre-
rent economic downturn where cooperation is almost dient. For instance, both humans and animals con-
a necessity for firms to survive (Frangoul 2020). sume corn, yet the commodity is an important
Furthermore, most of the aforementioned papers ingredient in fuel production such as ethanol; humans
assume that capacity levels for processing and storage eat the beef of cows, while a variety of industries use
resources are given exogenously. The uncertainty in beef hide, fats and bones to create products. On the
spot prices and production yield may affect capacity other hand, there is typically an economic link
investment decisions because the profits from pro- between oil prices and agricultural and industrial
cessing depend on the yield and price. For instance, commodity prices. For example, lower energy prices
could help farmers on the input expenses side of the have adopted a different approach to aid including
balance sheet. Meanwhile, falling ethanol demand measures that help farmers to manage debt, facilitate
could hurt corn usage, and lower energy prices could access to credit and create a distinct program for
lead to a lower production cost. Therefore, spikes in farmers selling in local markets (Lilliston 2020).
one commodity market could inevitably trigger sub- Besides, apart from the current system of subsidies
sequent “spill-over” changes in other commodity and massive trade aid payments, a set of policies
markets. Investigating how these correlations across known as “supply management” is starting to gain
different commodity markets affect firms’ operational attention, under which the government could directly
and financial decisions in risk management could be manage agricultural supply through a variety of mea-
another important research direction. sures (Holmberg 2019). These initiatives—setting
In addition, most of the aforementioned papers (ex- marginal farmland aside, storing grain as reserves,
cept Kouvelis et al. 2018b) assume that commodity implementing price floors and ceilings, and control-
firms have sufficient capital. In reality, however, ling the volume of imports—could work together to
farmers in United States have been managing low ensure a fair price for farmers that covers their costs.
incomes, rising costs, increasing debt and bankruptcy, Hence, it would be meaningful to study how these
volatile export markets, and a series of extreme subsidies and trade aid payments as well as the sup-
weather events tied to climate change (Lilliston 2020). ply management measures can benefit the producers
In the meantime, many US oil companies are already and further revamp the operations of the agricultural
paring back spending and closing wells (Domm commodity related firms, especially with the advent
2020b). It is shown that probably 25 or 30% of the US of the new coronavirus.
shale firms are going to be restructured or go bank-
rupt in the next 9 to 12 months (Domm 2020a). 4.5.2. Energy Commodities. Most above papers
Besides, the trade war between United States and on valuation for energy commodities are conducted
China, and the COVID-19 are imposing new disrup- from the asset value maximization perspective. For
tive challenges for firms dealing with commodities. firms that can adapt production, suspension, and in
On the one hand, these global events have introduced particular shutdown decisions over time to the evolu-
greater price volatility in the commodity markets as tion of uncertain market factors, this asset value per-
traders built positions on growing concerns, for exam- spective is obviously not appropriate despite its
ple, the plunge of crude oil price during the COVID- popularity. Because the cost of a permanent plant
19 crisis (Clifford 2020, Garber 2020, Lahiff 2020). On shutdown is hard to assess as it may impact societal
the other hand, supply chain disruption results in far entities outside the specific plant being shut down,
less revenue than before yet with the same expendi- which could include the parent company owning the
tures or more to alter operations strategy. Hence, it plant and the local community (Trivella et al. 2017).
would be of great importance to study the impact of Therefore, societal impact has to be considered when
financial constraints on commodity risk management managing the permanent shutdown decisions in mer-
and the effectiveness of financing mechanisms. chant commodity and energy production assets and
calculating the value. More research could be con-
4.5.1. Agricultural Commodities. Analogous to ducted on production suspension that is frequently
that for energy commodities, conversion is an impor- used in the energy industry, for example, in response
tant form of operational flexibility in agricultural oil to changes of energy prices or government policy
refining, such as the oil extracted from soybeans, sun- (Plambeck and Taylor 2013, Seay 2012).
flower, canola, and safflower seeds. Although great In addition, how to achieve the goal of a low-carbon
similarity exists between the oil refining processes in energy future is one fundamental issue. Environmen-
these two sectors, the agribusiness has limited, often tal friendly and renewable energies only account for a
illiquid spot markets for the end products, and small portion of the overall energy consumption and
refineries face different challenges (Dong et al. 2014). there are still many challenges ahead. For instance, as
Therefore, investigating operational flexibility strate- a clean and energy-efficient fuel, hydrogen has to be
gies in dealing with these challenges can be a fruitful generated from compounds, for example, natural gas.
direction for future research. The cost could be expensive if cleaner sources like
Second, many countries have set a number of poli- biomass are used. Meanwhile, a tax on greenhouse
cies to support their agricultural sectors. For instance, gas emissions (or any other policy that increases the
US Department of Agriculture (USDA) has provided cost of fossil fuels) could backfire by reducing invest-
an unprecedented $26 billion trade aid to farmers ment in improving energy efficiency in manufactur-
through the Commodity Credit Corporation (CCC) ing (Plambeck and Taylor 2013). Consequently, even
prior to the COVID-19 outbreak. Family farm groups as fossil fuel companies claim to be pivoting toward
and Institute for Agriculture & Trade Policy (IATP) clean energy, they are planning to invest trillions of
dollars in new oil and gas projects that are inconsis- can be viewed as the application of financing schemes
tent with global commitments to limit climate change to enhance the efficiency of monetary flows in supply
(Reich 2020). Therefore, another important future chain, that is, “the inter-firm optimization of financing
research direction could be studying how to incen- as well as the integration of financing processes with
tivize the energy related firms to turn to renewable customers, suppliers, and service providers in order
energy considering the environmental impact. to increase the value of all participating firms” (Pfohl
and Gomm 2009). Third, SCF may merely refer to
4.5.3. Metal-Based Commodities. Analogously, supplier financing as a buyer-driven payables solu-
the mining industry faces intense global scrutiny for tion, that is, reverse factoring, where “the lender pur-
the environmental footprint. For example, crack- chases accounts receivables (of suppliers)... from
downs on environmental pollution have caused the specific informationally transparent, high-quality
shutdowns of more than half of the lead and zinc buyers.” (Klapper 2006). In this study, we adopt the
mines in China. While the mining sector starts to first approach to view SCF in a broader scope.
adopt cleaner ways of doing business, restrictions on The investigation of SCF begun with the explo-
mining activity might limit supplies and raise prices. rations on its drivers, major benefits, potential resis-
In the meantime, the BRICs countries have great tance, adoption process, and overall effects on
impact on metals markets and pricing, which supplier–buyer relationships. Supply chain finance
depends critically on the government’s fiscal and programs are typically initiated by established buyers
monetary policy. In general, stimulating measures (or suppliers), financial institutions (banks), or spe-
can stoke demand for metals, while tighter monetary cialized service providers (such as LSPs) to provide
policies can depress demand. Besides, one US trade financial assistance for SME suppliers (or buyers) in
policy imposed tariffs on steel and aluminum imports need of working capital. Thus working capital posi-
from China (Suppan 2019b). Most steel and metal tions in the supply chain are the primary antecedents
commodities have been affected by the escalating of SCF adoption and determine the types of SCF
coronavirus crisis. Therefore, there are many impor- instruments used. In the meantime, supply chain
tant factors besides price volatility deserve further finance typically establishes a conceptual foundation
investigation for the operational and financial deci- —based on principal-agent theory—while assuming
sions of metal commodity-related firms. that firms within and outside the supply chain have
asymmetric information. Firms within the supply
chain can serve as intermediaries to resolve the issue
5. Supply Chain Finance of asymmetric information between capital seekers
5.1. Foundational Research on Supply Chain and capital markets (Pfohl and Gomm 2009). Hence,
Finance supply chain finance aims to enhance the allocation of
Supply chain finance jointly optimizes operations and working capital through cross-functional coordina-
finance under capital constraint in various supply tion of operational and financial departments and
chain settings. There are typically three scopes of SCF inter-organizational collaboration among supply
(Liebl et al. 2016, Templar et al. 2016), as shown in chain partners (Hofmann 2005, Pfohl and Gomm
Figure 1. First, supply chain finance generally denotes 2009). The mechanism of a chosen SCF instrument
the management of monetary flows or financial pro- determines timing of the trigger event, the duration
cesses in supply chains, which is also referred to as and amount of funding, and the financing rate.
financial supply chain management, that is, “opti- The major benefits of SCF programs rely on the
mized planning, managing, and controlling of supply reduction of financing costs for suppliers (due to the
chain cash flows to facilitate efficient supply chain interest spread between SMEs and established firms)
material flows” (Wuttke et al. 2013a). Second, SCF or for buyers (because of extended payment terms).
For instance, the Swiss Post Group (the LSP) offers
Figure 1 Definitions of Supply Chain Finance combined logistics and financial services as a supply
chain intermediary in a pilot project with Procter &
Gamble (P&G), under which Swiss Post Logistics can
sell goods to retailers at standard prices determined
by P&G’s policies plus a logistics and finance fee
(Hofmann 2009), with the capital costs for the retailers
being much lower than that they would incur individ-
ually. Meanwhile, these programs have the further
advantage of strengthening supply chain relation-
ships, increasing its members’ negotiating power, and
improving service. The dependence between supplier
and buyer—and their respective bargaining power— shipping document, or bill drawn on the buyer. As a
are determined by the buyer’s order quantity, the consequence, the credit risk is relatively low and the
ordered product’s strategic value, and the intensity of financing rate is favorable. (2) In-transit finance pro-
market competition. These factors affect, in turn, the vides the borrower with a loan from a financial insti-
product’s purchase price (Liebl et al. 2016). The SCF tution, where the loan is based on product or
solutions driven by incentives to improve the adop- inventory (of a certain quantity and quality) that is
ter’s own financial performance are typically imple- currently being transported or enmeshed in other
mented based on bargaining power, and SCF logistics processes. The portable collateral of in-transit
practices driven by incentives to secure the entire sup- finance is the product deposit in shipment, so the
ply chain through risk mitigation efforts depend on a associated credit risk is less than in the pre-shipment
high level of trade process digitalization (Caniato finance case; hence the loan’s interest rate is accord-
et al. 2016). ingly somewhat lower. (3) Pre-shipment finance
For both the anchor buyers and suppliers, the enables a supplier to receive funding from a financier
onboarding process of involved parties is ranked —based on a buyer’s purchase order—for working
as the most important success factor of a SCF pro- capital needs (e.g., the purchase of raw materials,
gram (Herath 2015). The main costs of establishing inventory processing, personnel and management
SCF programs are (i) management costs of inter- costs) before product delivery. Because the collateral
organizational supply chain collaboration and of for pre-shipment finance is a purchase order instead
intra-firm cross-functional coordination and (ii) invest- of an invoice, the credit risk is relatively high; hence
ments in digital platforms for the trade process the interest rate for advancing liquidity to the sup-
(Wandfluh et al. 2016). Therefore, the success of supplier is typically high, though it could be reduced in
ply chain finance instruments depends crucially on light of a well-established buyer’s creditworthiness.
the alignment of incentives in supply chain collabora- An example application of this type of SCF is the
tion and cross-functional coordination (Blackman launch of a new product; here the supplier needs cap-
et al. 2013, Wandfluh et al. 2016, Wuttke et al. 2013b). ital for capacity investment in new production facili-
Buyers can categorize suppliers based on their strate- ties requested by a reputable buyer, which (together
gic importance and creditworthiness, bringing the with the bank) then initiates financing for the sup-
most crucial ones onboard first and then gradually plier. (4) Miscellaneous SCF instruments that span
incorporating more suppliers into the system (Wuttke across various time periods thus cannot be catego-
et al. 2013a). In the meantime, the SCF team needs to rized into one of the three types above. (5) The inter-
work closely with managers from the procurement, actions between general financing (i.e., without
operations, IT, legal, treasury, and finance depart- specific financing instrument) and sourcing decisions
ments. Furthermore, the extent of digitalization plays in supply chain settings, as defined in section 5.1.
a key role in providing the real-time transparency of
supplier invoice processing and other functions. 5.2.1. Post-Shipment Financing. As a major
Ensuring that a corporation’s enterprise resource plan- source of short-term financing, trade credit has
ning (ERP) system is compatible with the SCF plat- attracted great research attention (Paul and Boden
form typically requires both managerial effort and 2014, Seifert et al. 2013). The frequently explored
technical modifications. Besides, data transmission in topics in this substream include: (i) the motives of the
SCF transactions must comply with the involved existence of trade credit, (ii) the setting of the optimal
countries’ applicable electronic security laws. credit terms, and (iii) the impact of trade credit on
operations (mainly on inventory decisions in a
5.2. Categories of Supply Chain Finance newsvendor setting) and the supply chain members’
The extensive variety of supply chain finance solu- profit. For detailed elaborations of literature review
tions can be categorized from diverse perspectives, on credit term decisions and settlement period deci-
including timing of the trigger event, focal point of sions, especially for that under deterministic demand
credit risk, availability of collateral, and financed ele- or within one single firm, please refer to Chang et al.
ments in the balance sheet (Wuttke et al. 2013a). (2008), Bougheas et al. (2009), Seifert et al. (2013), Luo
Please refer to Camerinelli and Bryant (2014), BAFT and Shang (2014) and the references therein. In this
2016 and Babich and Kouvelis (2017) for related prin- subsection, we mainly focus on the first and third
ciples of categorization. In this section, we classify topics.
SCF instruments into four categories with regard to The motivations for firms to provide credit has been
the timing of trigger event. (1) Post-shipment finance actively researched for more than 30 years (Seifert
establishes a line of credit from a financier for a bor- et al. 2013), which can be classified into financial and
rower based on (typically, discounted) accounts operational motives. With regard to the financial
receivable. The collateral in this case is the invoice, motives, firms offering trade credit could have
advantages over their smaller and less financially the advantage of limited liability. Based on an empirical
secure customers, in either obtaining money study, Wu et al. (2018a) find that although both trade
(Schwartz 1974) or credit evaluation and collection credit and bank credit help with inventory investments,
over other competing lenders (Mian and Smith 1992). trade credit requires a higher cash level, while the bank
Trade credit can be seen as a liquid reserve held by credit serves as an insurance and can reduce a firm’s
the firm to meet its cash requirements in future; and cash reserve requirements.
meanwhile, the credit provider can earn an interest Furthermore, the research indicates that trade
rate by assuming a financial intermediary’s role credit is typically preferred if the supplier finances
(Emery 1984). Furthermore, the firm can profit from the retailer at rates less than or equal to the risk-free
the tax effect (Brick and Fung 1984) and the pooling rate (Cai et al. 2014, Kouvelis and Zhao 2012). Never-
effect of liquidity shocks (Hu et al. 2018). From the theless, trade credit might be chosen even if the sup-
perspective of operational motives, Ferris (1981) first plier is at a disadvantaged position (Yang and Birge
derives a transactions theory of trade credit use by 2017). It is demonstrated that the specific answer to
considering the trading partners’ exchange cost every both questions, on the one hand depends on whether
time the goods are delivered. Trade credit can be used there is only a single credit channel or both credit
as an operational response to deterministic variations channels are viable, and on the other hand, varies
in demand (Emery 1987), or to price discriminate with a lot of factors. For instance, Jing et al. (2012)
(Brennan et al. 1988, Petersen and Rajan 1997). More- show that trade credit is always less attractive than
over, trade credit can be seen as an efficient contrac- bank credit financing when there is only a single
tual device, such as in screening the buyer’s default credit channel, whereas bank credit might be more
risk (Smith 1987), signaling the product’s quality preferred when both credit channels are viable (see
(Emery and Nayar 1998, Lee and Stowe 1993, Long Cai et al. 2014, Chod 2016, Kouvelis and Zhao 2017,
et al. 1993), and aggregating the supplier’s informa- Yang and Birge 2011 for other related papers). Fur-
tion with the bank’s (or investors’) (Biais and Gollier thermore, the optimal trade credit policy and the
1997, Chod et al. 2016, Freixas 1993, Jain 2001, Maksi- equilibrium financing choice might depend on the
movic and Frank 2005). Besides, trade credit could be retailer’s net wealth or cash position (Cai et al. 2014,
effective in avoiding the borrowers’ opportunistic Raghavan and Mishra 2011, Rene Caldentey 2011,
behavior (Burkart and Ellingsen 2004), in improving Yang and Birge 2013, 2017, Zhou 2009), the priority
vertical supply chain relationship and therefore bene- rules among multiple creditors in a bankruptcy
fit all firms (Cunat 2006, Dass et al. 2014, Fisman and (Yang and Birge 2011), the production cost (Jing
Raturi 2004), or in softening price competition in a et al. 2012), the relative competitiveness of trade
horizontal supply chain (Peura et al. 2017). credit and bank credit market (Cai et al. 2014, Chod
There is extensive research on how a firm should 2016), the magnitude of the risk shifting problem
make order quantity decisions under trade credit and (Chod 2016), the supplier’s share of the retailer’s
further the relative effectiveness between trade credit expenditures (Chod et al. 2019a, Lee et al. 2017), and
and bank finance under stochastic demand, when the supplier’s credit rating (Kouvelis and Zhao 2017)
either the retailer (buyer) or both the retailer and the as well. Zhou (2009) and Dada and Hu (2008) con-
supplier (manufacturer) are capital constrained. The sider the problem in a setting where the bank is
essential research questions are: (i) What interest rate profit maximizing. Besides, when both the retailer
the supplier should set when offering trade credit, and and the supplier are capital constrained, Raghavan
should the bank finance the retailer or the supplier and Mishra (2011) suggest that a lender who finances
when both of them are capital constrained? (ii) For a the manufacturer has a motivation to finance the
capital-constrained retailer or buyer, how the order retailer as well; whereas Jing et al. (2012) argue that
quantity has changed, and further which financing the bank should finance the manufacturer if produc-
method the retailer should choose and what is he relation cost is low and finance the retailer otherwise. In
tionship between bank credit and trade credit? the meantime, when both bank and trade credit are
To address these questions, the bank credit market is viable, there is a divergence regarding the relation-
generally assumed to be competitive, that is, the bank ship between these two types of credits. Cai et al.
asks for an interest rate so that it is indifferent between (2014) show that it rests with the retailer’s internal
issuing the loan to the retailer and earning a risk-free capital, whereas Chod (2016) conclude that a combi-
rate. In this case, it is shown that the optimal order nation of bank and supplier financing is always opti-
quantity depends on the interest rate set by the sup- mal since each has their own merits. In addition,
plier; yet in general, the retailer orders a larger quantity Babich et al. (2012) suggest that internal financing
under trade credit compared to that without financing and trade credit loans are substitutable.
or in bank financing (see Jing et al. 2012, Kouvelis and Factoring is a form of debtor finance where a firm
Zhao 2012, Yang and Birge 2011, Zhou 2009), to take sells accounts receivable (i.e., invoices) to a third party
(i.e., a factor) at a discount. Since the receivables are (BFS), for the supplier and whole supply chain,
sold rather than pledged, traditional research mostly whereas the reverse holds for the retailer. The entire
focuses on the impact of moral hazard—a factor can- supply chain could perform better if one partner bor-
not contract upon a seller’s ex-post level of credit rows from bank and then shares credit with another
management—on factoring decision and at the same than the case in which both partners borrow sepa-
time supports the finding with empirical data rately.
(Sopranzetti 1998), or studies how factoring can miti-
gate under-investment problem (Sopranzetti 1999). 5.2.2. In-Transit Finance. Inventory pledge
Compared with factoring where suppliers typically credit is provided by a financial institution to a bor-
have higher credit ratings, reverse factoring is a quite rower while using secured inventory as collateral.
novel supply chain finance solution, which mainly This financial instrument can be used to fulfill work-
enables SME suppliers to obtain financing at a more ing capital needs for capacity expansion, equipment
favorable interest rate. Thus, the research on reverse renewal, or material supply. When other types of firm
factoring, on the one hand, typically compares reverse assets are already leveraged, pledged inventory can
financing with conventional sources of financing, serve as collateral to secure a loan. In the meantime, it
such as bank financing (Van der Vliet et al. 2015, van is widely used to develop agricultural markets in
der Vliet 2015), or with other supply chain finance countries such as in Latin America and in Asia (Coul-
solutions, such as early payment financing (Chen ter and Shepherd 1995). Particularly, how to set the
et al. 2017), and addresses the question of what exten- impawn rate is of great importance in inventory
sions of payment terms or underlying mechanisms financing. For instance, by using the database of spot
allow the supplier to benefit from reverse factoring steel and dividing the impawn periods into different
(Kouvelis et al. 2019, Tanrisever et al., 2020a). On the risk windows, He et al. (2012) demonstrate that the
other hand, from the perspective of the buyer, key to setting the impawn rate is to predict the long-
whether a buyer can expect to be served better from term risk, and moreover the log-returns of inventory
offering cheaper financing to its supplier by means of is autocorrelative.
reverse factoring, and further how much extra service In warehouse receipt finance, a financial institution
the buyer can contractually agree with the supplier provides loans to a supplier based on a warehouse
when the supplier serves demands of two buyers receipt that certifies—as portable collateral—the
with a minimum fill rate constraint are investigated secured storage of product in a specified quantity and
(van der Vliet 2015; van der Vliet et al. 2015). More quality. Here, the transfer of a warehouse receipt from
recently, to overcome the problem that the firm must supplier to financier conveys the right to withdraw a
sell the whole receivable when it chooses to sell it in certain amount of the commodity, at any time, from
reverse factoring, receivables pooling has emerged. the secured warehouse. The financier provides a loan
For instance, van der Vliet (2015) study how pooling up to an agreed percentage (the discounted value) of
receivables with other firms can mitigate the inherent the stored product. Like inventory pledge credit,
cost of indivisibility, and it interacts with pooling warehouse receipt finance is frequently used in the
investment (cf. van der Vliet et al. (2017) for the latest agribusiness sector to enhance the overall efficiency
version). of markets when producers and commercial entities
Although manufacturer/supplier guarantor financ- can convert inventories of agricultural raw materials
ing has been adopted in practice for years, relatively or intermediary or finished products into a readily
less research attention has been devoted to this tradable device (Lacroix and Varangis 1996, Mahanta
scheme. Zhou (2009) studies how a manufacturer 2012). The key aspects of warehouse receipt finance
teams up with a bank to offer an interest-free loan are risk assessment, provisions for performance guar-
program to a financially constrained retailer to sell antees and the establishment of systems for ware-
more products. Recently, Yan et al. (2016) focus on house inspection, and the financing ratio as well as
bank financing with a partial credit guarantee (PCG) funding structures (Jones 2018, Mahanta 2012). In
provided by the upstream firms in a setting where the addition, a recognized basis in law so that the owner-
bank acts as a leader. It is shown that with a suitable ship established by the receipt is not challenged is a
guarantee coefficient, the proposed PCG contract may precondition for the viability of warehouse receipt
realize coordination, even super coordination, finance (Lacroix and Varangis 1996).
whereas the bank loans without guarantee could not.
In addition, Jin et al. (2018b) find that overall, collabo- 5.2.3. Pre-Shipment Finance. Pre-shipment financ-
rative strategies, that is, bank financing with sup- ing solutions aim to alleviate capital constraint of firms
plier’s guarantee (BF-with-SG) and bank financing (mainly of the suppliers) prior to the shipment, which
with trade credit (BF-with-TC), dominate non-colla- can be initiated either by suppliers or by buyers. Typi-
borative strategy, that is, bank financing separately cally, buyers facilitate the financing provided the
suppliers’ financial constraint has an impact on the Manufacturers (or suppliers) can collect partial
buyers’ supply and thereby expected profit. payment from retailers (or buyers) in advance to
Buying firms could provide financial support cover the production cost, with the remaining pay-
directly to their suppliers by issuing both sourcing ment being collected upon delivery of the product to
contracts and loan directly, which is called buyer the retailer (Chen et al. 2017). Early payment financ-
direct financing (BDF). Deng et al. (2018) explore the ing is typically related to preorder/advance selling
efficacy of buyer finance in an assembly system with and advanced payment (discount). Since there is no
multiple suppliers by comparing buyer finance with interest rate imposed on the payment and it is only
bank finance, and further show that the assembler part of the wholesale revenue to the manufacturer,
may charge an interest rate that is even below its unit early payment is not a loan. The research in this sub-
capital opportunity cost in buyer finance, to reap the stream mainly focuses on the scheme design, effec-
benefit from enhanced inventory backup and lower tiveness and impact of early payment financing on
component purchasing prices. Besides, analogous to operational decisions. In particular, Lai et al. (2009)
manufacturer/supplier guarantor finance, buyer study preorder, consignment, and the combination of
intermediated financing is another approach for buy- these two modes. Chen et al. (2013) examine internal
ers to mitigate their suppliers’ cash flow risk by col- financing, delayed order payment and advanced pay-
laborating with banks. In particular, Tunca and Zhu ment. It is shown that the presence of financial con-
(2017) reveal that buyer intermediated financing can straint has a significant impact on the choice of
significantly improve channel performance, and different modes. Moreover, Chen et al. (2017) investi-
simultaneously benefit both supply chain participants gate the efficiency of early payment financing in a pull
by building a game-theoretical model and comparing supply chain by comparing with bank financing and
buyer intermediated financing with commercial loan in-house factor financing, which indicates that the
in a setting where the supplier’s product might be result depends on the manufacturer’s production cost
defective. and initial capital, as well as the demand variability.
Furthermore, to mitigate negative externalities result- Besides, Jin et al. (2018a) compare advance selling
ing from supply chain partners’ financial constraints, and delayed payment. It is demonstrated that
subsidizing scheme is frequently adopted (Daripa and advance selling strategy is preferable for the retailer
Nilsen 2005). As one of the pre-shipment finance when she is sufficiently capital-constrained or cus-
instruments that gain the earliest research attention, tomers are relatively price sensitive; in contrast,
most papers conclude that subsidizing can improve the delayed payment strategy is preferable for the sup-
performance of a supply chain in different settings. For plier and the entire supply chain when the retailer is
instance, Nagarajan and Rajagopalan (2008) demon- sufficiently capital-constrained.
strate that a simple holding cost subsidy based contract Besides, purchase order financing (POF) is fre-
can improve the performance of vendor managed quently employed to fund capital-constrained suppli-
inventory system. Babich (2010) indicates that subsidies ers, which allows financial institutions to offer loans
could have a significant value in mitigating supply risk to SME suppliers by considering the value of pur-
using a dynamic, stochastic, periodic-review model. He chase orders issued by reputable buyers (Tang et al.
shows that the optimal capacity orders do not depend 2017). POF has been studied in connection with other
on the subsidy decision under certain assumptions. pre-shipment finance solutions. For instance, Tang
Chen et al. (2016b) suggest that an inventory subsidiz- et al. (2017) investigate the relative efficiency of the
ing scheme plays a key role in coordination in a decen- POF and BDF in a supply chain where a financially
tralized supply chain. To secure production or constrained supplier can exert unobservable effort to
distribution, firms might invest in the capital-con- improve delivery reliability. It is demonstrated that
strained supply chain partner’s operations as equity the manufacturer’s information advantage about the
and later obtain a portion of dividends in return. In this operational efficiency makes BDF the more preferred
aspect, Yan et al. (2018) show that the supplier can financing scheme than POF if the supplier is severely
achieve the highest profit when offering a financing financially constrained. Analogously, Wu et al. (2014)
portfolio of the pure supplier finance (SF)/trade credit consider buyer-backed purchase order financing
and pure supplier investment (SI). In addition, long- (BPOF) in which a creditworthy manufacturer sup-
term contract is another strategy that is recently ports its unreliable SME supplier to make POF in
explored to help suppliers prone to default. By compar- line with a guarantee agreement. It indicates that
ing with short term contract, Swinney and Netessine BPOF significantly improves the core enterprise’s
(2009) reveal that dynamic long-term contracts, where profitability. Reindorp et al. (2018) address another
the contract price is partially tied to some index, new perspective in purchase order financing: the
allow the buyer to coordinate the supply chain in the potential of purchase commitments for mitigating
presence of default risk. capital market frictions. Specifically, a commitment
brings to potentially opposing effects for the retailer: roles of 3PLs with a few exceptions. The earliest work
the financing effect and the risk-sharing effect. In on 3PL financing is Chen and Cai (2011), which indi-
addition, Zhao and Huchzermeier (2019) recently cate that 3PL financing might yield higher profits not
investigate both BPOF and advance payment dis- only for a 3PL firm but also for the supplier, the retail-
count (APD). They show that when either APD or ers, and the entire supply chain. Huang et al. (2018)
BPOF can be chosen, the retailer prefers APD to BPOF investigate a similar problem. Different from Chen
if her internal asset level is above a certain threshold; and Cai (2011), it is the supplier rather than the retai-
yet when both APD and BPOF are available, the retailer that pays for the transportation fee in Huang et al.
ler prefers APD and does not initiate BPOF unless the (2018) and the impact of wholesale price contract on
marginal cost of financial distress dominates the bene- supply chain coordination is studied. Furthermore,
fit of unit discount. Chen et al. (2018) and Zhou et al. (2017) incorporate
the impact of the leadership. Specifically, Chen et al.
5.2.4. Miscellaneous SCF Instruments. There is (2018) show that the supply chain profit can be higher
extensive research on SCF schemes that features vari- under leadership by the 3PL than by the manufac-
ous timing of trigger event. To start with, leasing (in- turer. Zhou et al. (2017) compare 3PL guarantor
cluding equipment leasing and leaseback) is another financing (LG) and manufacturer guarantor financing
important source of financing when acquiring equip- (MG) in a four party supply chain under different
ment. Equipment leasing could be provided by banks, power structures (between the manufacturer and the
captives and independent financial firms. Leaseback, 3PL). It concludes that when either the manufacturer
short for “sale-and-leaseback,” is typically a financial or the 3PL is the Stackelberg leader, the entire supply
transaction in which a firm sells an asset and leases it chain can benefit from letting the Stackelberg follower
back for the long term. In this substream, the first be the guarantor, whereas the follower’s preference of
managerial question is the lease-versus-purchase either MG or LG depends on the upstream firms’
decision (Smith and Stulz 1985) and whether enter economies of scale in operational costs. Nevertheless,
into a sale-and-leaseback agreement or not (Kim et al. there is no difference between MG and LG for the
1978) given certain financial frictions and various retailer and the supply chain under the Nash game, in
incentives. For example, Eisfeldt and Rampini (2008) which case both upstream firms prefer the other to be
study the financing role of leasing and secured lend- the guarantor.
ing considering that repossession of a leased asset is As one of the recently emerging SCF schemes,
easier than foreclosure on the collateral of a secured crowdfunding features an alternative fund-raising
loan but leasing involves agency costs due to the sep- solution to support innovative ideas and entrepre-
aration of ownership and control. They find that firms neurial ventures, typically by raising small amounts
that are more credit constrained tend to lease, while of money from a large number of people via Internet
firms that are less constrained tend to buy the asset. (Chakraborty and Swinney 2019). Depending on the
Besides, leasing is a financial mechanism frequently form of payment/reward to the investors, it generally
adopted in agribusiness for processors without capital can be classified into four types: donation-based,
to buy land for a certain product or for farm- reward-based, equity-based, and debt-based. The
ers/landowners without capital to maintain the land strong growth in crowdfunding has sparkled research
appropriately. Hence, the optimal amount of leasing interest. In particular, Moritz and Block (2016), Short
along with the use of spot markets in their production et al. (2017), and McKenny et al. (2017) provide excel-
planning decisions has been examined from the per- lent literature reviews of the current state of research
spective of (supply) risk mitigation. Interested readers in this area. Basically, the majority of the existing
can refer to section 4.1 for a comprehensive review of research focus on predicting crowdfunding campaign
the related research. outcomes and on the optimal campaign design
With an increasingly open global economy and (Babich et al. 2018). Two exceptions are Babich et al.
advanced technologies, third-party and fourth-party (2018) and Xu et al. (2018a), with both studying how
logistics providers (3PLs/4PLs) have emerged as crowdfunding interacts with more traditional financ-
finance providers in addition to their traditional roles. ing sources in a supply chain. To be concrete, Babich
Compared with trade credit and bank financing et al. (2018) compare crowdfunding with venture cap-
modes, in 3PL financing service mode, a 3PL is able to ital (VC) and bank financing in a double-sided moral-
take advantage of his position to coordinate material, hazard setting. Interestingly, it is shown that the eco-
financial, and information flows, and thus is conve- nomic value of crowdfunding might harm the entre-
nient in supervising goods and reducing financing preneur and the VC since competition from other
risk (Chen and Cai 2011, Chen et al. 2018, Huang investors reduces value to VC investors and entrepre-
et al. 2018, Zhou et al. 2017). The operations manage- neurs could lose valuable operational expertise of
ment literature has not paid much attention to these VCs. Xu et al. (2018a) investigate a firm’s optimal
funding choice by taking market uncertainty and is a higher upfront signaling cost owing to the allevia-
word-of-mouth (WoM) communication into account. tion effect of holdup. Besides, Babich et al. (2012) find
Compared with bank financing, it demonstrates that that a buyer is inclined to have more suppliers if the
crowdfunding is preferred only when the market internal financing is not available, facing either an
uncertainty is very small or relatively large. uncertain demand or an uncertain supply under capi-
Moreover, blockchain technology enables new tal constraint. Yang et al. (2015) indicate that a firm’s
levels of collaboration among supply chain partners potential bankruptcy can hurt its competitors and
as opportunities in SCF. On the one hand, firms have benefit its suppliers/customers. In addition, Agca
announced the creation of a blockchain platform for et al. (2017) show that credit risk propagates through
SCF, such as blockchain-based letters of credit, bills of multiple supply chain tiers for both positive and neg-
lading, factoring and reverse factoring (Hofmann ative credit shocks. Tong et al. (2018) study the inven-
et al. 2017). On the other hand, a new form of financ- tory policy under various payment timing contracts
ing—initial coin offering (ICO)—has emerged, in a multi-echelon supply chain, and demonstrate that
whereby an entrepreneurial venture obtains funds a wholesale price contract with partial consignment
from investors in exchange for crypto tokens timing can achieve the centralized inventory levels at
(“coins”) that are the sole means of payment for the both the supplier and the retailer.
venture’s future products of services (Chod and Recent advances in this substream focus on the con-
Lyandres 2018). Although it was first held by Master- tract design for supply chain coordination under
coin in July 2013, it became popular in 2017. The oft- financial constraint (Lee and Rhee 2010, Xiao et al.
cited advantages of ICOs over traditional financing 2017). In this aspect, Lee and Rhee (2010) consider the
include low transaction costs and global investor out- impact of inventory financing costs on supply chain
reach, as well as the ability to combine financing with coordination under all-unit quantity discount, buy-
customer base building. Interested readers can refer backs, two-part tariff, and revenue-sharing contracts.
to Cong and He (2018) and Babich and Hilary (2018) It is shown that these contracts fail to achieve joint
for more details of blockchain and ICO. Given that profit maximization if each agent relies on financing
both are quite new and still being actively developed, from a financial institution. Nevertheless, the supply
there is very few literature studying blockchain and chain can be fully coordinated if trade-credit in addi-
ICO in the operations and finance field. In particular, tion to these contracts is adopted. Meanwhile, Cha-
Chod et al. (2018) first explore both practical and the- harsooghi and Heydari (2010) propose a model that
oretical implications of blockchains for supply chain coordinates the reorder point and order quantities in
finance and operations management by comparing a two-level supply chain with backorder. Kouvelis
the efficiency of signaling a firm’s operational capabil- and Zhao (2015) show that buyback contracts are
ities to lenders through inventory transactions and coordinating and equivalent to revenue sharing with
that through loan requests. Furthermore, Chod and only variable default costs, while would be Pareto
Lyandres (2018) investigate the choice between ICO dominated by revenue sharing contracts in the pres-
and conventional equity-based financing for entrepre- ence of fixed default costs. Hence, revenue sharing
neurial ventures and identify several determinants of contracts are recommended for working capital coor-
optimal ICO structure. In addition, Nguyen (2018) dination in supply chains under bankruptcy risks.
reviews the literature in crowdfunding, initial coin Analogously, Xiao et al. (2017) find that all unit quan-
offering, and venture capital, as well as the potential tity discount contract fails to coordinate, whereas the
relationship among them. revenue sharing and buyback contracts can coordi-
nate when the supply chain has a sufficient total
5.2.5. General Financing and Sourcing in working capital.
Supply Chains. Since both the financial and opera-
tional status of a supplier is crucial for a buyer (vice 5.3. Future Research Directions
versa), the interactions between sourcing and financ- In contrast to its prevalence in practice, research
ing (without explicit financing instrument) are fre- endeavor of supply chain finance is relatively limited
quently investigated in SCF (see section 5.1). For in scale and thus features high potential for develop-
instance, Wu et al. (2018b) focus on how the buyer ing both qualitative and quantitative managerial
makes sourcing and production decisions when fac- insights. The recent economic downturn owing to
ing a spot market and multiple suppliers under COVID-19 poses corporates under a series of financial
capacity constraint and correlated disruption risk. risks that could strongly affect supply chain. This
Furthermore, Chod et al. (2019b) explore whether a advocates increasingly greater research effort on sup-
manufacturer facing default risk should single-source ply chain finance in the mitigation of financial risk
or multi-source, and demonstrate that diversification along the supply chain. To begin with, supply chain
is the preferred strategy in equilibrium although there finance is a concept that lacks coherent conceptual
foundation and thorough empirical investigation. further. For instance, the interplay between inventory
Moreover, analytics of SCF could be the next wave of policies and financing schemes in supply chain coor-
research in light of the rapid growth of SCF practice dination deserves more research attention (Chahar-
in the past decade, while new developments in Fin- sooghi and Heydari 2010), and the impact of
Tech (Lee et al. 2020)—for example, blockchain tech- competition among multiple suppliers/retailers on
nology—could spur research advancement in both supply chain coordination and financing could be
OM and Finance (Babich and Kouvelis 2017). studied in future (Lee and Rhee 2010). In practice,
supply chain partners could renegotiate credit terms
5.3.1. Trade Credit. As one of the primary in the presence of information asymmetry and credit
sources of short-term financing, trade credit has rating fluctuations, which can be incorporated in
attracted the majority of research attention in SCF. future explorations (Kouvelis & Zhao 2017; Xiao et al.
Although numerous theoretical advantages have been 2017).
demonstrated in trade credit, evidence indicates that
these advantages are far from always achieved (Paul 5.3.4. Coopetition of Supply Chain Finance
and Boden 2014). Meanwhile, how to extend the trade Providers. SCF features the diversity of participants
credit over time is another interesting topic worth including financial institutions, FinTech platforms,
investigating, considering the factors such as reputa- leading corporates, supply chain partners, logistics
tion formation (Diamond 1989), the maturity structure providers, etc. It is notable that potential competi-
of the project return stream and the durability and tors might team up to offer a SCF solution. On the
specificity of project assets (Wilner 2000), the depen- one hand, this could be demanded by the buyers to
dence between the creditor and the debtor (Wilner increase the magnitude of available funding, partic-
2000), the evolution of the bargaining power (Fabbri ularly for long tail suppliers, or to utilize the com-
and Klapper 2016), as well as contract incompleteness petition among SCF providers to lower financing
(Fabbri and Menichini 2016). cost and secure funding by diversification (Bickers
2018). On the other hand, the collaborating SCF pro-
5.3.2. Innovative Supply Chain Finance viders could benefit from the synergy effect in
Solutions. Besides trade credit, there are a wide leveraging geographic, funding, and technological
range of innovative supply chain finance solutions, strength (Herath 2015). Nevertheless, a few poten-
such as manufacturer/supplier guarantor finance, tial questions might arise despite these benefits. The
factoring and forfaiting, invoice discounting, pur- first question is how should financial institutions
chase order financing, buyer direct financing, early collaborate with FinTech platforms. A good portion
payment financing, buyer intermediated financing, of financial institutions might seek to consolidate
3PL/4PL financing, equipment leasing and leaseback, their leadership with a comprehensive proprietary
crowdfunding, blockchain-based SCF such as ICO, platform; while others would either partner with
etc. On the one hand, each of these SCF solutions is another financial institution or a third-party to pur-
rapidly emerging in practice, yet there is relatively sue a combination of in-house development and
limited research on these innovative SCF solutions, external partnership (Hurtrez and Salvadori 2010).
especially the buyer-led ones. Hence, it would be Second, it would be interesting to explore how
interesting to study how these innovative financing externalities across borrowing channels lead banks
mechanisms affect the supply chain profitability. On to structure their lending contracts in when multi-
the other hand, the research on the selection among ple lending channels are available. Third, a corpo-
various SCF solutions in various supply chain settings rate would typically pick a lead bank in a multi-
and objective formulations is likewise very limited bank financing to keep all banks engaged in their
(Bals 2018, Gelsomino et al. 2016). Therefore, it would pool without having to manage multiple relation-
be interesting to figure out supply chain members’ ships. Therefore, a follow-up question is how the
preferences among SCF solutions by comparison lead bank should share credit information with the
studies. uninformed follower banks.
5.3.3. Supply Chain Finance and Coordination. 5.3.5. Risk Management in Supply Chain
The supply chain coordination under financial con- Finance. While SCF is highly perceived as promising
straints was first studied by Dada and Hu (2008) in a in practice, the potential associated risks should be
non-linear loan schedule. Coordination contract well managed to ensure its effectiveness. On the one
design in joint financing and operational decisions hand, SCF might not be secured by fixed tangible col-
including reorder point and order quantity, the per- lateral. On the other hand, SCF involves the commit-
vasive use of various SCF instruments, and the com- ment of multiple parties in a contract on timely
petitive structure in supply chains could be examined fulfillment of obligations (Zhao et al. 2015). Hence,
the quality of supply chain relationships and collabo- this issue could generate more managerial insights for
ration across functional units are prerequisites for the robust development of SCF.
SCF excellence. Although SCF platforms could have a
solid grasp of the detailed operational and financial 5.3.7. Supply Chain Finance in Agribusiness.
status of their clients and technically can assess the Agriculture in China and India is primarily carried
risks of potential defaults, risk management remains out by smallholders with typically limited and poorly
the name of the game (Ren 2017): Once there is oppor- documented assets. Provided that these assets can
tunistic behavior or supply chain disruption, the rarely be used as collateral for seeking loans from
entire SCF system may suffer. In addition, agency financial institutions, and the policy-induced distor-
issues between financial and operational stakeholders tions in the rural financial markets (such as those
of a firm (Babich and Kouvelis 2015), and incentive caused by credit subsidies, taxes on financial services
misalignment between insiders and outsiders of the and loan wave-off) could discourage financial institu-
firm or different classes of investors might hold back tions to fund smallholder agriculture, capital con-
the adoption of innovative SCF solutions, and affect straint has therefore been one of the main challenges
potential value generation (Babich and Kouvelis in the transition toward commercial agriculture (Chen
2017). Hence, it is crucial to study how to design et al. 2016a). Nevertheless, with increasing attention
incentive schemes to promote cross-functional collab- paid to social responsibility and sustainability (Xu
oration within a firm and across supply chain part- et al. 2018b), large buyers have begun to place these
ners and thereby mitigate the risks in SCF programs issues as priorities and try to help the farmers to
by mechanism design and game theory (Bals 2018, tackle the capital issue in upgrading and modernizing
Birge et al. 2007). In addition, various factors, for their farms. For instance, Nestle collaborates with
example, market differences and business cycles on local governments and banks to provide farmers with
SCF adoption/competition, the impact of SCF pro- financial support (Gong et al. 2018). The emerging
grams on risk metrics, and the risk mitigation of technologies such as FinTech have created opportuni-
financial institutions and solution providers of SCF ties for scaling up institutional finance for smallholder
could be further investigated (Bals 2018, Gelsomino agriculture. In the meantime, governments can
et al. 2016). Besides, mitigating risks in SCF programs finance the farmers through rural development and
through regulations and third party guarantee provi- poverty alleviation programs or by providing direct
ders (e.g., insurance firms) could be explored (Paul financial support to the institutions linking farmers to
and Boden 2014). Meanwhile, it would be interesting markets. Moreover, cooperatives, joint liability groups
to examine the effectiveness of frequently adopted or self-help groups (SHGs) could be important financ-
risk control techniques such as international factoring, ing channels for farmers (Chen et al. 2016a). Besides,
funded or unfunded sub-participation, securitization, many agribusiness firms could provide inputs and
syndication, multilateral institution or export credit services such as information and technical support to
agency finance, intermediation platforms and services the farmers. In addition, the agricultural supply chain
(BAFT 2016). may suffer from risks such as weather risk, yield
and quality uncertainty, market volatility, mortality
5.3.6. Liquidity of Supply Chain Finance-Related risk, property risk and strategic breach of the contract,
Assets. As SCF could becoming prevalent or even a which could significantly affect the development of
necessity for most firms in future, one issue in tandem SCF.
is the liquidity of SCF-related assets. Recently, a few Recently, a few OM scholars start to study the social
innovative mechanisms of liquidating SCF-related responsibility and sustainability in agriculture, espe-
assets have been proposed. For instance, firms could cially that in emerging economies. However, the exist-
issue debt secured by account receivables, and sell ing SCF research in agricultural supply chains is
their receivables to a financial institution who will fairly rudimentary. First, most papers in this field fea-
pool them with other firms’ receivables and issue a ture qualitative research such as case study, see Chen
package of securities against them, which is known as et al. (2016a) for instance. Second, in economics, Sti-
securitization (Mian and Smith 1994). Ant Financial glitz (1990) and Arnott and Stiglitz (1991) have quan-
(operator of Alipay) launched 2 billion CNY (US titatively studied peer monitoring, which is mainly
$317.4 million) worth of asset-backed securities (ABS) adopted to ensure borrowers exercising prudence of
on Shanghai Stock Exchange in 2018, and is China’s fund-in-use and therefore enhance the likelihood
first traded security backed by loans to online of repayment. Recently, de Zegher et al. (2018)
retailers, opening up a new financing channel in show how eliminating payment delay can improve
e-commerce (Ren 2018). Nevertheless, despite the productivity and welfare for farmers by combining
importance of the liquidation schemes in SCF, there is dynamic programming and non-cooperative game
scant research on this topic. Hence, a deeper dive into theory, and can increase profitability for processors
and (if the buyer’s discount rate is not too high) buy- match supply and demand. Nevertheless, a firm
ers. In comparison with the SCF practice in agricul- might face a capital constraint when making these
tural sector, research on SCF in agribusiness is far investments, and therefore an external source of
from sufficient, especially from risk management per- financing could be needed. In this case, how the finan-
spectives. On one hand, the underlying mechanisms cial factors would affect these operational flexibility
of innovative SCF solutions in agriculture (such as decisions should be taken into consideration. For
internal financing, leasing of movable assets, the instance, Gaur et al. (2011) study the impact of finan-
financing through tripartite agreements among farm- cial innovations (i.e., securitization) on real invest-
ers, leading firms and financial institutions, and ment decisions within the framework of an
group lending) can be explored further to show how incomplete market economy consisting of firms,
they alleviate the farmers’ capital constraints and investors, and an intermediary. The main result indi-
improve social welfare. On the other hand, it would cates that pooling and tranching are valuable in
be fruitful to combine both the operational and financ- reducing ambiguity surrounding the valuation of
ing decisions in agriculture and study the interactions new real investments in incomplete markets. Chod
between them. and Zhou (2013) examine how the optimal investment
in the capacity of flexible and nonflexible resources is
affected by financial leverage and, conversely, how a
6. Integrated Operations and firm’s resource flexibility affects its optimal capital
Financing in Non-Supply Chain structure in a two-product firm. It is shown that
Settings resource flexibility could not only reduce the mis-
match between supply and demand but also mitigate
After reviewing the research on supply chain finance, the shareholder–debtholder agency conflict and the
this section mainly explores the literature on capital risk of costly default. Boyabatli et al. (2015) study
budgeting in operational investment in non-supply how the tightening of the capital budget for financing
chain settings, which has recently gained significant the capacity investment and a lower financial flexibil-
research attention. Section 5 mainly explores the ity in the production stage shape the optimal choice
impact of capital constraint on operational decisions between flexible and dedicated technology for a mul-
in supply chain settings and thereby how various ti-product firm.
supply chain finance solutions could interacts with Most research attention on capacity investment has
each other and optimize chain-wide material and been devoted to cases in single-firm settings. In partic-
monetary flows. In contrast, this section focuses on ular, de Vericourt and Gromb (2017) study how a
the interactions between operational and financing firm’s capacity choice interacts with funding from
aspects to achieve joint optimization in single-firm investors to derive the optimal contract. It is sug-
settings, competitive settings, or multi-player net- gested that operational managers should challenge
works, respectively. In this stream, operational per- the financial policy and check whether adjustments to
spectives could include capacity investment, financial contracts can avoid the distortions of deviat-
production planning, inventory/sourcing manage- ing from efficient capacity investment. Ning and
ment, and incentive alignment; while the financial Sobel (2017) investigate the joint production and
aspects incorporate capital structure, payment time, capacity management with internal financing and
cash allocation, dividend issuing, subsidy, covenant, dividend issuing in a multi-period setting, and find
and capital market frictions (Tanrisever et al. 2020b) that internal financing creates a spillover between the
such as information asymmetry, transactions cost, liq- endogenous values of two operationally independent
uidity shock, interest rates, taxation, and bankruptcy. facilities, which thereby leads to an interdependence
Next, we adopt a process view and categorize this among the optimal policies.
research stream as follows. Moreover, capacity investment has likewise been
explored in competitive settings. For instance, Swin-
6.1. Capacity Investment and Financial Leverage ney et al. (2011) analyze the timing of capacity invest-
This research substream primarily explores how capi- ment decisions of both established firms and start-ups
tal budgeting, agency costs associated with the finan- in a competition of entering new markets. Ning and
cial leverage and costly bankruptcy process affects Babich (2017) study a R&D investment problem in the
the investment in operational flexibility for risk miti- presence of knowledge spillover and debt financing.
gation. Traditional research on operational flexibility Interestingly, it is shown that even firms with
(typically conducted in isolation from financial con- unlimited internal capital may prefer external debt
siderations) compares two counterbalancing opera- financing, because the incentive for risk shifting of
tional effects: Investment expenses with a potential debt financing can cure free-riding problem arising
increment in unit costs vs. an improved ability to from knowledge spillover and thereby the first-best
investment becomes feasible. They conclude that debt that public firms adopt riskier and more aggressive
can be used by firms as commitment device in a mul- output market strategies than private firms since the
ti-stage game. capital market has a greater ability to diversify
idiosyncratic risk.
6.2. Production and Financing Decisions
Analogously, the research on the interactions 6.3. Inventory and Financing Decisions
between production and financing decisions is There is extensive literature on the interactions between
mostly discussed in single-firm settings. For instance, inventory management and financial leverage in non-
Damon and Schramm (1972) study the interrelation- supply chain settings. For instance, Agrawal and Sesha-
ships among short-run production, workforce level, dri (2000) study the impact of risk aversion on price
investment or disinvestment in marketable securities, and order quantity in a setting similar to the newsven-
the additional short-term debt incurred or retired, dor problem, in which the demand distribution is a
advertising and pricing decisions by developing a function of the selling price and the risk-averse retailer
simultaneous and a sequential production-finance can trade after the demand is realized. Similarly, Sesha-
decision model, respectively. Xu and Birge (2004) dri and Wu (2014) provides a unified approach to con-
develop a single-period model where the production duct sensitivity analysis in production and inventory
and financing decisions are made simultaneously, planning problems when the decision maker is risk
and demonstrate that the interactions between a averse and faces uncertainties in future cash flows. In
firm’s production and financing decisions is actually the meantime, how a firm should dynamically replen-
a trade-off between the tax benefits of debt and ish its stock under cash flow constraint has been investi-
financial distress costs. Birge and Xu (2011) extend gated (Chao et al. 2008, Luo and Shang 2015). Alan and
Xu and Birge (2004) to a multi-period setting and Gaur (2018) explore how a bank can mitigate informa-
suggest the firm’s financial and operational decisions tion asymmetry by screening firms and thereby control-
are linked through the leveraging effect of fixed costs ling each firm type’s order quantity and leverage under
and the amount of risk taken in production commit- asset-based lending. Iancu et al. (2016) examine an
ments. There is a nonlinear form of the relationship inventory-heavy firm facing uncertain demand that can
among profitability, leverage, and inventory volatil- issue competitively priced debt to fund its inventory
ity. Moreover, de Korte (2016) examines how invest- investments and is afforded different degrees of opera-
ment in production postponement affects a firm’s tional flexibility to adjust inventory in response to
financial and operational processes (i.e., early or observed sales. They demonstrate that flexibility in
delayed product differentiation) in the presence of a replenishing or liquidating inventory by providing risk-
costly bankruptcy and salvage markets. It is found shifting incentives could lead to borrowing costs that
that the optimal production postponement might be erase more than one-third of the firm’s value; neverthe-
reversed in contrast to the case when capital markets less, these aforementioned agency costs and operating
are perfect. distortions can be fully alleviated by simple covenants
Early research on the interactions between finance widely used in practice when properly designed.
and production decisions in competitive settings
include Brander and Lewis (1986) and Brander and 6.4. Pricing/Customer Behavior and Financing
Lewis (1988), both of which consider a two-stage Decisions
sequential duopoly game where the two firms decide The research on the impact of financing decisions on
upon financial structure in the first stage and select pricing is relatively scarce. The earliest work to our
output levels in the second stage. However, Brander knowledge, Lam and Chen (1986) integrate pricing
and Lewis (1986) focus on the “limited liability” effect and credit decisions in a setting where both product
of debt financing whereas Brander and Lewis (1988) demand and customers’ cash flows are uncertain.
consider the strategic bankruptcy effects of financial More recently, Besbes et al. (2017) study dynamic
decisions. It is shown that limited liability may com- pricing under debt and find that limited liability
mit a leveraged firm to a more aggressive output could lead to performance spiral down. However,
stance, whereas the impact of bankruptcy costs varies debt amortization or financial covenants, debt relief
with its form. Parsons (1997) further extends Brander and early repayment options could be used to
and Lewis (1988) to incorporate a broader range of mitigate these inefficiencies in a decreasing order.
specifications. In contrast to the result in Brander and Besides, Chun et al. (2017) study how point valuation
Lewis (1988), firms initially have an incentive to and cash price decisions should be made optimally in
decrease output levels in certain cases if they take on light of the inherent liabilities in a dynamic model
more debt. Moreover, Chod and Lyandres (2011) where a firm sells one product and rewards cus-
examine the impact of the firms’ incentives to go pub- tomers purchasing in cash with points. Regarding the
lic on the product market competition. They indicate impact of financial distress/bankruptcy on the
operational decisions, Craig and Raman (2015) intro- global operations in the past decades that features
duce the store liquidation problem to the literature outsourcing and global collaboration. Reshoring and
and present a technique for optimizing key store liq- relocation decisions would be dependent on the
uidation decisions including markdowns, inventory trade-offs among flexibility, security, quality, stan-
transfers, and the timing of store closings. Further- dardization, automation, labor cost, and market fac-
more, Birge et al. (2017) investigate how customers’ tors. These considerations would thereby affect the
strategic waiting behavior to a firm’s financial distress interactions between financing (of higher importance
influences the firm’s probability of bankruptcy in in an economic downturn) and operational processes.
return, the firm’s operational decisions such as inven- To begin with, as the majority of extant research on
tory and price, as well as its profitability. What it indi- capacity investment and financial leverage focus on
cates is that deferred discounts, such as rebates and credit risk, future extension could incorporate addi-
store credit, can serve as an effective mechanism to tional sources of uncertainty, for example, commodity
mitigate strategic waiting. price volatility, exchange, and interest rate fluctua-
tions. Besides, global firms’ capacity investment
6.5. Incentive Alignment and Financing Decisions strategies and diversification effect could be explored
Traditionally, the incentive issues are examined pri- in various competitive settings including supplier or
marily between the managerial team and sharehold- buyer competition, price or quantity competition,
ers of a firm. In addition to shareholders, there are supply chain competition, or market entry and exit
other stakeholders, for example, banks and bondhold- games. The primary findings regarding agency issues,
ers who provide financing to the firm. In this case, cash reserves, dividend issuance, and capital struc-
financing providers could play an important role in ture from theoretical models could be tested as
shaping the firm’s operational and financial strate- hypothesis in field studies. The interactions among
gies. The earliest research in this substream mainly market changes, product portfolio, and capital struc-
investigate how capital structure, that is, the conflict- ture could be explored further in capacity investment.
ing incentives of bondholders and stockholders, can In addition, financial hedging strategies of various
control other incentive/conflict issues, such as the risks to secure capacity investment under competition
agency relationship between a firm and its customers could be examined.
when a firm liquidates (Titman 1984), and the agency Moreover, the inherent connection between pro-
issue between atomistic shareholders and manage- duction and financing decisions enables future
ment on investment (Stulz 1990). Dasgupta and Shin research opportunities. For instance, the impact of
(1999) study the impact of capital structure on the capital structure on product line expansion could be
incentive alignment in a Cournot duopoly to share studied in various types of market competition (i.e.,
information through a trade association, where the from perfectly competitive, oligopolistic, to monopoly
two firms are asymmetric in terms of their ability to market settings). The relative effectiveness of making
observe demand. They find that the frequent result production and financial decisions either sequentially
for all-equity firms that information will not be shared or simultaneously could be examined to further vali-
could be reversed. Moreover, Xu and Birge (2008) date the Modigliani–Miller theorem. Besides, the
explore the interactions among a firm’s production interactions of more underlying factors such as infor-
decisions, capital structure, and managerial compen- mation asymmetry, agency issues, competitive reac-
sation policy in a unified newsvendor framework, tions, public offering, market share, debt structure,
which observes that financial leverage can vary with and maturity could be analyzed and tested in joint
the profit margins. Besides, de Korte (2016) studies financing and production optimization (cf. Brander
the impact of conflicting benefits among the firm’s and Lewis 1986, Chod and Lyandres 2011).
shareholders, management and bondholders simulta- To further explore the interplay between inventory
neously in a three-stage newsvendor model. The and financing strategies, dynamic decision-making
results indicate that the portion of equity incentive in process in collaborative settings could be examined
the optimal contract is critical and should decrease in (Protopappa-Sieke and Seifert 2010). The interplay
bankruptcy costs and the leverage ratio of the firm. In between trade credit and inventory management in
addition, Lai and Xiao (2017) examine how manage- one-firm models (either as supplier or buyer) could be
rial short-termism can affect a firm’s inventory deci- examined in scenarios where a buyer has alternative
sion when external investors have only partial source of capital, a supplier sells multiple products,
information. or different competitive settings. Moreover, both
internal and external factors including multi-product,
6.6. Future Research Directions information asymmetry, default risk, payment timing,
The ongoing COVID-19 pandemic and global trade and upstream/downstream competition could be
conflicts would inevitably reshape the prevalent considered in further exploitations. The integrated
Table 2 Summary of Future Research Directions on Operations–Finance Interface in Risk Management
Category Research stream Major future research directions

Currency risk Capacity investment and facility (1) Risk measures of currency exposure; (2) relationship among exchange-rate
management location stabilization policies, capacity utilization, and location decision; (3) innovative
solution methodologies in optimization and valuation; (4) impact of capacity
strategies in global manufacturing on competitive advantage.
Global production and distribution (1) Implications of automation and reshoring on financial hedging in currency risk
network mitigation; (2) cost structure analysis, pricing, product differentiation, market
uncertainty, competitive advantage, and coopetition strategy; (3) utility formulations
and risk attitudes; (4) innovative operational strategies (e.g., modularization,
product line expansion, price-setting strategies); (5) impact of operational strategies
on valuation of global production network.
Interactions between operational (1) Interrelated disruption risks and currency fluctuations in multi-tier supply chains;
flexibility and financial hedging (2) simplification methodology for implementation of downside risk measures under
currency exposure; (3) extension to more complex settings, for example, multi-
currency and multi-stage; (4) operational and financial hedging in mitigating
competitive exposure to currency risk; (5) global supply chain restructuring and
financial hedging under pandemic and tariff uncertainty.
Commodity risk General (1) Risk mitigation in inefficient derivative markets; (2) impact of speculation and
management position limits on commodity trading; (3) effectiveness of inventory sharing and
innovative cooperative risk management strategies; (4) impact of insufficient
capacity and infrastructure on commodity operations; (5) operational and financial
strategies in light of supply chain partners’ strategies.
Agricultural commodities (1) Innovative operational flexibility strategies in agribusiness; (2) subsidies, trade
aid payments, and supply management measures to revamp agricultural operations.
Energy commodities (1) Social impact of permanent shutdown in merchant commodity and energy
production assets and valuation; (2) how to incentivize energy firms to adopt
renewable and clean energy.
Metal-based commodities Impact of environmental policy, stimulating measures, and monetary policies on
operational and financial decisions of metal commodity.
Supply chain finance Trade credit (1) Field study on how to achieve theoretical advantages of trade credit in practice;
(2) trade credit contact in dynamic settings considering reputation formation,
project maturity structure, bargaining power evolution, etc.
Innovative SCF solutions (1) Impact of innovative financing on supply chain profitability; (2) selection among
various SCF solutions in different supply chain settings and objective formulations.
SCF and coordination (1) Interplay between SCF and coordination contract design; (2) impact of
competition among multiple suppliers/retailers on supply chain coordination and
financing.
Coopetition of SCF providers (1) Competition and diversification effect of multiple SCF providers; (2) risk sharing
and synergy effect from the collaboration of SCF providers; (3) how externalities
across borrowing channels lead banks to structure lending contracts.
Risk management in SCF (1) Design of incentive schemes to promote cross-functional collaboration in risk
mitigation of SCF programs; (2) key factors of SCF adoption and competition in risk
management; (3) effectiveness of risk control techniques in SCF.
Liquidity of SCF-related assets Innovative mechanisms of liquidating SCF-related assets, for example, securitization
and asset-backed securities.
SCF in agriculture sector (1) Risk management in innovative SCF solutions for smallholders in agribusiness;
(2) social and environmental aspects of SCF in agriculture.
Integrated operations Capacity investment and financial (1) diversification effect in various competitive settings of capacity investment
and financing in leverage games; (2) field study on agency issues, cash reserves, dividend issuance, and
non-supply chain capital structure; (3) hedging strategies to secure capacity investment under
settings competition.
Production and financing decisions (1) Impact of capital structure on product line/inventory management in market
competition; (2) effectiveness of making production and financial decisions either
sequentially or simultaneously.
Inventory and financing decisions (1) Dynamic decision making in extended settings including multi-product,
collaboration and competition; (2) internal and external financing in inventory
replenishment.
Incentive alignment and financing (1) Impact of capital structure, managerial short-termism, and inventory decisions on
decisions incentive alignment; (2) empirical research on capital structure and interactions
between competition and incentive alignment under uncertainty.
Pricing/customer behavior and (1) Extensive operational and financial aspects, for example, product features,
financing decisions inventory metrics, loan maturity, and interest rate; (2) interaction of exogenous/
endogenous financing and pricing/customer behavior.
inventory replenishment and cash retention policy in the potential reciprocity between operational strate-
different settings can be further extended by incorpo- gies and financial instruments in extensive settings.
rating external financing options. Nevertheless, the research to date merely repre-
In addition, the interactions between pricing/cus- sents the beginning of investigation into the interac-
tomer behavior and financing decisions could be tions between operations and finance (Birge 2015).
enriched as follows. From operational aspects, addi- The majority of the aforementioned research contribu-
tional product features, third-party partnerships, tions in this filed has emerged in the recent two dec-
marketing strategies, and competitive settings could ades, which are far from sufficient to fathom the
be incorporated to study customer behavior in light of profound knowledge on OFI, especially from risk
financing decisions. From financial perspectives, loan management perspectives. Therefore, an overview of
maturity, interest rate, debt relief, mortgage claim, major future research directions proposed in sections
and managerial compensation could be jointly exam- 3–6 is presented in Table 2.
ined with pricing/revenue-related decisions. Besides, In addition, we propose general research directions
most extant papers in this substream focus on exoge- spanning across diverse research streams on OFI in
nous financing, thus more effort could be devoted to risk management as follows: (1) Extension to more
endogenous financing and its implications for opera- complex settings, for example, multi-product, market
tional decisions. Moreover, empirical research could entry/exit, competition, collaboration, multi-cur-
further test hypotheses on the relationships among rency, and multi-tier supply chain networks. (2)
financial distress, loyalty program, customer behav- Incorporation of information asymmetry/incomplete-
ior, and operational performance metrics (Besbes ness and incentive alignment issues, and thereby
et al. 2017, Chun et al. 2017). examine how they could affect operations and finance
Meanwhile, incentive alignment could be studied as well as their interactions. (3) Exploration of rele-
further in different settings including various types of vant operational decision variables including contract
principal-agency relationship, atomistic shareholder, terms, modularization, product line expansion, and
and Cournot/Bertrand competition. The impact of sustainability metrics. (4) Additional financial per-
capital structure, managerial short-termism, and spectives such as default probability, capital struc-
inventory decisions on firms’ information sharing and ture, payment timing, taxation, interest and exchange
incentive alignment could be examined further under rates, and credit rating. (5) Intricate sources of uncer-
information asymmetry (Dasgupta and Shin 1999, Lai tainty from both financial and operational aspects and
and Xiao 2017). Meanwhile, empirical research on their correlations. (6) Extension of single-period mod-
optimal capital structure and the interactions between els to multi-period settings, and thereby study, for
competition and incentive alignment under uncer- example, how operational and financial strategies
tainty deserves future research attention (Xu and would vary over time with growing information
Birge 2008). transparency, higher automation, and customer mar-
ket changes. (7) Consideration of alternative objective
formulations, risk attitudes, and decision timing. (8)
7. Conclusion Application of OFI theories in specific sectors, for
This study attempts to provide a comprehensive over- example, agricultural, automotive, electronic, and
view of research landscape and a navigation for logistics sectors. (9) Investigation of extant theoretical
future explorations on the interface between opera- conclusions using empirical and case study methods.
tions and finance in risk management. In sum, our (10) The impact of innovative technologies on market
research contributes to the extant literature in three dimensions (e.g., multi-bank platforms fostering
main aspects. First, we synthesize research spanning transparency/competition) and opportunities of
across diverse topics and divergent methodologies applying new technologies such as blockchain. (11)
and unveil potential research opportunities to advo- Innovative varieties and combinations of operational
cate future research attention in this dynamic and hedging and financial flexibility strategies.
emerging field through an abridgment of topical map-
ping employing analytical, conceptual, or empirical
approaches. Moreover, to elaborate the evolution of
Acknowledgments
each research stream, we trace the historical progres- The authors thank a senior editor and two anonymous refer-
sion from research origins to recent contributions in ees for their helpful comments and suggestions. Jiao Wang’s
detail and thereby pinpoint prospective discrepancy research was supported by the National Natural Science
in literature as future research directions. Third, risk Foundation of China (Grant No. 71902124), by China Post-
management aspects of operations-finance interac- doctoral Science Foundation (Grant No. 2019M663543), by
the Soft Science Project of Sichuan Science and Technology
tions have been emphasized in light of the interrela-
Department (Grant No. 2020JDR0057), and by the Chengdu
tionships among operational and financial risks, and
Philosophy and Social Science Planning Office (Grant No. Berling, P., Z. Xie. 2014. Approximation algorithms for optimal
2019L10), as well as by Sichuan University (Grant No. purchase/inventory policy when purchase price and demand
2018hhf-48, and Grant No. skbsh2019-37). are stochastic. OR Spectrum. 36: 1077–1095.
Besbes, O., D. A. Iancu, N. Trichakis. 2017. Dynamic pricing
under debt: Spiraling distortions and efficiency losses. Man-
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Vol. 30, No. 2, February 2021, pp. 355–389 DOI 10.1111/poms.

Operations–Finance Interface in Risk Management:

reality, markets imperfections (e.g., tax, bankruptcy

Table 1 Overview of Research Syntheses on Operations–Finance Interface and New Contributions

Focal methodology of reviewed

References Research scope Review methods Analytical Conceptual Empirical Concentration

and financial flexibility are adopted (Trigeorgis 1993),

Table 2 Summary of Future Research Directions on Operations–Finance Interface in Risk Management

Category Research stream Major future research directions

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