Inventory financing a risk-averse newsvendor with strategic default

Publication Date15 Apr 2020
AuthorTianyun Li,Weiguo Fang,Desheng Dash Wu,Baofeng Zhang
SubjectInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Inventory financing a risk-averse
newsvendor with strategic default
Tianyun Li
School of Economics and Management, Beihang University, Beijing, China
Weiguo Fang
School of Economics and Management, Beihang University, Beijing, China and
Key Laboratory of Complex System Analysis, Management and Decision, Beihang
University, Ministry of Education, Beijing, China
Desheng Dash Wu
School of Economics and Management, University of Chinese Academy of Sciences,
Beijing, China, and
Baofeng Zhang
School of Economics and Management, Beihang University, Beijing, China
Purpose The paper aims to explore the optimal strategies of inventory financing when the risk-averse
retailerhas differentobjectives, in the presence of multi-risk, i.e. demand risk, non-operational risk and retailers
strategic default risk.
Design/methodology/approach This paper develops an inventory financing model consisting of a bank
and a risk-averse retailer with strategic default. This paper considers two scenarios, i.e. the capital-constrained
retailer cares about its profit or firm value. In the first scenario, the bank acts as a Stackelberg leader
determining its interest rate, and the retailer acts as a follower determining its pledged quantity. In the second
one, the bank capital market is perfectly competitive. Lagrange multiplier method is adopted to solve the
Findings The optimal strategies in inventory financing scheme in two scenarios are derived. Only when the
initial stock is relatively high, the retailer pledges part of the initial stock. Retailers risk aversion reduces its
pledged quantity and performance. The strategic default reduces its profit. When it is relatively high, the bank
refuses to offer the loan.
Practical implications Analytical inventory and financing strategies are specified to help retailers and
banks to better understand the interaction of finance and operations management and to better respond to
Originality/value New results and managerial insights are derived by incorporating partially endogenous
strategic default and risk aversion into inventory financing, which enriches the interfaces of operations
management and finance.
Keywords Inventory financing, Newsvendor, Risk aversion, Strategic default
Paper type Research paper
1. Introduction
A healthy financial flow is vital to firmsoperations management in the highly competitive
economic environment. However, financially constrained firms are commonly seen,
especially if they are start-ups or small or medium-sized. The difficulty in financing has
always been an essential obstacle that prevents them from operating optimally. The key
factors resulting in the financing difficulty are the risks being detrimental to the loan
repayment. It reports that, in the first quarter of 2018, the non-performing loan ratio in China
financing a
This work was supported by the National Natural Science Foundation of China [grant number
71901010] and the China Postdoctoral Science Foundation [grant number 2018M641157].
The current issue and full text archive of this journal is available on Emerald Insight at:
Received 4 August 2019
Revised 22 January 2020
Accepted 24 February 2020
Industrial Management & Data
Vol. 120 No. 5, 2020
pp. 1003-1038
© Emerald Publishing Limited
DOI 10.1108/IMDS-08-2019-0417
is 1.89% (CEIC, 2018). This consequence may originate from multi-risk, including operational
risks, hazards and the debtorsstrategic default risk.
Demand risk is one of the most important risks in operations management. When the
demand realization is too low, the debt-financed firm does not gain as expected and fails to
afford the loan obligations, leading itself to bankruptcy liquidation. Besides, debtors are also
challenged by other risks that are independent of the current business, such as the debtors
resistance to emergency event. For example, when a firm encounters fire disaster in the
warehouse before sales season, no revenue can be used for repayment. This type of risk is
outlined as non-operational risk and modeled by credit rating (Kouvelis and Zhao, 2017). It
has a significant impact on the debtors profitability and its repayment ability.
Debtors strategic default, which is deliberate when the debtor is able to repay the loan,
causes serious loss for repayment. In 2010, the American companies Tishman Speyer
Properties and BlackRock strategically default on the loan used for their billion-dollar-worth
joint purchase (Bagli and Haughney, 2010). Besides big companies, 2635% homeowners
quit repaying the loan with affordability (Guiso et al., 2013). Strategic default plays a non-
negligible role in the financial market and the firmsoperations management. Debtors
strategical defaults significantly seize the creditors profit. Few works model the impact of
debtors strategic default on the operational and financing decisions (Zhang et al., 2014,2017;
Zhang and Wu, 2019) by assuming an exogenous strategic default probability. Differently,
we assume that the strategic default possibility is partially endogenous and varies according
to difference between the loan repayment and the salvage value.
To cope with those risks, the bank usually requires the debtor to pledge assets. Different
from credit financing, where the lender has zero pledge value, the inventory financing, as one
type of asset-based financing, requests the debtor to pledge its inventory, thus providing
small companies with more flexibility. In practice, though they may not possess fair assets,
their inventory is remarkably high. It reports that in China, by the end of 2018, the total value
of finished products inventory of industrial enterprises accounted for U4311.91bn (RMB),
with a 7.4% year-to-year growth (National Bureau of Statistics of China, 2019). This high
inventory level provides vast potential development for inventory financing. Practical service
is provided by third-party logistics companies (Chen and Cai, 2011).
In the presence of multi-risk, the bank will charge a higher interest rate or set a lower credit
limit, which makes it more difficult for debt-financed firms to operate optimally. Therefore, it
is interesting to explore the operational and financing decisions under inventory financing.
To answer this question, we propose an inventory financing model with a capital-constrained
retailer selling a single product to a stochastic market. Specifically, we explore the problem in
two scenarios: the retailer, as a Stackelberg follower, is concerned with its profit; and the
retailer cares about its firm value. Specifically, in two scenarios, we are interested to answer
the following research questions: the optimal operational and financing strategies, i.e. optimal
pledged quantity (inventory level) and interest rate? The impact of the key factors, such as
retailers initial stock, risk aversion, strategic default and credit rating on the optimal
strategies and the performance?
The main contribution of this paper is twofold. It provides two types of refined models with
analytical optimal inventory (respectively interest rate) strategy for the retailer (respectively
the bank) when multi-risk exists, i.e. demand risk, non-operational risk and retailers strategic
default risk. We show that only when the retailer initial stock is relatively high, the retailer
pledges partial initial stock. It demonstrates the insights of how these risks impact the optimal
decisions and the performances. For example, when strategic default risk is relatively high,
the bank earns a non-positive profit, which implies that the bank would not lend to the retailer.
The remainder of this paper is organized as follows. We review the related literature in
Section 2. The model is presented in Section 3.Section 4 studies the Stackelberg game where
the retailer cares about the profit. Section 5 investigates the problem where retailer cares
about the firm value. Section 6 concludes the work.
2. Literature review
Our work is related to two streams literature, i.e. interaction of finance and operations
management and risk aversion in decision-making, which are reviewed as follows.
The first stream is interaction of finance and operations management. Early papers can be
found in Buzacott and Zhang (2004),Xu and Birge (2004) and Dada and Hu (2008).As
inventory financing is compatible in practice, recent papers have covered a wide range of
topics in this field. Readers are referred to see Hofmann (2009),Gupta and Wang (2009),Lee
and Rhee (2010),Yang (2011), etc. In practice, the debtor usually gets a loan merely equivalent
to a portion of the inventory value, known as the advance rate or the loan-to-value ratio.
Hence, we limit ourselves to the literature related to asset-based financing with loan-to-value
ratio. Alan and Gaur (2018) investigate the asset-based financing between the bank and the
retailer, by assuming an advanced rate to describe the credit limit. Li et al. (2007) study the
optimal loan-to-value ratio of inventory financing under price uncertainty. Fu et al. (2017)
study the inventory financing problem with advance rate in a multi-period model and find the
over-stock phenomenon of the retailer. Our inventory financing setting is similar to Ma (2012),
who explores the problem in a risk-neutral newsvendor setting with fixed interest rate.
However, we go further to explore the interplay of a risk-averse newsvendor and a bank
exposed to multi-risk, where the interest rate is endogenously determined.
Generally, bank capital market is assumed to be perfectly competitive or oligopolistic. In
the former one, the bank can only get the repayment as that of risk-free investment (Kouvelis
and Zhao, 2011;Jing et al., 2012;Yang and Birge, 2018;Wu et al., 2019). The later one assumes
the bank as a profit maximizer (Dada and Hu, 2008). Bankruptcy liquidation is usually costly,
which has attracted the attention of scholars in operations management. Kouvelis and Zhao
(2011) find that when the bankruptcy costs exist, the suppliers wholesale price increases in
retailers wealth. Kouvelis and Zhao (2015) investigate whether conventional contracts can
coordinate the supply chain when bankruptcy costs exist. Yang and Birge (2018) explore how
bankruptcy costs impact the inventory financing portfolios. Similarly, we consider
bankruptcy costs under inventory financing in both perfectly competitive and oligopolistic
bank capital market scenarios by incorporating the debt-financed retailers strategic default
and non-operational risk.
Strategic default on loan obligations is widely studied in finance (see, e.g. Bharat and Sean,
2010;Gerardi et al., 2017). Recently, some works incorporate strategic default into operations
management under debt financing. Zhang et al. (2014) assume that the retailer strategic
default with an exogenous probability even though it has enough working capital. Zhang
et al. (2017) consider an exogenous strategic default coefficient of a capital-constrained
retailer financed by bank credit or trade credit under option contract. Zhang and Wu (2019)
incorporate strategic default into an overconfident supply chain to explore the joint pricing
and ordering decisions under trade credit. Differently, we design a partially endogenous
effective strategic default probability. The results show that debtors with different effective
strategic default possibilities bring different impacts to the bank and that high effective
strategic default possibility raises the interest rate and thus harms the financing process.
We would like to mention some papers related to our work. Berman et al. (2012) analyze
four types of maximization problems for the risk-neutral retailer considering bankruptcy
costs. One major difference is that they consider issuing bond while we consider inventory
financing. Kouvelis and Zhao (2017) examine how non-operational risk affect the optimal
financing modes. We follow the similar credit rating setting to characterize the retailers non-
operational risk. We find that poor credit rating reduces the retailers profit and increases the
banks risk.
financing a

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