There has been consensus that logistics as well as supply chain management is a vital research field, yet with few literature reviews on this topic. This paper sets out to propose some hot issues in the current research, through a review of related literature from the perspective of operations management. In addition, we generate some insights and future research directions in this field.
By Xiang Li
Abstract
There has been
consensus that logistics as well as supply chain management is a vital research
field, yet with few literature reviews on this topic. This paper sets out to
propose some hot issues in the current research, through a review of related
literature from the perspective of operations management. In addition, we
generate some insights and future research directions in this field.
1.
Introduction
Organizations
adopt numerous business improvement methodologies to improve business
performance. Logistics as well as supply chain management has been regarded to
be the crucial factor for the companies to obtain competitive edge. In fact,
logistics as well as supply chain management has received attention since the
early 1980s, yet conceptually the management of supply chains is not
particularly well understood, and many authors have highlighted the necessity
of clear definitional constructs and conceptual frameworks on supply chain
management. In this paper, we provide a tutorial on the current research of
operations management of logistics and supply chain. We first clarify the conception
of logistics and supply chain management in this paper, which defines the scope
of our related research papers. The core of this paper is that we provide
several hot issues in this field with examples to show how these researches
contribute from different research angles. Finally, we conclude the paper with
the insights obtained from our analysis and future study directions in this
field.
The paper is
organized as follows. In the next section, we specify the definitions of the
terms of logistics and supply chain used in our paper, with a comparison
between these two popular conceptions. In Section 3, which is
the core section of this paper, we provide several hot topics in current
research with detailed examples. In Section 4, we provide
insights and further research directions.
2. Conception
and Scope
2.1. Logistics
Logistics is
the management of the flow of goods between the point of origin and the point
of consumption in order to meet some requirements, for example, of customers or
corporations. The resources managed in logistics can include physical items,
such as food, materials, animals, equipment, and liquids, as well as abstract
items, such as time, information, particles, and energy. The logistics of
physical items usually involves the integration of information flow, material
handling, production, packaging, inventory, transportation, warehousing, and
often security. The complexity of logistics can be modeled, analyzed,
visualized, and optimized by dedicated simulation software. The minimization of
the use of resources is a common motivation in logistics for import and export.
Note that the
above definition of logistics is not unified, although it might be indeed, in
current environment, a commonly acknowledged one. For example, Council of
Logistics Management (now renamed as Council of Supply Chain Management Professionals)
referred to logistics as “the process of planning, implementing, and
controlling the efficient, effective flow and storage of goods, services, and
related information from point of origin to point of consumption for the
purpose of conforming to customer requirements,” which includes inbound,
outbound, internal, and external movements and return of materials for
environmental purposes.
As we can see,
the concept of logistics focuses on the product flow, which is the meaning by
which this word has been translated in Chinese. It also puts emphasis on the
activities of handling product, which include the storage, transportation,
distribution, and packaging and processing. Although business logistics
involves many activities, the traditional research of operations management on
logistics mainly relates to the fields of logistics facility, transportation,
and inventory planning.
2.2. Supply
Chain
Compared to
“logistics,” there appears to be even less consensus on the definition of the
term “supply chain management.” Kathawala and Abdou [1] point out
that SCM “has been poorly defined and there is a high degree of variability in
people’s minds about what is meant.” Nevertheless, we present a rather widely
adopted definition, which is given by Mentzer et al. [2] which is
rather broad, not confined to any specific discipline area, and adequately
reflecting the breadth of issues that are usually covered under this term: “Supply
chain management is defined as the systemic, strategic coordination of the
traditional business functions and the tactics across these business functions
within a particular company and across businesses within the supply chain, for
the purposes of improving the long-term performance of the individual companies
and the supply chain as a whole.”
The terms of
“logistics” and “supply chain” are usually comparative in academy and industry,
since both of them are closely relevant to the product circulation during its
whole life cycle, and both have been regarded as the central unit of
competitive analysis of model management science. Generally speaking, supply
chain is a more broadened conception with a wider range which can involve other
similar subjects, such as network sourcing, supply pipeline management, value
chain management, and value stream management [3–5].
In addition,
we can see that the conception of logistics has no relationship with
organization, which is the opposite of supply chain, since supply chain is made
up of multiple organizations, usually companies. An important issue in supply
chain management is that companies will not seek to achieve cost reductions or
profit improvement at the expense of their supply chain partners but rather
seek to make the supply chain as a whole more competitive. Hence, the
contention that it is supply chains, and not a single company, that compete is
a central tenet in the field of supply chain management [6]. A central
research methodology for supply chain management is game theory (and also
incentive theory for the scenario of incomplete information).
3. Hot Issues
Due to the
extensive research ranges in operations management of logistics and supply
chain management, we cannot possibly make a comprehensive review in one paper.
In this section, we point out several of the most important issues and hot
topics in recent research, which draws great attention from both academy and
industry.
3.1. Inventory
and Transportation Management on Specific Fields
As has been
pointed out in the previous section, the operations research on logistics
management still mainly focuses on the traditional domain, that is, the
inventory (including production planning) and transportation management. However,
a noticeable phenomenon is that most papers are putting emphasis on specific
fields with remarkable features captured into their models and thus making new
contributions to the literature.
For example,
the inventory management of perishable products (also referred to as
deteriorating product) is a rather old and mature field in logistics and supply
chain management, with replenishment policies for inventory being the main
focus of study. Whitin [7]
investigated such a problem, where fashion goods deteriorating at the end of
certain storage periods were considered. Since then, considerable attention has
been paid to this line of research. Nahmias [8] provides a
comprehensive survey of research published before the 1980s. Studies in recent
years on the deteriorating inventory models can be found in Raafat [9] and Goyal
and Giri’s [10]
papers, in which relevant literature published in the 1980s and 1990s is
reviewed, respectively. A more updated review is given in Blackburn and
Scudder’s [11]
paper. However, new models can still be developed to capture the current
management feature and obtain new managerial insights. Generally, two types of
perishable loss, quantity loss and quality loss, may take place for a
perishable product. The majority of the literature has dealt mainly with only
one type of loss. In this regard, Cai et al. [12] adopt a
stochastic model to study a supply chain in which a distributor procures from a
producer a quantity of a fresh product. During the transportation process, the
distributor has to make an appropriate effort to preserve the freshness of the
product, and his success in this respect impacts both the quality and quantity
of the product delivered to the market. Cai et al. [13] further
extend the model into a 3-stage supply chain with outsourcing transportation
involved.
Another
important field is transportation. It is generally known that the research on
VRP (vehicle routing problem) and its various extensions has been extensive.
However, other new domains on transportation can still be interesting topics.
For example, the remarkable growth in intermodal transportation over the past
decade has not been matched by a comparable level of academic activity, and,
hence, the research on intermodal transportation appears to have a great
potential. Chang [14] explores
one of the intermodal operational issues: how to select best routes for
shipments through the international intermodal network. The problem is
formulated as a multiobjective multimodal multicommodity flow problem with time
windows and concave costs, and an efficient heuristic is proposed. Vermaa and
Verter [15]
present a first attempt for the development of an analytical framework for
planning rail-truck intermodal transportation of hazardous materials by
developing a biobjective optimization model to plan and manage intermodal
shipments to represent the current practice; the routing decisions in the model
are driven by the delivery times specified by the customers. Bruns and Knust [16] study the
problem of load planning for trains in intermodal container terminals. The
objective is to assign load units to wagons of a train such that the
utilization of the train is maximized and setup and transportation costs in the
terminal are minimized. Bruns et al. [17] further
study the problem of robust load planning for trains in intermodal container
terminals. The goal of load planning is to choose wagon settings and assign
load units to wagons of a train such that the utilization of the train is
maximized and setup and transportation costs in the terminal are minimized.
García et al. [18]
adopt a new hybrid approach by combining OR techniques with AI search methods
in order to obtain good quality solutions for complex intermodal transport
problems, by exploiting the benefits of both kinds of techniques. The solution
has been applied to a real-world problem from one of the largest Spanish
companies using intermodal transportation.
3.2. Sourcing
and Marketing in Supply Chain
Sourcing is
the first step in a supply chain. The research on sourcing has been extensive
in recent years. This leaves open room for a supplier to improve efficiency
over time by further optimizing the production processes. In general, OEMs’
shifting of more development and engineering work, which require complex tasks
and customized products, to their suppliers implies a significant potential for
a supplier to accumulate knowledge and experience from learning, thus reducing
costs over time [19–21]. This
dynamic change of supply costs affects the negotiation of sourcing contracts.
A noticeable
issue is the utilization of auctioning in the sourcing strategy. One of the
first researches in this regard might be Chen’s [22], which
studies a procurement problem with one buyer and multiple potential suppliers
who hold private information about their own production costs. An optimal
procurement strategy is considered for the buyer who first specifies a payment
for each possible purchase quantity and then invites the suppliers to bid for
this contract. The auction can be conducted in many formats such as the English
auction, the Dutch auction, the first-priced auction, sealed-bid auction, and
the Vickrey auction. Chen and Vulcano [23] study a
supply chain where an upstream supplier auctions his inventory or capacity as a
bundle, which formulates the problem as a two-stage supply chain comprising a
single supplier and two resellers. Huh and Janakiraman [24] study
periodic-review inventory replenishment problems with auctions and other sales
channels and show that the optimality of (s, S) inventory replenishment
policies extends well beyond the traditional sales environments studied so far
in the inventory literature. Chen et al. [25, 26] study a
supply chain in which a single buyer wishes to procure a package of products or
services from various competing suppliers that possess private cost information
and show how the buyer can optimize his/her profit and at the same time
coordinate the channel by using a contract scheme involving auctions, audits,
and profit sharing.
For a supplier
that provides critical and customized components, the demand closely depends
on, and hence is susceptible to, the variation of the final product demand. In
the automotive industry, unstable and uncertain domestic volume of individual
models is cited as one of the biggest challenges faced by manufacturers due to
increased consumer choices [27]. The
consumer electronics industry is notorious for risk stemming from short product
life cycles and high demand uncertainty [28].
Furthermore, there is typically more uncertainty about the future demand than
about the current demand. This demand uncertainty adds another source of future
uncertainty, besides possible supplier switching (in a short-term
relationship), that influences the decision of initial capacity investment.
Marketing is
another end in supply chain. The collaboration with marketing science massively
extends the domain of supply chain management. Pricing, promotion, and channel
management are the three most important areas in this regard. Pricing and
promotion are the central issues in marketing management, let alone under
consideration of the supply chain environment. Li and Graves [29] explore
the pricing decisions during intergenerational product transition, by
formulating the dynamic pricing problem and deriving the optimal prices for
both the old and new products. The optimal initial inventory for each product
is also determined, and a heuristic method is discussed. Li and Zhang [30] study the
preorder strategy that a seller may use to sell a perishable product in an uncertain
market with heterogeneous consumers. They find that accurate demand information
may improve the availability of the product, which undermines the seller’s
ability to charge a high preorder price. As a result, advance demand
information may hurt the seller’s profit due to its negative impact on the
preorder season. Sainathan [31] considers
pricing and ordering decisions faced by a retailer selling a perishable product
with a two-period shelf life over an infinite horizon. Sinitsyn [32]
investigates the outcome of a price competition between two firms, each
producing two complementary products. It is found that each firm predominantly
promotes its complementary products together, which is correlationally
supported by data in the shampoo and conditioner and in the cake mix and cake
frosting categories. Liu et al. [33] examine
the efficacy of cost sharing in a model of two competing manufacturer-retailer
supply chains who sell partially substitutable products that may differ in
market size. Some counterintuitive findings suggest that the firms performing
the advertising would rather bear the costs entirely if this protects their
unit profit margin. Gao et al. [34] show that
the weather-conditional rebate program can increase sales by price
discriminating among a customer’s postpurchase states. Taking advantage of the
early sales, it can also reduce the inventory holding cost and ordering cost
and hence can increase the retailer’s expected profits.
In addition,
channel management is also an important interface between marketing and supply
chain. Chen et al. [25, 26] study a
manufacturer’s problem of managing his direct online sales channel together
with an independently owned bricks-and-mortar retail channel, when the channels
compete in service. They identify optimal dual channel strategies that depend
on the channel environment described by factors such as the cost of managing a
direct channel, retailer inconvenience, and some product characteristics.
Brynjolfsson et al. [35] investigate
local market structures for traditional retailers and then match these data to
a dataset on consumer demand via two direct channels: Internet and catalog.
Their analyses show that Internet retailers face significant competition from
brick-and-mortar retailers when selling mainstream products but are virtually
immune from competition when selling niche products. Guo [36]
investigates optimal disclosure strategies/formats in a channel setting with
bilateral monopolies and shows that retail disclosure leads to more equilibrium
information revelation. Chiang [37] extends
the single-period vertical price interaction in a manufacturer-retailer dyad to
a multiperiod setting, in which a manufacturer distributes a durable product
through an exclusive retailer to an exhaustible population of consumers with
heterogeneous reservation prices. The open-loop, feedback, and myopic
equilibria for this dynamic pricing game are explored and compared to the
centralized solution.
3.3. Green
Logistics and Supply Chain
Green
logistics refers to a logistics form which plans and implements green
transport, green storage, green packaging, green circulation processing, green
recovery, and other activities via advanced logistics technology. It aims to
reduce environmental pollution and resource consumption arising from logistics
activity so as to realize a “win-win” consequence in logistics development and
eco-environmental conservation. As an important avenue for realizing the
sustainable development strategy, greater attention has been given to green
logistics which will play an important role in industrial upgrading,
transformation of economic structure, promotion of logistics development level,
and other relevant aspects. Green supply chain is the supply chain management
with similar objectives and core implications. Green logistics as well as
supply chain management is also usually referred to “sustainable” management.
A typical
field in green logistics and supply chain management is reverse logistics,
sometimes called closed-loop supply chains, in which there are reverse flows of
used products (postconsumer) back to manufacturers. There has been substantial
research into production planning and inventory management in remanufacturing
systems. Simpson [38] first
studies a periodic review inventory system with stochastic and mutually
dependent demands and returns and provides the optimality of a three-parameter
inventory policy. Kelle and Silver [39] consider a
different model with independent demand and return processes, where all
returned products should be remanufactured. Inderfurth [40] shows that
the optimal policy derived by Simpson [38] is still
optimal in the case of fixed cost when lead times for remanufacturing and
manufacturing are identical. Van der Laan et al. [41] analyze a
push control strategy and a pull control strategy in a hybrid system and
compare them with the traditional systems without remanufacturing. Teunter et
al. [42]
explore the superior inventory strategies for hybrid
manufacturing/remanufacturing systems with a long lead time for manufacturing
and a short lead time for remanufacturing. Wang et al. [43] analyze
the impacts of the amount of products manufactured and the proportion of the
remanufactured part to the returned products on the total cost of the hybrid
system, showing that the cost could be reduced significantly if these two
critical values are optimally set. Other related works include Kiesmüller [44], Tang and
Grubbström [45],
Aras et al. [46].
For a comprehensive review, I refer the reader to Fleischmann et al. [47], Dekker et
al. [48],
and Ilgin and Gupta [49].
A typical
feature in reverse logistics and closed-loop supply chains is the quality
uncertainty of acquired used product, which is usually expressed by a random
remanufacturing yield and has been studied in some recent papers. Inderfurth [50] shows that
the uncertainty in returns and demand can be an obstacle to an
environmental-benign recovery strategy within a reverse logistics system.
Inderfurth and Langella [51] develop
heuristics for the problem of obtaining parts for remanufacturing by
disassembling used products or procuring new ones, under the consideration of
random disassembly yields. Galbreth and Blackburn [52] explore
acquisition and sorting/remanufacturing policies in the case of a continuum of
quality levels for cores with fixed quality distribution. The main premise is
that remanufacturing costs will go down if only the returned products with
better quality are remanufactured. Ketzenberg et al. [53] explore
the value of information in the context of a firm that faces uncertainty with
respect to demand, product return, and product remanufacturing yield by first
analyzing a simple single-period model and then proving that the results carry
over multiperiod setting. Çorbacioǧlu and van der Laan [54] analyze a
two-product system with end-product stock containing both manufactured and
remanufactured products while the remanufacturable stock may contain products
of different quality. Zikopoulos and Tagaras [55]
investigate the production problem in a reverse supply chain consisting of two
collection sites and a refurbishing site and examine how the profitability of
reuse activities is affected by uncertainty regarding the quality of returned
products. Denizel et al. [56] propose a
stochastic programming formulation to solve the remanufacturing production
planning problem when inputs of the remanufacturing system have different and
uncertain quality levels and capacity constraints.
Although the
research on remanufacturing systems is vast, there are only a few papers that
consider a market-driven acquisition channel for used products. Guide and
Jayaraman [57]
and Guide and van Wassenhove [58] are the
first to investigate this field, pointing out the importance of used product
acquisition management to deal with the uncertainty in timing, quantity, and
quality of the returned products. Guide et al. [59] develop a
quantitative model to determine the optimal acquisition prices of used products
and the selling price of remanufactured products, assuming that the quantity of
return items can be fully controlled by the acquisition price. Bakal and Akcali
[60] extend
the model of Guide et al. [59] into the
case of random remanufacturing yield and analyze the impact of yield on the
remanufacturing profitability. Karakayali et al. [61] study the
problem of determining the optimal acquisition price of the end-of-life
products and the selling price of the remanufactured parts under centralized as
well as decentralized remanufacturer-driven and collector-driven decentralized
channels.
3.4. Behavior
Operations
The decisions
under the consumers’ behavior are important for the firms to gain competitive
edge and obtain more profit. The customer’s behavior can be loss averse, risk
averse, regretful, and strategic, and the papers incorporating such factors are
regarded as increasingly important. Kök and Xu [62] study
assortment planning and pricing for a product category with heterogeneous
product types from two brands by modeling consumer choice using the nested
multinomial logit framework with two different hierarchical structures: a
brand-primary model in which consumers choose a brand first and then a product
type in the chosen brand and a type-primary model in which consumers choose a
product type first and then a brand within that product type. Nasiry and
Popescu [63]
study the dynamic pricing implications of a new, behaviorally motivated
reference price mechanism based on the peak-end memory mode, which suggests
that consumers anchor on a reference price that is a weighted average of the
lowest and most recent prices. They find that a range of constant pricing
policies is optimal for the corresponding dynamic pricing problem. Nasiry and
Popescu [64]
further characterize the effect of anticipated regret on consumer decisions and
on firm profits and policies in an advance selling context where buyers have
uncertain valuations. Tereyaǧoǧlu and Veeraraghavan [65] propose a
model that addresses pricing and production decisions for a firm, using the
rational expectations framework. They show that firms may offer high
availability of goods despite the presence of conspicuous consumption and
scarcity strategies are harder to adopt as demand variability increases.
Parlaktürk [66]
considers a firm that sells two vertically (quality) differentiated products to
strategically forward-looking consumers over two periods, setting the prices
dynamically in each period. It is found that the loss due to strategic customer
behavior can be less with two product variants compared to the single-product
benchmark, which indicates that product variety can serve as a lever when
dealing with strategic customers. Cachon and Swinney [67] consider a
retailer that sells a product with uncertain demand over a finite selling
season, with three types of consumers: myopic, bargain-hunting, and strategic
consumers. They find that the retailer stocks less, takes smaller price
discounts, and earns lower profit if strategic consumers are present than if
there are no strategic consumers, and a retailer should generally avoid
committing to a price path over the season.
Another stream
of research focuses on the risk attitude of the firms in the supply chain.
Lau’s [68]
might be the first piece of work that studies the newsvendor boy problem under
mean-variance framework, which takes the variance of system profit or cost into
the utility function. Other recent works employing similar methodology to
investigate supply chain problem include H. S. Lau and A. H. L. Lau [69] on supply
chain model with return policy, Buzacott et al. [70] on the
commitment-option contracts, Choi et al. [71] on channel
coordination, and Wei and Choi [72] on
wholesale pricing and profit sharing scheme.
4. Insights
and Future Directions
From the above
analysis, we can absorb the following insights and future directions in the
area of operations research of logistics and supply chain management.
First, the
logistics issue regarding the people’s livelihood becomes a hot spot. The
traditional research in this regard is related to perishable product, fashion
product, and electronic product, which have short life cycle. Nowadays, such
topics might include city logistics, emergency logistics, and agriculture
supply chain.
Second, new
directions on logistics and supply chain management can be brought about by the
development of economy and technology. A typical example is the information
technology which leads to the research on e-business and related distribution
channel choice. Nowadays, the common usage of RFID, cloud technique, and big
data can be important research directions for future study.
Third, the
environmental related research will continue to be big issue. With the steady
increase in global population and economic scale, resource crisis, ecological
damage, environmental pollution, and other issues have drawn universal concern.
It has been the consensus of the international community to attain
socioeconomic sustainable development through a greener economic pattern and
lifestyle. Many countries create a new outlook in industrial and technical
competition by increasing investment in the green logistics and supply chain
field, formulating and implementing various bills, plans, and strategies, and
strengthening the implementation of green economic development strategy. In the
future, the range of this topic will not only be just re-manufacturing, reverse
logistics, and closed-loop supply chain. Low-carbon issues can be an important
research direction.
Finally,
multi-methodology is an important direction for future study. Traditionally,
major research methodologies in operations management can be classified into
several categories, such as theoretical modeling, computation and simulations,
surveys, cases, event studies, and behavioral experiments. In recent years,
there is an emerging trend towards combining multiple research methodologies to
explore research problems in logistics and supply chain management. For
example, in addressing the issues of supply chain coordination, some papers
establish the respective models and verify the findings by real-world cases and
some papers conduct behavioral experiments with the goal of exploring the
real-world relevance of some theoretical models. Moreover, the number of the
papers with new applications of the existing methodology, such as cooperative
game and behavior operations, is expected to grow continuously.
About The
Author:
Xiang Li, College
of Economic and Social Development, Nankai University, Tianjin 300071, China
Conflict of
Interests
The author
declares that there is no conflict of interests regarding the publication of
this paper.
Acknowledgment
The author
gratefully acknowledges the support by the Fundamental Research Funds for the
Central Universities, no. NKZXB1228.
Publication
Details:
Copyright ©
2014 Xiang Li. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
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