Physical-internet-enabled auction logistics in perishable supply chain trading. State-of-the-art and research opportunities

DOIhttps://doi.org/10.1108/IMDS-10-2017-0486
Pages1671-1694
Date10 September 2018
Published date10 September 2018
AuthorXiangtianrui Kong,G.Q. Huang,Hao Luo,Benjamin P.C. Yen
Subject MatterInformation & 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
Physical-internet-enabled
auction logistics in perishable
supply chain trading
State-of-the-art and
research opportunities
Xiangtianrui Kong
Department of Transportation Economy and Logistics Management,
College of Economics, Shenzhen University, Shenzhen, China
G.Q. Huang
HKU-ZIRI Lab for Physical Internet,
Department of Industrial and Manufacturing Systems Engineering,
The University of Hong Kong, Hong Kong
Hao Luo
Department of Transportation Economy and Logistics Management,
College of Economics, Shenzhen University, Shenzhen, China, and
Benjamin P.C. Yen
School of Business, The University of Hong Kong, Hong Kong
Abstract
Purpose While significant eff orts have been made to study auction and l ogistics theories in the context
of perishable supply ch ain trading (PSCT) ove r the last few years, the co nsensus has not yet been
reached on how best to ex amine the impact of phys ical-internet-ena bled auction logistic s (AL) decisions
and processes on dynamic perishable products transactions. The purpose of this paper is to address
this gap by investigatin g the existing situations and i dentifying future opportunit ies for both academic and
industrial communiti es.
Design/methodology/approach The relevant literature was sort out along with three dimensions,
namely auction mechanism, level of decision and coordination. The methods of field investigation and focus
group discussion were also used to explore the factors influencing AL performance.
Findings A number of key findings presented. First, there is an emerging paradigm shift from offline
auction to online auction. Robust and resilient AL are needed to fulfill the massive number of orders from
different channels while considering dynamic decisions. Second, three-level decisions in AL have been
explicitly classified and defined. Various mathematical techniques used in literature vis-à-vis the contexts of
AL were mapped. Third, a coordination mechanism that dynamically balances trade-off between logistics
efficiency and transaction price was discussed. Lastly, several opportunities for future research were
distinguished with coherent connection of research domains and open questions.
Originality/value This paper not only summaries key themes of current research dimensions, but also
indicates existing deficiencies and potential research directions. The findings can be used as the basis for
future research in PSCT and related topics.
Keywords Physical internet, Auction logistics, Perishable supply chain trading,
Planning, scheduling and execution
Paper type Literature review
Industrial Management & Data
Systems
Vol. 118 No. 8, 2018
pp. 1671-1694
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-10-2017-0486
Received 17 October 2017
Revised 4 February 2018
Accepted 8 March 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
This work was supportedin part by Zhejiang Provincial,Hangzhou Municipal, LinanCity governments,
ITF Innovation and Technology Support Programme of Hong Kong Government (ITP/079/16LP),
HKSAR RGC GRF (No. 17212016; No. 17203117) and National Natural Science Foundation of China
(No. 71671116; No. 71701079; No. 71801154).
1671
Perishable
supply chain
trading
1. Introduction
A perishable supply chain is a network of enterprises that typically involves stakeholders of
suppliers, auctioneers, wholesalers, retailers and logistics service providers for perishable
products whose value diminish over time (Lambert et al., 1998; Van der Vorst et al., 2005).
Perishable supply chain trading (PSCT) is the process of buying, selling, transferring or
exchanging products, services, and/or information across a perishable supply chain (Cheng
et al., 2016). Auction is the main selling method in PSCT. This trend remains strong in the
floriculture sector of the Netherlands with transactions for 12.4bn plants and flowers each
year (The New York Times, 2014). Perishable produces auction is also increasingly popular
in China due to its fair and fast pricing determination mechanisms (Qin et al., 2010).
However, current auction planning and execution is usually designed with a more or less
fixed capacitywhile conforming to the staticrules. It is unable to cope with lumpydemands at
peak seasonsand becomes under-utilized duringoff-peak periods (Huang et al.,2015; Qin et al.,
2015). Several challenges have been observed based on the investigation from our
collaborating company. First of all, volatile auction supply and demand (usually caused by
seasonality, regionality or unpredictable customerspreferences) boost the randomness of
product variety, quality, quantity and date of delivery. For example, emergency auction
orders may interrupt processing sequence of auction trolleys. Such strong randomness
will further lead to unsynchronized decisions and processes (Van der Vorst et al., 2007;
Verdouw et al., 2010). Moreover, the existing data collection, transmission and analysis are
often lagging. Managers can only make subjective decisions according to their own
experience. Due to the lack of real-time visibility and traceability for the materials,personnel
and equipment, mutual conflicts among departments still exist (Qin and Yang, 2008).
Faced with those practical challenges, robust and resilient logistics is necessary to ensure
required throughput time with large auctioning volumes (de Koster and Yu, 2008).
According to Huang and Kong (2013), it has to fulfill the dynamic processing decisions and
requirements within limited auction time window in addition to the major functions of
traditional warehousing. New material handling activities have been added such as
products grading and auction trolley (un)consolidation. Auction and associated logistics are,
thus, considered in an integrated context, leading to the concept of auction logistics (AL) put
forward in this paper.
Advanced information technologies are expected to make AL decisions and processes
scalable with respect to transient demands. Physical internet (PI) might be a possible
solution to auction dynamics (Ballot et al., 2012; Montreuil et al., 2013). PI-enabled auction
logistics (PIAL) is founded on physical, digital and operational interconnectivity through
exploiting Internet-of-Things (IoT) technologies to address the related efficiency challenges.
Several benefits could be gained in PIAL. First, physical AL assets can be virtualized,
controlled and coordinated as digital representations in the cyber system (Dat, 2010).
Second, operational information, physical facilities and logistics assets (e.g. storage
locations) can be shared synchronously (Qiu et al., 2015). Third, through enjoying
information and resource sharing, adaptive decisions of PIAL can be made to deal with
plethora of uncertainties from both supply and demand side (Ashayeri and Kampstra, 2005;
Amorim et al., 2011).
Over the last two decades, significant efforts have been made to study auction and
logistics theories in the context of PSCT (Kambil and Van Heck, 1998; Katok and Roth, 2004;
Van der Vorst et al., 2007; de Keizer et al., 2015; Kong et al., 2016b). However, the AL
scenario for the perishables has received relatively less attention (Van der Vorst et al., 2005).
Many research questions are wide open for intense discussion; for example, if there is a need
for a new technical framework for dynamic auction-stage performance modeling and
analysis. Moreover, reports on PSCT industrial practices are limited to the floriculture sector
and majority of the related studies are still based on laboratory experiments (Qu et al., 2012).
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IMDS
118,8

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