A new risk assessment model for agricultural products cold chain logistics
| Pages | 1800-1816 |
| DOI | https://doi.org/10.1108/IMDS-03-2016-0098 |
| Date | 16 October 2017 |
| Published date | 16 October 2017 |
| Author | Hao Zhang,Bin Qiu,Keming Zhang |
| Subject Matter | Information & 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 |
A new risk assessment model
for agricultural products
cold chain logistics
Hao Zhang
Business School, Beijing Technology and Business University, Beijing, China, and
Bin Qiu and Keming Zhang
School of Economics and Management, Beijing Jiaotong University, Beijing, China
Abstract
Purpose –The purpose of this paper is to develop a quantitative risk assessment method for agricultural
products cold chain logistics to assess the condition of the fresh agricultural products cold chain process
objectively and accurately.
Design/methodology/approach –A risk assessment index system of agricultural products cold chain
logistics is designed on the basis of the risk identification for the process of agricultural products cold chain
logistics.This paper first uses catastrophe progressionmethod and a new maximum deviationmethod to build
an improvedcatastrophe progression assessment modelfor agricultural productscold chain logistics. In orderto
verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.
Findings –The results in the empirical research indicate strong support for the assessment model and
coincide with the reality. The risk assessment index system can also reflect the key risk factors from
agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression
assessment method proposed in this paper can be scientific and reasonable to predict risk.
Research limitations/implications –This paper contributes to provide a new risk assessment model for
agricultural products cold chain logistics. The new model overcomes the limitation of subjective
empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk
assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can
manage the potential risk by a set of scientific methods for assessing the risk before the accident.
Practical implications –The paper provides a practical guideline to practitioners, especially for cold chain
logistics managers, relevant management departments, and cold chain logistics management consultants. It is
proved that the new risk assessment method and the risk assessment index system of agricultural products
cold chain logistics can help them assess the risk scientifically and reasonably.
Originality/value –Although the calculation is simple, the new model can overcome the limitation of
subjective empowerment scientifically and reasonably, and thus has important practical value.
Keywords Agricultural products cold chain logistics, Improved catastrophe progression method,
New maximum deviation method, Risk assessment model
Paper type Research paper
1. Introduction
In recent years, with the overall improvement of people’sliving standards, consumers demand
for the market of fresh agricultural products has been expanded rapidly and food safety issues
has also been a great deal of attention. Freshagricultural products have some characteristics,
such as a short shelf life, great demand of the market, high requirements for storage and
transportation technology, so the appropriate operation mode and efficient information
management system play an important role in ensuring products quality, especially in the
Industrial Management & Data
Systems
Vol. 117 No. 9, 2017
pp. 1800-1816
Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-03-2016-0098
Received 13 March 2016
Revised 5 June 2016
Accepted 13 July 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
© Hao Zhang, Bin Qiu and Keming Zhang. Published by Emerald Publishing Limited. This article is
published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute,
translate and create derivative works of this article (for both commerc ial & non-commercial purposes),
subject to full attribution to the original publication and authors. The full terms of this licence may be seen
at: http://creativecommons.org/licences/by/4.0/legalcode
This research was supported by the Project of National Social Science Foundation of China
(15BGL202) and the Project of Beijing Philosophy and Social Science (17GLB013).
1800
IMDS
117,9
stage of cold chain logistics (Manning et al., 2006; Jin et al., 2013). As the intermediate links of
consumers and suppliers, cold chain logistics play a very important role in terms of quality of
agricultural products. However, there isa big risk in the logistics operation of each link since
fresh agricultural products in the process of the cold chain logistics operation are not
completelyunder the certain specific environment, so it is vital to study howto assess the risk
of cold chain logistics objectively and accurately and avoid the risk effectively.
For decades, with the development of technology boom and the rise of globalization
trend, cold chain logistics has got a systematic promotion and application, and it has formed
a comprehensive and integrated cold chain system. The earliest and most fruitful field
research on cold chain logistics is the study of the pharmaceutical cold chain logistics.
Then, it has been gradually extended to the cold chain logistics of processed food and
agricultural products. At present, most scholars research on cold chain logistics mainly
concentrate in the field of technology. From the perspective of technology, Lixin et al. (2013)
proposed a new enzymatic Time-temperature indicators (TTI）based on enzyme reaction
and diffusion. They proved the new TTI has a good stability and reliability at dynamic
storage conditions and it could be used to monitor the fresh products during the cold chain
logistics. Yujun et al. (2015) put forward a monitoring and decision system based on wireless
sensor networks (WSN) and ontology which presents great advantages such as
effective regulation, low power consumption, and accurate ontology-based analysis.
Kuo and Chen (2010) developed an advanced multi-temperature joint distribution system for
the food cold chain, which provides a new scheme for continuously temperature-controlled
logistics. It can also jointly deliver and store multi-temperature goods. In order to improve
the efficiency of monitoring system for frozen and chilled aquatic products, a temperature
monitoring system based on WSN with compressed sending was developed, which provides
effective decision support traceability for quality and safety assurance of frozen and chilled
aquatic products (Xinqing et al., 2016). Xinqing et al. (2015) also indicated that the WSN and
adaptive optimal weighted data fusion methods could effectively reflect the real-time
temperature and quality property. Xuefeng et al. (2012) proposed a new cold chain logistics
system based on cloud computing, which can be used to link the database between cold
chain logistics with external customers. It can accelerate the speed of cold chain logistics
and maximize the interests of all parties.
At present, the academic research on agricultural products cold chain logistics has not
yet built a complete research system and it mainly focuses on the cold chain logistics
technology and temperature controlling, such as the methods and means to maintain a
stable temperature in the process of refrigerated and frozen (Shabani et al., 2012).
Abad et al. (2009) demonstrate the intercontinental logistics chain of fresh fish and put
forward the application of RFID smart labels for food cold chain monitoring and analysis.
Hans Rediers et al. (2008) use experiments show that small fluctuations in supply chain was
little affected on temperature, but a great influence on microbial activity that affected the
quality and safety of agricultural products. A wireless sensor network can be used to
monitor the milk temperature in the process of transportation, which makes the
microprocessors, wireless transmitting device and battery placed within the milk bottle cap
(Carullo et al., 2009). James et al. (2006) elaborate the modeling of food temperature, microbial
growth and other parameters in the transportation of food. Since fresh agricultural products
can cause huge losses in the process of transportation, an “intelligent container”is able to
precisely monitor the condition of agricultural products, as well as track its geographical
position (Lutjen et al., 2013). By doing berry logistics field studies, Cecilia et al. (2014) show
that a significant reduction of up to 98 percent in the root-mean-square-error difference
between the product temperature and air temperature, which has a great improvement in
logistics quality of fresh fruit and vegetable. For the research of cold chain performance
assessment, Defraeye et al. (2016) propose a comprehensive performance evaluation of the
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A new risk
assessment
model
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