Quality Risk Evaluation of the Food Supply Chain …downloads.hindawi.com/journals/jfq/2018/2637075.pdfFailure Mode, Effects, and Criticality Analysis LibiaoBai , 1 ChunmingShi , 2

Research ArticleQuality Risk Evaluation of the Food SupplyChain Using a Fuzzy Comprehensive Evaluation Model andFailure Mode Effects and Criticality Analysis

Libiao Bai 1 Chunming Shi 2 Yuntao Guo 3 Qiang Du 1 and Youdan Huang1

1School of Economics and Management Changrsquoan University Xirsquoan 710061 China2Wilfrid Laurier University Waterloo ON Canada N2L3C53School of Management Northwestern Polytechnical University Xirsquoan 710072 China

Correspondence should be addressed to Chunming Shi cshiwluca

Received 21 September 2017 Revised 5 January 2018 Accepted 14 January 2018 Published 4 March 2018

Academic Editor Susana Fiszman

Copyright copy 2018 Libiao Bai et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Evaluating the quality risk level in the food supply chain can reduce quality information asymmetry and food quality incidents andpromote nationally integrated regulations for food quality In order to evaluate it a quality risk evaluation indicator system for thefood supply chain is constructed based on an extensive literature review in this paper Furthermore a mathematical model basedon the fuzzy comprehensive evaluation model (FCEM) and failure mode effects and criticality analysis (FMECA) for evaluatingthe quality risk level in the food supply chain is developed A computational experiment aimed at verifying the effectiveness andfeasibility of this proposed model is conducted on the basis of a questionnaire survey The results suggest that this model can beused as a general guideline to assess the quality risk level in the food supply chain and achieve the most important objective ofproviding a reference for the public and private sectors when making decisions on food quality management

1 Introduction

In 2016 the State Council of the Peoplersquos Republic of Chinaissued guidelines on food safety work These provisionsemphasized improving the quality of edible agricultural prod-ucts strengthening risk prevention and control measurespromoting quality management throughout the food supplychain and accelerating nationally integrated regulations forfood safety These guidelines highlight Chinarsquos attention toquality risk management in the food supply chain [1]

Food quality is defined as the access of all people to suffi-cient safe and nutritious food that meets their dietary needsand food preferences for an active and healthy life [2 3] Foodquality covers a broad area that can be characterized by a setof different risk factors [4ndash6] such as the agricultural con-ditions [7] production process [8] use of antimicrobials [9]and consumer demand [10 11] These factors can be repre-sented by various indicators such as environmental pollution

microbial contamination logistics warehousing and trans-portation The risk indicators are related to the food supplychain processes [12] and can be evaluated and documentedon the basis of imprecise inputs The data of these processesare imprecise and difficult to quantify since they pertainto both the resilience of the food supply chain and theconsumer demand and supply channels such as retail outletsand restaurants Therefore it is difficult to use traditionaldata-based approaches to evaluate food quality Addressingthis challenge requires the managers to develop some precisemethods for assessing the risk level of all factors in every linkof the food supply chain [13] and calculating them as a whole[14] Unfortunately few related studies have been done

The quality risk level of food is defined as the potentialhazard which is caused by unsafe practices in the food supplychain The uncertainty of the ability to acquire safe foodsis also called food insecurity and can be measured by the

HindawiJournal of Food QualityVolume 2018 Article ID 2637075 19 pageshttpsdoiorg10115520182637075

2 Journal of Food Quality

risk level of food quality [15] And the quality risk level offood security is an important problem related to the foodsupply chain environment One effective solution to solve thisproblem is to build an evaluation indicator system based onthe fuzzy sets theory [16] Several studies have consideredthat building the indicator system is the first step in assessingthe quality risk and many research results have been madesuch as in the case of Wang et al who developed an indexsystem to evaluate the transparency of the supervision of foodsafety in China as a prerequisite for an accurate evaluationof the food safety risk level Jie et al analyzed the supplychain performance of Australian cattle producers based onfood supply chain performance indicators [17] Turi et alproposed aggregate indicators to assess the performance ofthe food supply chain by considering economic social andenvironmental development [18] Nilsson et al proposed totalquality indicators for the food production chain [19] Salvo etal focused on the toxic inorganic pollutants in foods fromagricultural producing to evaluate the risks for consumers[20] In these studies however the evaluation objects wereonly a single link not the whole food supply chain Moreoverthe food quality risk supervision at the national level ismissedin these studies Therefore the existing literature cannotprovide an effective guidance for the quality risk evaluationthroughout the whole food supply chain which means thata comprehensive and systematic study on the area of qualityrisk evaluation in the food supply chain is still missing

Many affecting factors of the quality risk evaluation in thefood supply chain exhibit highly fuzzy uncertainty and can-not be analyzed quantitativelyTherefore it is difficult to eval-uate the level of quality risk by a single defined managementcriterion [21] To address this fuzzy uncertainty problem in1965 Zadeh proposed the concept of fuzzy sets which laidthe foundation for the application of the fuzzy comprehensiveevaluation model (FCEM) in risk management [22] TheFCEM is a method to evaluate fuzzy mathematics which cantransform a qualitative evaluation into a quantitative evalu-ation [23ndash25] Combined with other methods the greatestfeature of the FCEM is that it can integrate the intuition andfuzziness of human thinking thus circumventing the unityof results required by traditional mathematical methods [26]Therefore the FCEM has become an effective multifactordecision-making tool for comprehensive evaluations [27] andreal-word problem solving in areas such as internationalrelations [28] aircraft flight safety [29] swine building envi-ronment [23] health safety and environmental management[30] regional water resources capacity [31] and teaching per-formance [32] Therefore in this paper an FCEM for model-ing these uncertainties and assessing food quality risk levelis developed to determine the overall food quality risk bymonitoring various independent risk factors and indictors inthe food supply chain

The rest of this paper is structured as follows Section 2describes the construction of a quality risk evaluation indica-tor system that covers the whole food supply chain based onan extensive literature review Section 3 proposes an FCEMfor the quality risk evaluation of the food supply chain basedon FCEM and FMECA Section 4 verifies the effectivenessand feasibility of the model using a computational experi-ment and Section 5 presents the conclusions

2 Quality Risk EvaluationIndicator System for the FoodSupply Chain

To ensure the accuracy and effectiveness a quality risk eva-luation indicator system that covers the entirety of the foodsupply chain should be established before evaluating foodquality risk Existing research on this system has been verylimited There is no ready-made quality risk evaluation indi-cator system for the food supply chain [13] Here the effectiveapproach to establishing the preliminary indicator frame-work is to analyze the existing literature and the laws andregulations of food safety regulatory [58] On this basis thequality risk evaluation indicator system for the food supplychain can be built by the method which is based on the fuzzyanalytic hierarchy process (FAHP) proposed by Wang et al[59] shown as Table 1

According to Table 1 the evaluation objects for qualityrisk of the food supply chain can be generalized into fivecategories raw material supply risk [33ndash37] production andprocessing risk [34 37ndash42] logistics warehousing and trans-portation risk [40ndash46] sales and consumption risk [42 47ndash51] and government regulatory risk [52ndash57] Raw materialsupply production and processing logistics warehousingand transportation sales and consumption are the four dif-ferent links of the food supply chain while government reg-ulations could affect every link of the food supply chain Theconnotations of each evaluation object could be described asfollows

(1) Raw Material Supply RiskThe risk of raw material supplyinvolves the raw materials produced by human pollutionnatural pollution and other factors that lead to pesticideresidues pathogen pollution and illegal additives during theprocess of planting or breeding which results in long-term orshort-term harm to human health [34] Raw material supplyrisk is a source of food quality risk including soil pollutionair pollution water pollution heavy metal pollution illegaluse of additives residual inputs microbial contaminationpathogenic bacteria pollution and transgenic technologyrisk

(2) Production and Processing Risk This risk arises when thesafety management and production environment during theprocesses of production and packaging are not compliantwith regulations this risk could lead to possible food con-tamination and illegal additives and produce potential safetyhazards to human health As this link involves the food qual-ity and safety in the whole food industrial chain its impactis relatively large The main quality risk evaluation indicatorsincluded in this link are illegal use of additives contamina-tion with foreign matter inability to wash a food productclean presence of detergent residue pathogen contamina-tion microbial contamination uncertified processing equip-ment nonstandardized processing personnel operationinsufficient processing environment insufficient processingequipment inappropriate packaging insufficient packagingquality uncertified packaging logo insufficient assurance of

Journal of Food Quality 3

Table1Qualityris

kevaluatio

nindicatorsystem

forthe

food

supp

lychain

Evaluatio

nob

jects

Risk

evaluatio

nindicators

References

Rawmaterialsup

plyris

k

Soilpo

llutio

nAirpo

llutio

n

[33ndash37]

Water

pollu

tion

Heavy

metalpo

llutio

nIllegaluseo

fadd

itives

Resid

ualinp

uts

Microbialcontam

ination

Pathogenicbacteriapo

llutio

nTransgenictechno

logy

risk

Prod

uctio

nandprocessin

gris

k

Illegaluseo

fadd

itives

Con

taminationwith

foreignmatter

[3437ndash4

2]

Inabilityto

washafoo

dprod

uctclean

Presence

ofdetergentresidue

Pathogen

contam

ination

Microbialcontam

ination

Uncertifi

edprocessin

gequipm

ent

Non

standardized

processin

gperson

neloperatio

nInsufficientp

rocessingenvironm

ent

Insufficientp

rocessingequipm

ent

Inapprop

riatepackaging

Insufficientp

ackaging

quality

Uncertifi

edpackaginglogo

Insufficientassurance

ofperson

nelh

ealth

Qualityinspectio

nris

kInsufficientstorage

process

Logisticswarehou

singand

transportatio

nris

k

Inventorycontroltechn

olog

yIntelligent

temperature-con

trolfacilitie

s

[40ndash

46]

Transportvehiclesanitatio

nColdchainhardwares

uppo

rtingfacilities

Third

-partylogisticslevel

Partnertechn

olog

yplatform

convergence

Prod

uctp

ortfo

liosto

rage

transport

Coldchainlogistics

inform

ationtransm

ission

Logisticsroadinfrastructure

Illegalop

erationof

Logisticstranspo

rtperson

nel

Vehicle

schedu

lingandmon

itorin

ginform

ationfeedback

Salesa

ndconsum

ptionris

k

Selling

expiredfood

Falsifyingthed

ateo

fprodu

ction

[4247ndash52]

False

repo

rtingof

food

ingredients

Poor

sanitatio

nin

dining

establish

ments

Poor

sanitatio

ncond

ition

sIm

prop

erdisposalof

wastefood

Poor

sanitatio

nin

cook

ingfacilities

Improp

ereatin

gmetho

dsInsufficientstorage

environm

ent

Governm

entregulatoryris

k

Imperfe

ctregu

latory

syste

mSuperviso

rysta

fflevel

[53ndash57]

Superviso

rmoralhazard

Supervision

channels

Regulatoryorganizatio

nRe

gulatoryagency

efficiency

Regu

latoryprocessm

anagem

ent

Regu

latory

results

feedback

Regu

latorydetectiontechno

logy

Other

risks


personnel health quality inspection risk and insufficientstorage process

(3) Logistics Warehousing and Transportation Risk Thelogistics warehousing and transportation risk involves theraw foodmaterials and finished products containing harmfulsubstances or being subject to pollution or deteriorationduring the process of transport or storage which results in theexistence of potential safety hazards In this paper logisticswarehousing and transportation includes both the processfrom the raw materials to production and the process fromthe finished product to consumption The indicators of thisevaluation objective include inventory control technologyintelligent temperature-control facilities transport vehiclesanitation cold chain hardware supporting facilities third-party logistics level partner technology platform conver-gence product portfolio storage transport cold chain logis-tics information transmission logistics road infrastructureillegal operation of logistics transport personnel vehiclescheduling and monitoring information feedback

(4) Sales and Consumption Risk The sales and consumptionrisk involves food contamination deterioration and con-tamination with harmful substances due to expired shelflife food fraud improper sales environments or improperconsumption of food which poses a potential hazard tohuman health The quality risk evaluation indicators inthis link include selling expired food falsifying the date ofproduction false reporting of food ingredients poor sani-tation in dining establishments poor sanitation conditionsimproper disposal of waste food poor sanitation in cookingfacilities improper eating methods and insufficient storageenvironment

(5) Government Regulatory Risk In the food industrymanufacturers may add chemical additives to augment theappearance or the taste of food This process may increasefood demand and sales profits but cause health problemsamong consumers [53] The government can take punitivemeasures to regulate such risky behavior and benefit from thetax income generated by the increased revenues arising fromsuch additives An analysis of the current status of Chinarsquosfood quality regulations reveals that the quality risk eval-uation indicators regarding government regulation includeimperfect regulatory system supervisory staff level supervi-sor moral hazard supervision channels regulatory organiza-tion regulatory agency efficiency regulatory processmanage-ment regulatory results feedback and regulatory detectiontechnology

3 Evaluation Model

31 Fuzzy Comprehensive Evaluation Method FCEM is amethod based on the membership degree theory in fuzzymathematics which transform the qualitative evaluation intoquantitative evaluation [27 60 61] It has now become aneffectivemultifactor decision-making tool for comprehensiveevaluation Combined with experts grading method FCEMcan make a full reflection on the fuzziness of evaluation

criteria and the influence factors and produce evaluationresults closer to the actual situation [62] The typical FCEMprocess could be shown in Figure 1

Shown as Figure 1 the typical process of FCEM could bedivided into five stages the main task in the 1st stage is toestablish a scientific set of indicators which is determined bythe situation of evaluation objective this indicators set willlay the foundation for the application of FCEM In the 2ndstage the assessment comment set of evaluation objective andthe criterion used to reflect the standard of scoring should beestablished and proposed this will provide the data founda-tion for quantifying the results of assessment comment Eachelement in the set of indicators makes a different contribu-tion to the realization of risk assessment the weights of thesefactors are important and different therefore in the 3rd stagethe weight matrixes which are determined by the contribu-tion of the evaluation objective should be built andmeasuredThere are many ways to build the weight matrix such asanalytic hierarchy process (AHP) entropy and FMECAthe criterion for the selection of these methods is whetherthe proposed method could satisfy the characteristics andrequirements of the evaluation objectives In the 4th stage afuzzy comprehensive assessment matrix which could reflectthe risk level of assessment objective should be established onthe basis of the construction results of weight matrixes Com-bined with the assessment comment set the fuzzy compre-hensive assessment matrix the value of the whole and eachevaluation objective should be calculated in 5th stage whichwill provide a reference for managers to make risk manage-ment decisions

32 Construction of the Food Quality Risk Evaluation ModelUsing FCEM The process of food quality risk evaluation inthe food supply chain is a typical FCEMprocess According toSection 31 using FCEM to evaluate the level of food qualityrisk in the food supply chain could be divided into five stages(1) construct the food quality risk evaluation indicator set (2)establish the food quality risk assessment comment set (3)determine the weightmatrix (4) establish the comprehensiveassessment matrix and (5) finalize the FCEM [63]

In the first stage construct a food quality risk evaluationindicator set 119876 which is composed of the evaluation objects119876119894 and their corresponding evaluation indicators 119876119894119895 shownas follows

119876 = 1198761 119876 119876119894 119876 119876119899 119876119894 = 1198761198941 119876119894119895 119876119894119898

(119894 = 1 2 119899 119895 = 1 2 119898) (1)

where 119876 is the food quality risk evaluation indicator set 119899is the number of evaluation objects 119876119894 (119894 isin [0 119899]) is the 119894thevaluation object 119876119894119895 is the 119895th food quality risk evaluationindicator of119876119894 and119898 is the number of food quality risk eva-luation indicators in 119876119894

In the second stage establish the food quality riskassessment comment set L to describe the fuzzy logic rela-tionship among different indicators Here L is a collection


Input

Output

Assessment Assessment Assessmentcomment

Weight matrixes Weight matrixes Weight matrixes

comment comment

Comprehensiveassessment

matrix


matrix


matrix

e 1ststage

e 2ndstage

e 3rdstage

e 4thstage

e 5thstage

Determined by the situationof evaluation objective

Propose the evaluationand assessment standards

Determined by thecontribution of evaluation

objective

Reflect the risk level ofevaluation objective

Calculate the level of whole evaluation objective

Construct the set of evaluation indicators

Finalize the results of evaluation

Q = Q1 Q2 Q3 Q Qn

Q1 Q2 Q

Figure 1 The application stage of FCEM

of five comments used to evaluate the food quality risk levelaccording to the criterion of the FCEM shown as follows

L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 (2)

where L is the food quality risk assessment comment setand ℓ1 ℓ2 ℓ3 ℓ4 and ℓ5 are the comments representing thefood quality risk levels of ldquoTerriblerdquo ldquoUnacceptablerdquo ldquoFairrdquoldquoAcceptablerdquo and ldquoDesirablerdquoThese levels are represented byscores of 1 2 3 4 and 5The risk assessment comment setLcan be expressed as follows

L = 1 2 3 4 5 (3)

According to this criterion the fuzzy comprehensiveevaluation matrixes 119877 and 119877119894 (119894 = 1 2 119899) can bedetermined by

119877119894 =

11990311989411 11990311989412 11990311989413 11990311989414 1199031198941511990311989421 11990311989422 11990311989423 11990311989424 1199031198942511990311989431 11990311989432 11990311989433 11990311989434 11990311989435 1199031198941198981 1199031198941198982 1199031198941198983 1199031198941198984 1199031198941198985

(4)

where119877 = 1198771 119877 119877119894 and119877119894 (119894 = 1 2 119899) are the fuzzycomprehensive evaluation matrixes of 119876 and 119876119894 119903119894119898119896 (119896 =1 2 3 4 5) is the comment level of 119876119894119898

In the third stage determine the weight matrixes119882 and1198821015840119894 Different elements in sets119876 and119876119894 provide different con-tributions to the level of food quality risk Thus the weights

of these indicators are differentThe assessment indexweightsvector can be determined by

119882 = 11988211198822 119882119894 119882119899 (119894 = 1 2 119899) 1198821015840119894 = 1198821015840119894111988210158401198942 1198821015840119894119895 1198821015840119894119898

(119894 = 1 2 119899 1 le 119895 le 119898) 119899sum119894=1

119882119894 = 1119898sum119895=1

1198821015840119894119895 = 1

(5)

where119882 and1198821015840119894 are the weight vectors of food quality riskevaluation objects and indicators119882119894 and1198821015840119894119898 are the weightsof119876119894 and119876119894119898 The values of119882119894 and1198821015840119894119898 can be calculated bythe method of FMECA

In the fourth stage establish the comprehensive assess-mentmatrix119881 to reflect the food quality risk level of each eva-luation objective by

119881 =W ∘ X119879 (6)

119883 = (1198831 1198832 119883119894) (7)

119883119894 = 1198821015840119894 times 119877119894 (8)

where 119881 is the fuzzy comprehensive assessment matrix thatcan reflect the food quality risk level of the evaluationobjective 119883119894 is the fuzzy comprehensive assessment matrix


of 119876119894 and 119883 is the fuzzy comprehensive assessment matrixset

Finally finalize the FCEM Recording the food qualityrisk level and each evaluation objective as119884 and1198841015840 combinedwith L 119881 and 119883119894 the values of 119884 and 1198841015840 can be calculatedby

119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)

where 119884 and 119884119894 are the food quality risk levels of119876 and119876119894 1198841015840is the set of 119876119894srsquo food quality risk levels According to (9) thefood quality risk levels of 119876 and 119876119894 can be obtained

33 Determinants of the Weight Vectors Using FMECAAccording to Section 32 when applying the FCEM to eval-uate the food quality risk level the weight of indicator isvery important Generally the weights of indicators duringthe application of the FCEM are usually given based on theexperience of various experts which leads to the limitationof subjectivity To reduce this subjectivity this paper takesthe FMECA as the method to determine the weight vectorsof evaluation indicators

FMECA is a safety and reliability analysis tool whichhas been widely used for the identification of systemprocesspotential failures their causes and consequences Thismethod focuses on ldquodiscussions before system failurerdquo per thenotion that ldquoprevention is better than curerdquo [64] FMECAprovides an appropriate method to determine the weights ofthe elements depending on the occurrences of food qualityrisk parameters their severity the detection and ability tocontrol or compensate for the loss after a failure [64] Accord-ing to the FMECA the weights of the indicators can be calcu-lated by

11988210158401015840119894 = 119874119894 times 119878119894 times 119863119894119862119894 11988210158401015840119894119895 = 119874119894119895 times 119878119894119895 times 119863119894119895119862119894119895

119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)

where11988210158401015840119894 is the cross-sectional area of the evaluation object119876119894 and 11988210158401015840119894119895 is the cross-sectional area of the evaluationindicator 119876119894119895 119874119894 is the occurrence probability of 119876119894 119878119894 is theseverity after the occurrence of 119876119894 119863119894 is the likelihood ofdetection of119876119894 and 119862119894 is the ability to control or compensatefor the loss following the occurrence of 119876119894 The values of 119874119894119878119894119863119894 and 119862119894 can be obtained by the experts grading method(EGM) where 119874119894 isin [1 5] 119878119894 isin [1 5] 119863119894 isin [1 5] and

119862119894 isin [1 5] The principles of expert evaluation are shown as(11)ndash(14)

119874119894 =

1 lowest probability

5 highest probability

119900119894 otherwise(11)

where 1 lt 119900119894 lt 5 The higher the value of 119900119894 the higher theprobability of 119876119894

119878119894 =

1 slightest severity

5 worst severity

119904119894 otherwise(12)

where 1 lt 119904119894 lt 5 The higher the value of 119904119894 the worse theseverity after the occurrence of 119876119894

119863119894 =

1 highest likelihood of detection

5 lowest likelihood of detection

119889119894 otherwise(13)

where 1 lt 119889119894 lt 5 The higher the value of 119889119894 the lower thelikelihood of detection of 119876119894119862119894

=

1 most difficult to control or compensate for the loss

5 least difficult to control or compensate for the loss

119888119894 otherwise(14)

where 1 lt 119888119894 lt 5 The higher the value of ℎ119894 the easier tocontrol or compensate for the loss after the occurrence of 119876119894

According to (11)-(12) 11988210158401015840119894 isin [02 125]and 1198821015840119894119898 isin[02 125]Then the weights of different elements119882119894 and119882119894119898can be obtained after normalizing11988210158401015840119894 and1198821015840119894119898 by (13)-(14)4 Computational Experiment and Results

Henan is an important province of China with a populationof 10722 million in 2017 accounting for 78 of Chinarsquostotal population Thus Henan plays an important role inChinarsquos food consumption Food quality directly affects peo-plersquos health and economic development therefore improvingfood quality and safety and making the food chain moreecofriendly are the development goals pursued by HenanProvince However Henan is a large agricultural provincethe food supply chain from farm to fork includes so manylinks such as rawmaterial supply production and processinglogistics warehousing and transportation and sales andconsumption In such a food supply chain there are manyrisk factors that could affect the food quality level at eachlink The probability of occurrences and the severity of eachoccurrence are uncertain thus identifying the risk factorsand evaluating the risk level of each link in the food supplychain are the prerequisite for controlling the food quality


This issue aligns with the problem addressed by the modelproposed in this paper Therefore the food supply chain ofthe Henan Province (FSCHP) is taken as a computationalexperiment to introduce the process of food quality riskevaluation in order to verify the validity and effectiveness ofthe proposed model

According to Table 1 and the process of risk evaluationdescribed in Section 32 the risk evaluation indicator set ofFSCHP 119876 can be constructed as shown in Table 2

In Table 2119876 is the risk evaluation indicator set of FSCHP119899 is the number of evaluation objects in 119876 in which 119899 = 5119876119894 (119894 isin [1 119899]) is the 119894th evaluation object 119876119894119895 is the 119895thrisk evaluation indicator of 119876119894 and 119898 is the number of riskevaluation indicators As shown in Table 2 the number ofFSCHPrsquos risk evaluation indicators is

119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)

According to the criterion of FCEM and (2) the riskassessment comment set of FSCHP L can be establishedwhere L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 = 1 2 3 4 5 To aggregatethe risk assessment comments of the FSCHP and establishthe fuzzy comprehensive evaluation matrixes 119877 and 119877119894 (119894 =1 2 119899) a questionnaire survey was designed (shownas Appendix A) The objectives of this survey includedfive categories of respondentsmdashfarmers food processingenterprises logistics and warehousing enterprises retailersand consumers and government regulatorsmdashto ensure theaccuracy of the survey results A total of 1000 questionnaireswere issued and 898 were returned which included 22unfinished and 27 identical questionnaires these 49 ques-tionnaires were considered invalid according to the statisticalprinciples Thus 849 questionnaires were considered validand completed questionnaires The recovery rate and thevalid questionnaire rate were 898 and 849Therefore theresults of this survey are robust and effective and thus can beused for further analyses

According to the results of the assessment comments ofthe risk evaluation indicators the fuzzy comprehensive eval-uation matrixes of evaluation objects 119876 can be constructedHere this paper takes the evaluation object 1198762 (1198762 wasselected because the number of risk evaluation indicators of1198762 is the highest) as an example to introduce the calculationprocess of the fuzzy comprehensive evaluation matrix 1198772

By analyzing the results of the survey questionnairesthe assessment comment of evaluation objective 1198762 can beobtained as shown in Table 3

In Table 3 the level of comment of risk evaluation indica-tor 119876119894119898 can be calculated by 119903119894119898119896 = Frequency(119876119894119898119901

120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the

number of times that the objectives of this questionnairesurvey scored 119876119894119898 as 119901120572 (120572 = 1 2 3 4 or 5) Then the fuzzycomprehensive evaluation matrix 1198772 can be established asfollows

1198772 =[[[[[[[[[[

119903211 119903212 sdot sdot sdot 119903215119903221 119903222 sdot sdot sdot 119903225119903231 119903232 sdot sdot sdot 119903235sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot11990321198981 11990321198982 sdot sdot sdot 11990321198985

]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)

Similarly the fuzzy comprehensive evaluation matrix ofthe other evaluation objects 1198771 1198773 1198774 and 1198775 can beestablished as follows

1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith

foreignmatter119876 22

Inabilityto

washafoo

dprod

uctclean119876 23

Presence

ofdetergentresidue119876 24

Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop

riatepackaging119876 211

Insufficientp

ackaging

quality119876 212

Uncertifi

edpackaginglogo119876 213


ofperson

nelh

ealth

119876 214Qualityinspectio

nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou

singandtransportatio

nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo

rtingfacilities119876 34

Third

-partylogisticslevel119876 35

Partnertechn

olog

yplatform

convergence119876 36

Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38

Logisticsroadinfrastructure119876 39

Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform

ationfeedback119876 311

Salesa

ndconsum

ptionris

k119876 4

Selling

expiredfood119876 41

Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food

ingredients119876 43

Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook

ingfacilities119876 47

Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso

rmoralhazard119876 53

Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510


Table 3 Assessment comment of evaluation objective 1198762Risk evaluation indicators Frequency Comment 1198751 1198752 1198753 1198754 1198755Production and processing risk 1198762

Illegal use of additives 11987621 58 202 303 245 90Contamination with foreign matter 11987622 84 218 323 211 62Inability to wash a food product clean 11987623 86 254 343 151 64Presence of detergent residue 11987624 76 208 307 229 78Pathogen contamination 11987625 42 180 275 255 146Microbial contamination 11987626 40 212 301 239 106Uncertified processing equipment 11987627 58 208 313 241 78Nonstandardized processing personnel operation 11987628 64 220 321 233 60Insufficient processing environment 11987629 60 212 299 249 78Insufficient processing equipment 119876210 78 244 325 209 42Inappropriate packaging 119876211 218 280 247 113 40Insufficient packaging quality 119876212 224 268 241 121 44Uncertified packaging logo 119876213 156 206 305 151 80Insufficient assurance of personnel health 119876214 158 256 255 163 66Quality inspection risk 119876215 166 212 251 179 90Insufficient storage process 119876216 192 216 319 97 74

1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)

Weight vectors are very important in determining thefood quality risk level and can be calculated by FMECAaccording to Section 33 To calculate the weights of evalua-tion objects and risk indicators five experts on food qualityrisk management were invited to score the values of 119874119894 119878119894119863119894 and119862119894 with the principles of (11)ndash(14) (the scoring table isshown in Appendix B) The scoring results of the evaluationobjects are shown in Table 4 Taking the average as the finalscore the weights of evaluation objects 119882119894 can be obtainedaccording to (10)

119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)

Similarly the weights of risk evaluation indicator1198821015840119894 canbe calculated


11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)

According to (8) the fuzzy comprehensive assessmentmatrix of evaluation objects can be calculated

1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)

According to (6)-(7) the fuzzy comprehensive assess-ment matrix 119881 can be established

119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)

According to (9) the level of FSCHPrsquos food quality risk 119884and the level of evaluation objects 119884119894 can be calculated

119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)

The food quality risk levels of evaluation objects areshown in Figure 2

According to the calculation results the risk level ofFSCHPrsquos food quality 119884 is 3273 This means that the risklevel of FSCHP is much higher than the average level of riskcomments of 25 more than 3029 it indicates that therisk level of FSCHPrsquos food quality is relatively higher andrequires scientificmanagement in the process of supply chainmanagement

In Figure 2 the value of FSCHPrsquos food quality riskassessment in descending order is sales and consumptionrisk 1198764 logistics warehousing and transportation risk 1198763government regulatory risk 1198765 production and processingrisk 1198762 raw material supply risk 1198761 Comparing the cal-culation results the conclusion that the risk levels of salesand consumption risk 1198764 and logistics warehousing andtransportation risk 1198763 which are similar and equal to 309and 306 are the highest two of the risk evaluation of FSCHPcould be obtainedMeanwhile the values of other indictors inFSCHPrsquos quality risk 1198765 1198762 and 1198761 which are equal to 299285 and 282 can be also obtained these values are 325


Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531

Figure 2 Food quality risk levels of evaluation objects

777 and 874 lower than the highest evaluation object1198764Analyzing this phenomenon we can find that the reasonwhy the risk levels of sales and consumption risk and thelogistics warehousing and transportation risk are the highestis because there are too many uncontrollable factors such ascold chain hardware supporting facilities cold chain logisticsinformation transmission poor sanitation in cooking facil-ities and poor sanitation in dining establishments existingin these management processes and the standard of themis missing or implemented poorly or supervised poorly Theresults are consistent with the actual situation of the FSCHPTherefore if managers want to control the food quality risk ofthe FSCHP effectively sales and consumption and the logis-tics warehousing and transportation are the key factors thatshould be addressed first What is more seen from Figure 2we can find that the raw material supply risk 1198761 in FSCHPis the lowest which is because Henan is one of the largestagricultural provinces in China and in order to improve thefood quality the standardized food cultivation model hasbeen promoted and accepted by all farmers which makes agreat contribution to achieving the goal of controlling thefood quality from its source [65]

Through the statistical analysis of the existing literatureit can be found that a lot of studies have been carried out toexplore food quality in the food supply chain such as FearneHornibrook and Dedman who conducted two exploratorycase studies of retailer-led quality assurance schemes (QAS)for beef in Germany and Italy and found that QAS have thepotential to reduce perceived risk and increase consumerconfidence in specific fresh beef products [66] Ting et altook the quality sustainability in the food supply chain as re-search object and proposed a supply chain quality sustain-ability decision support system to support managers in foodmanufacturing firms to define good logistics plans in order tomaintain the quality and safety of food products [67] Chenet al presented a mutually supporting analytical model andexploratory case to study the managerial and policy issuesrelated to quality control in food supply chain managementwith a focus on the Chinese dairy industry and discussednumbers of important managerial and policy insights andimplications in managing the global food supply chainquality and risk [68] These studies and findings have alreadyprovided a valid reference for controlling the food quality inthe supply chain food however many of them are focused on

the quality or risk control in a single link [66 67] or someindependent aspects [68] in the food supply chain whichcould only provide a basis for the quality and risk manage-ment of the single or independent aspect not the whole foodsupply chain Compared with these literatures the evalua-tion model proposed in our paper based on the FCEM andFMECA can be used as a general guideline to assess thequality risk level of the food supply chain as a whole by theintegration of all links in the food supply chain what is moreit can achieve themost important objective bymeasuring andsorting the risk level of different links These superioritieswhich could be obtained by comparing with other methodsnot only could reflect the potential in evaluating the qualityand risk level in food supply chain but also could make upthe gap between the traditional food risk evaluation from theaspect of single or independent link and themodern food riskevaluation from the aspect of thewhole food supply chain andprovide a reference for the public and private sectors whenmaking decisions on food quality management

5 Conclusion

The food industry in China is facing various challengesincluding but not limited to reducing food waste improvingfood quality and safety and becoming more ecofriendly Toaddress these challenges and improve the food quality it iscritical to implement efficient and effective quality and oper-ations management measures by identifying food quality riskfactors and evaluating the risk levels of each link in the foodsupply chain This study adopted a comprehensive approachto establish a fuzzy evaluation model for food quality riskevaluation Through an extensive literature review a qualityrisk indicator system for the food supply chain covering fiveevaluation objectives and 55 quality risk evaluation indicatorswas built to provide a basis for evaluating the food quality risklevel Then the methods of FCEM and FMECA were appliedbased on surveys of experts to evaluate the food quality risklevel The results of a computational experiment suggest thatthis approach is reasonable for evaluating the food quality risklevel

The resulting quality risk evaluation model of the foodsupply chain can be used as a general guideline to highlightthe most important objectives regarding the level of foodquality risk evaluation according to the results of the compu-tational experiment Furthermore the evaluationmodel pro-vides a useful foundation for future case analysesThegovern-ment agencies responsible for food quality in supply chainmanagement may adopt this model to assess the food qualityrisk level of each region A food industry sector might alsoapply thismodel to review the strengths andweaknesses of itscurrent food quality risk management so that better qualitymanagement plans could be developed for the food supplychain In addition compared with other provinces it is clearthat the food quality risk levels of the same objects such assales and consumption risk and logistics warehousing andtransportation risk are different due to the differences incold chain logistics technology and eating habitsThis finding


Table 5

Indicators Assessment comments Level of food quality risk indicators1 2 3 4 5

Raw material supply risk 1198761Soil pollution 11987611Air pollution 11987612Water pollution 11987613Heavy metal pollution 11987614Illegal use of additives 11987615Residual inputs 11987616Microbial contamination 11987617Pathogenic bacteria pollution 11987618Transgenic technology risk 11987619

Production and processing risk 1198762Illegal use of additives 11987621Contamination with foreign matter 11987622Inability to wash a food product clean 11987623Presence of detergent residue 11987624Pathogen contamination 11987625Microbial contamination 11987626Uncertified processing equipment 11987627Nonstandardized processing personnel operation 11987628Insufficient processing environment 11987629Insufficient processing equipment 119876210Inappropriate packaging 119876211Insufficient packaging quality 119876212Uncertified packaging logo 119876213Insufficient assurance of personnel health 119876214Quality inspection risk 119876215Insufficient storage process 119876216

Logistics warehousing and transportation risk 1198763Inventory control technology 11987631Intelligent temperature-control facilities 11987632Transport vehicle sanitation 11987633Cold chain hardware supporting facilities 11987634Third-party logistics level 11987635Partner technology platform convergence 11987636Product portfolio storage transport 11987637Cold chain logistics information transmission 11987638Logistics road infrastructure 11987639Illegal operation of logistics transport personnel 119876310Vehicle scheduling and monitoring information feedback 119876311

Sales and consumption risk 1198764Selling expired food 11987641Falsifying the date of production 11987642False reporting of food ingredients 11987643Poor sanitation in dining establishments 11987644Poor sanitation conditions 11987645Improper disposal of waste food 11987646Poor sanitation in cooking facilities 11987647Improper eating methods 11987648Insufficient storage environment 11987649


Table 5 Continued


Government regulatory risk 1198765Imperfect regulatory system 11987651Supervisory staff level 11987652Supervisor moral hazard 11987653Supervision channels 11987654Regulatory organization 11987655Regulatory agency efficiency 11987656Regulatory process management 11987657Regulatory results feedback 11987658Regulatory detection technology 11987659Other risks 119876510Imperfect regulatory system 11987651Supervisory staff level 11987652

shows that the food quality risk level is relative requiringmanagers to take the actual situation into account whenmak-ing decisions on food quality risk management

There may be two limitations in this study First system-atic deficiencies of the risk evaluation indicator system mayexist because the potential negative interactions among indi-cators were not taken into account which might affect thevalidity of the evaluation results Second the effectiveness ofthis proposed model was verified by a computational experi-ment However the selected case to be implemented was con-sistent for only the problem of food quality risk evaluationThus the results of the computational experiment may notbe generalizable Future research should address these limita-tions

Appendix

A A Sample of Survey Questionnaire

A1 Basic Information

(1) Gender

◻male◻ female

(2) Age

◻ 20ndash29◻ 30ndash39◻ 40ndash49◻ 50 or more

(3) Length of service

◻Within 1 year◻ 1ndash5 years

◻ 6ndash10 years◻ 11ndash20 years◻ 20 years or more

(4) Your duties(5) Department(6) Nature of your department

◻ Farmer◻ Food processing enterprise◻ Logistics warehousing enterprise◻ Retailer and consumer◻ Government regulator◻ other

A2 Assessment Comments of FSCHPrsquos FoodQuality Risk Indi-cators See Table 5

B A Sample of Expert Scoring Table

See Table 6

Conflicts of Interest

The authors declare that they have no conflicts of interest re-garding the publication of this paper

Acknowledgments

This study is sponsored by the National Natural ScienceFoundation of China (no 51708039) Ministry of EducationHumanities and Social Sciences Fund (nos 17XJC630001 and17YJCZH125) Soft Science Foundation of Shaanxi Province(no 2017KRM123) and Social Science Planning Fund of


Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510


Shaanxi Province (nos 2017S028 and 2016R026) The man-agers who participated in this study are also greatly appreci-ated for giving their time and sharing their experiences

References

[1] T Chen L Wang and J Wang ldquoTransparent assessment of thesupervision information in chinarsquos food safety a fuzzy-anpcomprehensive evaluation methodrdquo Journal of Food Qualityvol 2017 Article ID 4340869 14 pages 2017

[2] P Pinstrupandersen ldquoFood security definition and measure-mentrdquo Food Security vol 1 no 1 pp 5ndash7 2009

[3] Food security Policy brief FAOrsquosAgriculture andDevelopmentEconomics Division Rome Author FAO 2006

[4] R H Abiyev K Uyar U Ilhan et al ldquoAssessment of food secu-rity risk level using type 2 fuzzy systemrdquo Procedia ComputerScience vol 102 pp 547ndash554 2016

[5] X J Chen ldquoAn analytical framework and supervision system forchinese government to protect food quality and safetyrdquo Journalof Nanjing Normal University vol 1 pp 29ndash36 2011

[6] L J Hubbard and C Hubbard ldquoFood security in the UnitedKingdom external supply risksrdquo Food Policy vol 43 pp 142ndash147 2013

[7] T Gomiero ldquoFood quality assessment in organic vs conven-tional agricultural produce findings and issuesrdquo Applied SoilEcology 2017

[8] L Ludikhuyze A Van Loey I S Denys and M Hendrickx Ef-fects of High Pressure on Enzymes Related to Food QualityFromKinetics to Process Engineering Kluwer AcademicplenumPublishers New York NY USA 2002

[9] Z-HDing J-T Li andB Feng ldquoRadio frequency identificationin food supervisionrdquo in Proceedings of the 9th InternationalConference on Advanced Communication Technology ICACTrsquo07 pp 542ndash545 IEEE Okamoto Kobe Japan 2007

[10] RWendyvan and F Lynnj ldquoConsumer perceptions of food qua-lity and safety and their relation to traceabilityrdquo British FoodJournal vol 110 no 10 pp 1034ndash1046 2008

[11] A V Cardello ldquoFood quality relativity context and consumerexpectationsrdquo FoodQuality and Preference vol 6 no 3 pp 163ndash170 1995

[12] M K A Kadir E Hines K Qaddoum et al ldquoFood security risklevel assessment a fuzzy logic-based approachrdquo Applied Artifi-cial Intelligence vol 27 no 1 pp 50ndash61 2013

[13] S Zhao andX Yang ldquoFood safety risk assessment in whole foodsupply chain based on catastrophe modelrdquo Advance Journal ofFood Science and Technology vol 5 no 12 pp 1557ndash1560 2013

[14] P J A Chavez and C Seow ldquoManaging food quality risk inglobal supply chain a risk management frameworkrdquo Interna-tional Journal of Engineering Business Management vol 4 no 12012

[15] X J Wang D Li and X L Shi ldquoA fuzzy model for aggregativefood safety risk assessment in food supply chainsrdquo ProductionPlanning and Control vol 23 no 5 pp 377ndash395 2012

[16] J Wang T Chen and J Wang ldquoResearch on cooperation stra-tegy of enterprisesrsquo quality and safety in food supply chainrdquoDiscrete Dynamics in Nature and Society vol 2015 Article ID301245 15 pages 2015

[17] F Jie K Barton and K Wang ldquoFood quality as a supply chainperformance indicator for Australian cattle producersrdquo inProceedings of the 10th International Research Conference on

Quality Innovation andKnowledge (QIK) pp 202ndash208MonashUniversity Melbourne Australia 2011

[18] A Turi G Goncalves and M Mocan ldquoChallenges and com-petitiveness indicators for the sustainable development of thesupply chain in food industryrdquo Procedia - Social and BehavioralSciences vol 124 pp 133ndash141 2014

[19] H Nilsson H J Trienekens and S W F Omta ldquoTotal qualityindicators for the food production chain is there a need formore labellingrdquo 2002

[20] A Salvo G T La VMangano et al ldquoToxic inorganic pollutantsin foods from agricultural producing areas of Southern Italylevel and risk assessmentrdquo Ecotoxicology and EnvironmentalSafety vol 148 pp 114ndash124 2017

[21] X Wang D Li and X Shi ldquoA fuzzy model for aggregative foodsafety risk assessment in food supply chainsrdquo Production Plan-ning and Control vol 23 no 5 pp 377ndash395 2012

[22] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[23] Q Xie J-Q Ni and Z Su ldquoFuzzy comprehensive evaluation ofmultiple environmental factors for swine building assessmentand controlrdquo Journal of Hazardous Materials vol 340 pp 463ndash471 2017

[24] J Cheng and J-P Tao ldquoFuzzy comprehensive evaluation ofdrought vulnerability based on the analytic hierarchy processmdashan empirical study from Xiaogan City in Hubei ProvincerdquoAgriculture and Agricultural Science Procedia vol 1 pp 126ndash1352010

[25] Y Y Chen FuzzyMathematics HuazhongUniversity of Scienceand Technology Press Wuhan China 1984

[26] R Zhu Q Liang and H Zhan ldquoAnalysis of aero-engine perfor-mance and selection based on fuzzy comprehensive evaluationrdquoProcedia Engineering vol 174 pp 1202ndash1207 2017

[27] A Yazdani S Shariati andA Yazdani-Chamzini ldquoA risk assess-ment model based on fuzzy logic for electricity distributionsystem asset managementrdquo Decision Science Letters vol 3 no3 pp 343ndash352 2014

[28] Z XHe FuzzyMathematics and Its Application Tianjin Scienceand Technology Publishing House Tianjin China 1983

[29] W Li W Liang L Zhang and Q Tang ldquoPerformance assess-ment system of health safety and environment based onexpertsrsquo weights and fuzzy comprehensive evaluationrdquo Journalof Loss Prevention in the Process Industries vol 35 pp 95ndash1032015

[30] J-F ChenH-NHsieh andQHDo ldquoEvaluating teaching per-formance based on fuzzy AHP and comprehensive evaluationapproachrdquo Applied Soft Computing vol 28 pp 100ndash108 2015

[31] F Deng C Wang and X Liang ldquoFuzzy comprehensive eval-uation model for flight safety evaluation research based on anempowerment combinationrdquo in Proceedings of the 10th Inter-national Conference on Management Science and EngineeringManagement pp 1479ndash1491 2017

[32] AAfful-Dadzie E Afful-Dadzie S Nabareseh andZKOplat-kova ldquoTracking progress of African Peer Review Mechanism(APRM) using fuzzy comprehensive evaluation methodrdquo Ky-bernetes vol 43 no 8 pp 1193ndash1208 2014

[33] L KrizOva A Vollmannova E Margitanova et al ldquoCan beblueberries the risk food and rawmaterialrdquo Journal of Microbi-ology Biotechnology and Food Sciences vol 1 pp 769ndash776 2012

[34] M-H Moncel A-M Moigne M Arzarello and C PerettoldquoRaw material supply areas and food supply areas integratedapproach of the behaviorsrdquo in Proceedings of the XV WorldUISPP Congress 2007


[35] A Olsson and C Skjoldebrand ldquoRisk management and qualityassurance through the food Ssupply chain - case studies in theSwedish food industryrdquo The Open Food Science Journal vol 2no 1 pp 49ndash56 2008

[36] W Huang and L Chen ldquoResearch on food safety and qualitycontrol process modeling and simulation based on the supplychainrdquo Journal of Convergence Information Technology vol 8no 4 pp 34ndash42 2013

[37] T Matuszek ldquoFood production quality and risk assessment onmachinery designrdquo Journal of Hygienic Engineering and Design2012

[38] H Omura K Tanaka and N Sugimoto ldquoA hygienic hazard listfor risk assessment of food processing machineryrdquo The journalof Reliability Engineering Association of Japan vol 32 pp 367ndash375 2010

[39] TMatuszek ldquoBasic factors for food processing equipment hygi-enic design and its cleanabilities with minimal contaminationriskrdquo Journal of Hygienic Engineering and Design pp 38ndash452014

[40] X U Fucai and S Meng ldquoAnalysis on risk management of thefood supply chainrdquo in Midwives Research and Childbirth pp465ndash475 Springer New York NY USA 1989

[41] L I U Yongsheng and W E I Xuan ldquoFood supply chain riskmanagement situation evaluation model based on factor anal-ysisrdquo International Business and Management vol 12 no 2 pp40ndash46 2016

[42] A Marucheck N Greis C Mena and L Cai ldquoProduct safetyand security in the global supply chain issues challenges andresearch opportunitiesrdquo Journal of OperationsManagement vol29 no 7-8 pp 707ndash720 2011

[43] I Vlachos and E Dimitropoulos ldquoSupply chain management3rd party logistics and food quality and safety evidence fromGreecerdquo in Proceedings of the nternational Conference on Man-agement in Agrifood Chains and Networks 2006

[44] L Xu Q Dong and K Xiao ldquoResearch on early-warningmodelfor food supply chain risk based on logistic regressionrdquo inProceedings of the 2010 International Conference on LogisticsEngineering and Intelligent Transportation Systems LEITS2010pp 1ndash4 IEEE Wuhan China 2010

[45] L Leger and D Berkin ldquoMethod for simulating and modelingthe presence and growth of microbes including pathogens andspoilage organisms through a food supply chainrdquo 2004

[46] B H Susheela and L M Cathleen ldquoFactors affecting microbialload and profile of potential pathogens and food spoilagebacteria from household kitchen tablesrdquo Canadian Journal ofInfectious Diseases and Medical Microbiology vol 2016 ArticleID 3574149 6 pages 2016

[47] R M W Yeung and J Morris ldquoFood safety risk consumer per-ception and purchase behaviourrdquo British Food Journal vol 103no 3 pp 170ndash187 2001

[48] C Hawkes ldquoSales promotions and food consumptionnurerdquoNu-trition Reviews vol 67 no 6 pp 333ndash342 2009

[49] R Mo W Yeung and Morris J Food Safety Risk ConsumerFood Purchase Models Cranfield University Bedfordshire UK2002

[50] B Bilska M Wrzosek D Kołozyn-Krajewska and K Krajew-ski ldquoRisk of food losses and potential of food recovery for socialpurposesrdquoWaste Management vol 52 pp 269ndash277 2016

[51] HWei University B W Study on supermarket food safety riskmanagement based on supply chain Logistics Technology 2013

[52] X Gellynck W Verbeke J Viaene et al ldquoQuality manage-ment in the food supply chain how does the food industryinteract with consumers retailers and public authoritiesrdquo inProceedings of the Quality assurance risk management andenvironmental control in agriculture and food supply networksProceedings of the 82nd Seminar of the European Association ofAgricultural Economists (EAAE) held in Bonn 2003

[53] V Hill ldquoGovernment regulation of food quality internationaland in france and the USrdquo in A Kaizen Approach to Food Safetypp 53ndash82 Springer International Publishing Berlin Germany2014

[54] B F V Waarden Ttraditions transactions and trust the publicand private regulation of food Ansell Richmond Australia2005

[55] D K Casey ldquoThree puzzles of private governance global gapand the regulation of food safety and qualityrdquo SSRN ElectronicJournal 2009

[56] V Mceachern A Bungay S B Ippolito et al ldquo4ndashRegulatoryverification of safety and quality control systems in the foodindustryrdquo Auditing in the Food Industry vol 73 no 23 pp 29ndash51 2001

[57] G Skogstad ldquoRegulating food safety risks in the EuropeanUniona comparative perspectiverdquo in Whatrsquos the Beef pp 213ndash236 2006

[58] J Zhou and S Jin ldquoOverview of food safety management inChinardquo in Food SafetyManagement in China A Perspective fromFood Quality Control System pp 1ndash32 2015

[59] S-H Wang M-T Lee P-A Chateau and Y-C Chang ldquoPer-formance indicator framework for evaluation of sustainabletourism in the Taiwan coastal zonerdquo Sustainability vol 8 no7 article 652 2016

[60] C Deng J Liu Y Liu and Z Yu ldquoA fuzzy comprehensive eva-luation for metropolitan power grid risk assessmentrdquo in Pro-ceedings of the 2016 International Conference on Smart Grid andClean Energy Technologies ICSGCE rsquo16 pp 1ndash5 IEEE ChengduChina 2016

[61] J An ldquoEvaluating the electric power utilitiesrsquo risk based on animproved FCEM under the smart grid environmentrdquo in Pro-ceedings of the 2010 International Conference on ComputerMechatronics Control and Electronic Engineering pp 468ndash471IEEE Changchun China 2010

[62] L Gong and C Jin ldquoFuzzy comprehensive evaluation for carry-ing capacity of regional water resourcesrdquoWater Resources Man-agement vol 23 no 12 pp 2505ndash2513 2009

[63] T J Dukes B M Schmidt and Y Yu ldquoFMECA-based analysesA SMART foundationrdquo in Proceedings of the 2017 Annual Re-liability and Maintainability Symposium 2017

[64] A Certa F Hopps R Inghilleri and C M La Fata ldquoA Demp-ster-ShaferTheory-based approach to the Failure Mode EffectsandCriticality Analysis (FMECA) under epistemic uncertaintyapplication to the propulsion system of a fishing vesselrdquo Relia-bility Engineering amp System Safety vol 159 pp 69ndash79 2017

[65] J M Sun M l Zhao M X Zhang and Y H Hu ldquoInvestigationreport on construction of quality and safety inspection systemof agricultural products in Henan Provincerdquo Journal of HenanAgriculture vol 4 pp 22-23 2016

[66] A Fearne S Hornibrook and S Dedman ldquoThe managementof perceived risk in the food supply chain a comparative studyof retailer-led beef quality assurance schemes in Germany andItalyrdquo International Food and Agribusiness Management Reviewvol 4 no 1 pp 19ndash36 2009


[67] S L Ting Y K Tse G T SHo SH Chung andG Pang ldquoMin-ing logistics data to assure the quality in a sustainable foodsupply chain a case in the red wine industryrdquo InternationalJournal of Production Economics vol 152 pp 200ndash209 2014

[68] C Chen J Zhang and T Delaurentis ldquoQuality control in foodsupply chain management an analytical model and case studyof the adulteratedmilk incident in Chinardquo International Journalof Production Economics vol 152 pp 188ndash199 2014

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Submit your manuscripts atwwwhindawicom


risk level of food quality [15] And the quality risk level offood security is an important problem related to the foodsupply chain environment One effective solution to solve thisproblem is to build an evaluation indicator system based onthe fuzzy sets theory [16] Several studies have consideredthat building the indicator system is the first step in assessingthe quality risk and many research results have been madesuch as in the case of Wang et al who developed an indexsystem to evaluate the transparency of the supervision of foodsafety in China as a prerequisite for an accurate evaluationof the food safety risk level Jie et al analyzed the supplychain performance of Australian cattle producers based onfood supply chain performance indicators [17] Turi et alproposed aggregate indicators to assess the performance ofthe food supply chain by considering economic social andenvironmental development [18] Nilsson et al proposed totalquality indicators for the food production chain [19] Salvo etal focused on the toxic inorganic pollutants in foods fromagricultural producing to evaluate the risks for consumers[20] In these studies however the evaluation objects wereonly a single link not the whole food supply chain Moreoverthe food quality risk supervision at the national level ismissedin these studies Therefore the existing literature cannotprovide an effective guidance for the quality risk evaluationthroughout the whole food supply chain which means thata comprehensive and systematic study on the area of qualityrisk evaluation in the food supply chain is still missing

Many affecting factors of the quality risk evaluation in thefood supply chain exhibit highly fuzzy uncertainty and can-not be analyzed quantitativelyTherefore it is difficult to eval-uate the level of quality risk by a single defined managementcriterion [21] To address this fuzzy uncertainty problem in1965 Zadeh proposed the concept of fuzzy sets which laidthe foundation for the application of the fuzzy comprehensiveevaluation model (FCEM) in risk management [22] TheFCEM is a method to evaluate fuzzy mathematics which cantransform a qualitative evaluation into a quantitative evalu-ation [23ndash25] Combined with other methods the greatestfeature of the FCEM is that it can integrate the intuition andfuzziness of human thinking thus circumventing the unityof results required by traditional mathematical methods [26]Therefore the FCEM has become an effective multifactordecision-making tool for comprehensive evaluations [27] andreal-word problem solving in areas such as internationalrelations [28] aircraft flight safety [29] swine building envi-ronment [23] health safety and environmental management[30] regional water resources capacity [31] and teaching per-formance [32] Therefore in this paper an FCEM for model-ing these uncertainties and assessing food quality risk levelis developed to determine the overall food quality risk bymonitoring various independent risk factors and indictors inthe food supply chain

The rest of this paper is structured as follows Section 2describes the construction of a quality risk evaluation indica-tor system that covers the whole food supply chain based onan extensive literature review Section 3 proposes an FCEMfor the quality risk evaluation of the food supply chain basedon FCEM and FMECA Section 4 verifies the effectivenessand feasibility of the model using a computational experi-ment and Section 5 presents the conclusions

2 Quality Risk EvaluationIndicator System for the FoodSupply Chain

To ensure the accuracy and effectiveness a quality risk eva-luation indicator system that covers the entirety of the foodsupply chain should be established before evaluating foodquality risk Existing research on this system has been verylimited There is no ready-made quality risk evaluation indi-cator system for the food supply chain [13] Here the effectiveapproach to establishing the preliminary indicator frame-work is to analyze the existing literature and the laws andregulations of food safety regulatory [58] On this basis thequality risk evaluation indicator system for the food supplychain can be built by the method which is based on the fuzzyanalytic hierarchy process (FAHP) proposed by Wang et al[59] shown as Table 1

According to Table 1 the evaluation objects for qualityrisk of the food supply chain can be generalized into fivecategories raw material supply risk [33ndash37] production andprocessing risk [34 37ndash42] logistics warehousing and trans-portation risk [40ndash46] sales and consumption risk [42 47ndash51] and government regulatory risk [52ndash57] Raw materialsupply production and processing logistics warehousingand transportation sales and consumption are the four dif-ferent links of the food supply chain while government reg-ulations could affect every link of the food supply chain Theconnotations of each evaluation object could be described asfollows

(1) Raw Material Supply RiskThe risk of raw material supplyinvolves the raw materials produced by human pollutionnatural pollution and other factors that lead to pesticideresidues pathogen pollution and illegal additives during theprocess of planting or breeding which results in long-term orshort-term harm to human health [34] Raw material supplyrisk is a source of food quality risk including soil pollutionair pollution water pollution heavy metal pollution illegaluse of additives residual inputs microbial contaminationpathogenic bacteria pollution and transgenic technologyrisk

(2) Production and Processing Risk This risk arises when thesafety management and production environment during theprocesses of production and packaging are not compliantwith regulations this risk could lead to possible food con-tamination and illegal additives and produce potential safetyhazards to human health As this link involves the food qual-ity and safety in the whole food industrial chain its impactis relatively large The main quality risk evaluation indicatorsincluded in this link are illegal use of additives contamina-tion with foreign matter inability to wash a food productclean presence of detergent residue pathogen contamina-tion microbial contamination uncertified processing equip-ment nonstandardized processing personnel operationinsufficient processing environment insufficient processingequipment inappropriate packaging insufficient packagingquality uncertified packaging logo insufficient assurance of


Table1Qualityris

kevaluatio

nindicatorsystem

forthe

food

supp

lychain

Evaluatio

nob

jects

Risk

evaluatio

nindicators

References

Rawmaterialsup

plyris

k

Soilpo

llutio

nAirpo

llutio

n

[33ndash37]

Water

pollu

tion

Heavy

metalpo

llutio

nIllegaluseo

fadd

itives

Resid

ualinp

uts

Microbialcontam

ination


llutio

nTransgenictechno

logy

risk

Prod

uctio

nandprocessin

gris

k

Illegaluseo

fadd

itives

Con

taminationwith

foreignmatter

[3437ndash4

2]

Inabilityto

washafoo

dprod

uctclean

Presence

ofdetergentresidue

Pathogen

contam

ination

Microbialcontam

ination

Uncertifi

edprocessin

gequipm

ent

Non

standardized

processin

gperson

neloperatio

nInsufficientp

rocessingenvironm

ent

Insufficientp

rocessingequipm

ent

Inapprop

riatepackaging

Insufficientp

ackaging

quality

Uncertifi

edpackaginglogo


ofperson

nelh

ealth

Qualityinspectio

nris


process

Logisticswarehou

singand

transportatio

nris

k


olog

yIntelligent

temperature-con

trolfacilitie

s

[40ndash

46]


nColdchainhardwares

uppo

rtingfacilities

Third


Partnertechn

olog

yplatform

convergence

Prod

uctp

ortfo

liosto

rage

transport

Coldchainlogistics

inform

ationtransm

ission


Illegalop

erationof

Logisticstranspo

rtperson

nel

Vehicle

schedu

lingandmon

itorin

ginform

ationfeedback

Salesa

ndconsum

ptionris

k

Selling

expiredfood

Falsifyingthed

ateo

fprodu

ction

[4247ndash52]

False

repo

rtingof

food

ingredients

Poor

sanitatio

nin

dining

establish

ments

Poor

sanitatio

ncond

ition

sIm

prop

erdisposalof

wastefood

Poor

sanitatio

nin

cook

ingfacilities

Improp

ereatin

gmetho


environm

ent

Governm

entregulatoryris

k

Imperfe

ctregu

latory

syste

mSuperviso

rysta

fflevel

[53ndash57]

Superviso

rmoralhazard

Supervision

channels


nRe

gulatoryagency

efficiency

Regu

latoryprocessm

anagem

ent

Regu

latory

results

feedback

Regu


logy

Other

risks






3 Evaluation Model






119876 = 1198761 119876 119876119894 119876 119876119899 119876119894 = 1198761198941 119876119894119895 119876119894119898

(119894 = 1 2 119899 119895 = 1 2 119898) (1)




Input

Output



comment comment


matrix


matrix


matrix

e 1ststage

e 2ndstage

e 3rdstage

e 4thstage

e 5thstage




objective





Q = Q1 Q2 Q3 Q Qn

Q1 Q2 Q



L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 (2)


L = 1 2 3 4 5 (3)


119877119894 =

11990311989411 11990311989412 11990311989413 11990311989414 1199031198941511990311989421 11990311989422 11990311989423 11990311989424 1199031198942511990311989431 11990311989432 11990311989433 11990311989434 11990311989435 1199031198941198981 1199031198941198982 1199031198941198983 1199031198941198984 1199031198941198985

(4)




119882 = 11988211198822 119882119894 119882119899 (119894 = 1 2 119899) 1198821015840119894 = 1198821015840119894111988210158401198942 1198821015840119894119895 1198821015840119894119898

(119894 = 1 2 119899 1 le 119895 le 119898) 119899sum119894=1

119882119894 = 1119898sum119895=1

1198821015840119894119895 = 1

(5)



119881 =W ∘ X119879 (6)

119883 = (1198831 1198832 119883119894) (7)

119883119894 = 1198821015840119894 times 119877119894 (8)





119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)





119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)



119874119894 =



119900119894 otherwise(11)


119878119894 =


5 worst severity

119904119894 otherwise(12)


119863119894 =



119889119894 otherwise(13)


=



119888119894 otherwise(14)








119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table1Qualityris

kevaluatio

nindicatorsystem

forthe

food

supp

lychain

Evaluatio

nob

jects

Risk

evaluatio

nindicators

References

Rawmaterialsup

plyris

k

Soilpo

llutio

nAirpo

llutio

n

[33ndash37]

Water

pollu

tion

Heavy

metalpo

llutio

nIllegaluseo

fadd

itives

Resid

ualinp

uts

Microbialcontam

ination


llutio

nTransgenictechno

logy

risk

Prod

uctio

nandprocessin

gris

k

Illegaluseo

fadd

itives

Con

taminationwith

foreignmatter

[3437ndash4

2]

Inabilityto

washafoo

dprod

uctclean

Presence

ofdetergentresidue

Pathogen

contam

ination

Microbialcontam

ination

Uncertifi

edprocessin

gequipm

ent

Non

standardized

processin

gperson

neloperatio

nInsufficientp

rocessingenvironm

ent

Insufficientp

rocessingequipm

ent

Inapprop

riatepackaging

Insufficientp

ackaging

quality

Uncertifi

edpackaginglogo


ofperson

nelh

ealth

Qualityinspectio

nris


process

Logisticswarehou

singand

transportatio

nris

k


olog

yIntelligent

temperature-con

trolfacilitie

s

[40ndash

46]


nColdchainhardwares

uppo

rtingfacilities

Third


Partnertechn

olog

yplatform

convergence

Prod

uctp

ortfo

liosto

rage

transport

Coldchainlogistics

inform

ationtransm

ission


Illegalop

erationof

Logisticstranspo

rtperson

nel

Vehicle

schedu

lingandmon

itorin

ginform

ationfeedback

Salesa

ndconsum

ptionris

k

Selling

expiredfood

Falsifyingthed

ateo

fprodu

ction

[4247ndash52]

False

repo

rtingof

food

ingredients

Poor

sanitatio

nin

dining

establish

ments

Poor

sanitatio

ncond

ition

sIm

prop

erdisposalof

wastefood

Poor

sanitatio

nin

cook

ingfacilities

Improp

ereatin

gmetho


environm

ent

Governm

entregulatoryris

k

Imperfe

ctregu

latory

syste

mSuperviso

rysta

fflevel

[53ndash57]

Superviso

rmoralhazard

Supervision

channels


nRe

gulatoryagency

efficiency

Regu

latoryprocessm

anagem

ent

Regu

latory

results

feedback

Regu


logy

Other

risks






3 Evaluation Model






119876 = 1198761 119876 119876119894 119876 119876119899 119876119894 = 1198761198941 119876119894119895 119876119894119898

(119894 = 1 2 119899 119895 = 1 2 119898) (1)




Input

Output



comment comment


matrix


matrix


matrix

e 1ststage

e 2ndstage

e 3rdstage

e 4thstage

e 5thstage




objective





Q = Q1 Q2 Q3 Q Qn

Q1 Q2 Q



L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 (2)


L = 1 2 3 4 5 (3)


119877119894 =

11990311989411 11990311989412 11990311989413 11990311989414 1199031198941511990311989421 11990311989422 11990311989423 11990311989424 1199031198942511990311989431 11990311989432 11990311989433 11990311989434 11990311989435 1199031198941198981 1199031198941198982 1199031198941198983 1199031198941198984 1199031198941198985

(4)




119882 = 11988211198822 119882119894 119882119899 (119894 = 1 2 119899) 1198821015840119894 = 1198821015840119894111988210158401198942 1198821015840119894119895 1198821015840119894119898

(119894 = 1 2 119899 1 le 119895 le 119898) 119899sum119894=1

119882119894 = 1119898sum119895=1

1198821015840119894119895 = 1

(5)



119881 =W ∘ X119879 (6)

119883 = (1198831 1198832 119883119894) (7)

119883119894 = 1198821015840119894 times 119877119894 (8)





119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)





119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)



119874119894 =



119900119894 otherwise(11)


119878119894 =


5 worst severity

119904119894 otherwise(12)


119863119894 =



119889119894 otherwise(13)


=



119888119894 otherwise(14)








119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018







3 Evaluation Model






119876 = 1198761 119876 119876119894 119876 119876119899 119876119894 = 1198761198941 119876119894119895 119876119894119898

(119894 = 1 2 119899 119895 = 1 2 119898) (1)




Input

Output



comment comment


matrix


matrix


matrix

e 1ststage

e 2ndstage

e 3rdstage

e 4thstage

e 5thstage




objective





Q = Q1 Q2 Q3 Q Qn

Q1 Q2 Q



L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 (2)


L = 1 2 3 4 5 (3)


119877119894 =

11990311989411 11990311989412 11990311989413 11990311989414 1199031198941511990311989421 11990311989422 11990311989423 11990311989424 1199031198942511990311989431 11990311989432 11990311989433 11990311989434 11990311989435 1199031198941198981 1199031198941198982 1199031198941198983 1199031198941198984 1199031198941198985

(4)




119882 = 11988211198822 119882119894 119882119899 (119894 = 1 2 119899) 1198821015840119894 = 1198821015840119894111988210158401198942 1198821015840119894119895 1198821015840119894119898

(119894 = 1 2 119899 1 le 119895 le 119898) 119899sum119894=1

119882119894 = 1119898sum119895=1

1198821015840119894119895 = 1

(5)



119881 =W ∘ X119879 (6)

119883 = (1198831 1198832 119883119894) (7)

119883119894 = 1198821015840119894 times 119877119894 (8)





119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)





119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)



119874119894 =



119900119894 otherwise(11)


119878119894 =


5 worst severity

119904119894 otherwise(12)


119863119894 =



119889119894 otherwise(13)


=



119888119894 otherwise(14)








119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Input

Output



comment comment


matrix


matrix


matrix

e 1ststage

e 2ndstage

e 3rdstage

e 4thstage

e 5thstage




objective





Q = Q1 Q2 Q3 Q Qn

Q1 Q2 Q



L = ℓ1 ℓ2 ℓ3 ℓ4 ℓ5 (2)


L = 1 2 3 4 5 (3)


119877119894 =

11990311989411 11990311989412 11990311989413 11990311989414 1199031198941511990311989421 11990311989422 11990311989423 11990311989424 1199031198942511990311989431 11990311989432 11990311989433 11990311989434 11990311989435 1199031198941198981 1199031198941198982 1199031198941198983 1199031198941198984 1199031198941198985

(4)




119882 = 11988211198822 119882119894 119882119899 (119894 = 1 2 119899) 1198821015840119894 = 1198821015840119894111988210158401198942 1198821015840119894119895 1198821015840119894119898

(119894 = 1 2 119899 1 le 119895 le 119898) 119899sum119894=1

119882119894 = 1119898sum119895=1

1198821015840119894119895 = 1

(5)



119881 =W ∘ X119879 (6)

119883 = (1198831 1198832 119883119894) (7)

119883119894 = 1198821015840119894 times 119877119894 (8)





119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)





119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)



119874119894 =



119900119894 otherwise(11)


119878119894 =


5 worst severity

119904119894 otherwise(12)


119863119894 =



119889119894 otherwise(13)


=



119888119894 otherwise(14)








119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018





119884 =L sdot 1198811198791198841015840 = (1198841 1198842 119884119894) 119884119894 =L sdot 119883119894119879

(9)





119882119894 = 11988210158401015840119894sum119899119894=111988210158401015840119894

119882119894119895 = 11988210158401015840119894119895sum119898119895=111988210158401015840119894119895

(10)



119874119894 =



119900119894 otherwise(11)


119878119894 =


5 worst severity

119904119894 otherwise(12)


119863119894 =



119889119894 otherwise(13)


=



119888119894 otherwise(14)








119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018






119898 =

9 119894 = 116 119894 = 211 119894 = 39 119894 = 410 119894 = 5

(15)





120572

)sum5120572=1 Frequency(119876119894119898119901

120572

) where Frequency(119876119894119898119901120572

) is the


1198772 =[[[[[[[[[[


]]]]]]]]]]

=

[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0065 0225 0337 0273 01000094 0243 0360 0235 00690096 0283 0382 0168 00710085 0232 0342 0255 00870047 0200 0306 0284 01630045 0236 0335 0266 01180065 0232 0349 0268 00870071 0245 0357 0259 00670067 0236 0333 0277 00870087 0272 0362 0233 00470243 0312 0275 0126 00450249 0298 0268 0135 00490174 0229 0340 0168 00890176 0285 0284 0182 00730185 0236 0280 0199 01000214 0241 0355 0108 0082

]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]

(16)


1198771 =

[[[[[[[[[[[[[[[[[[[[[[[

0056 0225 0346 0224 01490232 0310 0275 0088 00960122 0283 0384 0090 01200241 0310 0277 0079 00940220 0289 0317 0077 00980065 0236 0344 0215 01400118 0274 0386 0095 01270038 0238 0360 0217 01470053 0205 0271 0277 0194

]]]]]]]]]]]]]]]]]]]]]]]


Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table2Risk

evaluatio

nindicatorsetof

FSCH

P119876

Evaluatio

nob

ject119876 119894

Risk

evaluatio

nindicators119876 119894119895

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logisticstranspo

rtperson

nel119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510




1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018





1198773 =

[[[[[[[[[[[[[[[[[[[[[[[[[[[[

0105 0134 0311 0253 01980114 0220 0324 0190 01510067 0176 0237 0313 02070127 0247 0322 0175 01290120 023 0326 0186 01450116 0227 0326 0175 01560176 0247 0297 0146 01340096 0209 0317 0210 01670105 0209 0322 0202 01630203 0256 0239 0170 01310038 0238 0360 0219 0145

]]]]]]]]]]]]]]]]]]]]]]]]]]]]

1198774 =

[[[[[[[[[[[[[[[[[[[[[[

0067 0232 0358 0268 00800047 0203 0306 0284 01600076 0234 0342 0262 00870145 0321 0291 0175 00690071 0243 0367 0259 00690069 0238 0329 0277 00870040 0214 0362 0280 01050042 0225 0335 0277 01200022 0194 0268 0326 0189

]]]]]]]]]]]]]]]]]]]]]]

1198775 =

[[[[[[[[[[[[[[[[[[[

0062 0236 0346 0271 00850151 0261 0353 0168 00670069 0234 0331 0280 00870049 0176 0373 0326 00760145 0292 0277 0222 00650047 0241 0360 0206 01470045 0243 0369 0188 01560120 0272 0389 0092 01270116 0267 0391 0092 01340045 0216 0355 0235 0149

]]]]]]]]]]]]]]]]]]]

(17)


119882 = [11988211198822119882311988241198825]= [00925 0191 0243 0284 0190] (18)



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



11988210158401 = [119882101584011 119882101584019] = [0119 0143 0106 0104 0180 0060 0136 0092 0060] 11988210158402 = [ 119882

101584021 119882101584028119882101584029 1198821015840216 ] = [

0050 0133 0158 0033 0041 0027 0052 00550031 0037 0075 0035 0065 0063 0042 0102]

11988210158403 = [119882101584031 1198821015840311] = [0044 0089 0049 0086 0165 0186 0063 0177 0055 0025 0059] 11988210158404 = [119882101584041 1198821015840412] = [0152 0085 0055 0184 0162 0086 0054 0065 0156] 11988210158405 = [119882101584051 1198821015840510] = [0124 0149 0090 0078 0053 0123 0048 0148 0104 0083]

(19)


1198831 = [0144 0271 0330 0133 0122] 1198832 = [0128 0255 0338 0200 0079] 1198833 = [0112 0219 0317 0197 0155] 1198834 = [0071 0241 0322 0262 0105] 1198835 = [0089 0246 0359 0198 0108]

(20)


119881 = 119882 ∘ 119883119879 = 119882 ∘[[[[[[[[[

11988311198832119883311988341198835

]]]]]]]]]

= [00925 0191 0243 0284 0190]

∘[[[[[[[[[[[

0144 0271 0330 0133 01220128 0255 0338 0200 00790112 0219 0317 0197 01550071 0241 0322 0262 01050089 0246 0359 0198 0108

]]]]]]]]]]]

= [0206 0214 0215 0225 0219]

(21)


119884 =L sdot 119881119879 = [1 2 3 4 5] sdot[[[[[[[[[

02060214021502250219

]]]]]]]]]= 3273

1198841 =L sdot 1198831119879 = [1 2 3 4 5] sdot[[[[[[[[[

01440271033001330122

]]]]]]]]]= 2819

1198842 = 28471198843 = 30651198844 = 30891198845 = 2990

(22)





Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table4Va

lues

of119874 119894119878119894119863 119894

and119862 119894s

coredby

fivee

xperts

119876Scored

by1stexp

ert

Scored

by2n

dexpert

Scored

by3rdexpert

Scored

by4thexpert

Scored

by5thexpert

Average

12

34

51

23

45

12

34

51

23

45

12

34

5

119876 1119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 1

33

1224

6528

119876 2119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 2

7515

1210

101090

119876 3119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 3

62667

667

624

1387

119876 4119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 4

1020

1520

161620

119876 5119874

radicradic

radicradic

radic119878

radicradic

radicradic

radic119863

radicradic

radicradic

radic119862

radicradic

radicradic

radic11988210158401015840 5

1020

667

1075

1083


Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Q1 Q2 Q3 Q4 Q5

28194025072846845822

3064755443308923955

2990072697

26527

27528

28529

2953

30531





5 Conclusion




Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table 5







Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table 5 Continued





Appendix



(1) Gender

◻male◻ female

(2) Age









See Table 6



Acknowledgments



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table6

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Rawmaterialsup

plyris

k119876 1

Soilpo

llutio

n119876 11

Airpo

llutio

n119876 12

Water

pollu

tion119876 13

Heavy

metalpo

llutio

n119876 14

Illegaluseo

fadd

itives119876 15

Resid

ualinp

uts119876 16

Microbialcontam

ination119876 17


llutio

n119876 18

Transgenictechno

logy

risk119876 19

Prod

uctio

nandprocessin

gris

k119876 2

Illegaluseo

fadd

itives119876 21

Con

taminationwith


Inabilityto

washafoo

dprod

uctclean119876 23

Presence


Pathogen

contam

ination119876 25

Microbialcontam

ination119876 26

Uncertifi

edprocessin

gequipm

ent119876 27

Non

stand

ardizedprocessin

gperson

neloperatio

n119876 28

Insufficientp

rocessingenvironm

ent119876 29

Insufficientp

rocessingequipm

ent119876 210

Inapprop


Insufficientp

ackaging

quality119876 212

Uncertifi



ofperson

nelh

ealth


nris

k119876 215

Insufficientstorage

process119876 216


Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018



Table6Con

tinued

Factors

Scoring

Occurrencep

robability

(H)

Severityaft

eroccurrence

(S)

Likelih

oodof

detection

(D)

Abilityto

controland

compensate(C)

12

34

51

23

45

12

34

51

23

45

Logisticswarehou


nris

k119876 3


olog

y119876 31

Intelligent

temperature-con

trolfacilitie

s119876 32


n119876 33

Coldchainhardwares

uppo


Third


Partnertechn

olog

yplatform


Prod

uctp

ortfo

liosto

rage

transport119876 37

Coldchainlogistics

inform

ationtransm

ission119876 38


Illegalop

erationof

logistics

transportp

ersonn

el119876 310

Vehicle

schedu

lingandmon

itorin

ginform


Salesa

ndconsum

ptionris

k119876 4

Selling


Falsifyingthed

ateo

fprodu

ction119876 42

False

repo

rtingof

food


Poor

sanitatio

nin

dining

establish

ments119876 44

Poor

sanitatio

ncond

ition

s119876 45

Improp

erdisposalof

wastefood119876 46

Poor

sanitatio

nin

cook


Improp

ereatin

gmetho

ds119876 48

Insufficientstorage

environm

ent119876 49

Governm

entregulatoryris

k119876 5

Imperfe

ctregu

latory

syste

m119876 51

Superviso

rysta

fflevel119876 52

Superviso


Supervision

channels119876 54

Regu

latoryorganizatio

n119876 55

Regu

latoryagency

efficiency119876 56

Regu

latoryprocessm

anagem

ent119876 57

Regu

latory

results

feedback119876 58

Regu


logy119876 59

Other

risks119876 510



References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018




References










































































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018








































Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018







Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018




Volume 2018

Zoology











Volume 2018

















Advances in




Enzyme Research





Volume 2018


Documents

Quality Risk Evaluation of the Food Supply Chain …downloads.hindawi.com/journals/jfq/2018/2637075.pdfFailure Mode, Effects, and Criticality Analysis LibiaoBai , 1 ChunmingShi , 2