Accepted Manuscript Assessment of food fraud vulnerability in the spices chain: an explorative study
I.C.J. Silvis, S.M. van Ruth, H.J. van der Fels-Klerx, P.A. Luning PII:
S0956-7135(17)30262-1
DOI:
10.1016/j.foodcont.2017.05.019
Reference:
JFCO 5625
To appear in:
Food Control
Received Date:
30 March 2017
Revised Date:
12 May 2017
Accepted Date:
13 May 2017
Please cite this article as: I.C.J. Silvis, S.M. van Ruth, H.J. van der Fels-Klerx, P.A. Luning, Assessment of food fraud vulnerability in the spices chain: an explorative study, Food Control (2017), doi: 10.1016/j.foodcont.2017.05.019
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ACCEPTED MANUSCRIPT Highlights
Fraud assessment reveals vulnerabilities due to opportunities, motivations, and controls Interviewed spice chain actors assigned food fraud vulnerability overall as medium
Key risks are simple adulteration, detection difficulty, price and market competition
Hard fraud mitigation vary considerably among interviewed spice actors
ACCEPTED MANUSCRIPT 1
Assessment of food fraud vulnerability in the spices chain: an explorative study
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I.C.J. Silvisab (
[email protected]), S.M. van Ruthab* (
[email protected]) (corresponding author), H.J. van der Fels-Klerxa (
[email protected]), P.A. Luningb (
[email protected])
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a RIKILT
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Wageningen University and Research, P.O. Box 230, 6700 AE Wageningen, The Netherlands
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b Food
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Quality and Design Group, Wageningen University and Research, P.O. Box 17 / bode 30 6700 AA Wageningen, The Netherlands
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* Corresponding author
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Keywords: control measures, fraud, fraud mitigation, fraud indicators, motivations, opportunities, spices, vulnerability
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Abstract: Recent scandals have increased the need to strengthen companies’ ability to combat fraud within their own organizations and across their supply chain. Vulnerability assessments are a first step towards the inventory of fraud vulnerability and fraud mitigation plans. Spices are reported frequently in the international food fraud databases. In the current study the fraud vulnerabilities of various actors in the spices supply chain were examined. The SSAFE food fraud vulnerability assessment tool, which comprises of 50 indicators categorized in opportunities, motivations, and control measures was applied for getting insight into these fraud vulnerabilities. Eight companies participated in the study: a trader, two importers, two business to business companies, and three business-to- business/ business-to-consumer enterprises. The ease to adulterate spices combined with the complexity of fraud detection create considerable opportunities to commit fraud (high vulnerability), whereas opportunities associated with supply chain transparency and fraudulent incidences in the past were judged as medium vulnerable. The high competition level in the sector together with the high added value of spices are perceived as important economic drivers to commit fraud (high vulnerability). Cultural/behavioural factors such as ethical business culture were considered to contribute to the actual fraud vulnerability to a lesser extent. The implementation of both the hard and soft control measures varied widely among the actors. Hard fraud specific measures are merely lacking or are at a very basic level. For soft control measures of the own company, the scores were higher. From the results of the full assessments can be concluded that the various actors perceived the level of food fraud vulnerability in the spices chain as medium vulnerable.
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1. Introduction
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Food fraud scandals and issues in the last few years have reinforced the need to
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understand the vulnerability to fraud in food chains. The food industry is generally
19
vulnerable to crime and the spice industry is mentioned as one of the most vulnerable
20
ones, in addition to meat, fish, and olive oil industries (Morling & McNaughton, 2016).
21
For example, in 2014, ground peanut shells were discovered in powdered cumin.
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This caused a major recall because of the allergenic properties of the peanut material,
23
which is a severe risk to those that suffer from a peanut allergy (Sayers et al., 2016).
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Investigations revealed that fraudulent activity and not accidental contamination was
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behind the incident. The main motivation of the company was the economic benefit
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from the addition of cheaper bulk material to the premium quality cumin.
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Food fraud involves the deliberate substitution, addition, tampering or
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misrepresentation of food, food ingredients or food packaging, or false or misleading
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statements made about a product for economic gain (Spink & Moyer, 2011a). This
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definition has been widely adopted by various authors (e.g. Pustjens, Weesepoel, &
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van Ruth, 2016; Avery, 2014; GFSI, 2014), and by internationally acknowledged
32
bodies such as the Global Food Safety Initiative (GFSI). The addition of a cheaper
33
ingredient is the most common type of economically motivated adulteration (EMA)
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(Capuano & van Ruth, 2012), which can result in thousands of euros from illegal
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profits (Moyer, DeVries, & Spink, 2016). Food fraud can be committed by any
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individual person or group involved in the whole supply chain, including suppliers,
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food manufacturers, retailers and importers (Johnson, 2014). Adulteration is the
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preparation of foods for sale by replacing valuable with less valuable ingredients or
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constituents.
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In general, herbs and spices represent an attractive category for potential offenders,
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because the products have a high value by weight and consumers have a limited
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capacity to detect adulteration (Schaarschmidt, 2016; Moore, Spink, & Lipp, 2012).
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Common authenticity issues associated with spices are the addition of lower value
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product foreign and product own material (Peter, 2011), which may include addition
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of unapproved ‘enhancements’, such as dyes (Haughey, Galvin-King, Ho, Bell, &
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Elliott, 2015) to cover up the extension. Ground spices are particularly prone to
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adulteration, because the milling or grinding step changes the shape of both the
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spice and adulterant to a powder, which makes it difficult to detect adulterants in the
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final product.
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Although it is the governments’ responsibility to set clear legal requirements it is the
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responsibility of the industry to mitigate food fraud risks (Spink & Moyer, 2011b).
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However, such measures are not yet widely adopted in current food safety
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management systems. In the past few years, several initiatives to analyse, measure
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and/or mitigate food fraud risks have been developed because of the raised
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awareness. For example, the U.S. Pharmacopeia Convention (USP) developed the
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USP tool to assist food industries and regulators in developing and applying
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preventive management systems to identify the most vulnerable ingredients within
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their supply chains and to choose valid situation-specific mitigation measures (USP,
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2014). Grocery Manufacturers Association (GMA) established a tool for the purpose
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of assuring the integrity of brand and safety of food products (Kerney, 2010).
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Moreover, the British Retail Consortium (BRC) version 7, a private food safety
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standard, added a module on food fraud and provides food companies guidance on
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how to do a vulnerability assessment (BRC, 2015). Furthermore, SSAFE (2016) has
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published a science-based food fraud vulnerability self-assessment tool (SSAFE
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FFVA tool), which is based on the routine activities theory (Cohen & Felson, 2016). It
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consists of 50 questions which consider the three theory’s key elements:
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opportunities (suitable target), motivations (motivated offender), and control
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measures, the scientific background has been reported by van Ruth, Huisman, and
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Luning (2017).
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In principle, the SSAFE FFVA tool is developed as a basis for companies to self-
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assess their business, but it can also be used to compare companies (multiple
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respondents) and to analyse a specific chain.
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The aim of the current study is to get insight in potential fraud vulnerabilities of
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various actors in the spices supply chain by applying this new tool.
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2. Materials and methods
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2.1. The Food Fraud Vulnerability Assessment (FFVA) approach
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2.1.1.Theoretical aspects of the FFVA
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The principal structure of the FFVA is based on the routine activities theory (Cohen &
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Felson, 2016) and the “design rules” as used in the development of diagnostic tools
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for Food Safety Management System (FSMS) assessment (Kirezieva, Jacxsens,
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Uyttendaele, Van Boekel, & Luning, 2013; Luning et al., 2009; Luning, Bango,
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Kussaga, Rovira, & Marcelis, 2008). The routine activities theory defines the three
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key elements leading to crime: a suitable target, a motivated offender, and the
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absence of guardianship. These key elements were modified to suit food fraud and
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are the centre of the FFVA: i.e. opportunities, motivations and control measures. The
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“design rules” include focus on key factors/activities, identify indicators to analyse
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crucial aspects of these factors/activities, formulate questions linked to the indicators,
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and develop grids to enable a differentiated assessment. Grids depict typical
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descriptions that reflect for example, a high, medium, or low risk situation for the
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particular factor/activity. The situations are linked to a score system to enable the
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development of spider web diagrams to visualise the profiles (Luning et al., 2011;
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Sampers et al., 2010). The overall principle of the FFVA tool is reflected in the
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formula: opportunities x motivations x control measures = actual fraud vulnerability.
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So, more opportunities and motivations will increase fraud vulnerability, whereas
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control measures can counteract these vulnerabilities. The terms “risk” and
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“vulnerability” are used interchangeably and are therefore defined explicitly. The
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following definition of vulnerability applies and originate from USA food regulations
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(DHS, 2015): “A physical feature or operational attribute that renders an entity open
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to exploitation or susceptible to a given hazard.”
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The tool was tested, discussed and adapted based on multiple workshops in The
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Netherlands (Zaandam), USA (Washington), and Singapore (Singapore) with
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representatives of global food industry actors.
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2.1.2. Practical aspects of the FFVA
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The FFVA consists of 50 indicators (Table 1) each with a related question and
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corresponding assessment grid to enable companies to judge their actual situation
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with respect to the key risk factors related to opportunities, motivations, and control
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measures, which provide an overall profile of their fraud vulnerability. Potential
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opportunities, motivations, and control measures for food fraud are assessed related
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to both the internal organization and the external environment of the company. The
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environment consists of multiple levels: i.e. the company, the direct suppliers and
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customers, the industry segment, and the national and/or international environment.
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The various environmental levels are all considered in the FFVA.
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Opportunities related fraud factors of raw material and final product include
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indicators, such as the complexity of adulterating spices and whether the technology
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to adulterate is common knowledge or complex. In addition to these technical
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indicators, there are indicators to analyse opportunities in time and space, such as
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the accessibility to materials in production and the transparency of the network. The
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questions and answers have the following template. The question linked to the
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indicator “complexity of adulteration” reads: “Is it simple or complex to adulterate the
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raw material”? The assumption is that easy alteration of the composition of raw
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materials provides opportunities for potential offenders to commit fraud. Three
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answer options are provided, one of which need to be selected. Low vulnerability
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answer option 1 is: “Composition of the materials cannot be modified and products
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can only be replaced, i.e. it concerns large objects such as fruit”. Medium
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vulnerability answer option 2 is: “Composition of the raw materials can be modified by
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mixing with low-quality product-own material or foreign material, i.e. as is feasible
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with grinded products (e.g. powders, grinded beef, etc.)” and high vulnerability
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answer option 3 is: “Composition of the raw materials can be modified by mixing with
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low-quality or foreign material (e.g. powders, ground meat, etc.) and by altering
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valuable food components (e.g. protein content)”.
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Motivations related fraud factors concern economic aspects as well as cultural and
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behavioural facets. For instance, prices, supply and demand, and value-adding
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attributes of the materials are important economic factors, as well as the level of
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competition in the sector and the economic health of the business. Behaviour and
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culture related aspects include for instance business strategy, ethical business
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culture, and corruption level of the country in which the company and/or supplier is
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based. These factors can enhance fraudsters’ motivations to commit fraud.
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The control measures are divided in soft and hard control ones. Hard control
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measures are well observable and can be tested (Drechsler, Halff, Huisman, & Post,
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2012). They affect the ‘hard’ aspects of an organization such as planning, control,
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tasks and responsibilities. Soft controls are non-tangible behaviour influential factors
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in an organization and focuses on e.g. personality of employees and behaviour. The
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soft control measures can influence motives, loyalty, integrity, inspiration, norms and
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values of employees and are on a more personal level. A subdivision is provided for
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the environmental layers, i.e. the internal hard and soft controls, and the external
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controls at the level of the direct suppliers/customers and the wider (inter) national
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environment including law enforcement.
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2.2. Case study design: the spices chain network
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2.2.1. Selection and characteristics of respondents
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Eight companies, members of the European Spices Association (ESA), participated
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in the study. Seven were based in the Netherlands and one in Germany. Six
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interviews were conducted face-to-face and two assessments were carried out by
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online survey. The characteristics of the companies and the participants are listed in
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Table 2. Altogether, the eight companies represent trader, importer, business-to-
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business enterprises (b2b), and business to business/business-to-consumers
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enterprises (b2b/b2c) in the spices chain. Some of their processing activities overlap,
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but the spices they trade or produce may differ.
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2.2.2. The vulnerability assessments
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The original questions in English were translated into Dutch, and some questions
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were adjusted to spices. For example, the word ‘raw material’ in the survey was
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substituted with ‘spice’. A questionnaire was sent by e-mail one week prior to the
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interview to prepare respondents for the face-to-face interview. They had time to
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consult additional documents and ask experts in their organization about certain
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questions. This was necessary for the interviews to ease the conversation with the
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representatives of the spice companies. The interviewer asked the 50 questions one
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by one. The interviewer interpreted the answers and allocated the answer to one of
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the options in the grid, which was discussed with the respondent. The duration of the
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interview was between 1.5 and 2 hours. The first author performed the face-to-face
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interviews and all were voice recorded with permission of the respondents. The
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conversations were replayed for data analysis.
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2.2.3. Data analysis
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After the interview was completed, the options were transformed to the score system,
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to enable a frequency analysis. A high vulnerability situation for the opportunities and
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motivations corresponds to a score of 3 (e.g. the knowledge required for adulteration
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is generally available). A medium vulnerability situation obtains a score of 2 (e.g.
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advanced technologies, methods, facilities and knowledge are required to adulterate
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the raw materials) and a low vulnerability situation corresponds to a score 1 (i.e.
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technologies and/or methods to adulterate the raw materials are neither available,
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known, or reported). For the control measures, a score of 1 is assigned to high
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vulnerability situation (i.e. no specific fraud focus in control), a score of 2 to a medium
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vulnerability situation (e.g. some basic/simple fraud related measures in place), and 3
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to answers linked to a low vulnerability situation (e.g. fraud dedicated measures in
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place). For all 50 questions, the most frequently given answer (i.e. the mode) to a
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certain situation (and corresponding score) was determined.
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3. Results and discussion
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3.1. Overall food fraud vulnerability profiles
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The results of the FFVA are presented in the spider web diagrams in Fig. 1 showing
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the scores for the most frequently given (mode) answers for each indicator. The
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indicators are grouped per category, “opportunities”, “motivations” and “control
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measures”. The dashed line shows the second score with the highest frequency, in
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case of identical frequencies for two answers (ties). A larger surface corresponds
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with a higher fraud vulnerability. For the control measures, the larger the surface area,
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the more measures are in place and the more fraud specific/dedicated they are.
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Overall, the respondents scored between 2-3 (medium to high vulnerability) for the
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opportunities, and scored between 1-2 (low to medium) for the motivations. For the
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control measures mean scores distributed widely from 1 to 3. Eleven indicators out of
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19 scored 1 (high vulnerability, low level of control) indicating that fraud specific
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measures are merely lacking or are at a very basic level. For soft control measures of
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the own company, the scores were higher (low vulnerability, high level of control).
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3.2. Food fraud profiles of individual actors
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The individual scores for all indicators and actors are presented in Table 3. The
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scores for the low, medium, and high vulnerability situations for the opportunities,
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motivations, and control measures related indicators are coloured green, orange, and
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red respectively. The actors in this case study operated independently from each
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other and the importers were not the suppliers of the other actors presented in the
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table.
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3.2.1. Opportunities- related fraud factors
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Technical opportunities
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All the respondents rated the technical opportunities (indicator 1-5) as medium to
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high vulnerability,demonstrated with red (high vulnerable) and orange (medium
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vulnerable) per actor in the table. This is in line with the fact that spices are
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commonly easy to adulterate when they are milled (Everstine, Spink, & Kennedy,
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2013). The technology required for adulteration is generally available and is not
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complex. When the spices are milled with a potential adulterant, the shape is similar
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and detection of adulterant material requires advanced analytical techniques
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(Sasikumar, Swetha, Parvathy, & Sheeja, 2016). One of the reasons why companies
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buy spices from their suppliers in their whole form (not milled) is because they wish to
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ensure that the material is free from adulterants. To the “complexity of counterfeiting”
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indicators, (indicators 6-7) different scores were assigned. Only b2b/b2c (h)
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answered with a score 1 (low vulnerability). However, counterfeiting is a full imitation
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of the genuine product passed off deceptively as genuine. This kind of full
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replacement of spices with other (non) plant-based material is not an issue, only
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partial replacement and mixing.
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Opportunities in time and space
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“Production lines/processing activities” (indicator 8) scored 1 (low vulnerability) for all
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companies, except from trader (a) (medium vulnerable) but all companies have
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specific requirements in terms of food defence. The accessibility should be strictly
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authorised to particular persons to prevent intentionally contamination by people who
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want to do harm (Guide to developing a food defence plan for Food Processing
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Plants, 2008). All participants mentioned that their facilities allow little interference
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and modification between batches and accessibility for unauthorised personnel
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during day and night is not possible. “Transparency chain network” (indicator 9),
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scored 2 (medium vulnerability) by most respondents, because they consider their
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chain to some extent transparent. However, trader(a) and importer(b) – and (c) at the
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beginning of the chain assigned score 3 (high vulnerability), because they perceive
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their supply chain as not being transparent. Transparency in the chain is important,
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because without visibility into the supply chains and due to the dispersed nature of
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today’s supply chains, there are multiple opportunities to commit fraud (Manning &
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Soon, 2014). Supply chain transparency cannot be easily achieved, because it
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requires a solid foundation and continuous improvement over time (Linich, 2014).
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According to Linich (2014), a four-step plan could support in mitigating risks on fraud
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due to lack of chain transparency. This plan includes identifying and prioritizing risks;
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visualizing risks; using transparency levers to close information gaps and managing
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and monitoring resulting information. With respect to “Fraudulent incidences in past”
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(indicators 10-11), only one company b2b (d) assigned a score 1 (low vulnerability).
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All other respondents assigned a score 2 (medium vulnerability), because they
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acknowledged fraudulent incidences that occurred in the past, such as the addition of
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the harmful adulterations with the forbidden colorant Sudan red in capsicum products
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and the peanut-shell in cumin case. Other examples of less harmful adulterations are
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low quality pepper and various kinds of foreign matter in whole or ground pepper,
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and the removal of essential oil in nutmeg (Peter, 2011).
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3.2.2. Motivations-related fraud factors
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Economic drivers
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“Supply and pricing raw materials” (indicator 12) scored 3. It is considered as highly
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vulnerable, because the prices of spices by weight are high compared to other food
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materials and they can vary considerably. It is a seasonal product and the quality is
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affected by multiple factors such as climate, harvesting and large variation is
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common (Hübert, Tiebe, & Banach, 2016). Spices also contain valuable contents
271
such as volatile oils, which are important value determinants. Measuring the volatile
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oil (V/O) helps to identify whether the spice has been adulterated, such as addition of
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foreign materials; addition of low quality materials or addition de-oiled or defatted
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material (spent). Other more spice specific compounds are piperine in black pepper
275
and safranol in saffron (Peter, 2011).The indicator 13 “Valuable components or
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attributes raw materials” scored 3 (high vulnerability) for all actors, because the value
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of the spices is largely determined by the purity. Absence of impurities is a measure
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of the amount of foreign and extraneous matter, for example insect contamination,
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but also product foreign adulterants. Furthermore, geographical origin determines the
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value of spices as well as the type of production system. Organic spices will be
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dearer than spices from the conventional production. For indicator 31”price
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assymetries”, different scores were given because this is dependent on the type of
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spice the company trades.
284
Overall, the level of competition in the spices industry is high (indicator 30), which is
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reflected by the fact that the respondents assigned a score 2 or 3 (medium and high
286
vulnerability). The high competition originates from multiple reasons. There is an
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increase in scarcity of raw materials and suppliers have to comply with strict buyer
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requirements such as, quality, food safety, and traceability (Manning & Soon, 2014).
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Moreover, the market entry requirements are becoming stricter as a result of
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technological advances and food safety scandals. These trends and the rising prices
291
are changing the market place (CBI 2015). Even though the competition is high, the
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respondents rated their “economic conditions own company” (indicator 14) with 1 or 2
293
(low and medium vulnerability). The economic condition of their suppliers is judged
294
as medium vulnerability, except for trader (a), who mentioned that his supplier are
295
primitive farmers and therefore highly vulnerable. The spice sector as a whole it is
296
rated as medium vulnerable as well (indicators 20, 26).
297 298
Culture and behaviour
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“Organizational strategy own company” (indicator 15) and “ethical business culture
300
own company” (indicator 16) were assigned a score 1 (low vulnerability). This is due
301
to the fact that the companies interviewed strive for long-term financial goals and
302
sustainable relationships with their suppliers. However, for the actors in their
303
environmental layer, they assigned a score 1 (low vulnerability) and 2 (medium
304
vulnerability), i.e. for the ethical business culture of the suppliers and sector
305
(indicators 21, 22, 28). None of the companies was involved in criminal offences
306
(indicator 17) with a score 1 (low vulnerability), but interestingly, for the criminal
307
offences of their suppliers and customers (indicators 23, 24, 27) they all assigned a
308
score 2 (medium vulnerability) as they lack concise information. Spice companies
309
commonly operate in and with countries in which the corruption level is high (indicator
310
18 and 25)but whether this is a potential high risk, is dependent on the spice and
311
origin of the spicethe company trades with. More than half of European imports
312
come from developing countries (97% of total imported volume) (CBI: Trends: Spices
313
and Herbs in Europe, 2016). These countries are rated as highly corrupt, based on
314
the Corruption Perception Index, from “Transparency International” (Corruption
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Perceptions Index 2015, 2016). The spice companies give different scores to
316
indicator 29. Criminal offences occurred in the chain according to 5 respondents, but
317
importer (c), b2b (d) and b2b/b2c (h) gave answer 1 ( low vulnerability).
318 319
3.2.3. Control measures related risk factors
320
Hard control measures
321
Measures dedicated to fraud control are not common in the spice industry. “Fraud
322
monitoring system raw materials” (indicator 32) scores range from 1 to 3. The
323
medium and large size companies have raw material controls with fraud monitoring,
324
such as b2b(e),b2b/b2c(f) –and (h) score 3 (low vulnerability), whereas the small
325
companies such as trader(a) and importer(b) score 1 (high vulnerability), because
326
they do not have the money and resources to build a fraud mitigation plan. This is
327
also another explanation of why they show more often high vulnerability in their
328
scores. . According to Professor Elliot from Queens University Belfast - who reviewed
329
the horse meat incident and made recommendations tackling fraud in the Elliot
330
Review for the UK Food Standards Agency - said in an interview with (Levitt, 2016)
331
that smaller businesses do not have the resources to map out dangers of food fraud
332
in their supply chain and says bigger companies should help smaller ones to
333
safeguard consumers. When it comes to adulterations, the difficulty is that offenders
334
are seeking for adulterants that have not been reported so far. Therefore, companies
335
are not conscious of what to find in their product and how to determine the presence
336
of undeclared substances. “Fraud monitoring system final products” and “Systematics
337
and autonomy of verification of fraud monitoring system” (indicator 34, 33, 35),
338
scored 1 (high vulnerability) for most respondents. However, B2b(d) is the exception
339
and has a more dedicated final product fraud monitoring system (low vulnerability).
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Most other companies believe that a final product monitoring system is irrelevant,
341
because it suggests that you doubt the integrity of your product if such a system is in
342
place. This is in agreement with the alien conspiracy theory, which describes that
343
crime is often not perceived as part of the society/environment and shaped by the
344
society itself, but rather a problem of “outsiders” that threaten society (Kleemans,
345
2013). The medium- and large size companies have a comprehensive information
346
system including information on mass balance flows. The same was mentioned for
347
their tracking and tracing system (low vulnerability) (indicators 36, 37). Mass balance
348
traceability is a pre-requisite within the food supply chain for ensuring extrinsic quality
349
(Manning & Soon, 2014). The elementary conditions in which suppliers usually
350
operate, explain the dominant score 1 (high vulnerability) for the indicators “Fraud
351
control system supplier”, ”Mass balance control supplier” and “Tracking and tracing
352
system supplier” (indicators 42, 43, 44). Especially the larger b2b/b2c companies
353
have a fraud contingency plan in place when they suspect fraudulent products of
354
suppliers (indicator 50). The plan involves breach of contract with the supplier.
355 356
Soft controls
357
“Ethical code of conduct own company” (indicator 39) was assigned score 3 (low
358
vulnerability) except for trader(a) (small company), which assigned score 1 (high
359
vulnerability). When present, code-of-conduct rules are advertised in the organisation
360
via brochures and trainings. Scores 1 and 3 (high and low vulnerability) were
361
assigned to “Integrity screening own employees” (indicator 38). A few companies
362
questioned if integrity screening is allowed in terms of privacy regulations. “Whistle
363
blowing own company” (indicator 40), scores varied from 1 to 3 (high, medium and
364
low vulnerability). When employees suspect unethical behaviour and malpractices,
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they should be able to report this to a confidential mediator. A whistle blowing system
366
protects those that accuse. For the companies who have a system, it is usually a
367
dependent person (medium vulnerability). B2b(e) has an independent person (low
368
vulnerability).
369
Food fraud is an issue widely emphasized by governmental and non-governmental
370
institutions that results in strict requirements to which the buyer has to conform (CBI:
371
Trends: Spices and Herbs in Europe, 2016). The indicator (number 41) “Contractual
372
requirements supplier”, which is related to this topic, got a score 3 (low vulnerability)
373
by all the companies with exception of trader(a). For “Social control chain network”
374
(indicator 45) score 2 was assigned (medium vulnerability), which means the
375
enterprises perceive medium social control in the spice chain. Companies indicated
376
that during the European Spice Association (ESA) meetings, companies are warned
377
about fraud and an “adulteration awareness document” has been distributed (ESA,
378
2015).
379
The control measures “Fraud control industry”, “Specificity national food policy” and
380
“Law enforcement chain network” (indicators 46-49) scored 1 (high vulnerability).
381
Even though the ESA provides an adulteration awareness document, there is control
382
by auditing parties on a limited scale. The reason for this is that the interest in
383
tackling food fraud at that level has only recently developed. The interviewees
384
perceived that laws and policies that address particular fraud issues are not actively
385
enforced in their country.
386 387 388 389
3.3. Methodology consideration The SSAFE tool is based on the routine activities theory and is operationalised in grids with qualitative descriptions and assigned scores to enable a differentiated
17
ACCEPTED MANUSCRIPT 390
assessment of the vulnerability inherent to opportunities, motivations, and control
391
measures to mitigate fraud. The outcome of the assessment should be used
392
qualitatively because data uncertainty is common in early stage assessment of
393
vulnerabilities, as emphasized by John Spink who takes COSO concepts into
394
consideration (Spink, Moyer, & Speier-Pero, 2016). The Committee of Sponsoring
395
Organizations of the Treadway Commission (COSO) is an initiative of five private
396
sector organizations (i.e. the institute of internal auditors) and develops frameworks
397
and guidance on enterprise risk management, internal control and fraud deterrence.
398
Furthermore, the tool is initially designed as a self-assessment tool for companies.
399
However, in this research the companies filled in the survey or discussed it in the
400
interview. It is commonly known that in face-to-face interviews, the chance on social
401
desirable answering is high (Bradburn, Sudman, & Wansink, 2004). Especially for
402
sensitive topics as fraud, respondents might have the tendency to answer according
403
to societal norms and answers that will be best valued by the interviewer (Goffman &
404
Edinburgh Social, 1958). However, the decisions—and the data—must be justifiable.
405 406
4. Conclusions and outlook
407 408
The current assessment of the spices chain reveals that the vulnerability to fraud in
409
the chain is overall perceived as medium vulnerable by the various respondents.
410
Technical opportunities and economic drivers scored high vulnerability across the
411
board, opportunities in time and place as well as culture and behaviour related
412
motivations scored medium vulnerable. The control measures varied widely and
413
especially the smaller sized companies in this study lacked control measures. This
414
kind of fraud vulnerability studies allow comparison of the vulnerability of different
18
ACCEPTED MANUSCRIPT 415
supply chains. Furthermore, the fraud vulnerability assessments of individual actors
416
are a solid base for further development of the companies’ fraud mitigation plans.
417 418 419 420
Acknowledgements
421
This research was executed in the framework of the EU-project SPICED (Grant
422
Agreement: 312631) with the financial support from the 7th Framework Programme
423
of the European Union, European Commission - Directorate-General Enterprise &
424
Industry. This publication reflects the views only of the authors, and the European
425
Commission cannot be held responsible for any use which may be made of the
426
information contained therein. Furthermore, authors acknowledge co-financing of the
427
project through the ‘Kennisbasis’ funding programme by the Ministry of Economic
428
Affairs of the Netherlands and financial support of the PhD project by Intertaste, the
429
Netherlands. Authors are grateful to the eight companies for their participation in the
430
assessment
431
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ACCEPTED MANUSCRIPT Table 1. Indicators for the three key elements opportunities, motivations, and control measures and their numbering used in the food fraud vulnerability assessment Opportunities Motivations Control measures 1. Complexity of 12. Supply and pricing raw 31. Price asymmetries adulteration raw materials materials 2. Availability technology 13. Valuable components or 32. Fraud monitoring and knowledge to attributes raw materials system raw materials adulterate raw materials 3. Detectability 14. Economic conditions 33. Verification of fraud adulteration raw materials own company mon. system raw materials 4. Availability technology 15. Organizational strategy 34. Fraud monitoring and knowledge to own company system final products adulterate final products 5. Detectability 16. Ethical business culture 35. Verification of fraud adulteration final products own company monitoring system final products 6. Complexity of 17. Criminal offences own 36. Information system counterfeiting company own company 7. Detectability of 18. Corruption level country 37. Tracking and tracing counterfeiting own company system own company 8. Production lines/ 19. Financial strains 38. Integrity screening processing activities supplier own employees 9. Transparency chain 20. Economic conditions 39. Ethical code of network supplier conduct own company 10. Historical evidence 21. Organizational strategy 40. Whistle blowing own fraud raw materials supplier company 11. Historical evidence 22. Ethical business culture 41. Contractual fraud final products supplier requirements supplier 23. Criminal offences 42. Fraud control system supplier supplier 24. Victimization of supplier 43. Mass balance control. supplier 25. Corruption level country 44. Tracking and tracing supplier system supplier 26. Economic conditions 45. Social control chain sector network 27. Criminal offences 46. Fraud control industry customer 28. Ethical business culture 47. National food policy sector 29. Historical evidence 48. Law enforcement branch of industry local chain 30. Level of competition in 49. Law enforcement sector chain network 50. Fraud contingency plan 432
20
ACCEPTED MANUSCRIPT 433
Table 2.
434
Characteristics of the interviewed enterprises and people Company/
Company Interviewees
Business
size
Trader(a)
small
Head
Importer(b)
small
Head
Importer(c)
large
Vice-president
B2B(d)
medium
Quality manager
B2B(e)
medium
Spices flavourist & MVO coordinator
B2B/B2C(f)
large
Strategic buyer and head of customer quality
B2B/B2C(g) large
Quality manager
B2B/B2C(h) large
Quality manager and director of sustainability
435 436
21
ACCEPTED MANUSCRIPT 437
Table 3
438
Fraud factors inherent to opportunities, motivations, and control measures. The
439
scores for the indicators and actors are presented in Table 2, categorized per actor.
440
“b2b” stands for business-to-business and “b2b/b2c” for a combination of a business-
441
to-business and business-to- consumer enterprise. The mode scores for the low,
442
medium, and high vulnerability situations for the opportunities, motivations, and
443
control measures related indicators are coloured green, orange, and red respectively. Opportunities-related fraud factors
Indicator
(a) trader
(b) importer
(c) importer
(d) b2b
(e) b2b
(f) b2b/b2c
(g) b2b/b2c
Technical Complexity of adulteration Availability technology and knowledge to adulterate Complexity counterfeiting
1,3 2,4,5 6,7
In time and space Production lines /processing activities
8
Transparency chain network
9
Fraudulent incidences in past
10,11
Motivations-related fraud factors Economic drivers Supply & pricing materials Valuable components or attributes raw materials
12
Price asymmetries
31
Level of competition in sector
30
Economic conditions own company
14
Economic condition supplier
20
Economic conditions sector
26
13
Culture and behaviour Organizational strategy own company
15
Organizational strategy supplier
21
Ethical business culture own company
16
Ethical business culture supplier
22
Ethical business culture sector
28
Criminal offences own company
17
Criminal offences supplier
23
Criminal offences customer
27
Corruption level country own company
18
Corruption level country supplier
25
22
(h) b2b/b2c
ACCEPTED MANUSCRIPT Historical evidence branch of history
29
Victimization of supplier
24
Control measures related factors Hard control measures Fraud monitoring system raw materials
32
Fraud monitoring system final products
34
Fraud control system supplier Systematics and autonomy of verification of fraud monitoring system
42 33,35
Information system own company
36
Mass balance control supplier Tracking and tracing system own company
43
Tracking and tracing system supplier
44
Fraud contingency plan
50
37
Soft control measures Ethical code of conduct own company
39
Integrity screening own employees
38
Whistle blowing own company
40
Contractual requirements supplier
41
Social control network
45
Fraud control industry
46
Specificity national food policy Law enforcement chain network
47, 48 49
444 445
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ACCEPTED MANUSCRIPT 446
447 448
Fig. 1
449
Spider web diagrams for opportunities (indicator 1-11), motivations (indicator 12-30),
450
and control measures (indicator 31-50) for scores with highest frequencies
451
(continuous line). In case of identical frequencies for two answers (ties), the second
452
score with highest frequency is presented as well (dashed line). Numbers with
453
corresponding indicators are listed in Table 1.
454
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ACCEPTED MANUSCRIPT 455
References
456 457 458
Avery, J. (2014). Fighting food fraud. European Parliamentary Research Service, 1–7. Retrieved from http://www.europarl.europa.eu/RegData/bibliotheque/briefing/2014/130679/LDM_BRI(2014)130679_REV 1_EN.pdf
459 460
Bradburn, N., Sudman, S., & Wansink, B. (2004). Asking questions: The definitive guide to questionnaire design for market research, political polls, and social and health questionnaires.
461 462 463
BRC Global Standard for Food Safety Issue 7. (2015). Retrieved from http://www.brcglobalstandards.com/Portals/0/library/files/newsletters/BRC Global Standards newsletter February 2015.html
464 465
Capuano, E., & van Ruth, S. M. (2012). QA: Fraud Control for Foods and Other Biomaterials by Product Fingerprinting. In Latest Research into Quality Control. InTech. https://doi.org/10.5772/51109
466 467 468
CBI: Trends: Spices and Herbs in Europe. (2016). The Hague . Retrieved from https://www.cbi.eu/sites/default/files/market_information/researches/trends-europe-spices-herbs2016_0.pdf
469 470 471
CBI Field of Competition: Spices and Herbs. (2015). The Hague . Retrieved from https://www.cbi.eu/sites/default/files/market_information/researches/competition-europe-spices-herbs2015_0.pdf
472 473 474
Cohen, L. E., & Felson, M. (2016). SOCIAL CHANGE AND CRIME RATE TRENDS : A ROUTINE ACTIVITY APPROACH *. Source: American Sociological Review American Sociological Review, 44(4), 588–608. Retrieved from http://www.jstor.org/stable/2094589
475
Corruption Perceptions Index 2015. (2016). Retrieved from http://www.transparency.org/cpi2015
476
DHS. (2015). National Critical Infrastructure Security and Resilience Research and Development Plan.
477 478 479
Drechsler, H., Halff, M., Huisman, P., & Post, F. (2012). Toepassen soft controls: balanceren tussen wens en werkelijkheid. Retrieved October 6, 2016, from http://www.softcontrols.nu/docs/toepassen-soft-controlsbalanceren-tussen-wens-en-werkelijkheid.pdf
480
ESA. (2015). European Spice Association Quality Minima Document, rev 5(December).
481 482 483
Everstine, K., Spink, J., & Kennedy, S. (2013). Economically motivated adulteration (EMA) of food: common characteristics of EMA incidents. Journal of Food Protection, 76(4), 723–35. https://doi.org/10.4315/0362-028X.JFP-12-399
484 485
GFSI. (2014). GFSI position on mitigating the public health risk of food fraud. Retrieved from file:///D:/Thesis/5.Keten studie/References/Food_Fraud_Position_Paper.pdf
486 487
Goffman, E., & Edinburgh Social. (1958). The presentation of self in everyday life. Edinburgh University of Research Centre (Vol. 55). The Overlook Press The Overlook Press.
488 489
Guide to developing a food defence plan for Food Processing Plants. (2008). Retrieved from https://meathaccp.wisc.edu/additional_info/assets/Guide Food Processing.pdf
490 491 492
Haughey, S. A., Galvin-King, P., Ho, Y. C., Bell, S. E. J., & Elliott, C. T. (2015). The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye. Food Control, 48, 75–83. https://doi.org/10.1016/j.foodcont.2014.03.047
493 494
Hübert, T., Tiebe, C., & Banach, U. (2016). Electronic Noses and Tongues in Food Science. Electronic Noses and Tongues in Food Science. https://doi.org/10.1016/B978-0-12-800243-8.00012-3
495 496
Johnson, R. (2014). Food Fraud and “ Economically Motivated Adulteration ” of Food and Food Ingredients. Retrieved from https://www.fas.org/sgp/crs/misc/R43358.pdf
497
Kerney, A. T. (2010). Consumer product fraud: Deterrence and detection.
498 499 500
Kirezieva, K., Jacxsens, L., Uyttendaele, M., Van Boekel, M. A. J. S., & Luning, P. A. (2013). Assessment of Food Safety Management Systems in the global fresh produce chain. Food Research International, 52(1), 230–242. https://doi.org/10.1016/j.foodres.2013.03.023
501 502
Kleemans, E. R. (2013). Theoretical Perspectives on Organized Crime. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199730445.013.005
503
Levitt, T. (2016). Three years on from the horsemeat scandal: 3 lessons we have learned.
25
ACCEPTED MANUSCRIPT 504
https://doi.org/10.1017/CBO9781107415324.004
505 506 507 508
Linich, D. (2014). The path to supply chain transparency: A practical guide to defining, understanding, and building supply chain transparency in a global economy. Retrieved from https://dupress.deloitte.com/content/dam/dup-us-en/articles/supply-chaintransparency/DUP785_ThePathtoSupplyChainTransparency.pdf
509 510 511
Luning, P. A., Bango, L., Kussaga, J., Rovira, J., & Marcelis, W. J. (2008). Comprehensive analysis and differentiated assessment of food safety control systems: a diagnostic instrument. Trends in Food Science and Technology, 19(10), 522–534. https://doi.org/10.1016/j.tifs.2008.03.005
512 513 514 515
Luning, P. A., Jacxsens, L., Rovira, J., Osés, S. M., Uyttendaele, M., & Marcelis, W. J. (2011). A concurrent diagnosis of microbiological food safety output and food safety management system performance: Cases from meat processing industries. Food Control, 22(3–4), 555–565. https://doi.org/10.1016/j.foodcont.2010.10.003
516 517 518
Luning, P. A., Marcelis, W. J., Rovira, J., Van der Spiegel, M., Uyttendaele, M., & Jacxsens, L. (2009). Systematic assessment of core assurance activities in a company specific food safety management system. Trends in Food Science & Technology. https://doi.org/10.1016/j.tifs.2009.03.003
519 520
Manning, L., & Soon, J. M. (2014). Developing systems to control food adulteration. Food Policy, 49, 23–32. https://doi.org/10.1016/j.foodpol.2014.06.005
521 522 523
Moore, J. C., Spink, J., & Lipp, M. (2012, April). Development and Application of a Database of Food Ingredient Fraud and Economically Motivated Adulteration from 1980 to 2010. Journal of Food Science. https://doi.org/10.1111/j.1750-3841.2012.02657.x
524 525
Morling, A., & McNaughton, R. (2016). A 2016 Baseline FOOD CRIME ANNUAL STRATEGIC ASSESSMENT. Retrieved from https://www.food.gov.uk/sites/default/files/fsa-food-crime-assessment-2016.pdf
526 527 528
Moyer, D. C., DeVries, J. W., & Spink, J. (2016). The economics of a food fraud incident – Case studies and examples including Melamine in Wheat Gluten. Food Control. https://doi.org/10.1016/j.foodcont.2016.07.015
529 530
Peter, K. V. (2011). Handbook of herbs and spices (1st ed., p. 319). Cambridge: Woodhead Publishing Limited. Retrieved from http://vanveenorganics.com/ebooks/Herbs. Handbook of Herbs and Spices Vol 1.pdf
531 532 533
Pustjens, A. M., Weesepoel, Y., & van Ruth, S. M. (2016). Innovation and Future Trends in Food Manufacturing and Supply Chain Technologies. Innovation and Future Trends in Food Manufacturing and Supply Chain Technologies. https://doi.org/10.1016/B978-1-78242-447-5.00001-0
534 535 536
Sampers, I., Jacxsens, L., Luning, P. A., Marcelis, W. J., Dumoulin, A., & Uyttendaele, M. (2010). Performance of food safety management systems in poultry meat preparation processing plants in relation to Campylobacter spp. contamination. Journal of Food Protection, 73(8), 1447–1457.
537 538 539
Sasikumar, B., Swetha, V. P., Parvathy, V. A., & Sheeja, T. E. (2016). 22 – Advances in Adulteration and Authenticity Testing of Herbs and Spices. In Advances in Food Authenticity Testing (pp. 585–624). https://doi.org/10.1016/B978-0-08-100220-9.00022-9
540 541 542
Sayers, R. L., Gethings, L., Wallace, A., Semic-Jusufgic, A., Simpson, A., Barran, P., … Mills, E. N. C. (2016). How Much of a Problem Is Peanut in Ground Cumin for Individuals with Peanut Allergy? Journal of Allergy and Clinical Immunology, 137(2). https://doi.org/10.1016/j.jaci.2015.12.597
543 544 545
Schaarschmidt, S. (2016). Public and private standards for dried culinary herbs and spices—Part I: Standards defining the physical and chemical product quality and safety. Food Control, 70, 339–349. https://doi.org/10.1016/j.foodcont.2016.06.004
546 547
Spink, J., & Moyer, D. C. (2011a). Backgrounder: Defining the Public Health Threat of Food Fraud. Retrieved from http://foodfraud.msu.edu/wp-content/uploads/2014/07/food-fraud-ffg-backgrounder-v11-Final.pdf
548 549
Spink, J., & Moyer, D. C. (2011b). Defining the Public Health Threat of Food Fraud. Journal of Food Science, 76(9), R157–R163. https://doi.org/10.1111/j.1750-3841.2011.02417.x
550 551
Spink, J., Moyer, D. C., & Speier-Pero, C. (2016). Introducing the Food Fraud Initial Screening model (FFIS). Food Control, 69, 306–314. https://doi.org/10.1016/j.foodcont.2016.03.016
552 553
van Ruth, S.M., Huisman, W., & Luning, P.A. (2017). Food fraud vulnerability and its key factors. Trends in Food Science and Technology, submitted.
554
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