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Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned

“Support to the development of geographical

indications in the Bursa region, Turkey and the

promotion of local exchange of lessons learned”

Product Selection Report

BURSA - 2016


Contents

TABLES ..................................................................................................................................................... 2

INTRODUCTION ....................................................................................................................................... 3

METHOD USED IN PRODUCT SELECTION ............................................................................................... 6

1. SIMPLE SCORING ......................................................................................................................... 7

2. ANALYTIC HIERARCHY PROCESS ................................................................................................. 9

3. Geographical Indication Assessment Form .............................................................................. 15

GENERAL EVALUATION ......................................................................................................................... 15

REFERENCES .......................................................................................................................................... 17

ANNEX 1. Geographical Indication Assessment Form ......................................................................... 18

TABLES Table 1. General Data and Information of Products ............................................................................... 5

Table 2. Average Scores of Products According to Simple Scoring ......................................................... 9

Table 3. Ranking of simple scoring .......................................................................................................... 9

Table 4. Criteria Weights ....................................................................................................................... 13

Table 5. Assessment of alternatives together with criteria weights ..................................................... 14

Table 6. Total Scores of Products According to AHP Method ............................................................... 14

Table 7. Scores According to Geographical Indication Assessment Form ............................................ 15

Table 8. Assessment Results .................................................................................................................. 16


“Support to the development of geographical indications in the Bursa region, Turkey and the

promotion of local exchange of lessons learned” Product Selection Report

INTRODUCTION Geographical indications are considered as an important means for regional or local development

throughout the world and especially in European Union Countries. Generally, a region or an area has

more than one local product, however, these local products have different advantages or

disadvantages in the registration phase of geographical indication. While some products have more

positive criteria in order to possess the geographical indication and to benefit from this geographical

indication; others don’t. Therefore, selection of the product that will be the subject of geographical

indication in a certain region becomes an issue to put emphasis on.

The number of scientific sources in relation to the selection of local products to be commercialized is

very limited today. Two of the most important studies among these are the studies of Barjolle et al.

(2009) and Bramley and Biénabe (2013). In both studies, objective and subjective data were used to

work on local products with a high potential of being successful. Barjolle et al. considered criteria such

as, comparison of the position of the product before and after geographical indication protection, costs

during the registration phase of geographical indications, added value that may be obtained from the

product, income earned by each actor in the supply chain of product with and without geographical

indication protection, environmental impacts of products with and without geographical indication

protection etc. as objective (quantitative) methods. However, this study is limited as an impact

assessment for regions that have already obtained geographical indication and have been using this

geographical indication for a certain period. Barjolle et al. made use of scales such as benchmarking

and likert scale for subjective criteria; in other words they drew analogies by reviewing successful

examples and digitized their meetings with the producers of local products and relevant institutions

using various scales. Barjolle et al. defined 3 basic levels for successful geographical indication practices

and product selection; and made assessments on the basis of the criteria they find important for each

level;

Economic Level Social Level Environmental Level

Stabilization of markets and/or increase in market share

Local employment Native races and varieties

Price increase Producers’ power /

competence Extensive cultivation

Creation of added value for the region

Cultural values and traditions

Natural resources

Bramley and Biénabe defined the following as the most important criteria for product selection;

Product characteristics, that are specific to a region, being dominant (distinctive properties)

Product’s recognition/reputation throughout the country or the world


Existence of organizations that bring producers together and ensure their collaboration

Existence of an umbrella organization that will support and coordinate studies regarding local

products

Attraction of markets in relation to local products and properties of the supply chain

Structure of producers (traditionalism, being innovative etc.)

Environmental impacts.

It was necessary to use a combination of qualitative (subjective) and quantitative (objective) data for

product selection because, data regarding local products were insufficient and standard data could not

be obtained for each product.

Qualitative data were obtained as a result of site meetings; from face to face meetings held with the

officials of institutions and organizations related to local products

Primarily, products that possess the characteristics of a local product were determined for Bursa

region. These products are listed as follows;

Bursa Peach

Bursa Deveci Pear

Candied Chestnut

Mihaliç Cheese

Bursa Black Fig

Hasanağa Artichoke

Ürünlü Pepper

Bursa Wild Strawberry

Yenişehir Pepper

Müşküle Grapes

Ovaazatlı Pepper

There are also products that are already registered and that are in the registration phase as local

products of Bursa region. These are;

Gemlik Olives

İnegöl Meatballs

Karacabey Onion

Bursa Knife

Bursa Silk

Gemlik Horse

During product selection, a pre-selection was performed as a first stage by considering the “reputation

of the product” and “region-specific” characteristics that are very important in terms of geographical

indication as well as the existing legal regulations. The mentioned assessments are shown in Table 1.


Table 1. General Data and Information of Products

Quantitative Data (2015) 1= yes 0 = no General Information and Assessment

Local Products Production Amount (tons)

Export Amount (tons)

Export Value (000 USD)

Local Variety

Existence of Organizations

Harvest Period Other important factors Potential GI Type

Bursa Peach 86 428 687 797 1 1** July - September Low resistance PDO

Bursa Deveci Pear 173 550 1 612 1 028 0 1 October -November Too many chemicals are used, MRL problem for export, Variety name problem

PDO

Bursa Black Fig 22 541 7 708 20 396 1 1 August - September Variety name problem PDO

Candied Chestnut * * * 0 No region-specific characteristics PGI

Mihaliç Cheese * * * 0 No region-specific characteristics PGI

Hasanağa Artichoke 2 449 * * 1 1** Reputation limited to the region PDO

Ürünlü Pepper 1 910 * * 1 1** Reputation limited to the region PDO

Bursa Wild Strawberry * * * 1 0 Reputation limited to the region, Low production amount

PDO

Trilye Olive 16 415 * * 1 1 September -December Synonym of the registered Gemlik Olives, application denied before by TPI

PDO

Yenisehir Pepper 45 152 * * 1 1** July - October Reputation limited to the region PDO

Müşküle Grapes 7 000 * * 1 1** July - August Reputation limited to the region, Low production amount

PDO

Ovaazatlı Pepper * * * 1 1** July - October Reputation limited to the region PDO

* Data not found

** Organization is not directly related to the product and generally structured as an agricultural development cooperative and works in relation to

several products.


Assessments made using subjective and objective data are not solely sufficient for the selection of local

products. In the meantime, structure of markets, competitive properties, consumer expectations,

estimation of product’s progress in time based on the current status of the product, saturation of the

market and such factors should also be taken into account. Even though numerical values offer an

insight to product selection, they should also be evaluated in conjunction with other factors.

Products, whose reputation is limited to the region and products that have a very low production

amount; Hasanağa Artichoke, Ürünlü Pepper, Bursa Wild Strawberry, Yenisehir Pepper, Müşküle

Grapes and Ovaazatlı Pepper were left out of the assessment. The mentioned products are generally

known within the city and don’t have a certain reputation within the country. In addition, their

production amount is low enough to significantly reduce the chances of commercialization. Those

products aren’t exported either. Trilye Olive, among local products, is another name for Gemlik Olive

that has already obtained geographical indication protection in 2003. Geographical indication

application was made for Trilye Olives in the past but it has been rejected by Turkish Patent Institute

(TPE) (Gonenc 2006). The products listed below, have been analyzed in more detail after pre-selection.

Gemlik Olive, that is already registered, was included in the assessment as control group.

Bursa Peach

Deveci Pear

Bursa Black Fig

Candied Chestnut

Mihaliç Cheese

Gemlik Olives

METHOD USED IN PRODUCT SELECTION The fact that, data related to local products is very limited and many products don’t have data although

some do; makes it necessary to turn qualitative data into quantitative data during the phase of product

selection and classification. Turning qualitative data into quantitative data is a frequently used

scientific method in social research and when data is insufficient (Dey, 2005; Driscoll et al. 2007; Srnka

and Koeszegi, 2007; Abeyasekera, 2015). A combination of methods that can express qualitative data

as quantitative data was used because, data for the selection of local products to apply for

geographical indication were insufficient and standard data could not be obtained for each product.

The following methods were used within this scope. Application of each method is briefly explained.

1. Simple scoring

2. Analytic Hierarchy Process


3. Geographical Indication Assessment Form

1. SIMPLE SCORING

In scoring; Likert scale, Hedonic scales and Stapel scale are the most frequently used scales (Green, Tull

and Albaum, 1988; Crimp, 1990). Since Likert and Hedonic scales are generally used to indicate

judgment, (I agree – I don’t agree etc.), “Stapel Scale” that is characterized as more suitable in terms

determining ratings was used in this study. Stapel scale is a continuous and multi-item scale, wherein

the respondent indicates the most suitable assessment between two extreme values based on his/her

knowledge, experience and judgment. The mentioned assessment is made for more than one criterion

on the same subject. Scales may involve even or odd numbered categories. In odd numbered

categories, a mid-point indicates indecision or neutrality. On the contrary, in even numbered

categories researchers force respondents to pick a side (Green, Tull and Albaum, 1988; Büyükyılmaz,

2015).

Stapel scale was preferred in the project, since respondents were requested to indicate a magnitude

rather than judgment. Moreover, even numbered categories were selected so as to determine the

indecision of persons regarding each local product.

WEAK STRONG

4 main criteria were used in evaluating local products from various aspects.

Characteristics due to the region (Specificity)

Reputation of the product

Power of the organization

Marketing potential

Sustainability

Export Potential

Income Generation Potential

Weights were scaled between 0-4 by giving maximum 4 points to the “most important” criterion.

Characteristics due to the region (Specificity): In case a product can be produced outside its territory

(or region) without losing its characteristics, its contribution to Bursa City will be limited or inexistent.

Moreover, if it has the same quality when produced outside its territory, then its characteristics are

not specific to the region and naturally it will not be a subject of geographical indication.

Reputation of the product: The fact that local products are known within their territory does not have

much of a meaning alone. It is very important during commercialization process that the population

living outside the city/region knows these products. Primarily, products should be known along with

0 1 2 3 4


their region, should be put to use in a high-quality manner, should be positioned differently as

compared to its peers and should be known by a wide range of consumers.

Power of the Institution/Organization: For each product, the existence of an organization that will

protect the quality and producers of the product, conduct marketing studies and lead all kinds of

studies in relation to the product is significantly important so as to place the product in markets and

ensure its sustainability. However, existence of an institution or organization in relation to the local

product is not a criterion that is sufficient alone. It is also very important that this

institution/organization is powerful and works effectively. Herein “powerful institution/organization”

means institutions/organizations with strong capital and management structure, that possess or can

access financial funds to conduct various activities and that employ professional staff.

Marketing Potential: Although local products are not generally produced in high volumes, it is

important that the produced amount is a marketable amount, that the product is perceived to be a

high-quality one by consumers, that there is consumption of the product and marketing mixes such as

promotion, price and publicity are usable.

Sustainability: Sustainability includes not only the sustainability of production but also the

sustainability of production technique and production against the market conditions. In other words,

this criterion also shows environmental, economic and social sustainability.

Export Potential: Criteria such as export amount, value and export opportunities also gain importance

in order to take the value of local products out of the country and increase the added value to be

obtained from this product.

Income Generation Potential: Regardless of how featured the local product is, its effect in developing

the region would be weak as long as it doesn’t have a certain income generation potential. Therefore,

this criterion should also be considered.

Six local products considered for product selection were scored by various experts throughout the city

according to the above-mentioned criteria. The mentioned experts include 2 academicians who have

especially worked on local products, two experts who work at TÜBİTAK (The Scientific and

Technological Research Council of Turkey) and who also have prepared a project on local products and

geographical indications as well as officials from Bursa Governor’s Office and BTSO (Bursa Chamber of

Commerce and Industry).

Average scores are obtained after scoring. Average score of each product according to different criteria

are shown on Table 2.


Table 2. Average Scores of Products According to Simple Scoring

Characteristics due to the region (Specificity)

Reputation of the product

Power of the organization

Marketing Potential

Sustainability Export Potential

Income Generation Potential

Bursa Peach 3,33 3,67 1,67 3,67 2,67 3,67 2,67

Deveci Pear 2,75 3,50 2,50 3,75 2,75 2,50 2,75

Bursa Black Fig 3,75 4,00 1,75 4,00 3,25 4,00 3,50

Candied Chestnut 0,67 4,00 0,00 3,67 3,33 3,83 3,17

Mihaliç Cheese 2,00 2,50 0,00 2,75 2,25 1,00 2,50

Gemlik Olives 4,00 4,00 3,67 3,67 4,00 1,67 3,67

Ranking of the products according to the results of total scores from simple scoring (Table 3);

Table 3. Ranking of simple scoring

Simple scoring

Gemlik Olives 3,52

Bursa Black Fig 3,46

Bursa Peach 3,05

Deveci Pear 2,93

Candied Chestnut 2,67

Mihaliç Cheese 1,86

In the selection performed using this method, Gemlik Olive, which is already registered, obtained the

highest score. It is observed that Bursa Black Fig and Bursa Peach are the first two products with priority

for selection not including Gemlik olives.

2. ANALYTIC HIERARCHY PROCESS

The method of simple scoring assumes that all criteria have the same weight. However, the importance

of each criterion is different. Therefore, above-mentioned simple scoring should be weighted and

superior characteristics of each product compared to its peers should be evaluated separately

according to each criterion. For this reason, the method of Analytic Hierarchy Process was applied in

order to determine the weights of criteria and make pairwise comparisons of products for each

criterion.

AHP was first suggested by Myers and Alpert in 1968, developed by Prof. Dr. Thomas L. Saaty in 1970s

and turned into a model in 1977. AHP was published in 1980s and used in many subjects as a multi-

criteria decision-making method. AHP has been successfully applied in many fields from making


investment decisions in the private sector to the selection of government policies and scientific

research until today (Özden, 2008; Saaty, 2008; Haas and Meixner 2009; Ömürbek and Tunca 2013).

AHP is one of the multi-criteria decision-making methods. AHP is a measurement theory based on

pairwise comparison of alternatives according to a common criterion. A multilevel hierarchical

structure of objectives, criteria, possible subcriteria and alternatives is used for each problem in

Analytic Hierarchy Process (Ömürbek and Tunca 2013). AHP obtains priorities from judgements of

pairwise comparisons of decision-related items according to the item of the higher level (Topçu, 2001);

Pairwise comparison judgements are input to a matrix

Priorities are obtained by calculating the highest eigenvector of the matrix

In the meantime, inconsistencies in judgements are also calculated

Solution steps of AHP are shown below.

Importance scale used in AHP is as follows;

OBJECTIVE

CRITERIA

ALTERNATIVES

Definition of the

Problem Definition of Criteria

Calculating the

Percent (%) Weight

of Criteria

Pairwise Comparisons

of Criteria Determination of

Intensity of Importance

Determination of

Alternatives

Constructing the

Hierarchical Structure

Performing the

Consistency Analysis

Calculating the Intensity

of Importance for

Alternatives

Selection of the

Alternative with the

Highest Intensity of

Importance


Intensity of Importance Conceptual Explanation

1 3 5 7 9 Activities are of equal importance / there is no judgement about any of them

1 3 5 7 9 The first activity is slightly important / favored compared to the other one

1 3 5 7 9 The first activity is more important / favored compared to the other one

1 3 5 7 9 The first activity is much more important / favored compared to the other one

1 3 5 7 9 The first activity is extremely important / favored compared to the other one

2 4 6 8 Intermediate values

There are n(n+1)/2 comparisons in a decision process with n criteria. Decision matrix;

jth criterion

Criterion 1 Criterion 2 Criterion 3 Criterion (n)

İth c

rite

rio

n

Criterion 1

Criterion 2

Criterion 3

Criterion

(n)

When aij denotes the intensity of importance of the ith criterion and the jth criterion, the pairwise

comparison matrix is as follows.

A = [

a11 a12 . . a1n

a21 a22 . . a2n

. . . . .an1 an2 . . ann

]

Due to the reciprocity rule, lower side of the diagonal of the matrix is denoted as aji=1/aij.

After the matrix is completed, values of the A matrix are normalized. More than one method can be

used in the normalization stage. The most commonly used method is diving each element in a column

by the sum of that column;

bi= ∑ ai1ni=1

(1)

Elements of the pairwise comparison matrix are divided by the total value of their column, using the

formula below;


cij=

aij

bi

(2)

This way, a nxn-dimension C matrix consisting of cij elements is obtained;

C = [

c11 c12 . . c1n

c21 c22 . . c2n

. . . . .cn1 cn2 . . cnn

] (3)

The formula given below is used to obtain the percent weights of criteria relative to each other;

wi = ∑ cij

nj=1

n (4)

Arithmetic mean of the row elements constituting matrix C is calculated and then, W column vector is

calculated.

W= ||

w = c11+ c12+⋯+ c1n

n

w = c21+ c22+⋯+c2n

n

w = cn1+ cn2+⋯+cnn

n

|| = [

w1

w2

.wn

] (5)

Success of AHP method results depends on the consistency between pairwise comparisons of decision

makers. Therefore, a consistency analysis is performed after the calculation of matrix C. Consequently,

consistency vector CR is calculated as follows;

In order to calculate CR, D column vector should be obtained and then eigenvector and consistency

indicator (CI) should be obtained.

D = [

a11 a12 . . a1n

a21 a22 . . a2n

. . . . .an1 an2 . . ann

] x [

w1

w2

.wn

] = [

d1

d2

.dn

] (6)

Eigenvector (e) related to each assessment criteria is calculated by dividing the corresponding

elements of D column vector and W column vector.

ei = di

wi (i = 1, 2, …, n) (7)

A base value (λ) is calculated by arithmetic mean of eigenvector values;

λ = ∑ ei

ni=1

n (8)


CI = λ−n

n−1 (9)

After CI value is calculated, this value is divided by the Random Index (RI) value developed by Saaty

and others, who developed the AHP analysis method.

CR = CI

RI (10)

The acceptable upper limit for consistency is 0,10. Criteria above this value are considered inconsistent

and not included in the study or reviewed once more.

In the stage after normalization of matrix A, weights defined for each criterion are weighted using

qualitative or quantitative data on hand; and each alternative is evaluated according to its scores. The

alternative/alternatives with the highest score/value is selected.

Criteria weights after the

assessment are shown on

Table 4;

Table 4. Criteria Weights

Criteria Criteria Weights

During the application of the AHP method, weights of criteria were

determined primarily. Within this scope, first of all a “Criteria

Importance Matrix” was prepared using the 7 criteria in site

meeting forms. Subsequently, experts who could prioritize the

determined criteria in accordance with the main objective of

commercialization of local products were selected. 10 people were

selected and they were asked to fill out an empty criteria

importance matrix. Criteria importance values in criteria

importance matrices filled out by experts and AHP weight

calculation formulas were used to calculate the weights (on the

basis of 1) given to each criterion by each expert. Then a

“Consistency Ratio” was calculated for each expert’s assessment.

For expert assessments with consistency rates that were higher

than 0,10, which is the acceptable upper limit in the AHP method;

relevant persons were asked to fill the criteria importance matrix

again. After these steps, criteria importance assessments of 5

experts, who satisfied the consistency upper limit 0,10, were taken

into account. Finally, “Geometric Mean” of criteria importance

assessments that satisfied the consistency upper limit was

calculated; and final criteria weights (on the basis of 1) were

determined by re-calculating AHP criteria weights for mean

values.)

Determination of Criteria

Creation of Criterion

Importance Matrix

Selection of Experts

Filling the Criterion

Importance Matrices

Calculation of Criteria

Weights

Conducting Consistency

Tests

Calculation of Geometric

Mean

Calculation of Final Criteria

Weights


Reputation of the product 0,242

Power of organization 0,215

Characteristics due to the Region

(Specificity) 0,196

Sustainability 0,101

Marketing Potential 0,099

Export Potential 0,099

Income Generation Potential 0,047

As per the assessment, the most important criteria have been shown to be the reputation of the

product and the power of organization.

After criteria weights are determined by the AHP method, importance matrix was created separately

for each product according to criteria to obtain the following (Table 5);

Table 5. Assessment of alternatives together with criteria weights

CR

ITER

ION

ALTERNATIVES CRITERION WEIGHTS

Bursa Peach

Deveci Pears

Bursa Black Fig

Candied Chestnut

Mihalic Cheese

Gemlik Olive

Specificity 0,125 0,125 0,229 0,026 0,027 0,467 0,196

Reputation 0,215 0,062 0,230 0,236 0,032 0,226 0,242

Pow. Of Org 0,157 0,175 0,146 0,026 0,026 0,470 0,215

Mar. Potantial 0,058 0,109 0,287 0,261 0,038 0,246 0,099

Sustainability 0,052 0,054 0,110 0,282 0,226 0,276 0,101

Exp. Pot 0,121 0,048 0,411 0,338 0,026 0,057 0,099

Inc. Gen. Pot 0,031 0,054 0,188 0,416 0,126 0,184 0,047

TOTAL 0,135 0,101 0,221 0,175 0,054 0,314

According to the AHP assessment, product ranking from the highest total score to the lowest is given

in Table 6;

Table 6. Total Scores of Products According to AHP Method

Products Total AHP Score


Gemlik Olive 0,314

Black Fig 0,221

Candied Chestnut 0,175

Bursa Peach 0,135

Deveci Pears 0,101

Mihalic Cheese 0,054

Gemlik Olive is again the first ranking product according to AHP method. It is followed by Bursa Black

Fig and Candied Chestnuts.

3. Geographical Indication Assessment Form

Another assessment was prepared in order to measure the knowledge of relevant producers and

actors in the industry in relation to their product and their willingness to own their product. The

mentioned geographical indication assessment form is given in Annex 1. The form was filled exclusively

for each product by meeting with producers, companies, academicians, and cooperative officials

working in relation to the production of the product. Meetings were held with 12 persons in total.

Result obtained by summing the scores is given in Table 7;

Table 7. Scores According to Geographical Indication Assessment Form

Product Total Score

Gemlik Olive 108

Black Fig 94

Bursa Peach 83

Mihalic Cheese 77

Deveci Pears 76

Candied Chestnut 70

Gemlik Olive again has the highest score in this assessment. It is followed by Bursa Black Fig and Bursa

Peach. During the meetings it was observed that some companies showed a very weak approach

towards geographical indication and low willingness to own the product especially for candied

chestnuts. Some companies do not seem to intend to be a part of a group that has the relevant

geographical indication. In addition, a direct link between the geographical area and the product could

not be established for Mihaliç Cheese and Candied Chestnuts. Producers of candied chestnuts as well

as Mihaliç cheese both indicated that these products became famous in their region and the

production technique was shaped within the region, however the same product could be produced

with the same quality in other parts of the country.

GENERAL EVALUATION Results of assessments made using three different methods are shown collectively on Table 8;


Table 8. Assessment Results

Simple Score AHP GI Assessment

Gemlik Olive 3,52 Gemlik Olive 0,31 Gemlik Olive 108

Black Fig 3,46 Black Fig 0,22 Black Fig 94

Bursa Peach 3,05 Candied Chestnut 0,18 Bursa Peach 83

Deveci Pears 2,93 Bursa Peach 0,14 Mihalic Cheese 77

Candied Chestnut 2,67 Deveci Pears 0,10 Deveci Pears 76

Mihalic Cheese 1,86 Mihalic Cheese 0,05 Candied Chestnut 70

As a result of all the analyses, the first ranking product other than Gemlik Olive is “Bursa Black Fig”.

The second highest-ranking product is “Bursa Peach” in all methods except for AHP method. Due to

the fact that candied chestnuts especially do not have a distinctive property, in other words they don’t

have a quality element specific to the region, and that producers do not really intend to take place

within the geographical indication system; it was found suitable to select “Bursa Peach” as the second

product.


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https://ozanbuyukyilmaz.files.wordpress.com/2015/02/8-hafta.pptx


ANNEX 1. Geographical Indication Assessment Form

Criteria GI project assessment weak

strong

0 1 2 3 4 REPUTATION

LOCAL REPUTATION

Do we have relevant information to claim that the product has some reputation at local level?

REGIONAL REPUTATION

Do we have relevant information to claim that the product has some reputation at regional level?

NATIONAL REPUTATION

Do we have relevant information to claim that the product has some reputation at national level?

INTERNATIONAL REPUTATION

Do we have relevant information to claim that the product has some reputation at international level?

On which criteria is based this reputation? (taste, color, traditional product, …) SPECIFICITY

DESCRIPTION OF THE PRODUCT

Can the involved people in the product process name the product?

Can we get from people involved in the production process a clear description of the product?

Is the description complete?

Do they know if some imitation of the product exists?

PRACTICES

Can we have a clear description of the agricultural practices?

Do some practices seem to be adequate and adapted to the product?

Are they (people involved in the commodity chain) able to describe the technological characteristics of the production system?

PRACTICE IMPACT

Do the local practices improve social issues?

Do the local practices enhance sustainability of the production? AREA OF PRODUCTION

DEFINED AREA

Can the people involved in the production process describe an area of production?


Can we define such area with other tools easily available? (studies, administrative boundary, soil characteristics…)

QUALITY MANAGEMENT

QUALITY ASSESSMENT

Are the people involved in the commodity chain aware of the quality criteria?

Do they define easily what is the quality of their product? Is their definition relevant?

EXPERIENCE

Do the people involved in the commodity chain already implement a quality management?

Which one? (ISO 9000, good practices, HACCP,…)

Are they compliant with the basic food safety rules? COLLECTIVE COMMITMENT

ASSOCIATIVITY

Are the people involved already members of a cooperative (or other collective organization)?

YES: Does the membership imply a strong commitment? (compulsory contribution, providing input, advices…)

NO: Do they consider possible of be part of a group with common production rules?

Are they ready to support a collective action?

Are they ready to contribute to a group to promote and protect their product?

Does some transformer or distributor agree to incentive the commodity chain organization?

CONTROL

In case of incompliance with the group rules, do involved people risk a sanction?

If it isn't the case, are they ready to accept a sanction system in case of infringement of the GI rules?

PROJECT

Do the involved people met during this inquiry show a great interest in GI project?

Is the product part of commodity chain involving all relevant partners?

Are producer, processors, dealers part of a possible commitment to consider a GI?

Knowing the GI concept, are the involved people voluntary

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