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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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
“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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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.
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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.
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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.
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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;
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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)
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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;
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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.
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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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
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?
Support to the development of geographical indications in the Bursa region, Turkey and the promotion of local exchange of lessons learned
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
0 0 0 0 0