INNOVOIL “Implementation of an innovative protocol for the valorisation of extra virgin olive oil”
REGIONAL UNIT OF THESPROTIA (P6)
MARKET RESEARCH STATISTICAL ANALYSIS
April 2014
European Territorial Cooperation programme Greece - Italy 2007-2013
Table of contents MARKET RESEARCH DELIVERABLE CONTENTS ...... 4 1 REGIONAL INNOVATION PERFORMANCE AND POTENTIAL ...... 6 2 Olive Oil Quality Determination criteria and results ...... 11 2.1 Quality Criteria ...... 11 2.2 Classification of the results ...... 16 3 Market research analysis survey ...... 17 3.1 Survey analysis overview ...... 17 3.2 Sampled Population size...... 18 3.3 Random simple samples ...... 19 3.4 Sampling planning and implementation stages ...... 19 3.5 Simplifications and modifications performed ...... 21 1 Personal/Demographic details...... 22 1.1 Area of Residence ...... 22 1.2 Age Distribution of Participants ...... 24 1.3 Gender distribution of the sampled participants ...... 25 1.4 Marital Status Distribution ...... 26 1.5 Number of children per family ...... 27 2 Type of oil and/or fat usually utilized ...... 28 3 Olive Oil Procurement frequency Distribution ...... 29 4 Quality of Olive Oil procured distribution ...... 32 5 Quantity of Olive Oil monthly consumed ...... 33 6 Preferable Container Volumes ...... 34 7 Preferable material type of container ...... 36 8 Procurement of organic products ...... 37 9 Determination of Olive Oil Choice factors ...... 38 10 Product label reference ...... 40 11 Most significant label information ...... 41 12 Packaging Significance for product procurement ...... 43 13 Most important packaging detail ...... 44 INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 2 of 53
14 Significance of packaging vs price ...... 45 15 Best packaging material decision factors ...... 46 15.1 Best packaging material for olive oil ...... 47 15.2 Color determination factors ...... 48 4 DERIVED CONCLUSIONS ...... 50
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MARKET RESEARCH DELIVERABLE CONTENTS
Abstract
In order to provide a brief spherical statistical background of the current profile of the Region of Epirus which is participating in the INNOVOIL project related with its performance and potential, as well as, in order to provide a brief analysis of the procedures necessary to be followed for the classification of the olive oil in one of the three commonly used categories i.e., extra virgin oil, virgin oil and lampante, this deliverable together with the market research analysis consisting the final part, has been duly arranged in the following three sections:
Section 1: Regional Innovation Performance and potential. This brief report provides a short presentation of the Region of Epirus in terms of innovation performance and potential capabilities.
Section 2: Olive Oil Classification criteria and procedures. Briefly describes the procedures, quality criteria and final results necessary to classify olive oil in one of the existing qualitative categories. This statistical analysis is regarded as a prerequisite, necessary for the understanding of the statistical results obtained through the market research analysis and the conclusions drawn.
Section 3: Market research statistical analysis. This section consists of the Market research analysis and results, based on an approved common among the project partners questionnaire, related with the qualitative considerations and packaging criteria utilized for the procurement of extra virgin olive oil from the local market.
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SECTION 1
1 REGIONAL INNOVATION PERFORMANCE AND POTENTIAL
Located in Northwest Greece, Epirus is a mountainous, sparsely populated (39.4 inh/km2) and relatively isolated region accounting for only 3% of the Greek population (336,650 inhabitants). The region has suffered from emigration and there are significant disparities between rural and urban areas. The regional capital, Ioannina, accounts for nearly a third of the population.
Epirus is the poorest Greek region with a regional GDP per capita (in PPS)1 of €15,300 in 2009, 65% of the EU27 average, making. The region has been hard hit by the economic crisis: unemployment rose to 16.7% in 2011 up from 9.9% in 2008. The educational level is relatively low: only 23.3% of the population aged 25-64 have completed tertiary education (25.4% in Greece, 26.8% in EU27), although Epirus is ranked 4th out of the Greek regions. This is allied to a low and declining level of lifelong learning (but this is similar to the national trend) with only 2.5% of adults aged 25-64 participating in education and training (Greece 2.9%, EU27 9.4%).
A 2007 technology foresight exercise (as part of an ERDF co-financed Regional Programme of Innovative Actions) identified a number of drivers for improving competitiveness: the major infrastructure projects (the Egnatia and Ionian Roads, Igoumenitsa port, expansion of the Ioannina University, the technology park, etc.) combined with emerging sectors such as eco-tourism, for which the region has a natural competitive advantage2, provide a basis for future development.
Although traditionally a rural economy, the importance of the agricultural sector has declined to only 6.3% of regional GDP over the past decade, with a slight upturn between 2008 and 2009. While the rugged landscape makes agriculture difficult, sheep and goat herding are important and Epirus provides more than 45% of meat to the Greek market and is home to a number of
1 All data provided is sourced from Eurostat unless stated otherwise. 2 The flora in Epirus is one of the richest in Greece, due both to its diversity, and the presence of rare species. It also has the highest rainfall of all Greek regions and significant water resources. The mountainous area, dominated by the Pindus massive (a national park). The region hosts: 31 Natura 2000 protected areas and one Ramsar site, Wetlands of International Importance, the Amvrakikos Gulf. INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 6 of 53
major dairy brands, producing feta and other regional cheese. However, the services sector dominates the economy, accounting for 74.3% of the regional GDP, while industry and construction account for 19.5%. The main regional services activities are transport, financial intermediation, tourism, health, education and trade (RIM 2012). The renewable energy sector, particularly wind and hydro-power, is growing in importance. The manufacturing sector is dominated by traditional industries with a majority of small family-run firms, with limited export capacity. The most dynamic regional industries are the dairy products and other food products industries that are vertically integrated.
Based on 2005 data (most recent available) on research and development (R&D) expenditures, the region accounted for only 2.6% of the Greek gross R&D expenditure (GERD) or a total investment of €29.82m. However, this is equivalent to 0.68% of GDP, placing the region third amongst Greek regions (equal with Western Greece), a share that increased by 23% between 2003 and 2005. The vast majority (96%) of the regional R&D investments efforts occur in the higher education sector (47.5% in Greece, 22.5% in EU27) and to a limited extent in the government sector for 3.52% (20.3% in Greece, 13.6% in the EU27). Consequently, the business sector contributes only 0.73% of regional GERD (t31% nationally and 63% for the EU27). This enormous gap is due to the low-to-medium technology structure of the regional economy and the dominance of traditional sectors. In addition, since 2008, the economic crisis is likely to have negatively affected business R&D investment. The low business R&D intensity is reflected in the level of patenting activities, with 5.68 patents registered, at the European Patent Office, per million inhabitants in Epirus, in 2008, against 8.04 on average in Greece and 111.58 in the EU27.
In 2011 the region hosted 2.7% of the national Human Resources in Science and Technology (HRST) or 28.8% of the regional workforce (active population)3, ranking the region third (after Attica and Central Macedonia). The total R&D personnel in 2005 was 1,037 full time equivalent (FTE), or 0.75% of the regional active population against 0.69% in Greece and 0.95% in EU27. Not surprisingly, most of those were to be found in the higher education sector (97.5%), with only 29 FTE to be found in the business sector and 15 in the government sector. Looking specifically at the share of researchers (0.47% of active population against 0.4% in Greece and 0.59% in
3 The percentage of the total labour force aged 15-74 having successfully completed a third level degree or employed in an occupation where such an educational level is normally required INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 7 of 53
EU27), 98% of the 656 regional FTE are working in the higher education sector. Only 11 FTE researchers worked in Epirus’ businesses. The RIM reports argues that the low HRST employment rate by regional enterprises is the direct outcome of the manufacturing production structure, where low skill cost competition dominates. Despite the fact that Epirus has a strong education tradition, the HIDDEN report (2011) highlighted that 80% of the graduates from the University of Ioannina turn towards the public sector and lack an entrepreneurial perspective.
Looking closer at the scientific production, between 1996 and 2010, the University of Ioaninna (UOI) ranked sixth among the 21 Greek universities analyzed based on Thomson Reuters data in 2010 (714 publications in 2010 against 250 in 1996). Over the period 2006-2010, UOI had a total of 3,481 publications (8.6% of total Greek universities’ publications), 42% of those involving national co-authorship and 41% international collaboration. Publications of the UOI were cited 20,705 times over the period 2006-2010, giving the UOI an overall citation impact of 1.04. The main fields of scientific activity in the UOI are to be found in natural sciences (1,890 publications, over 2006-2010, 10,505 citations, citation score of 1) and medical and heath sciences (10,122 publications, 1,409 citations, citation score of 1.11). There is also some activity in engineering and technology (2,769 publications, 685 citations, citation impact of 1). Interestingly, there are not many publications and citations in the field of agricultural sciences (167 publications, 51 citations) but the citation impact is relatively high (1.24).
The Technological Education Institute of Epirus (TEI Epirus) has a considerably lower level of scientific outputs, with 99 publications over the period 2006-2010 (ranked 8th out of the 16 Greek TEI), 257 citations (ranked 8th) and a citation impact of 0.81. The TEI Epirus is particularly active in natural sciences (120 publications over 2006-2010, 47 citations, citation impact of 0.58) and agricultural sciences (107 publications, 44 citations, citation score of 1.05). From the total publications, 85% involved a national collaboration and 24% an international collaboration.
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Figure 3: SWOT of regional innovation potential and specialization
Strengths Weaknesses Good quantity and quality of • Quasi non-existent business R&D scientific production investments
• High level of HRST • Traditional structure of the economy, dominated by small low- • Presence of regional academic tech companies research capacities with specialisation relevant to regional • Remote, under-developed area economy • Low level of ICT diffusion • Past experience in the • Low level of education of the development of regional population and lifelong learning innovation policies (RIS, RPIA, practices RISI, etc.). • Low level of science-business • Significantly better transport collaboration infrastructures for inter-regional connections • Weak entrepreneurial and innovation culture in business sector • Rich and relatively well- protected natural and aquatic resources Opportunities Threats • Enhancement of the • Economic specialisation in low- competitiveness of agriculture tech sectors (agriculture, tourism) and tourism and increased focus • Competition from low-cost on quality (e.g. green products) economies based on scientific specialization • Brain drain • Increase coordination of national and regional policies to support ICT diffusion
• Improvement and upgrading of infrastructure in the industrial areas and of support infrastructures
• Improve support to upgrading of SMEs technological capacity
• Potential for expanding renewable energy generation Data on scientific specialization is therefore partly in line with the regional economic specialization profile in particular for the agricultural area. This would
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suggest the existence regionally of a potential for upgrading the agricultural capacities and production towards activities generating more added value for the regional economy.
Briefly, the region should focus future research and innovation investment in developing 2-3 core competencies of relevance for the regional economy, these are most likely to be found in research and technology extension services for the dairy industry and other agro-food firms, ICT technologies and their application in improving regional health and tourism services and manufacturing production and, technology know-how related to environmental protection and sustainable exploitation of the natural biodiversity. The RIS3 process should include a more detailed analysis of technology needs and opportunities in regional firms.
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Section 2
2 Olive Oil Quality Determination criteria and results
2.1 Quality Criteria Based on the analysis that is been demonstrated analytically in this section, there are many qualitative physical and chemical parameters and lengthy procedures involved through which the characteristic olive oil quality categories namely: extra virgin oil, virgin oil and Lampante could be determined. The quality characteristics involved refer either to its nutritional value, organoleptic determination and lifespan of the product.
In this respect, for the sake of this project, 18 Italian and 9 Greek producers (with IDs: IT-2042 up to GR-780) as shown on the horizontal axis of the graphical presentations bellow, participated with oil samples when requested for the determination and classification of their olive oil qualitative characteristics.
Therefore, through the results of the laboratory analysis performed and the results shown bellow, each individual product was classified as extra virgin oil, virgin oil and Lampante, proving that only acidity measurement test is not a sufficient to determine the quality characteristics of the product and classify it in one of the above categories.
Therefore, bearing the following lab analysis in mind, the prospective olive oil consumer should seek in the market a product with its qualitative characteristic below the relevant red line. Additionally, the existing olive oil producers planning to promote their product in the local, national or European market should obtain the qualitative results shown bellow for each milling batch they process and illustrate these on a quality label of the product.
In this respect and in order to assist the purposes of the following statistical analysis, the basic quality parameters for which the oil should be tested and the results obtained should be recorded on a suitable table on the label of the product are listed below:
Acidity – this commonly utilized test, determining the effect of hydrolysis and the creation of free fatty acids. It is usually performed during the oil
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separation phase in the oil mill and helps determine the olive oil categorization. In this respect, the acidity laboratory results obtained for all project partners together with the maximum permissible limit of 0,8% which should not be exceeded, are shown on the following graphical presentation.
Apparently the project partners coded as GR-536 and GR-537 exceed nearly three times the permissible higher limit.
Acidity (% Oleic Acid) 003 002 001
000
38 68 69 70 71
- - - - -
110 214 111 116 117 120 127 128 129 130 215
532 533 534 535 536 537 538 779 780
------
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT
Alkyl esters. Rapid screening of fatty acid alkyl esters in olive oils represents one of the most important extraction process quality attributes. The maximum permissible limit for this test should not exceed 75mg/kg. Once again, referring to the actual laboratory results bellow, project partners coded GR-536 and GR-537 exceed the permissible max value.
Alkyl esters (mg/kg) Γενικός τύπος Γενικός τύπος Γενικός τύπος Γενικός τύπος
Γενικός τύπος
69 38 68 70 71
- - - - -
536 110 111 116 117 120 127 128 129 130 214 215 532 533 534 535 537 538 779 780
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT
Oxidation level. The oxidation level determines the state of oxidation and the age of olive oil, by showing the presence of various types of oxidized substances. The following tests have to be performed:
1. Peroxide number, indicating the state of oxidation of olive oil. Maximum permissible limit is 20meq02/kg. As it can be seen from the laboratory results obtained, once again GR-537 exceeds the higher permissible limit whereas the results of GR-532 and GR-533 are right at the limit.
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Peroxide level (meqO2/Kg) 40 20
0
38 68 69 70 71
- - - - -
111 116 117 120 127 128 129 110 130 214 215
532 533 534 535 536 537 538 779 780
------
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT 2. Spectrophotometric determination of the purity parameters of the olive oil by determining the following purity characteristics:
a. Parameter K232 indicates the age of olive oil together with the time duration the olives have been left unprocessed in sacks after their harvesting and the milling process, also the storage conditions of the olive oil and the level of oxidation incurred during production and/or storage. Its maximum permissible limit is 2,50. From the attached laboratory results it can be seen that only the Italian participant IT-69 exceeds the permissible value.
K232 030 020 010
000
38 68 69 70 71
- - - - -
116 129 110 111 117 120 127 128 130 214 215
532 533 534 535 536 537 538 779 780
------
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT b. The K270 parameter test detects the level of adulteration, blends with refined olive oil Wax content which determines the level of adulteration with pomace oil. Its maximum permissible limit is 0,022. From the laboratory results obtained and shown bellow, once again the project partners coded GR-536 and GR-537 exceed the permissible max value.
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K270 000 000 000
000
38 68 69 70 71
- - - - -
128 130 215 110 111 116 117 120 127 129 214
533 535 537 779 532 534 536 538 780
------
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT c. The D.K parameter shows the extra virgin oil purity characteristic derived from manipulated parameters such as K232, K270 and others with maximum permissible limit +0,01. With the red border line existing at the value +0,01 it can be seen that producer GR-537 exceeds the limit line, whereas all other calculations reside well within the red line.
D.K 0,015 0,010 0,005
0,000
70 38 68 69 71
- - - - -
110 111 116 117 120 127 128 129 130 214 215 532 533 534 535 536 537 538 779 780
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT
Waxes. Determines waxy substances that surround the olive fruit. During the crushing phase, minute quantities surrounding the fruit mix with the extracted olive oil. With a maximum permissible limit of 75mg/kg the Greek producers GR-536 and GR-537 exceed the permissible high limit.
Waxes (mg/kg) Γενικός τύπος Γενικός τύπος Γενικός τύπος Γενικός τύπος Γενικός τύπος
Γενικός τύπος
70 38 68 69 71
- - - - -
116 128 215 110 111 117 120 127 129 130 214
535 779 532 533 534 536 537 538 780
------
------
2042 2104
IT IT IT IT IT
- -
IT IT IT IT IT IT IT IT IT IT IT
GR GR GR GR GR GR GR GR GR IT IT
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Expiration date. Quality assurance indicator. Indicates the time span during which the company guarantees its product will remain unaltered. Obviously, olive Oil does not get bad health wise, but as time passes its aroma and fruitiness decreases. After 18 months from its production can no longer be considered extra virgin olive oil.
Batch ID number. Number that should be utilized in order to identity every batch produced. A 6-figure number could be used, identifying the olive oil producer, labeling date and the customers receiving this specific batch.
Extra virgin oil quality measurements. In the case of extra virgin oil the results obtained related with the following quality parameters should be “Zero”, i.e.:
Cholesterol: 0 mg Sodium: 0 mg Total Carbohydrate: 0 g Protein: 0 g
Organoleptic analysis. The purpose of this organoleptic method is to determine the availability of necessary or unfavorable taste criteria assessing the inherent flavor characteristics of the olive oil produced and develop a methodology for qualitative classification. In our case as shown bellow, the typical criteria tested for each participating producer were bitterness, spicy, fruity and defect tastes. Taking into considerartion that each producer is represented by a vertical line of results, their vast variation are shown on the graphical presentation bellow.
Organoleptic analysis 8,00
6,00 bitter
4,00 Spicy fruity 2,00 Defect ,00 ,00 5,00 10,00 15,00 20,00 25,00 30,00
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2.2 Classification of the results obtained The most important result of the laboratory analysis performed, was the classification of the samples consisting of 27 different samples of olive oil (18 from Italy and 9 from Greece). As shown on the following graphical presentation, is clearly demonstrated the fact that only 44% of the samples are extra virgin oil, 37% virgin and 19% lampante.
Olive oil Classification
Extra virgin Virgin Lampante
19% 44% 37%
This last classification result related with the olive oil quality, is of upermost importance for the true understanding of the following statistical section and the conclusions derived as a result of the statistical excersice. It shows that exact quality classification is not an art based only on the capitalized experience of an individual and the acidity of the olive oil. It requires a typical laboratory analysis which all oil mills, through their in house laboratories should be capable to perform. Thus they could determine the above quality indexes and provide the products and/or the producers with associated quality certificates.
Of course, in order to be able to produce olive oil with maximum qualitative and quantitative characteristics, the common cultivation, production and storage protocols developed as a result of this project should be followed.
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Section 3
3 Market research analysis survey
3.1 Survey analysis overview Statistical analysis is the study associated with the collection, organization, analysis, interpretation and presentation of data. In the present application, the statistical analysis deals with the olive oil preferences of the inhabitants of the Regional Unit of Thesprotia and includes the planning of data collection based on a suitably designed survey questionnaire, the execution of the actual field survey and experiments ensuring that data collection was undertaken in a way that produces valid conclusions, coding data and obtainable reporting results in ways comprehensible to those who will utilize them, satisfying at the same time the particular requirements associated with the implementation of the territorial INNOVOIL project and its deliverables.
The statistical method utilized for the fulfillment of this survey’s requirements can be summarized as a collection of data based on certain survey method called “descriptive statistics”. This type of statistical analysis is particularly useful in communicating the obtainable results of the research accomplished. In addition, the data layout presented through the help of the detailed questionnaire, were suitable to account for randomness and uncertainties of the sampled participants in the observations.
In applying statistics to a societal problem like the INNOVOIL market research, it was deemed necessary to begin with the needed population and the suitable process to be utilized. In this respect, the targeted population of this statistical survey, satisfying the purposes of the project, was approved through a territorial meeting of all project partners to be the random customers of the local supermarkets residing in our particular case around the multi-selective town of Igoumenitsa, the capital of the Regional Unit of Thesprotia. Thus the sampled population, consisting of mainly random consumers and olive producers, was composed of observations of the selection process at various times, with the data from each observation serving as a different member of the overall group. INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 17 of 53
For practical reasons, once a sample representative of the sampled population was determined, data were collected for each participant. Subsequently these collected data were subjected to statistical analysis utilizing the statistical and logistic capabilities of the currently available MS Excel package, serving at the same time the two related purposes of this survey: description and inference.
The descriptive statistical analysis utilized, summarizes the data of the sampled population by describing what was observed in the samples collected numerically and graphically. The numerical descriptors utilized such as percentage, were more useful in terms of describing the categorical data of each sample.
The inferential statistical analysis adopted, used the patterns formed of the various sections in the sample data to draw inferences about the sampled population of each segment of the questionnaire. In this respect, inferences were extended to estimation of unspecified fields associated with the population under observation.
Utilizing a sample as an interviewers guide for the entire population, it was important that each interview truly represented the overall population under statistical observation, thus assuring that inferences and conclusions could safely extend from the collected samples (supermarket customers around the town of Igoumenitsa) to the local population as a whole.
3.2 Sampled Population size As mentioned briefly above, for the purposes of the INNOVOIL project it was impossible or impractical to track down every member of the selected population. Therefore, the obvious utilized statistical option available for the purposes of this survey was to sample the population under survey. In this respect, for each sample selected, being a subset of the selected population under survey, its size could be small or large. To satisfy our project purposes, was decided to utilize a sample small enough to be representative, at the same time manageable by our computing power, yet large enough to give us statistically significant and reliable results.
Therefore, in order to strike a proper balance concerning the sample size, taking into consideration that this type of statistical survey typically have sample sizes of around 1.000 for the size of Greece, then a sample size with a population of around 250 was apparently going to be sufficient enough for our purposes. As a matter of fact, having manipulated the data downloaded and by taking into
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consideration the statistical results obtained it was obvious that the statistical results obtained were fully satisfactory.
3.3 Random simple samples In statistics is well known that having the right sample size is not usually sufficient enough to ensure good results. A good sample should contain people of different ages, from all walks of life, and preferably from all municipalities within the Regional Authority of Thesprotia. From the results obtained in this survey, in order to acquire such a sample we composed randomly our choices so that every individual had an equal probability of being in the sample. In such a random simple sample of n individuals, every member of the population had the same likelihood of being selected to participate in the sample.
Finally, it has to be mentioned that, in order to ensure acceptable and/or good results, it was necessary to plan in advance our field survey, brief the task members of each group responsible for picking the individuals and fill the questionnaire on how to select randomly the various individuals and commence the recording procedure carefully. Good simple random samples require some preparatory work and behavioral approach to obtain. If our data had been obtained haphazardly and in a cavalier manner, then no matter how sophisticated our digital analysis was, the statistical technique utilized was not going to give us worthwhile conclusions.
3.4 Sampling planning and implementation stages As mentioned above, the sampling statistical technique utilized in our survey, is concerned with the selection of a subset of individuals from within a statistical population (supermarket customers), in order to estimate characteristics of the whole population of the Thesprotia region. As it can be seen explicitly through the questionnaire utilized to gather and record the necessary observations concerning the population, each observation measures one or more properties (such as personal and demographic details, whether they purchase olive oil or other products, quality considerations, size and type of containers, etc) of observable bodies distinguished as independent objects or individuals.
Therefore, taking all the above into consideration, the planning of the sampling process and subsequent statistical analysis that followed and methodologically implemented, fully focusing on the definition of our sampling problem demands, comprised from the following stages:
1. Defining the population of concern. As shown bellow, the necessary research characteristics defining the sampling population needs of the INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 19 of 53
project were obvious. Randomly picked customers (local or not) of the main supermarkets located around the periphery of Igoumenitsa, readily available and convenient for our interviewers, were chosen to represent our sampling population subjects.
2. Specifying a sampling method. The sampling method adopted, anticipating the collection of field data from local supermarkets, was based on the survey method identified as “descriptive statistics”. The method was implemented through the attached herewith questionnaire, which was dully prepared and approved through the Lead Partner of the project, in close collaboration and cooperation with AICAI as foreseen by the approved project proposal.
3. Determining the sample size. As mentioned above, taking into consideration that currently the population of a national gallop has been determined to be around 1.000 individuals, as well as the fact that 5% of the extrapolated local supermarket customers was expected to be around 200 then the sample size of 250 actually used is deemed to be adequate enough to cover fully the purposes of this survey.
4. Implementing the sampling plan. The implementation of the sampling plan, guided via the sampling protocol requirements, was conducted concurrently in all local supermarkets of Igoumenitsa, during a number of consecutive days through the various interviewing teams, formed specifically to satisfy the interviews thus conducted.
5. Sampling and data collecting. The data thus collected from each individual who participated in the sampling process, were subsequently downloaded on a suitable MS Excel spreadsheet which was developed in order to satisfy the demands of the necessary statistical analysis which followed.
6. Grouping of the data collected. Although the participating individuals were free to specify e.g. the place of their origin, or their exact age, nevertheless, due to the fact that this detailed analysis was proven to be cumbersome, it was decided to group as places of origin the three municipalities the Regional Unit of Thesprotia and “Other” all alternative contributions, whereas we utilized the decade each individual was born into instead of their exact year of birth.
7. Statistical analysis spreadsheet. As mentioned above, the data thus collected were carefully downloaded on the specifically developed INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 20 of 53
spreadsheet, were subjected to applicable statistical equations and mathematical manipulations and the statistical results thus obtained were automatically recorded on predetermined positions on the same spreadsheet.
8. Creation of graphics. Through the utilization of the statistically obtained results the pie graphs were developed in order to present the results in a more understandable way.
9. Documentation and presentation. The documentation and presentation of the results thus created consists the remainder of this survey.
3.5 Simplifications and modifications performed In order to ease the appearance and understanding of the results obtained through the statistical analysis the questionnaire utilized in the present survey, we have incorporated minor changes to its appearance and text in order to be easily accommodated in the logistic spreadsheet duly developed for this purpose. Additionally the questions used have been divided into separate segments in order to allow for the proper implementation and presentation of the statistical equations utilized.
It should also be noted that partially uncompleted data columns of each sampled participant and downloaded on the logistic spreadsheet, were duly completed paying particular attention not to alter the results of the survey.
Furthermore, just for simplicity reasons, as far as the percentage values on the graphical presentation of the results are concerned, it should be taken into consideration that their decimal part has been truncated and therefore only the integer part appears on the graphical presentations. However, all mathematical manipulations have been carried out utilizing all decimal places of each number.
Additionally, for simplicity and reference purposes, in order to follow the same segment numbering utilized on the original questionnaire the statistical analysis
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QUESTINNAIRE ANALYSIS
1 Personal/Demographic details
The first general section of questioning, 1. Personal/Demographic Details, of the approved and subsequently utilized questionnaire as it has been fragmented for analytical convenience, contains questions related with:
1.1 The area of residence of the sampled population
1.2 Age distribution,
1.3 Gender,
1.4 Marital status and the,
1.5 Number of children per household.
As it has been already mentioned the analysis of the results is based on the recorded answers of the sampled participants together with the manipulated results of the associated percentages. These numerical results are presented either on suitable tables constituting of relevant questionnaire fragments, as well as through graphical presentations of the percentages accordingly determined.
In this respect, the results pertaining to the personal and demographic details mentioned above of the sampled population are the following.
1.1 Area of Residence The contribution of this statistical result, related with the current area or residence of the random population sample utilized, provides to the survey and the prospective readers with background information concerning the area or residence of the participants.
It should also be noted that for simplification reasons the various neighboring areas of origin recorded in this survey, surrounding capital cities been included in those principal areas namely Igoumenitsa, Syvota, Filiates and Paramythia.
The category “Other” represents all random participants residing outside the Thesprotia Regional Unit.
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1. Personal/Demographic Details
Area of Residence
1.1. Area of residence Refer to table: 1.1
1.2. Age Distribution of Individuals Refer to table: 1.2
Table 1.1. Area of residence and age distribution questionnaire table
1.1. Area of residence distribution
Igoumenitsa Syvota Filiates Paramythia Other
165 53 15 9 8
66,00% 21,20% 6,00% 3,60% 3,20% Table 1.2. Distribution of residence
Table 1.1 represents the results of the statistical analysis in terms of actual contributions per area of residence and their corresponding percentages. Regardless the random nature of the winder dates the data collection procedure took place, as it was anticipated, 66,00% of the population resides around the town of Igoumenitsa. It should be mentioned however that, due to the fact that Igoumenitsa represents a touristic hub due to its international port and the surrounding holiday destinations, the above statistical outcome is fully related to the time interval the interviews were undertaken.
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1.1. Area of residence
Igoumenitsa Syvota Filiates Paramythia Other
4% 3% 6%
21%
66%
Figure 1.1. Percentages of the areas of residence
As mentioned above, the data collected through the questionnaire, were downloaded on the specifically and duly developed statistical spreadsheet, tailored according to the needs of the project. Accordingly, the downloaded results were subjected to associated statistical and mathematical manipulations and the statistical results such as the percentage of each area of residence, was recorder on a suitably designed table fragment of the questionnaire together with a graphical presentation as the figure 1.1 above.
1.2 Age Distribution of Participants The random results obtained and recorded related to the age distribution of the participants together with the graphical percentage distribution are shown on the table 1.2 and figure 1.2 bellow. It should also be noted that the percentage distribution of the age spans selected, covers practically in a proportional manner all possible ages of the population.
1.2. Age Distribution of Participants Age Age Age Age Age Age Span Span Span Span Span Span Unspecified > 64 54 - 63 44 - 53 34 - 43 24 - 33 < 14 8 31 75 80 46 4 6
3,20% 12,40% 30,00% 32,00% 18,40% 1,60% 2,40%
Table 1.3. Age distribution results
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1.2. Age Distribution of Participants
2% 3% 3% Age > 64 12% 18% Ages from 54 to 63 Ages from 44 to 53 30% Ages from 34 to 43 32% Ages from 24 to 33 Ages < 14 Unspecified
Figure 1.2. Age Distribution of Participants
In this respect, taking into consideration the graphical presentation of the manipulated results, it’s most interesting to observe the fact that all consumer ages contribute more or less to the procurement of goods through the local supermarkets.
However, referring to figure 1.2, it can easily be seen that 62,00% of the sampled population belong to the age group from 34 years of age up to 53.
1.3 Gender distribution of the sampled participants As it can be seen through the relevant questionnaire section included bellow, the obtained results and the manipulated percentages of the sampled population 59.20% consisted as profoundly anticipated of females, whereas the rest of the population consisted the male population.
1.3. Gender Distribution RECORD PERCENT
Male 102 40,80%
Female 148 59,20%
Table 1.4. Gender distribution results
These manipulated percentages, may also be easily seen on the attached graphical presentation of the figure 1.3 bellow. INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 25 of 53
1.3. Sex Distribution
Male Female
41%
59%
Figure 1.3. Recorder gender percentage distribution
1.4 Marital Status Distribution As shown on the questionnaire fragment table 1.5 and the graphical presentation figure 1.4 included bellow, this group of demographic data collected through this survey, represent the recorded values and manipulated percentages of the marital status of the questioned participants.
1.4. Marital Status Distribution RECORDED PERCENT
Single 72 28,80%
Married 178 71,20%
Table 1.5. Marital status distribution results
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1.4. Marital Status
Single Married
29%
71%
Figure 1.4. Marital Status Distribution percentages
1.5 Number of children per family Another interesting result derived through this survey represents the numbers of children each family is possessing. As anticipated and as it can be seen through the manipulated table 1.3 bellow and the included graphical presentation (figure 1.4), over 55% of the married families have 2 children.
1.5. Distribution of children per family
1 kid 2 kids 3 kids 4 kids or more
32 85 32 4
20,92% 55,56% 20,92% 2,61%
Table 1.6. Number of children per family
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1.5. Children distribution per family
1 kid 2 kids 3 kids 4 kids or more
3%
21% 21%
55%
Figure 1.4. Children Distribution per family
2 Type of oil and/or fat usually utilized
As far as the Questionnaire Section 2 of questioning is concerned, related with the type of oil and/or fat utilized by the local households, referring to the following table and graphical presentation bellow, as anticipated, due to the fact that Thesprotia is an oil producing region, the majority (82,27%) of the sampled population is obviously utilizing olive oil. In this respect, it should also be taken into consideration that a considerable percentage of the population is producing its own olive oil in adequate quantities, usually covering their consumption needs yearly.
2. Type of oil - fat usually utilized RECORDED PERCENT
Olive Oil 246 82,27%
Vegetable Oil 16 5,35%
Butter 29 9,70%
Other 8 2,68%
Table 2.1. Type of oil – fat utilized results
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It should also be noted that an adequate percentage of the local households are using vegetable oil for frying purposes, whereas butter as such, is only used for baking cakes and various pastries.
2. Type of oil - fat utilized for daily consumption
Olive Oil Vegetable Oil Butter Other
10% 3% 5%
82%
Figure 2.1. Percentages of the types of oil – fats utilized
3 Olive Oil Procurement frequency Distribution
This statistical result of the sampled population beyond the spread of the results among all procurement frequencies, shows at the same time beyond any doubt the fact that almost one quarter of the local population (47,20% x 55,08% = 25.99%) is producing its own olive oil or entirely rely on local producers and therefore is not procuring any oil from the local market.
3. Olive Oil Procurement Distribution RECORDED PERCENT
Every week 46 18,40%
Once a month 44 17,60%
Once a year 42 16,80%
3a. Other 118 47,20%
Table 3.1. Olive Oil procurement frequency results
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The figure 3.1 bellow shows graphically the percentage distribution of the oil procurement frequency of the individuals. Correlating these results with the results obtained in the section 5 of this survey, it could be derived that the 18,60% procuring olive oil every week utilize 1 liter containers, whereas those procuring olive oil once a month (17,60%) utilize 5 liter containers. It can also be seen that the remainder 16,80% of the population apparently utilize bulk containers.
A last observation that is worthwhile to be addressed is the fact that, as it can be derived from the above statistical results, the average consumption of olive oil per local family seems to be over 1kg/week.
3. Oil procurement frequency
18% Every week 47% 18% Once a month
17% Once a year Other
Figure 3.1. Frequency of Olive oil procurement
3a. Other
Olive Oil Producers Other type of fats
65 53
55,08% 44,92%
Table 3.2. The “Other” category distribution
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Referring to the table (“Other”) shown in correlation with the table 3.1, it can be seen that 47,20% of the sampled population is not procuring olive oil during the time intervals specified, whereas at the same time, referring to table 3.1, the 55,08% of the “Other” section are olive oil producers.
3a. Other
Olive Oil Produces Other types of fats
45%
55%
Figure 3.2. The “Other” category percentages
Taking into consideration all the above and the fact that the Thesprotia Region is an olive oil producing area, the remainder 44,92% of the “Other” section most probably represent sampled individuals procuring their olive oil through the local producers and not through the local supermarkets.
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4 Quality of Olive Oil procured distribution
Taking into consideration the results obtained, it is apparent that 41,60% of the consumers is actually procuring extra virgin oil relying entirely on the product’s label, whereas another 28,40% is either satisfied or comfortably settled with the procurement of virgin oil. This differentiation is either due to the price difference between the two products or due to the belief that there is no significant quality difference between the two products.
The “Other” preference section of the results obtained and subsequently manipulated, representing 29,20% of the sampled population, apparently rely entirely on the producers’ opinions in terms of oil quality reassurance.
4. Quality of Olive Oil procured RECORDED PERCENT
Extra virgin Olive Oil 104 41,60%
Virgin Olive Oil 71 28,40%
Lampante Olive Oil 2 0,80%
Other 73 29,20%
Table 4.1. Quality of Olive Oil procurement results
4. Quality of olive oil procured
Extra Virgin Olive Oil Virgin Olive Oil Labade Olive Oil Other
29% 42%
1% 28%
Figure 4.1. Quality preference percentages
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Finally referring to the graphical presentation of the figure 4.1, it can be seen that practically only an infinitesimal percentage representing only the 0,8% of the sampled population is consuming lampante olive oil.
5 Quantity of Olive Oil monthly consumed
In this section the sampled individuals were interviewed in relation with the quantity of olive oil they are using for their monthly consumption.
Referring to the following table If you take into consideration that the “Other” percentage choice (34,40%) represents mostly consumers utilizing bulk quantity oil containers (usually 17.5kg) and the fact that 48,00% consume 5 liters of olive oil on a monthly basis we conclude that over 82,00% consume around 5 liters of olive oil per month which represents an average quantity of 1.2kg per week.
5. Quantity of Olive Oil monthly consumed RECORDED PERCENT
1 Liter 44 17,60%
5 Liters 120 48,00%
Other 86 34,40%
Table 5.1. Quantity of olive oil consumed monthly
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5. Quantity of olive oil monthly consumed
1 Liter 5 Liters Other
34% 18%
48%
Figure 5.1. Quantity of olive oil monthly consumed
6 Preferable Container Volumes
Once again, as it can be seen from the percentage distributions of the preferable container volumes bellow represent those consumers which are either olive oil producers themselves or they procure their oil supplies from local producers in bulk containers such as the typical 17.5kg tinned container commonly and easily available through local suppliers.
The percentage of 39,20% is procuring as already emphasized olive oil once a month in 5 liter containers and therefore, only the moderate percentage of 15,20% among the sampled individuals actually procure olive oil in 1 liter packages.
6. Preferable container volumes RECORDED PERCENT
1 Liter 38 15,20%
5 Liters 98 39,20%
Other 114 45,60%
Table 6.1. Preferable container volume results
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6. Preferable Container Volume
1 Liter 5 Liters Other
15% 46%
39%
Figure 6.1. Preferable container volume percentages obtained
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7 Preferable material type of container
As already mentioned a large percentage of the sampled population is actually utilizing 5 liter and 17.5 liters tinned or plastic containers either due to their personal preference or due to the procurement of bulk quantities in tin or plastic packages through the local producers. This practical necessity to utilize this type of bulk tin or plastic containers is profoundly determining their decision to declare the decisions recorded.
7. Preferable material type of container RECORDED PERCENT
Glass 82 32,80%
Plastic 51 20,40%
Metallic 99 39,60%
Other 18 7,20%
Table 7.1. Preferable material type of the container
Therefore, in this respect, taking into consideration the above table 7.1 and the associated figure 7.1 attached, it can be seen that the metallic containers were preferable by the 39,60% of the sampled population participating in this experimental survey, whereas another 20,40% prefer plastic containers, through which nobody could ascertain the color and the clarity of the olive oil, unless of course the procured olive oil is purred into these containers in their presence.
It should also be noted that, regardless the fact that in section 15 of this survey the vast majority of the sampled population declared their preference for glass containers in order to ascertain the olive oil color quality, however on the other hand, only 32,80% of the population actually prefers glass containers.
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7. Preferable material type of container
Glass Plastic Metallic Other 7%
33% 40% 20%
Figure 7.1. Percentages of the preferable types of container materials
8 Procurement of organic products
This section of the questionnaire related with the distribution of the procurement preferences of organic products, shows that 46% of the consumers procure once a month organic products. A small percentage of 16% has declared that they procure organic products once a week, whereas another quarter (24%) of the sampled population is actually procuring organic products once a year.
8. Procurement of organic products RECORDED PERCENT
Every week 40 16,00%
Once a month 115 46,00%
Once a year 60 24,00%
Other 35 14,00%
Table 8.1. Procurement of organic products results
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8. Organic product procurement
Every week Once a month Once a year Other
14% 16%
24%
46%
Figure 8.1. Percentages manipulated related to organic products procurement
Still the “Other” result category of this section has chosen either not to answer or to choose this alternative because the prevailing environmental circumstances of the region provides for organic product development.
Once again, taking into consideration that adequate quantities of fresh mostly organic products sold in this region, of known and trustworthy locally produced quality, the consumers have developed a trust with the producers. In terms of olive oil, the majority of the consumers know for a fact that the producers do not use chemical fertilizers to increase their production and that’s why they rely on them.
9 Determination of Olive Oil Choice factors
Further with the sampled results and statistical manipulations, as it can be seen through the following Table 9.1 and the figure 9.1, the determination factors of the olive oil choice by 43,42% is due to the qualitative information printed on the product’s label, whereas 19,93% of the sampled population relies on the trademark of the product. Most probably, this population percentage, relies on some product, due to the fact that it has been utilizing satisfactorily that particular for a number of years and is already convinced about its quality without having to refer to the information printed on the product’s label.
The shop’s promotion choice of 16,73%, obviously depends on the fact that the product promoted is of known adequate and acceptable quality and the
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promotional price is apparently determining the consumer’s decision or the low price determines the procurement of an unknown product.
The “Other” category of choices of 19,93% consists of the local olive oil producers which rely on the presumed quality of their product and of course the quality of storage facilities they posses.
9. Determination of olive oil choice RECORDED PERCENT Label’s qualitative information 122 43,42% Product trademark 56 19,93% Shop’s promotion 47 16,73%
Other 56 19,93%
Table 9.1. Determination of olive oil choice
However, all producers rely only on the acidity test performed during the oil production and not on the other qualitative indexes which determine the nutritious quality of the oil. In this respect, as it has proven by the laboratory results of this project performed in Italy, on average only 45% of the olive oil produced is extra virgin oil, 30% virgin oil and 25% Lampante.
9. Determination of olive oil choice factors
Label's qualitative information Product trademark Shop's promotion Other
20% 43% 17% 20%
Figure 9.1. Determination of olive oil choice factors distribution
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Apparently, taking the matter a bit further, by referring to the figure 9.1 above, all populations recorded of all above category choices factors, each individual strongly believes that every choice is the ideal qualitative choice. Even the olive oil producers strongly believe that the quality of their individual product is of extra virgin quality.
Therefore, clearly nobody knows what the quality indexes (and therefore the quality) determining the nutritional value of their product should be, in order to classify their product as extra virgin oil based on real quality criteria.
Moreover, it should also be noted at this stage that, in order to achieve a cultivated oil product with adequate quality characteristics, the oil thus produced should posses the nutrients levels necessary to classify a product as extra virgin oil, or other. Therefore is imperative for all olive cultivators and oil millers to follow the simple cultivation practices developed by this project as well as the developed production protocols, together with the proper storage conditions.
10 Product label reference
Another fragment of the questionnaire was related with the need of the consumers to refer to the label of the product as qualitative reference. Apparently through the results obtained the vast majority of the sampled population individuals are referring to the product’s label for all kinds of qualitative information the labels might contain.
10. Product label reference RECORDED PERCENT
Always 180 72,00%
Frequently 48 19,20%
Occasionally 4 1,60%
Never 18 7,20%
Table 10.1. Product label reference
In this respect, in more detail, referring to the results shown on the attached table 10.1 and the graphical presentation of the figure 10.1, the majority of 72,00% of the sampled population interviewed is always referring to the informatory and qualitative details contained on the label of each product, whereas another 19,20% is frequently utilizing the product’s label as quality reference for its choice.
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10. Reference factors to product's label
Always Frequently Occasionally Never
2% 7% 19%
72%
Figure 10.1. Graphical presentation of the percentages achieved
Additionally a small percentage of 1,60% is occasionally referring to the label in order to ascertain the qualitative criteria of the product they procure.
Surprisingly there is a small percentage of 7,20% who never refer to the label information of the product. Most probably this is due to the fact that they never procure olive oil from the supermarkets shelves due to the fact that they are oil producers.
In this respect however, if we take into consideration the fact that a significant proportion of the interviewed olive oil consumers is either a local producer or is actually procuring bulk quantities of olive oil, then the percentages of the results obtained and presented of the graphical presentation are fully justified.
11 Most significant label information
By referring to the results of the following table 11.1 and the attached figure 11.1 bellow, we can conclude that a vast sum of 80% of the sampled population is checking the product samples in order to ascertain whether the product is a Greek product. That apparently represents a significant qualitative product criterion or decisive factor for oil procurement.
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11. Most significant label Information RECORDED PERCENT
Product origin 125 28,80%
Producer established in Greece 95 21,89%
Distribution company based in Greece 6 1,38%
Greek raw material (olive crop) 85 19,59%
Nutritional table 25 5,76%
Organic cultivation stamp 58 13,36%
Product of origin stamp 34 7,83%
Other 6 1,38%
Table 11.1. Most significant label information
On the other hand, the real quality characteristics of this question such as the nutritional table (scoring only a very low 5,76%) and the organically cultivated stamp (13,36%), totaling around 20,00% are too low compared with the prevailing origin criteria.
11. Most significant Label information
Product origin 1% 8% Producer established in 13% 29% Greece
6% Distribution company based in Greece
20% Greek raw material (olive 22% crop) Nutritional table
1% Organic cultivation stamp
Figure 11.1. Percentages of the most significant label information INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 42 of 53
12 Packaging Significance for product procurement
Referring to the following table 12.1 presenting the results of the interviews and the manipulated percentages as well as the graphical presentation of the attached figure12.1 it can be seen that 59,20% (three out of five participants) declared that they consider packaging to be very important decision factor contributing to the decision for the procurement of a product.
12. Packaging Significance for oil procurement RECORDED PERCENT
Non - significant 28 11,20%
Partially significant 74 29,60%
Very significant 148 59,20%
Table 12.1. Packaging significance for olive oil procurement
Moreover, another 29,60% declared that they consider packaging to be partially significant decision factor. Apparently this category of the interviewed population sample considers that other factors are equally or additionally relevant for the selection and procurement of a particular product.
12. Packaging significance
Non - significant Partially significant Very significant
11%
30% 59%
Figure 12.1. Percentages of packaging significance
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Only a small percentage of 11,20% is not taking into consideration the packaging for the determination of their procurement choice. Apparently, once again, this percentage represents the local olive oil producers who never procure olive oil from the supermarkets.
Additionally however, taking into consideration previous answers recorded, a large percentage of the same population sample, is procuring olive oil in bulk plastic containers from the local supermarkets, or oil in 5kg tin containers without bothering for any packaging attractiveness or finally they procure olive oil in bulk from local producers regardless of packaging.
13 Most important packaging detail
Referring to the following table 13.1 representing the results obtained together with the manipulated percentages through the spreadsheet utilized, as well as the graphical presentation of the achieved percentages of the figure 13.1, is obvious that the storing capability of the containers has attracted the vast opinion of 86,40% of the sampled individuals, that storing capability of the container is the most important packaging detail.
13. Most important packaging detail RECORDED PERCENT
Smart promotion 6 2,40%
Ease of usage 28 11,20%
Storing Capability 216 86,40%
Table 13.1. Most important packaging detail results
Apparently smart promotion attracting 2,40% of the sampled opinions, regardless how smart that the product promotion is expected to be, is nevertheless of no particular interest to the sampled population especially when other more important quality issues matter to be taken into consideration.
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13. Most important packaging detail
Smart promotion Ease of usage Storing capability
2% 11%
87%
Figure 13.1. Percentage results of the most important packaging detail
Ease of usage was another alternative choice which under the circumstances attracted a good 11,20%, regardless of its truly practical importance of usage friendliness of the product in a kitchen working environment.
Once again, taking seriously into consideration the above results particular attention should be paid to the training of the producers related with the storing capabilities of the packaging materials and techniques on how to avoid or decrease quality deterioration of the stored product.
14 Significance of packaging vs price
Regardless of the high interest rate shown by the sampled individuals, in the following table 14.1 illustrating the achieved results of the interview as well as the manipulated percentages, 42,40% of the sampled individuals consider the price to be a very decisive factor determining the final choice to either procure a certain product or not.
Equally important is the manipulated result that another almost equal percentage of 41,60% of the sampled population, also considers to be of partial significance for a decision to purchase a product to be made.
Therefore we could derive that 84% of the individuals do take into consideration the packaging arrangement when price represents a significant or even a partially significant decisive factor.
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14. Significance of packaging vs. price RECORDED PERCENT
Non-significant 40 16,00%
Partially significant 104 41,60%
Very significant 106 42,40%
Table 14.1. Significance of packaging vs. price results
However, as illustrated graphically on the figure 14.1 bellow, a 16,00% of the population is not likely to take into consideration packaging criteria when price represents an important decision factor taken into consideration instead.
14. Significance of packaging vs. product price Non - significant Partially significant Very significant
0% 16% 42%
42%
Figure 14.1. Achieved percentages of packaging vs. price
15 Best packaging material decision factors
The most important and decisive factor for the success of this statistical survey that was taken duly into consideration was the preference of the sampled individuals related to the packaging material of the targeted product. INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 46 of 53
This section was divided into two fragments:
1. The best packaging material and the
2. Color determination factors
In this respect, the results obtained and accordingly manipulated were the following:
15.1 Best packaging material for olive oil Referring to table 15.1, attached together with its associated figure 15.1 graphically representing the percentages obtained, is definitely obvious beyond any reasonable doubt, that glass container have attracted the unbiased and objective preference of 58,00% of the sampled population.
Another important percentage of 29,20% is preferring the metallic (tinned) containers coming in quantities of 5kg. Most probably this decision is based on the fact that the price difference between 1kg (generally glass or plastic) and 5kg containers of the same product is considerable. Alternatively, the once a month consumers prefer for practical, quality storage and preservation reasons prefer to procure the 5kg tin containers.
15. Best packaging material for olive oil RECORDED PERCENT
Glass 145 58,00%
Plastic 17 6,80%
Metallic 73 29,20%
Tetrapack 15 6,00%
Table 15.1. Results acquired for best packaging material for olive oil
What seems to be at a very low percentage is the recorded choice of 6,80% and attributed to the preference of plastic containers. It should be mentioned that there are numerous of olive oils brands sold in 1kg plastic bottles for a number of years, sharing the same shelves with the glass bottles in the supermarkets.
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15.1. Best Packaging material
Glass Plastic Metalic Tetrapack
6% 29%
58% 7%
Figure 15.1. Percentages obtained for best packaging material
Finally, 6,00% is the acquired results was attributed to the sampled population that prefer to procure oil in tetrapack containers. Although this percentage it seems to be negligible, however taking into consideration the fact that tetrapack containers locally are only utilized for wine, fruit juice and milk products and not for olive oil, this percentage seems to be considerable.
Color determination factors RECORDED PERCENT
Transparency enabling color testing 82 32,80%
Light weight container 6 2,40%
Bulk olive oil procurement 27 10,80%
Non-transparent for the prevention of sun rays 108 43,20%
Other 27 10,80%
Table 15.2. Manipulated results showing the factors choices depend upon
15.2 Color determination factors The influence of the color of the olive oil procured in the decision making process, was the final fragment under statistical analysis of this survey.
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Therefore, taking into consideration the recorded results and manipulated percentages shown on the following table 15.2 in association with the attached graphical presentation of the figure 15.2, there is a significant, clear and obvious opposition of opinion among those sampled participants who prefer to use transparent containers (32,80%) enabling them to check the color of the olive oil, with those who prefer dark, metallic containers (43,20%), in order to prevent the harmful sun rays from deteriorating the quality characteristics of the product.
There is however a significant percentage of 10,80% of the interviewed population which is not interested on the packaging of the product and their ability to test the color of the product, as they only procure bulk quantities of oil either from the local market or from the local producers.
15.2. Determination factors for product procurement
Transparency enabling color testing 11% Light weight container 33%
Bulk container procurement 43% 11% Non-transparent for the prevention of sun rays
2% Other
Figure 15.2. Transparency determination factors
Finally, without ignoring the 2,40% of those market customers who prefer light weight packaging regardless of packaging, quality considerations and quality deterioration due to the effects of the direct sunlight, the “Other” choice of 10,80% manipulated, once again is attributed to the local olive oil producers.
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4 DERIVED CONCLUSIONS
A surprising somehow high percentage of 82,27% of the sampled population has declared that they actually prefer to use olive oil whereas at the same time the quality of the olive oil procured is virtually totally unknown based on insignificant label information and the artistic capability and experience of the local producers. However the major conclusion of this survey is the fact that all sampled consumers, regardless whether they procure olive oil in small or bulk containers, metallic or plastic, transparent or dark the only decisive factor for their main choice and concern is product quality.
Therefore, this statistical survey provides producers and consumers of olive oil, substantially covering all ages of consumers, with valuable information related with the cultivation quality requirements of the fruit and the significance of each controlled processing stage necessary to produce extra virgin oil, as well as the interfering factors related with the subsequent natural deterioration (oxidation) that the oil will unfortunately undergo.
Total luck of quality assurance knowledge and product demand is the prevailing outcome of this exercise. Through the 2nd Section of this deliverable, was made quite clear that besides the oxidation criteria affecting the quality of olive oil, there are other important factors that have to be taken into consideration in order to produce and classify olive oil. It is additionally imperative for the consumers to realize that they should seek quality certificates either on the labels of the products they procure, or from the local producers when they procure bulk quantities of oil without any proof of quality indexes. As a matter of fact, the local producers should follow the recommendations appearing on the common cultivation and production protocols, as well as demand from the oil millers’ full quality lab tests in order to ascertain the quality of their product and for each processed batch. These recommended procedures and protocols will enable them to produce originally olive fruits of superb quality and the resulting olive oil will be of extra virgin quality. Certified production procedures will enable them to promote their product easily either to the local market or to the national and European market.
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Evidently, a large percentage of the sampled population is producing its own olive oil and besides the oxidation index and the in situ taste of the product no other quality criteria either during cultivation, during the extraction process and during the storage period is taken into consideration. Surly, even if their final product falls within the extra virgin oil specifications, still they don’t know how good the quality indexes are, even if they are within the extra virgin limits and surly they don’t know how to improve and/or maintain them.
It has also been shown that another reasonable percentage of the sampled population is procuring bulk olive oil from the local producers relying entirely on their artistic assessment regarding the quality of their product. In this respect, the bulk quantity customers from the local supermarkets utilize “other” containers to store their olive oil. These containers usually and traditionally are metallic tin 17.5kg containers, which most probably provide adequate storage quality protection in order to preserve the qualitative characteristics of the olive oil which unfortunately deteriorate with time and/or direct sunlight.
Storage quality by far is another main consideration of the sampled population. In this respect it should also be noted that although container residue considerations of the storage containers didn’t constitute part of this project, however olive pomace residues due to lack of proper olive filtration in any type of containers, results in quick deterioration of the quality indexes of the stored olive oil. The consumers should be informed about the need of occasional filtering and change of containers in order to collect the oil sentiment and avoid the development of a muddy and rotten organoleptic taste of the product. Even during harvesting the collected fruit should be washed carefully from accumulated dust and soil that might has been accumulated during collection. This action will contribute to the reduction of the K factors mentioned on the 2nd Section considerably.
Clear or transparent containers were only preferred by 32,80% of the sampled population. Most probably this percentage refers to the oil containers used for the weekly consumption needs of the families. This percentage coincides with that percentage of the consumers which prefer to procure olive oil weekly. However the olive oil shelf life contained in transparent containers is reduced considerably compared with the metallic or nowadays the tetra pack packages. In this respect, although tetra pack containers have received a low 6,00% preference via the sampled population, nevertheless this percentage is contributed to local market unavailability and obviously the lack of its quality advantages. Probably suitable provision of a small plastic window on the 1kg or INNOVOIL Project. Territorial Cooperation Programme “Greece – Italy 2007 – 2014, Market Research Analysis. Regional Unit of Thesprotia (P6) Page 51 of 53
bulk quantity tetrapack packages, like the ones improvised at the nozzles of the 5kg metallic packages, enabling color inspection of the product, will improve considerably and probably unbeatably the preference of the tetra pack package.
Price on the other hand is considered to be non-significant by the 42,00% of the sampled population. The obtained quality versus price results, undoubtedly show that consumers regardless of the current economic crisis, are prepared to pay more for the procurement of a quality product instead of sacrificing quality for a better price.
In terms of the most important label information more or less 80,00% of the sampled population prefer their oil to be of Greek origin, regardless of the inherent quality uncertainties of the product due to the lack of associated laboratory quality test and the lack of proper information related with the bulk procurement through the local producers. Apparently, traditional awareness of the producers and consumers based on their inherent and artistic organoleptic testing (smell, color, clarity, taste, swallowing), acidity measurements and years of related experience, enabled them to predict the quality of their oil. However, in order to improve or maintain the existing quality the common cultivation, production and storage protocol considerations developed through this project should be adhered to.
Qualitative information provided by a limited manner either on the labels of the products, or through the experience of the producers, definitely is of prime importance from the majority of the interviewed customers. Obviously, if the majority of the qualitative criteria and their maximum permissible limits will be attached on the labels of the market products or through associated quality certificates of the bulk olive oil producers, will enhance considerably the marketing promotion and the value of the product. The place and establishment of origin is definitely desirable to be known, however knowledge of the quality indexes should be an uncompromised priority.
Another factor of this survey is related with the procurement of organic products, which apparently represents another high percentage prerequisite of the interviewed population. Additionally, as a result of the laboratory quality testing of this project, in this region the majority of the orchards do not get any kind of chemical fertilization, insecticides and pesticides other than, in some remote instances “Mediterranean Fly” insecticides. However, organic fertilization, pruning and surly irrigation of the olive trees is of prime importance in order to produce a fruit of high nutritional value, whereas at the same time secure the
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maximum possible production of extra virgin oil. Therefore, organic olive oil is easily possible to be produced from the currently existing orchards.
Finally, it should be noted for another time that the main outcome of this statistical survey is the fact that in order to procure a high quality product as demanded in so many diversified ways from the interviewed population, qualitative cultivation procedures, production considerations and storage requirements should be taken into consideration in order to produce extra virgin oil of superb nutritional and organoleptic characteristics, paying particular attention to the protection of the environment by minimizing the liquid effluents and their proper disposal.
On behalf of the Regional Unit of Thesprotia
Sotiris Georgoulis (BSc, MSc)
Process Control & Computer Engineer
Technical Consultant of the INNOVOIL project
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