| Literature DB >> 35329081 |
Jose Antonio Cava Jimenez1, Mª Genoveva Millán Vázquez de la Torre2, Mª Genoveva Dancausa Millán3.
Abstract
The profile of tourists during the COVID-19 pandemic is changing toward those seeking health, safety and quality products. One of the modalities that best adapts to these needs is gastronomic tourism and, within this segment, wine tourism (enotourism), which can be enjoyed in many areas across the world. The great diversity of grapes, climates, terrains and winemaking processes gives rise to an enormous variety of wines that ensures that no two wines are alike. The current situation of the tourism market necessitates enhancing the uniqueness of areas that offer differentiated products, helping to position such locations as benchmarks for gastronomic tourism. Gastronomic routes provide a way to unify and benefit rural areas through the recently increased demand of tourists seeking to experience regional foods. In this study, the Montilla-Moriles Wine Route is analyzed with the objective of forecasting the demand (using autoregressive integrate moving average, ARIMA models), establishing a tourist profile and calculating the probability that a wine tourist is satisfied with the visit based on their personal characteristics (logit model). The results obtained indicate a slight increase (3.6%) in wine tourists with a high degree of satisfaction, primarily derived from the gastronomic or catering services of the area, from the number of wineries visited, from the treatment received and from the age of the tourist. Consequently, a high percentage of these tourists recommend the route. By increasing the demand for enotourism in this area and applying the results obtained, marketing initiatives could be established, particularly for wine festivals to improve this tourist segment and generate wealth in that area.Entities:
Keywords: ARIMA; Montilla-Moriles; gastronomic routes; gastronomic tourism; logit model; protected designation of origin
Mesh:
Year: 2022 PMID: 35329081 PMCID: PMC8954465 DOI: 10.3390/ijerph19063393
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Elements of a gastronomic route. Source: Own elaboration.
Protected designations of origin and protected geographical indications of Spain (year 2021).
| Agri-Food Products | PDO | PGI | ||
|---|---|---|---|---|
| Spain | Andalusia | Spain | Andalusia | |
| Fresh meat (and offal) | - | - | 22 | - |
| Meat products | 5 | 1 | 11 | 2 |
| Cheeses | 27 | - | 2 | - |
| Other products of animal origin (honey | 3 | 1 | 4 | - |
| Oils and fats (32 oils and 2 butters) | 34 | 13 | 3 | 1 |
| Fresh and processed fruit, vegetables and grains | 1 | - | 4 | 4 |
| Other products (saffron, paprika, chufa (nutsedge), hazelnut, vinegar, cider) | 9 | 3 | - | - |
| Bakery, confectionary, pastry and biscuit products | - | - | 16 | 4 |
| Suckling pig (Cochinilla) | 1 | - | - | - |
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| Wine with a designation of origin (DO) | 73 | 6 | - | - |
| Wine with a guaranteed designation of origin (DOCa) | 2 | - | - | - |
| Wine of quality with a geographical indication (VC) | 10 | 2 | - | - |
| Vinos de Pago (VP) = Quality wines from a single estate that fall outside the DO | 11 | - | - | - |
| Wine with a geographical indication (GI) | - | - | 42 | 16 |
| Aromatized wine | - | - | 1 | 1 |
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| Spirits with PGIs | - | - | 19 | 1 |
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Source: Own elaboration based on data from the Ministry of Agriculture, Fisheries and Food (MAPA) [46].
Protected designations of origin and protected geographical indications for wine in the European Union (2021).
| Country | PDO | PGI |
|---|---|---|
| Greece | 33 | 45 |
| Spain | 96 | 43 |
| Italy | 420 | 127 |
| Netherland | 9 | 12 |
| Portugal | 36 | 17 |
| France | 478 | 76 |
| Belgium | 8 | 2 |
| Bulgaria | 54 | 1 |
| Czechia | 11 | 2 |
| Denmark | 1 | 4 |
| Germany | 19 | 26 |
| Cyprus | 7 | 4 |
| Luxembourg | 1 | |
| Hungary | 49 | 7 |
| Malt | 2 | 1 |
| Austria | 34 | 3 |
| Romania | 42 | 14 |
| Slovenia | 14 | 3 |
| Slovakia | 8 | 1 |
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Source: Own elaboration based on data from the Ministry of Agriculture, Fisheries and Food (MAPA) [46].
Figure 2Protected designations of origin for wine in Spain (2021). Source: Ministry of Agriculture, Fisheries and Food (MAPA) [46].
Figure 3Wine routes in Spain by autonomous community (year 2021). Source: Own elaboration based on data from the Ministry of Agriculture, Fisheries and Food (MAPA) [46].
Figure 4Number of visitors and wine routes in Spain (2019). Source: Own elaboration based on ACEVIN data [93].
Figure 5“Montilla-Moriles” wine route. Source ACEVIN.
Fact sheet for the survey.
| Offer Survey | Demand Survey | |
|---|---|---|
| Population | Companies that are part of AVINTUR and the wineries that belong to the Montilla-Moriles Regulatory Council | Tourists of any gender over 18 years old who undertook/visited a route/PDO/PGI Montilla-Moriles |
| Sample size | 39 | 500 |
| Sampling error | ±4.7% | ±3.9% |
| Sampling System | Simple Random | Simple Random |
| Level of confidence | 95%; p = q = 0.5 | 95%; p = q = 0.5 |
| Date of fieldwork | February to May 2019 | February to December 2019 |
Source: Own elaboration.
Logit model estimation.
| Dependent Variable: Satisf | ||||
|---|---|---|---|---|
| Method: ML—Binary Logit (Quadratic Hill Climbing) | ||||
| Variable | Estimated | Standard | Z | Prob |
| Intercept | B0 = 2.325 | 0.103 | 22.572 | 0.010 |
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| B1 = 0.631 | 0.002 | 315.500 | 0 |
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| B2 = 12.253 | 2.251 | 5.443 | <0.0002 |
| Professional, | B3 = 9.256 | 1.425 | 6.495 | <0.0002 |
| Entrepreneur, | B4 = 0.042 | 0.001 | 42.000 | 0 |
| Management, | B5 = 0.035 | 0.002 | 17.500 | 0 |
| Official, | B6 = 13.564 | 1.561 | 8.689 | <0.0002 |
| Skilled worker, | B7 = 17.891 | 3.458 | 5.174 | <0.0002 |
| Self-employed, | B8 = 10.584 | 2.231 | 4.744 | <0.0002 |
| Student, | B9 = −0.058 | 0.001 | −58.000 | 0 |
| Homemaker, | B10 = 9.856 | 2.521 | 3.909 | <0.0002 |
| Retired, | B11 = 8.642 | 1.658 | 5.212 | <0.0002 |
| Family income, | B12 = 15.324 | 2.567 | 5.969 | <0.0002 |
| Traveling alone, | B13 = −0.567 | 1.261 | −0.449 | 0.3264 * |
| Traveling as a couple, | B14 = 7.368 | 3.457 | 2.131 | 0.0166 |
| Traveling with family, | B15 = 14.658 | 1.578 | 9.289 | <0.0002 |
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| B16 = 4.328 | 0.679 | 6.374 | <0.0002 |
| Traveling with friends, | B17 = 6.745 | 2.012 | 3.352 | <0.0002 |
| Number of visits, | B18 = 2.561 | 0.123 | 20.821 | 0 |
| Expenditures, | B19 = 1.568 | 0.111 | 14.126 | 0 |
| Would recommend trip, | B20 = 14.572 | 2.877 | 5.065 | <0.0002 |
| Vacation days, | B21 = 0.045 | 0.001 | 45.000 | 0 |
| Wineries visited, | B22 = 17.568 | 3.684 | 4.768 | <0.0002 |
| Lodging opinion, | B23 = 0.536 | 0.014 | 38.285 | 0 |
| Complementary activities, | B24 = −4.983 | 1.021 | −4.881 | <0.0002 |
| Trip price, | B25 = −1.253 | 0.014 | 89.500 | 0 |
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| B26 = 3.762 | 0.985 | 3.819 | <0.0002 |
| Environmental conservation, | B27 = 1.236 | 0.021 | 58.857 | 0 |
| Information and signage, | B28 = 0.023 | 0.002 | 11.501 | <0.0002 |
R2 McFadden = 0.56. * All the parameters are significant α = 0.05 except B13. Source: Own elaboration.
Figure 6Evolution of enotourism demand in the Montilla-Moriles PDO (thousand tourists, January 2015 February 2020). Source. Own elaboration.
Figure 7Comparison of real enotourism (actual), estimated enotourism (fitted) and errors (residual). Source. Own elaboration.
Estimation results for the GARCH model.
| Dependent Variable: D(ENOTOURIST1,12) | ||||
|---|---|---|---|---|
| Method: ML ARCH (Marquardt) Normal Distribution | ||||
| GARCH = C(3) + C(4)*RESID(−1)2 | ||||
| Variable | Coefficient | Std. Error | z-Statistic | Prob. |
| AR(1) | −1.078216 | 0.040729 | −26.47281 | 0.0000 |
| MA(1) | −0.997914 | 0.009812 | −101.7076 | 0.0000 |
| Variance Equation | ||||
| C | 14419635 | 5663686. | 2.545981 | 0.0109 |
| RESID(−1)2 | −2.393621 | 1.099372 | −2.177263 | 0.0295 |
| R-squared | 0.910115 | Mean dependent var | −77.28674 | |
Source. Own elaboration.
Predictions of enotourism demand for the Montilla-Moriles PDO.
| Month | Year 2019 | Year 2022 | Difference |
|---|---|---|---|
| January | 636 | 735 | 99 |
| February | 779 | 824 | 45 |
| March | 1258 | 1328 | 70 |
| April | 2446 | 2566 | 120 |
| May | 3725 | 3846 | 121 |
| June | 2538 | 2624 | 86 |
| July | 2601 | 2700 | 99 |
| August | 2589 | 2695 | 106 |
| September | 4701 | 4928 | 227 |
| October | 3325 | 3432 | 107 |
| November | 2708 | 2652 | −56 |
| December | 3824 | 3924 | 100 |