A Multicriteria Analysis to Support Natural Resource Governance: The Case of Chestnut Forests
Abstract
:1. Introduction
1.1. Governance of Natural Resources
1.2. Strategies for Natural Resources
1.3. Multicriteria Decision Analysis and Its Classifications
- Selection: the best alternative is chosen from a small number of satisfactory alternatives;
- Sorting: alternatives are assigned to predefined categories;
- Ranking: alternatives are placed in descending order of preference, from best to worst;
- Description: the main characteristics of the alternatives are identified.
- Partially compensatory methods: Criteria with high value can only partially compensate those with low value. This category includes ELECTRE (elimination et choix traduisant la realité) [32], PROMETHEE (preference ranking organization method for enrichment evaluations) [33] and TOPSIS (technique for order of preference by similarity to ideal solution) [34].
- (H1) Several environmental, social, and economic factors contribute to the evaluation of the natural resource.
- (H2) Factors related to the resource have little leverage on governance strategies.
- (H3) Factors to the external environment have good leverage on governance strategies.
- (H4) Economic factors are prioritised to trigger new governance strategies.
2. Materials and Methods
2.1. Case Study
2.2. A’WOT
- Identification of the goal/problem to be achieved or solved and its breakdown into sub-elements that are easier to understand. In the case of the A’WOT, these sub-elements are the SWOT criteria and the relative factors of each criterion (Figure 1).
- 2.
- Pairwise comparisons of factors, by respondents, for the respective criteria identified. The number of pairwise comparisons is based on a combination and depends on the number of factors (m) present (Equation (1)).
- 3.
- Creation of a square matrix (Table 3), the so-called pairwise comparison matrix, in which the value of cell (j,i) is the reciprocal of that of cell (I,j). The values in the matrix correspond to the judgements expressed by the respondent. If the value of the ith cell is greater than 1, this factor is preferred over its respective value in the jth cell. The diagonal, on the other hand, has cell values equal to 1. This matrix is made for each group of factors compared and the values are then returned in aggregate form with the judgements of all respondents.
- 4.
- Identification of the principal eigenvalue (λmax) and the normalised principal eigenvector, also referred to as the priority vector. The latter corresponds to the weights of the individual factors under evaluation and is first derived by obtaining the sum of the individual columns of the pairwise comparison matrix. Then, the matrix values are normalised by dividing the individual cell value by that of the corresponding column sum. Finally, the average of the row sum of the normalised values will return the eigenvector. The eigenvalue, on the other hand, is obtained by summing the normalised principal eigenvector, multiplied by the respective column sums.
- 5.
- Analysis of the consistency of the judgements through the creation of the consistency index (CI, Equation (2)). Since the judgements are subjective, the technique tolerates up to a certain threshold value of inconsistency. If the consistency index fails, the judgements are inconsistent, and the evaluation questionnaire must be reformulated and pairwise comparisons repeated.
- 6.
- Local priorities are obtained from the weights of the different factors. These priorities are then multiplied by the weight of the relevant criterion to obtain the overall priorities.
2.3. Data Collection
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- UNFCCC. What Is the Triple Planetary Crisis? Available online: https://unfccc.int/blog/what-is-the-triple-planetary-crisis (accessed on 3 January 2023).
- IRP. Global Resources Outlook 2019: Natural Resources for the Future We Want; Oberle, B., Bringezu, S., Hatfield-Dodds, S., Hellweg, S., Schandl, H., Clement, J., Cabernard, L., Che, N., Chen, D., Droz-Georget, H., et al., Eds.; A Report of the International Resource Panel; United Nations Environment Programme: Nairobi, Kenya, 2019; p. 162. [Google Scholar]
- Graham, J.; Amos, B.; Plumptre, T. Governance Principles for Protected Areas in the 21st Century; Institute on Governance: Ottawa, ON, Canada, 2003; p. 50. [Google Scholar]
- Bauer, T.; de Jong, W.; Ingram, V.; Arts, B.; Pacheco, P. Thriving in Turbulent Times: Livelihood Resilience and Vulnerability Assessment of Bolivian Indigenous Forest Households. Land Use Policy 2022, 119, 106146. [Google Scholar] [CrossRef]
- Luyen, N.T.; Son, N.T. The Importance of Socio-Economic Development to Sustainable Natural Resources Management in Rural Areas: A Case Study of Sustainable Livelihoods and Forest Management in Xuan Nha Nature Reserve in Northwestern Vietnam. Vietnam. J. Agric. Sci. 2022, 5, 1345–1358. [Google Scholar] [CrossRef]
- UN. United Nations Conference on Environment and Development, Rio de Janeiro, Brazil, 3–14 June 1992. Available online: https://www.un.org/en/conferences/environment/rio1992 (accessed on 3 January 2023).
- UN. The 17 GOALS|Sustainable Development. Available online: https://sdgs.un.org/goals (accessed on 3 January 2023).
- UNFCCC Paris Agreement. Climate Action—European Commission. Available online: https://ec.europa.eu/clima/eu-action/international-action-climate-change/climate-negotiations/paris-agreement_en (accessed on 29 October 2021).
- Springer, J.; Campese, J.; Nakangu, B. The Natural Resource Governance Framework—Improving Governance for Equitable and Effective Conservation; IUCN: Gland, Switzerland, 2021; ISBN 978-2-8317-2161-3. [Google Scholar]
- FAO. Framework for Environmental and Social Management; FAO: Rome, Italy, 2022; ISBN 978-92-5-136118-4. [Google Scholar]
- Li, B.; Zhang, H.; Huang, K.; He, G.; Guo, S.; Hou, R.; Zhang, P.; Wang, H.; Pan, H.; Fu, H.; et al. Regional Fauna-Flora Biodiversity and Conservation Strategy in China. iScience 2022, 25, 104897. [Google Scholar] [CrossRef] [PubMed]
- Pfeifer, M.; Sallu, S.M.; Marshall, A.R.; Rushton, S.; Moore, E.; Shirima, D.D.; Smit, J.; Kioko, E.; Barnes, L.; Waite, C.; et al. A Systems Approach Framework for Evaluating Tree Restoration Interventions for Social and Ecological Outcomes in Rural Tropical Landscapes. Philos. Trans. R. Soc. B Biol. Sci. 2023, 378, 20210111. [Google Scholar] [CrossRef]
- Mansourian, S.; Parrotta, J.; Balaji, P.; Bellwood-Howard, I.; Bhasme, S.; Bixler, R.P.; Boedhihartono, A.K.; Carmenta, R.; Jedd, T.; de Jong, W.; et al. Putting the Pieces Together: Integration for Forest Landscape Restoration Implementation. Land Degrad. Dev. 2020, 31, 419–429. [Google Scholar] [CrossRef]
- Davis, E.J.; Huber-Stearns, H.; Caggiano, M.; McAvoy, D.; Cheng, A.S.; Deak, A.; Evans, A. Managed Wildfire: A Strategy Facilitated by Civil Society Partnerships and Interagency Cooperation. Soc. Nat. Resoure 2022, 35, 914–932. [Google Scholar] [CrossRef]
- Mattila, O.; Hämäläinen, K.; Häyrinen, L.; Berghäll, S.; Lähtinen, K.; Toppinen, A. Strategic Business Networks in the Finnish Wood Products Industry: A Case of Two Small and Medium-Sized Enterprises. Silva Fenn. 2016, 50, 8. [Google Scholar] [CrossRef] [Green Version]
- Deane, F.; Hamman, E.; Huggins, A. Market-Based Instruments, Ecosystem Services and Natural Capital; Edward Elgar Publishing: Cheltenham, UK, 2022; pp. 84–115. ISBN 978-1-83910-416-9. [Google Scholar]
- Molinaro, M.; Orzes, G. From Forest to Finished Products: The Contribution of Industry 4.0 Technologies to the Wood Sector. Comput. Ind. 2022, 138, 103637. [Google Scholar] [CrossRef]
- Graversgaard, M.; Jacobsen, B.H.; Hoffmann, C.C.; Dalgaard, T.; Odgaard, M.V.; Kjaergaard, C.; Powell, N.; Strand, J.A.; Feuerbach, P.; Tonderski, K. Policies for Wetlands Implementation in Denmark and Sweden – Historical Lessons and Emerging Issues. Land Use Policy 2021, 101, 105206. [Google Scholar] [CrossRef]
- Awoke, A.; Beyene, A.; Kloos, H.; Goethals, P.L.M.; Triest, L. River Water Pollution Status and Water Policy Scenario in Ethiopia: Raising Awareness for Better Implementation in Developing Countries. Environ. Manag. 2016, 58, 694–706. [Google Scholar] [CrossRef]
- Warren, B.; Nanus, B. Leaders. The Strategies for Taking Charges (Translated into Italian: Leader, Anatomia Della Leadership: Le 4 Chiavi della Leadership Effettiva); Franco Angeli: Milan, Italy, 1993; p. 216. ISBN 978-88-204-7899-5. [Google Scholar]
- Ceballos, B.; Lamata, M.T.; Pelta, D.A. A Comparative Analysis of Multi-Criteria Decision-Making Methods. Prog. Artif. Intell. 2016, 5, 315–322. [Google Scholar] [CrossRef]
- Dodgson, J.S.; Spackman, M.; Pearman, A.; Phillips, L.D. Multi-Criteria Analysis: A Manual; Department for Communities and Local Government: London, UK, 2009. [Google Scholar]
- Dean, M. Chapter Six—Multi-Criteria Analysis. In Advances in Transport Policy and Planning; Mouter, N., Ed.; Standard Transport Appraisal Methods; Academic Press: Cambridge, MA, USA, 2020; Volume 6, pp. 165–224. [Google Scholar]
- Danila, N. Méthodologie multicritère d’aide à la décision. Polit. Et Manag. Public 1986, 4, 138–140. [Google Scholar]
- Bottero, M.; Lami, I.M.; Lombardi, P. Analytic Network Process: The Evaluation of Urban and Spatial Transformation Scenarios (Original Version: Analytic Network Process: La Valutazione Di Scenari Di Trasformazione Urbana e Territoriale); Alinea Editrice: Mantova, Italy, 2008; p. 160. ISBN 88-6055-315-6. [Google Scholar]
- Bakır, M.; Atalık, Ö. Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry. Decis. Mak. Appl. Manag. Eng. 2021, 4, 127–152. [Google Scholar] [CrossRef]
- Moradpanah, M.; Monavari, S.M.; Shariat, S.M.; Mohammadi, M.K.; Ghajar, I. Evaluation of Ecological Vulnerability of Coasts of the Caspian Sea Based on Multi-Criteria Decision Methods (Iran). J. Indian Soc. Remote Sens. 2022, 50, 2479–2502. [Google Scholar] [CrossRef]
- Ibrahim, A.; Surya, R.A. The Implementation of Simple Additive Weighting (SAW) Method in Decision Support System for the Best School Selection in Jambi. J. Phys. Conf. Ser. 2019, 1338, 012054. [Google Scholar] [CrossRef] [Green Version]
- Pérez-Cañedo, B.; Verdegay, J.L.; Rosete, A.; Concepción-Morales, E.R. A Multi-Objective Berth Allocation Problem in Fuzzy Environment. Neurocomputing 2022, 500, 341–350. [Google Scholar] [CrossRef]
- Janani, K.; Pradeepa Veerakumari, K.; Vasanth, K.; Rakkiyappan, R. Complex Pythagorean Fuzzy Einstein Aggregation Operators in Selecting the Best Breed of Horsegram. Expert Syst. Appl. 2022, 187, 115990. [Google Scholar] [CrossRef]
- Yang, F.; Zhao, F.; Liang, L.; Huang, Z. SMAA-AD Model in Multicriteria Decision-Making Problems with Stochastic Values and Uncertain Weights. Ann. Data. Sci. 2014, 1, 95–108. [Google Scholar] [CrossRef]
- Nesticò, A.; Passaro, R.; Maselli, G.; Somma, P. Multi-Criteria Methods for the Optimal Localization of Urban Green Areas. J. Clean. Prod. 2022, 374, 133690. [Google Scholar] [CrossRef]
- Abacı, N.; İç, Y.T. Variable Refrigerant Flow Air Conditioning System Applicant Company Selection Using PROMETHEE Method. Int. J. Energy Environ. Eng. 2022, 13, 1177–1204. [Google Scholar] [CrossRef]
- Corrente, S.; Tasiou, M. A Robust TOPSIS Method for Decision Making Problems with Hierarchical and Non-Monotonic Criteria. Expert Syst. Appl. 2023, 214, 119045. [Google Scholar] [CrossRef]
- Vanderpooten, D. The Interactive Approach in MCDA: A Technical Framework and Some Basic Conceptions. Math. Comput. Model 1989, 12, 1213–1220. [Google Scholar] [CrossRef]
- Anteneh, Z.S.; Awoke, B.G.; Reda, T.M.; Jothimani, M. Groundwater Potential Mapping Using Integrations of Remote Sensing and Analytical Hierarchy Process Methods in Ataye-Watershed, Middle Awash Basin, Ethiopia. Sustain. Water Resoure Manag. 2022, 8, 183. [Google Scholar] [CrossRef]
- Anuradha; Gupta, S. AHP-Based Multi-Criteria Decision-Making for Forest Sustainability of Lower Himalayan Foothills in Northern Circle, India-a Case Study. Environ. Monit. Assess 2022, 194, 849. [Google Scholar] [CrossRef]
- Shelar, R.S.; Shinde, S.P.; Pande, C.B.; Moharir, K.N.; Orimoloye, I.R.; Mishra, A.P.; Varade, A.M. Sub-Watershed Prioritization of Koyna River Basin in India Using Multi Criteria Analytical Hierarchical Process, Remote Sensing and GIS Techniques. Phys. Chem. Earth Parts A/B/C 2022, 128, 103219. [Google Scholar] [CrossRef]
- Bianco, S.; Marcianò, C. Using an Hybrid AHP-SWOT Method to Build Participatory Ecotourism Development Strategies: The Case Study of the Cupe Valley Natural Reserve in Southern Italy. In New Metropolitan Perspectives; Calabrò, F., Della Spina, L., Bevilacqua, C., Eds.; Springer: Cham, Switzerland, 2019; pp. 327–336. [Google Scholar]
- Lee, S.; Kim, D.; Park, S.; Lee, W. A Study on the Strategic Decision Making Used in the Revitalization of Fishing Village Tourism: Using A’WOT Analysis. Sustainability 2021, 13, 7472. [Google Scholar] [CrossRef]
- Ossadnik, W.; Schinke, S.; Kaspar, R.H. Group Aggregation Techniques for Analytic Hierarchy Process and Analytic Network Process: A Comparative Analysis. Group Decis Negot 2016, 25, 421–457. [Google Scholar] [CrossRef] [Green Version]
- Bruzzese, S.; Blanc, S.; Brun, F. Strategies for the Valorisation of Chestnut Resources in Italian Mountainous Areas from a Sustainable Development Perspective. Resources 2020, 9, 60. [Google Scholar] [CrossRef]
- Gasparini, P.; Di Cosmo, L.; Floris, A. Area and Characteristics of Italian Forests. In Italian National Forest Inventory—Methods and Results of the Third Survey: Inventario Nazionale delle Foreste e dei Serbatoi Forestali di Carbonio—Metodi e Risultati della Terza Indagine; Gasparini, P., Di Cosmo, L., Floris, A., De Laurentis, D., Eds.; Springer Tracts in Civil Engineering; Springer International Publishing: Cham, Switzerland, 2022; pp. 151–325. ISBN 978-3-030-98678-0. [Google Scholar]
- Gabrielli, A. The Civilization of the Chestnut Tree (Original Version: La Civiltà Del Castagno). Monti E Boschi 1994, 65, 3. [Google Scholar]
- Mariotti, B.; Maltoni, A.; Maresi, G. Tradition, innovation and sustainability: Silviculture for the chestnut tree (original version: Tradizione, innovazione e sostenibilità: Una selvicoltura per il castagno da frutto). In Atti del III Congresso Nazionale Selvicoltura Taormina (ME); Accademia italiana di scienze forestali: Florence, Italy, 2008; Volume 1619, pp. 851–857. [Google Scholar]
- Manetti, M.C.; Becagli, C.; Carbone, F.; Corona, P.; Giannini, T.; Romano, R.; Pelleri, F. Guidelines for silviculture of chestnut coppices (original version: Linee guida per la selvicoltura dei cedui di castagno). Rete Rural. Naz. 2017, 3, 275–295. [Google Scholar]
- Kurttila, M.; Pesonen, M.; Kangas, J.; Kajanus, M. Utilizing the Analytic Hierarchy Process (AHP) in SWOT Analysis—A Hybrid Method and Its Application to a Forest-Certification Case. For. Policy Econ. 2000, 1, 41–52. [Google Scholar] [CrossRef]
- Jayaprakash, S.; Swamy, V. Spatial SWOT Analysis: An Approach for Urban Regeneration. In Recent Advances in Civil Engineering; Nandagiri, L., Narasimhan, M.C., Marathe, S., Eds.; Springer: Singapore, 2023; pp. 21–38. [Google Scholar]
- Da Silva, R.P.; Fernandes, A.H.S.; Carneiro, P.T.d.S.; Gurgel, A.L.C.; Santos, V.L.F. Strategic Diagnosis of a Property Specialized in Breeding, Rearing and Finishing Beef Cattle in the Southern Region of Piauí. Acta Scientiarum. Anim. Sci. 2022, 45, 12. [Google Scholar] [CrossRef]
- Andriani, A.; Adji, B.M.; Ramadhani, S. The Analysis of Impact and Mitigation of Landslides Using Analytical Hierarchy Process (AHP) Method. In Proceedings of the 5th International Conference on Rehabilitation and Maintenance in Civil Engineering, Surakarta, Indonesia, 8–9 July 2021; Kristiawan, S.A., Gan, B.S., Shahin, M., Sharma, A., Eds.; Springer: Singapore, 2023; pp. 457–466. [Google Scholar]
- Ranji, A.; Parashkoohi, M.G.; Zamani, D.M.; Ghahderijani, M. Evaluation of Agronomic, Technical, Economic, and Environmental Issues by Analytic Hierarchy Process for Rice Weeding Machine. Energy Rep. 2022, 8, 774–783. [Google Scholar] [CrossRef]
- Varolgüneş, F.K.; Çelik, F.; Del Río-Rama, M.d.l.C.; Álvarez-García, J. Reassessment of Sustainable Rural Tourism Strategies after COVID-19. Front. Psychol. 2022, 13, 13. [Google Scholar] [CrossRef]
- Cagliero, R.; Bellini, F.; Marcatto, F.; Novelli, S.; Monteleone, A.; Mazzocchi, G. Prioritising CAP Intervention Needs: An Improved Cumulative Voting Approach. Sustainability 2021, 13, 3997. [Google Scholar] [CrossRef]
- Novelli, S.; Vercelli, M.; Ferracini, C. An Easy Mixed-Method Analysis Tool to Support Rural Development Strategy Decision-Making for Beekeeping. Land 2021, 10, 675. [Google Scholar] [CrossRef]
- Saaty, R.W. The Analytic Hierarchy Process—What It Is and How It Is Used. Math. Model. 1987, 9, 161–176. [Google Scholar] [CrossRef] [Green Version]
- Goodman, L.A. Snowball Sampling. Ann. Math. Stat. 1961, 32, 148–170. [Google Scholar] [CrossRef]
- Pesonen, M.; Kurttila, M.; Kangas, J.; Kajanus, M.; Heinonen, P. Assessing the Priorities Using A’WOT Among Resource Management Strategies at the Finnish Forest and Park Service. For. Sci. 2001, 47, 534–541. [Google Scholar]
- Marini, F.; Portoghesi, L.; Manetti, M.C.; Salvati, L.; Romagnoli, M. Gaps and Perspectives for the Improvement of the Sweet Chestnut Forest-Wood Chain in Italy. Ann. Silvic. Res. 2021, 46, 16. [Google Scholar] [CrossRef]
- Becagli, C.; Amorini, E.; Fratini, R.; Manetti, M.C.; Marone, E. Problems and Prospects of the Chestnut Timber Chain in Tuscany. Acta Hortic. 2010, 693–700. [Google Scholar] [CrossRef]
- European Union SWOT (Strenghts, Weakness, Opportunities, Threats). Available online: https://europa.eu/capacity4dev/evaluation_guidelines/wiki/swot-strenghts-weakness-opportunities-threats-0 (accessed on 4 January 2023).
- Gürel, E.; Tat, M. SWOT Analysis: A Theoretical Review. J. Int. Soc. Res. 2017, 10, 994–1006. [Google Scholar] [CrossRef]
- Sarsby, A. A Useful Guide to SWOT Analysis; Pansophix Online: Nottingham, UK, 2012; ISBN 978-1-906460-89-1. [Google Scholar]
- Koo, L.c.; Koo, H. Holistic Approach for Diagnosing, Prioritising, Implementing and Monitoring Effective Strategies through Synergetic Fusion of SWOT, Balanced Scorecard and QFD. World Rev. Entrep. Manag. Sustain. Dev. 2007, 3, 62–78. [Google Scholar] [CrossRef] [Green Version]
- Lingua, F.; Mosso, A.; Brun, F.; Blanc, S. A Survey of Innovative Training Preferences Among Italian Loggers. Small-Scale For. 2019, 18, 21–38. [Google Scholar] [CrossRef]
- Negro, F.; Blanc, S.; Bruzzese, S.; Falaschi, A.; Ruffinatto, F.; Zanuttini, R.; Brun, F. Web-Based Communication of Wooden Sport Equipment: An Analysis Based on Six Olympic Sports. Forests 2022, 13, 1364. [Google Scholar] [CrossRef]
- Bruzzese, S.; Blanc, S.; Merlino, V.M.; Massaglia, S.; Brun, F. Civil Society’s Perception of Forest Ecosystem Services. A Case Study in the Western Alps. Front. Psychol. 2022, 13, 1000043. [Google Scholar] [CrossRef]
- Bruzzese, S.; Ahmed, W.; Blanc, S.; Brun, F. Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter. Int. J. Environ. Res. Public Health 2022, 19, 15012. [Google Scholar] [CrossRef] [PubMed]
Criteria | Factors |
---|---|
Strengths | S1. Good availability of the resource |
S2. Provision of ecosystem services (cultural and protection) | |
S3. Richness of wood assortments | |
S4. Chestnut tradition of use | |
S5. Vocational training initiatives | |
S6. Generational change of forest entrepreneurs | |
Weaknesses | W1. Negative stumpage value |
W2. Land pathology and orographic context | |
W3. Weakly harmonised forest management | |
W4. Old machinery and poor support for innovation in processing companies | |
W5. Technological defects of wood | |
W6. Modest public support for the provision of ecosystem services | |
Opportunities | O1. Chestnut research projects |
O2. Business networks | |
O3. Forest certification and quality labels | |
O4. Raising civil society’s awareness of ecosystem services | |
Threats | T1. Climate change, pests, and diseases |
T2. Depopulation of mountain areas | |
T3. Lack of market knowledge and strong foreign competition | |
T4. Weak granting of subsidies and incentives for the forest wood sector |
Value | Value Judgement |
---|---|
1 | Equally important |
3 | Moderately important |
5 | Strongly important |
7 | Very strongly important |
9 | Extremely important |
2, 4, 6, 8 | Intermediate values |
Strengths | S1 | S2 | S3 | S4 | S5 | S6 |
---|---|---|---|---|---|---|
S1 | c1,1 | c2,1 | c3,1 | c4,1 | c5,1 | c6,1 |
S2 | c1,2 | 1 | 1/5 | 1/9 | 7 | 6 |
S3 | c1,3 | 5 | 1 | 2 | 3 | 1/7 |
S4 | c1,4 | 9½2 | 1 | 9 | 1/6 | |
S5 | c1,5 | 1/7 | 1/3 | 1/9 | 1 | 3 |
S6 | c1,6 | 1/6 | 7 | 6 | 1/3 | 1 |
n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
---|---|---|---|---|---|---|---|---|---|---|
RI | 0 | 0 | 0.58 | 0.9 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 |
SWOT Criteria | Criteria Priority | SWOT Factors | CR * | Priority of Local Factors | Ranking of Local Factors | Priority Global Factors | Ranking of Global Factors |
---|---|---|---|---|---|---|---|
Strengths | 0.208 | S1. Good resource availability | 0.007 | 0.082 | 6 | 0.017 | 15 |
S2. Provision of ecosystem services (cultural and protection) | 0.155 | 4 | 0.032 | 10 | |||
S3. Richness of wood assortments | 0.116 | 5 | 0.024 | 12 | |||
S4. Tradition of chestnut use | 0.214 | 2 | 0.045 | 8 | |||
S5. Vocational training initiatives | 0.226 | 1 | 0.047 | 7 | |||
S6. Generational change of forest entrepreneurs | 0.207 | 3 | 0.043 | 9 | |||
Weaknesses | 0.226 | W1. Negative stumpage value | 0.008 | 0.138 | 4 | 0.031 | 11 |
W2. Land pathology and orographic context | 0.079 | 6 | 0.018 | 14 | |||
W3. Weakly harmonised forest management | 0.192 | 2 | 0.043 | 9 | |||
W4. Old machinery and poor support for innovation in processors | 0.307 | 1 | 0.069 | 4 | |||
W5. Technological defects of wood | 0.097 | 5 | 0.022 | 13 | |||
W6. Modest public support for the provision of ecosystem services (PES) | 0.188 | 3 | 0.042 | 10 | |||
Opportunities | 0.312 | O1. Chestnut research projects | 0.005 | 0.278 | 2 | 0.087 | 2 |
O2. Business networks | 0.152 | 4 | 0.047 | 7 | |||
O3. Forest certification and quality labels | 0.213 | 3 | 0.066 | 5 | |||
O4. Increasing civil society’s awareness of ecosystem services | 0.357 | 1 | 0.111 | 1 | |||
Threats | 0.253 | T1. Climate change, pests and diseases | 0.015 | 0.177 | 4 | 0.045 | 8 |
T2. Depopulation of mountain areas | 0.314 | 1 | 0.079 | 3 | |||
T3. Lack of market knowledge and strong foreign competition | 0.204 | 3 | 0.052 | 6 | |||
T4. Weak granting of subsidies and incentives for the forest-wood sector | 0.304 | 2 | 0.077 | 4 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Bruzzese, S.; Blanc, S.; Novelli, S.; Brun, F. A Multicriteria Analysis to Support Natural Resource Governance: The Case of Chestnut Forests. Resources 2023, 12, 40. https://doi.org/10.3390/resources12030040
Bruzzese S, Blanc S, Novelli S, Brun F. A Multicriteria Analysis to Support Natural Resource Governance: The Case of Chestnut Forests. Resources. 2023; 12(3):40. https://doi.org/10.3390/resources12030040
Chicago/Turabian StyleBruzzese, Stefano, Simone Blanc, Silvia Novelli, and Filippo Brun. 2023. "A Multicriteria Analysis to Support Natural Resource Governance: The Case of Chestnut Forests" Resources 12, no. 3: 40. https://doi.org/10.3390/resources12030040