IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v68y2017ip1p774-787.html
   My bibliography  Save this article

A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information

Author

Listed:
  • Mousavi, M.
  • Gitinavard, H.
  • Mousavi, S.M.

Abstract

In recent years, the selection of suitable renewable energy policy is very significant issue that could affect on environment and economic development. To address the issue, some researchers have focused on choosing the best renewable energy alternative by utilizing the decision-making analysis and fuzzy sets theory. In this paper, a new decision model based on modified elimination and choice translating reality (ELECTRE) is presented under a hesitant fuzzy environment for solving the multi-attribute group decision-making (MAGDM) problems in energy sector. Hesitant fuzzy set (HFS) is a powerful tool to cope with uncertainty in case of hesitant and incomplete information by considering some membership degrees for an energy alternative versus an evaluation criterion (attribute) under a set. In this model, a group of energy experts is provided to assess the potential alternatives among the conflicted attributes or criteria. Also, the decision matrix and relative importance of each attribute are considered by linguistic terms that can be transformed to hesitant fuzzy elements. In addition, the relative importance of each energy decision maker (DM) or expert is computed by proposed hesitant fuzzy modified preferences selection index (HF-M-PSI) method. Also, the significance of attributes is determined by an extended maximizing deviation method which is motivated by hesitant fuzzy Euclidean-Hausdorff distance measure. In this regard, opinions of each energy expert are applied to extend maximizing deviation method. Then, weights of attributes and experts are considered in the proposed hesitant fuzzy modified-ELECTRE (HF-M-ELECTRE) model. In the proposed decision model, the hesitant fuzzy effective outranking matrix may not help to rank the energy candidates. Thus, the proposed soft computing approach takes account of the thresholds as indifference, preference and veto for each attribute to compare the equivalent alternative. Finally, two real case studies in developing countries on renewable energy policy selection problem are presented to indicate the suitability and feasibility of the proposed HF-M-ELECTRE model in imprecise situations.

Suggested Citation

  • Mousavi, M. & Gitinavard, H. & Mousavi, S.M., 2017. "A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 774-787.
    • Handle: RePEc:eee:rensus:v:68:y:2017:i:p1:p:774-787
    DOI: 10.1016/j.rser.2016.09.125
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032116306359
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2016.09.125?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hatami-Marbini, Adel & Tavana, Madjid, 2011. "An extension of the Electre I method for group decision-making under a fuzzy environment," Omega, Elsevier, vol. 39(4), pages 373-386, August.
    2. Huchang Liao & Zeshui Xu & Meimei Xia, 2014. "Multiplicative Consistency Of Hesitant Fuzzy Preference Relation And Its Application In Group Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 47-76.
    3. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, December.
    4. Zamani, Mehrzad, 2007. "Energy consumption and economic activities in Iran," Energy Economics, Elsevier, vol. 29(6), pages 1135-1140, November.
    5. Cho, Sangmin & Kim, Jinsoo & Heo, Eunnyeong, 2015. "Application of fuzzy analytic hierarchy process to select the optimal heating facility for Korean horticulture and stockbreeding sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1075-1083.
    6. Goumas, M. & Lygerou, V., 2000. "An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects," European Journal of Operational Research, Elsevier, vol. 123(3), pages 606-613, June.
    7. Afgan, Nain H. & Carvalho, Maria G., 2008. "Sustainability assessment of a hybrid energy system," Energy Policy, Elsevier, vol. 36(8), pages 2893-2900, August.
    8. Govindan, Kannan & Jepsen, Martin Brandt, 2016. "ELECTRE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 250(1), pages 1-29.
    9. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    10. Burak Omer Saracoglu, 2013. "Selecting industrial investment locations in master plans of countries," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 7(4), pages 416-441.
    11. Kaya, Tolga & Kahraman, Cengiz, 2010. "Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul," Energy, Elsevier, vol. 35(6), pages 2517-2527.
    12. Keyhani, A. & Ghasemi-Varnamkhasti, M. & Khanali, M. & Abbaszadeh, R., 2010. "An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran," Energy, Elsevier, vol. 35(1), pages 188-201.
    13. Kahraman, Cengiz & Kaya, İhsan & Cebi, Selcuk, 2009. "A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process," Energy, Elsevier, vol. 34(10), pages 1603-1616.
    14. Beccali, M. & Cellura, M. & Mistretta, M., 2003. "Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology," Renewable Energy, Elsevier, vol. 28(13), pages 2063-2087.
    15. Afgan, Naim H. & Carvalho, Maria G., 2002. "Multi-criteria assessment of new and renewable energy power plants," Energy, Elsevier, vol. 27(8), pages 739-755.
    16. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    17. Topcu, Y.I & Ulengin, F, 2004. "Energy for the future: An integrated decision aid for the case of Turkey," Energy, Elsevier, vol. 29(1), pages 137-154.
    18. S. Meysam Mousavi & Fariborz Jolai & Reza Tavakkoli-Moghaddam, 2013. "A Fuzzy Stochastic Multi-Attribute Group Decision-Making Approach for Selection Problems," Group Decision and Negotiation, Springer, vol. 22(2), pages 207-233, March.
    19. Erdogmus, Senol & Aras, Haydar & Koç, Eylem, 2006. "Evaluation of alternative fuels for residential heating in Turkey using analytic network process (ANP) with group decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(3), pages 269-279, June.
    20. Balezentiene, Ligita & Streimikiene, Dalia & Balezentis, Tomas, 2013. "Fuzzy decision support methodology for sustainable energy crop selection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 83-93.
    21. Singh, Rana Pratap & Nachtnebel, Hans Peter, 2016. "Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 43-58.
    22. Papadopoulos, Agis & Karagiannidis, Avraam, 2008. "Application of the multi-criteria analysis method Electre III for the optimisation of decentralised energy systems," Omega, Elsevier, vol. 36(5), pages 766-776, October.
    23. Lee, Seong Kon & Mogi, Gento & Hui, K.S., 2013. "A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 347-355.
    24. Heo, Eunnyeong & Kim, Jinsoo & Boo, Kyung-Jin, 2010. "Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2214-2220, October.
    25. van de Kaa, Geerten & Rezaei, Jafar & Kamp, Linda & de Winter, Allard, 2014. "Photovoltaic technology selection: A fuzzy MCDM approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 662-670.
    26. Choudhary, Devendra & Shankar, Ravi, 2012. "An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India," Energy, Elsevier, vol. 42(1), pages 510-521.
    27. Na Chen & Zeshui Xu & Meimei Xia, 2015. "The ELECTRE I Multi-Criteria Decision-Making Method Based on Hesitant Fuzzy Sets," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 621-657.
    28. Various, 1973. "Conference Programs," NBER Chapters, in: The New Realities of the Business Cycle, pages 126-131, National Bureau of Economic Research, Inc.
    29. Şengül, Ümran & Eren, Miraç & Eslamian Shiraz, Seyedhadi & Gezder, Volkan & Şengül, Ahmet Bilal, 2015. "Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey," Renewable Energy, Elsevier, vol. 75(C), pages 617-625.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hassan Hashemi & Seyed Meysam Mousavi & Edmundas Kazimieras Zavadskas & Alireza Chalekaee & Zenonas Turskis, 2018. "A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    2. Arunodaya Raj Mishra & Pratibha Rani & Raghunathan Krishankumar & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Kattur S. Ravichandran, 2021. "A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    3. Abreu Kang, Takanni Hannaka & da Costa Soares Júnior, Antônio Marques & de Almeida, Adiel Teixeira, 2018. "Evaluating electric power generation technologies: A multicriteria analysis based on the FITradeoff method," Energy, Elsevier, vol. 165(PB), pages 10-20.
    4. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    5. Osman Taylan & Rami Alamoudi & Mohammad Kabli & Alawi AlJifri & Fares Ramzi & Enrique Herrera-Viedma, 2020. "Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions," Sustainability, MDPI, vol. 12(7), pages 1-27, March.
    6. Erick P. Massami & Malima M. Manyasi, 2021. "Analysis of determinants of work performance for seafarers based on fuzzy Electre model," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-20, December.
    7. Li, Tao & Li, Ang & Guo, Xiaopeng, 2020. "The sustainable development-oriented development and utilization of renewable energy industry——A comprehensive analysis of MCDM methods," Energy, Elsevier, vol. 212(C).
    8. Ali, Shahid & Stewart, Rodney A. & Sahin, Oz & Vieira, Abel Silva, 2024. "Spatial bayesian approach for socio-economic assessment of pumped hydro storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    9. Sitorus, Fernando & Brito-Parada, Pablo R., 2020. "A multiple criteria decision making method to weight the sustainability criteria of renewable energy technologies under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    10. Rivero-Iglesias, Jose M. & Puente, Javier & Fernandez, Isabel & León, Omar, 2023. "Integrated model for the assessment of power generation alternatives through analytic hierarchy process and a fuzzy inference system. Case study of Spain," Renewable Energy, Elsevier, vol. 211(C), pages 563-581.
    11. Muhammad Riaz & Wojciech Sałabun & Hafiz Muhammad Athar Farid & Nawazish Ali & Jarosław Wątróbski, 2020. "A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management," Energies, MDPI, vol. 13(9), pages 1-39, May.
    12. Dongxiao Niu & Hao Zhen & Min Yu & Keke Wang & Lijie Sun & Xiaomin Xu, 2020. "Prioritization of Renewable Energy Alternatives for China by Using a Hybrid FMCDM Methodology with Uncertain Information," Sustainability, MDPI, vol. 12(11), pages 1-26, June.
    13. Abdel-Basset, Mohamed & Gamal, Abduallah & Chakrabortty, Ripon K. & Ryan, Michael J., 2021. "Evaluation approach for sustainable renewable energy systems under uncertain environment: A case study," Renewable Energy, Elsevier, vol. 168(C), pages 1073-1095.
    14. Topcu, Ilker & Ülengin, Füsun & Kabak, Özgür & Isik, Mine & Unver, Berna & Onsel Ekici, Sule, 2019. "The evaluation of electricity generation resources: The case of Turkey," Energy, Elsevier, vol. 167(C), pages 417-427.
    15. Hashemizadeh, Ali & Ju, Yanbing & Bamakan, Seyed Mojtaba Hosseini & Le, Hoang Phong, 2021. "Renewable energy investment risk assessment in belt and road initiative countries under uncertainty conditions," Energy, Elsevier, vol. 214(C).
    16. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    17. Pratibha Rani & Jabir Ali & Raghunathan Krishankumar & Arunodaya Raj Mishra & Fausto Cavallaro & Kattur S. Ravichandran, 2021. "An Integrated Single-Valued Neutrosophic Combined Compromise Solution Methodology for Renewable Energy Resource Selection Problem," Energies, MDPI, vol. 14(15), pages 1-23, July.
    18. Raghunathan Krishankumar & Arunodaya Raj Mishra & Kattur Soundarapandian Ravichandran & Xindong Peng & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Abbas Mardani, 2020. "A Group Decision Framework for Renewable Energy Source Selection under Interval-Valued Probabilistic linguistic Term Set," Energies, MDPI, vol. 13(4), pages 1-25, February.
    19. Ezbakhe, Fatine & Pérez-Foguet, Agustí, 2021. "Decision analysis for sustainable development: The case of renewable energy planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 291(2), pages 601-613.
    20. María Carmen Carnero, 2020. "Fuzzy TOPSIS Model for Assessment of Environmental Sustainability: A Case Study with Patient Judgements," Mathematics, MDPI, vol. 8(11), pages 1-43, November.
    21. Noori, Amir & Bonakdari, Hossein & Salimi, Amir Hossein & Gharabaghi, Bahram, 2021. "A group Multi-Criteria Decision-Making method for water supply choice optimization," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    22. Li, Yi & Su, Da An & Mardani, Abbas, 2023. "Digital twins and blockchain technology in the industrial Internet of Things (IIoT) using an extended decision support system model: Industry 4.0 barriers perspective," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    23. Long, Yilu & Tang, Ming & Liao, Huchang, 2022. "Renewable energy source technology selection considering the empathetic preferences of experts in a cognitive fuzzy social participatory allocation network," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    24. Karaaslan, Abdulkerim & Gezen, Mesliha, 2022. "The evaluation of renewable energy resources in Turkey by integer multi-objective selection problem with interval coefficient," Renewable Energy, Elsevier, vol. 182(C), pages 842-854.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Strantzali, Eleni & Aravossis, Konstantinos, 2016. "Decision making in renewable energy investments: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 885-898.
    2. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Khalifah, Zainab & Zakuan, Norhayati & Jusoh, Ahmad & Nor, Khalil Md & Khoshnoudi, Masoumeh, 2017. "A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 216-256.
    3. Jamal, Taskin & Urmee, Tania & Shafiullah, G.M., 2020. "Planning of off-grid power supply systems in remote areas using multi-criteria decision analysis," Energy, Elsevier, vol. 201(C).
    4. Abbas Mardani & Ahmad Jusoh & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Zainab Khalifah, 2015. "Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches," Sustainability, MDPI, vol. 7(10), pages 1-38, October.
    5. Çelikbilek, Yakup & Tüysüz, Fatih, 2016. "An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources," Energy, Elsevier, vol. 115(P1), pages 1246-1258.
    6. Alkan, Ömer & Albayrak, Özlem Karadağ, 2020. "Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA," Renewable Energy, Elsevier, vol. 162(C), pages 712-726.
    7. Gitinavard, Hossein & Mousavi, S. Meysam & Vahdani, Behnam, 2017. "Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study," Energy, Elsevier, vol. 118(C), pages 556-577.
    8. Dongxiao Niu & Hao Zhen & Min Yu & Keke Wang & Lijie Sun & Xiaomin Xu, 2020. "Prioritization of Renewable Energy Alternatives for China by Using a Hybrid FMCDM Methodology with Uncertain Information," Sustainability, MDPI, vol. 12(11), pages 1-26, June.
    9. Liu, Gang, 2014. "Development of a general sustainability indicator for renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 611-621.
    10. Athanasios Kolios & Varvara Mytilinou & Estivaliz Lozano-Minguez & Konstantinos Salonitis, 2016. "A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs," Energies, MDPI, vol. 9(7), pages 1-21, July.
    11. Doukas, Haris, 2013. "Modelling of linguistic variables in multicriteria energy policy support," European Journal of Operational Research, Elsevier, vol. 227(2), pages 227-238.
    12. Kaya, Tolga & Kahraman, Cengiz, 2010. "Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul," Energy, Elsevier, vol. 35(6), pages 2517-2527.
    13. Atmaca, Ediz & Basar, Hasan Burak, 2012. "Evaluation of power plants in Turkey using Analytic Network Process (ANP)," Energy, Elsevier, vol. 44(1), pages 555-563.
    14. Fatih Tüysüz, 2017. "A Hybrid Multi-Criteria Analysis Approach for the Assessment of Renewable Energy Resources Under Uncertainty," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 5(2), pages 317-328, December.
    15. Khishtandar, Soheila & Zandieh, Mostafa & Dorri, Behrouz, 2017. "A multi criteria decision making framework for sustainability assessment of bioenergy production technologies with hesitant fuzzy linguistic term sets: The case of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1130-1145.
    16. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    17. Ishizaka, Alessio & Siraj, Sajid & Nemery, Philippe, 2016. "Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool," Energy, Elsevier, vol. 95(C), pages 602-611.
    18. Deveci, Muhammet & Cali, Umit & Kucuksari, Sadik & Erdogan, Nuh, 2020. "Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland," Energy, Elsevier, vol. 198(C).
    19. Caetani, Alberto Pavlick & Ferreira, Luciano & Borenstein, Denis, 2016. "Development of an integrated decision-making method for an oil refinery restructuring in Brazil," Energy, Elsevier, vol. 111(C), pages 197-210.
    20. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.

    More about this item

    Keywords

    Renewable energy policy selection; Hesitant fuzzy sets; Modified-ELECTRE method; Modified-PSI method; Group decision making;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • P18 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Energy; Environment
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:68:y:2017:i:p1:p:774-787. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.