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Peter Goos

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.

    Mentioned in:

    1. > Environmental and Natural Resource Economics > Environmental Economics > Valuation > Choice experiments and conjoint analyses

Working papers

  1. Marjolijn De Wilde & Peter Goos, 2017. "The Implementation of Social Policy: A Factorial Survey Approach," Working Papers 1706, Herman Deleeck Centre for Social Policy, University of Antwerp.

    Cited by:

    1. Marjolijn De Wilde & Sarah Marchal, 2018. "Weighing up work willingness in social assistance: a balancing act on multiple levels," Working Papers 1808, Herman Deleeck Centre for Social Policy, University of Antwerp.

  2. CUERVO, Daniel Palhazi & KESSELS, Roselinde & GOOS, Peter & SÖRENSEN, Kenneth, 2015. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Working Papers 2015004, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
    2. Großmann, Heiko, 2019. "A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    3. Bjørnåvold, Amalie & David, Maia & Bohan, David A. & Gibert, Caroline & Rousselle, Jean-Marc & Van Passel, Steven, 2022. "Why does France not meet its pesticide reduction targets? Farmers' socio-economic trade-offs when adopting agro-ecological practices," Ecological Economics, Elsevier, vol. 198(C).
    4. Van Acker, Veronique & Kessels, Roselinde & Palhazi Cuervo, Daniel & Lannoo, Steven & Witlox, Frank, 2020. "Preferences for long-distance coach transport: Evidence from a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 759-779.
    5. Verelst, Frederik & Willem, Lander & Kessels, Roselinde & Beutels, Philippe, 2018. "Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives," Social Science & Medicine, Elsevier, vol. 207(C), pages 106-116.

  3. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. VÁZQUEZ-ALCOCER, Alan & XU, Hongquan, 2018. "Construction of two-level nonregular designs of strength three with large run sizes," Working Papers 2018003, University of Antwerp, Faculty of Business and Economics.
    2. VÁZQUEZ-ALCOCER, Alan & GOOS, Peter & SCHOEN, Eric D., 2016. "Two-level designs constructed by concatenating orthogonal arrays of strenght three," Working Papers 2016011, University of Antwerp, Faculty of Business and Economics.

  4. SCHOEN, Eric D. & VO-THANH, Nha & GOOS, Peter, 2015. "Two-level orthogonal designs in 24 and 28 runs," Working Papers 2015016, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. SCHOEN, Eric D. & VO-THANH, Nha & GOOS, Peter, 2016. "Orthogonal blocking arrangements for 24-run and 28-run two-level designs," Working Papers 2016002, University of Antwerp, Faculty of Business and Economics.
    2. VÁZQUEZ-ALCOCER, Alan & GOOS, Peter & SCHOEN, Eric D., 2016. "Two-level designs constructed by concatenating orthogonal arrays of strenght three," Working Papers 2016011, University of Antwerp, Faculty of Business and Economics.

  5. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2014. "Bayesian D-Optimal Choice Designs for Mixtures," Tinbergen Institute Discussion Papers 14-057/III, Tinbergen Institute.

    Cited by:

    1. Boonaert, Eva & Hoyweghen, Kaat Van & Feyisa, Ashenafi Duguma & Goos, Peter & Maertens, Miet, 2021. "Twofold Gendered Preferences in the Quantity-Quality Trade-Off Impact the Demographic Transition in Ethiopia," 2021 Conference, August 17-31, 2021, Virtual 315224, International Association of Agricultural Economists.
    2. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.

  6. CASTRO, Marco & SÖRENSEN, Kenneth & GOOS, Peter & VANSTEENWEGEN, Pieter, 2014. "The multiple travelling salesperson problem with hotel selection," Working Papers 2014030, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Gabriel Bazi & John Khoury & F. Jordan Srour, 2017. "Integrating Data Collection Optimization into Pavement Management Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(3), pages 135-146, June.
    2. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).

  7. KESSELS, Roselinde & JONES, Bradley & GOOS, Peter, 2013. "An argument for preferring Firth bias-adjusted estimates in aggregate and individual-level discrete choice modeling," Working Papers 2013013, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Kupfer, Franziska & Kessels, Roselinde & Goos, Peter & Van de Voorde, Eddy & Verhetsel, Ann, 2016. "The origin–destination airport choice for all-cargo aircraft operations in Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 53-74.
    2. KUPFER, Franziska & KESSELS, Roselinde & GOOS, Peter & VAN DE VOORDE, Eddy & VERHETSEL, Ann, 2013. "A discrete choice approach for analysing the airport choice for freighter operations in Europe," Working Papers 2013028, University of Antwerp, Faculty of Business and Economics.

  8. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth & ARRÁIZ, Emely, 2013. "An iterated local search algorithm for the vehicle routing problem with backhauls," Working Papers 2013010, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    2. Huber, Sandra & Geiger, Martin Josef, 2017. "Order matters – A Variable Neighborhood Search for the Swap-Body Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 263(2), pages 419-445.
    3. CASTRO, Marco & SÖRENSEN, Kenneth & GOOS, Peter & VANSTEENWEGEN, Pieter, 2014. "The multiple travelling salesperson problem with hotel selection," Working Papers 2014030, University of Antwerp, Faculty of Business and Economics.
    4. Paredes-Belmar, Germán & Montero, Elizabeth & Lüer-Villagra, Armin & Marianov, Vladimir & Araya-Sassi, Claudio, 2022. "Vehicle routing for milk collection with gradual blending: A case arising in Chile," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1403-1416.
    5. Lei, Jieyu & Che, Ada & Van Woensel, Tom, 2024. "Collection-disassembly-delivery problem of disassembly centers in a reverse logistics network," European Journal of Operational Research, Elsevier, vol. 313(2), pages 478-493.
    6. Zhang, Li & Liu, Zhongshan & Yu, Bin & Long, Jiancheng, 2024. "A ridesharing routing problem for airport riders with electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    7. Dominguez, Oscar & Guimarans, Daniel & Juan, Angel A. & de la Nuez, Ignacio, 2016. "A Biased-Randomised Large Neighbourhood Search for the two-dimensional Vehicle Routing Problem with Backhauls," European Journal of Operational Research, Elsevier, vol. 255(2), pages 442-462.
    8. VANOVERMEIRE, Christine & CUERVO, Daniel Palhazi & SÖRENSEN, Kenneth, 2013. "Estimating collaborative profits under varying partner characteristics and strategies," Working Papers 2013031, University of Antwerp, Faculty of Business and Economics.
    9. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    10. José Brandão, 2016. "A deterministic iterated local search algorithm for the vehicle routing problem with backhauls," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 445-465, July.
    11. Queiroga, Eduardo & Frota, Yuri & Sadykov, Ruslan & Subramanian, Anand & Uchoa, Eduardo & Vidal, Thibaut, 2020. "On the exact solution of vehicle routing problems with backhauls," European Journal of Operational Research, Elsevier, vol. 287(1), pages 76-89.

  9. LUYTEN, Jeroen & KESSELS, Roselinde & GOOS, Peter & BEUTELS, Philippe, 2013. "Public preferences for prioritizing preventive and curative health care interventions: A discrete choice experiment," Working Papers 2013032, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
    2. Anna Nicolet & Antoinette D I van Asselt & Karin M Vermeulen & Paul F M Krabbe, 2020. "Value judgment of new medical treatments: Societal and patient perspectives to inform priority setting in The Netherlands," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
    3. Nguyen, Lien & Jokimäki, Hanna & Linnosmaa, Ismo & Saloniki, Eirini Christina & Batchelder, Laurie & Malley, Juliette & Lu, Hui & Burge, Peter & Trukeschitz, Birgit & Forder, Julien, 2021. "Do you prefer safety to social participation? Finnish population-based preference weights for the Adult Social Care Outcomes Toolkit (ASCOT) for service users," LSE Research Online Documents on Economics 110757, London School of Economics and Political Science, LSE Library.
    4. Fraeyman, Jessica & Symons, Linda & De Loof, Hans & De Meyer, Guido R.Y. & Remmen, Roy & Beutels, Philippe & Van Hal, Guido, 2015. "Medicine price awareness in chronic patients in Belgium," Health Policy, Elsevier, vol. 119(2), pages 217-223.
    5. Hannah Christensen & Hareth Al-Janabi & Pierre Lévy & Maarten J. Postma & David E. Bloom & Paolo Landa & David M. Salisbury & Javier Diez-Domingo & Adrian K. Towse & Paula K. Lorgelly & Koonal K. Shah, 2020. "Economic evaluation of meningococcal vaccines: considerations for the future," Post-Print hal-03120553, HAL.
    6. Juan Marcos Gonzalez, 2019. "A Guide to Measuring and Interpreting Attribute Importance," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(3), pages 287-295, June.
    7. Brendan Mulhern & Richard Norman & Koonal Shah & Nick Bansback & Louise Longworth & Rosalie Viney, 2018. "How Should Discrete Choice Experiments with Duration Choice Sets Be Presented for the Valuation of Health States?," Medical Decision Making, , vol. 38(3), pages 306-318, April.
    8. Vanoutrive, Thomas & Zijlstra, Toon, 2018. "Who has the right to travel during peak hours? On congestion pricing and ‘desirable’ travellers," Transport Policy, Elsevier, vol. 63(C), pages 98-107.
    9. LUYTEN, Jeroen & DESMET, Pieter & KESSELS, Roselinde & GOOS, Peter & BEUTELS, Philippe, 2015. "The future’s so bright, I gotta wear sunscreen: Dispositional optimism and preferences for prioritizing health care," Working Papers 2015015, University of Antwerp, Faculty of Business and Economics.
    10. Pius Krütli & Thomas Rosemann & Kjell Y Törnblom & Timo Smieszek, 2016. "How to Fairly Allocate Scarce Medical Resources: Ethical Argumentation under Scrutiny by Health Professionals and Lay People," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    11. Dana Alkhoury & Jared Atchison & Antonio J. Trujillo & Kimberly Oslin & Katherine P. Frey & Robert V. O’Toole & Renan C. Castillo & Nathan N. O’Hara, 2021. "Can financial payments incentivize short-term smoking cessation in orthopaedic trauma patients? Evidence from a discrete choice experiment," Health Economics Review, Springer, vol. 11(1), pages 1-10, December.
    12. Gemma Lasseter & Hareth Al-Janabi & Caroline L Trotter & Fran E Carroll & Hannah Christensen, 2018. "The views of the general public on prioritising vaccination programmes against childhood diseases: A qualitative study," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-18, June.
    13. James Buchanan & Laurence S. J. Roope & Liz Morrell & Koen B. Pouwels & Julie V. Robotham & Lucy Abel & Derrick W. Crook & Tim Peto & Christopher C. Butler & A. Sarah Walker & Sarah Wordsworth, 2021. "Preferences for Medical Consultations from Online Providers: Evidence from a Discrete Choice Experiment in the United Kingdom," Applied Health Economics and Health Policy, Springer, vol. 19(4), pages 521-535, July.
    14. Liz Morrell & Sarah Wordsworth & Sian Rees & Richard Barker, 2017. "Does the Public Prefer Health Gain for Cancer Patients? A Systematic Review of Public Views on Cancer and its Characteristics," PharmacoEconomics, Springer, vol. 35(8), pages 793-804, August.

  10. GOOS, Peter & JONES, Bradley & SYAFITRI, Utami, 2013. "I-optimal mixture designs," Working Papers 2013033, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.

  11. KUPFER, Franziska & KESSELS, Roselinde & GOOS, Peter & VAN DE VOORDE, Eddy & VERHETSEL, Ann, 2013. "A discrete choice approach for analysing the airport choice for freighter operations in Europe," Working Papers 2013028, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    2. Düzgün, Murat, 2020. "Assessment Of Istanbul Grand Airport (Iga) As A Global Cargo Base By The Topsis Method," Academic Review of Humanities and Social Sciences, Bursa Teknik Üniversitesi, vol. 3(1), pages 125-138.

  12. VERHETSEL, Ann & KESSELS, Roselinde & BLOMME, Nele & CANT, Jeroen & GOOS, Peter, 2013. "Location of logistics companies: A stated preference study to disentangle the impact of accessibility," Working Papers 2013024, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Khalili, Fatemeh Bagheri & Antunes, António Pais & Mohaymany, Afshin Shariat, 2020. "Evaluating interregional freight accessibility conditions through the combination of centrality and reliability measures," Journal of Transport Geography, Elsevier, vol. 83(C).
    2. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    3. Holl, Adelheid & Mariotti, Ilaria, 2016. "The geography of logistics firm location: the role of accessibility," Working Papers 16_2, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    4. Champagne, Marie-Pier & Dubé, Jean, 2023. "The impact of transport infrastructure on firms’ location decision: A meta-analysis based on a systematic literature review," Transport Policy, Elsevier, vol. 131(C), pages 139-155.
    5. Alexander T C Onstein & Lóránt A Tavasszy & Jafar Rezaei & Dick A van Damme & Adeline Heitz, 2020. "A sectoral perspective on distribution structure design," Post-Print hal-03884986, HAL.
    6. Cuccu, Liliana & Pontarollo, Nicola, 2024. "Logistic hubs and support for radical-right populism: Evidence from Italy," European Journal of Political Economy, Elsevier, vol. 82(C).
    7. Tsekeris, Theodore, 2016. "Interregional trade network analysis for road freight transport in Greece," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 132-148.
    8. Champagne, Marie-Pier & Dubé, Jean & Legros, Diègo, 2024. "Standing strong? The causal impact of metro stations on service firms’ survival," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    9. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    10. Robichet, Antoine & Nierat, Patrick, 2021. "Consequences of logistics sprawl: Order or chaos? - the case of a parcel service company in Paris metropolitan area," Journal of Transport Geography, Elsevier, vol. 90(C).
    11. Beckers, Joris & Vanhoof, Maarten & Verhetsel, Ann, 2019. "Returning the particular: Understanding hierarchies in the Belgian logistics system," Journal of Transport Geography, Elsevier, vol. 76(C), pages 315-324.
    12. Ahmed, Usman & Hawkins, Jason & Roorda, Matthew J., 2022. "Establishment location choice model considering intra-firm interactions," Journal of Transport Geography, Elsevier, vol. 102(C).
    13. Adam, Arnaud & Finance, Olivier & Thomas, Isabelle, 2021. "Monitoring trucks to reveal Belgian geographical structures and dynamics: From GPS traces to spatial interactions," Journal of Transport Geography, Elsevier, vol. 91(C).
    14. Olga Porro & Francesc Pardo-Bosch & Núria Agell & Mónica Sánchez, 2020. "Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method," Energies, MDPI, vol. 13(10), pages 1-29, May.
    15. Yang, Zhiwei & Chen, Xiaohong & Pan, Ruixu & Yuan, Quan, 2022. "Exploring location factors of logistics facilities from a spatiotemporal perspective: A case study from Shanghai," Journal of Transport Geography, Elsevier, vol. 100(C).
    16. Sakai, Takanori & Kawamura, Kazuya & Hyodo, Tetsuro, 2020. "Logistics facilities for intra and inter-regional shipping: Spatial distributions, location choice factors, and externality," Journal of Transport Geography, Elsevier, vol. 86(C).
    17. Akhavan, Mina & Ghiara, Hilda & Mariotti, Ilaria & Sillig, Cécile, 2020. "Logistics global network connectivity and its determinants. A European City network analysis," Journal of Transport Geography, Elsevier, vol. 82(C).
    18. Li, Guoqi & Sun, Wenjie & Yuan, Quan & Liu, Sijing, 2020. "Planning versus the market: Logistics establishments and logistics parks in Chongqing, China," Journal of Transport Geography, Elsevier, vol. 82(C).
    19. McLeod, Sam & Schapper, Jake H.M. & Curtis, Carey & Graham, Giles, 2019. "Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature," Transport Policy, Elsevier, vol. 74(C), pages 24-34.
    20. David Guerrero & Jean Paul Hubert & Martin Koning & Nicolas Roelandt, 2022. "On the Spatial Scope of Warehouse Activity: An Exploratory Study in France," Post-Print hal-03551270, HAL.
    21. Haining Jiang & Wei Xu & Wenzhong Zhang, 2018. "Transportation Accessibility and Location Choice of Japanese-Funded Electronic Information Manufacturing Firms in Shanghai," Sustainability, MDPI, vol. 10(2), pages 1-21, February.
    22. Aljohani, Khalid & Thompson, Russell G., 2016. "Impacts of logistics sprawl on the urban environment and logistics: Taxonomy and review of literature," Journal of Transport Geography, Elsevier, vol. 57(C), pages 255-263.
    23. Meiling He & Jiaren Shen & Xiaohui Wu & Jianqiang Luo, 2018. "Logistics Space: A Literature Review from the Sustainability Perspective," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    24. Pajones, Markus & Pfoser, Sarah, 2018. "Supporting the selection of sustainable logistics locations," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Logistics 4.0 and Sustainable Supply Chain Management: Innovative Solutions for Logistics and Sustainable Supply Chain Management in the Context of In, volume 26, pages 169-182, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    25. Bowen Sun & Haomin Li & Qiuyun Zhao, 2018. "Logistics agglomeration and logistics productivity in the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(2), pages 273-293, September.
    26. Nefs, Merten & van Haaren, Jeroen & van Oort, Frank, 2023. "The limited regional employment benefits of XXL-logistics centres in the Netherlands," Journal of Transport Geography, Elsevier, vol. 109(C).
    27. Ilona Berková, 2020. "Spatial analysis of financial health of companies," Economics Working Papers 2020-02, University of South Bohemia in Ceske Budejovice, Faculty of Economics.
    28. Xiuyan Zhao & Changhong Miao, 2023. "Research on the Spatial Pattern of the Logistics Industry Based on POI Data: A Case Study of Zhengzhou City," Sustainability, MDPI, vol. 15(21), pages 1-38, November.
    29. Guerrero, D. & Hubert, J.-P. & Koning, M. & Roelandt, N., 2022. "On the spatial scope of warehouse activity: An exploratory study in France," Journal of Transport Geography, Elsevier, vol. 99(C).
    30. Martine Mostert & Sabine Limbourg, 2016. "External Costs as Competitiveness Factors for Freight Transport — A State of the Art," Transport Reviews, Taylor & Francis Journals, vol. 36(6), pages 692-712, November.
    31. Dalila Ribaudo, 2023. "Tracking the Van: The role of forward linkages in logistics MNEs' location choices across European NUTS 3 regions," Papers in Regional Science, Wiley Blackwell, vol. 102(2), pages 331-362, April.
    32. Sakai, Takanori & Beziat, Adrien & Heitz, Adeline, 2020. "Location factors for logistics facilities: Location choice modeling considering activity categories," Journal of Transport Geography, Elsevier, vol. 85(C).

  13. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.

  14. DUQUE, Pablo A. Maya & COENE, Sofie & GOOS, Peter & SÖRENSEN, Kenneth & SPIEKSMA, Frits, 2012. "The accessibility arc upgrading problem," Working Papers 2012009, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Sullivan, James L. & Novak, David C., 2024. "A method for evaluating accessibility in transportation problems considering social vulnerability," European Journal of Operational Research, Elsevier, vol. 317(3), pages 646-659.
    2. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    3. Michael Holzhauser & Sven O. Krumke & Clemens Thielen, 2016. "Budget-constrained minimum cost flows," Journal of Combinatorial Optimization, Springer, vol. 31(4), pages 1720-1745, May.
    4. Lazar Mrkela & Zorica Stanimirović, 2022. "A variable neighborhood search for the budget-constrained maximal covering location problem with customer preference ordering," Operational Research, Springer, vol. 22(5), pages 5913-5951, November.
    5. Sakineh Lakzaei & Donya Rahmani & Babak Mohamadpour Tosarkani & Sepideh Nasiri, 2023. "Integrated optimal scheduling and routing of repair crew and relief vehicles after disaster: a novel hybrid solution approach," Annals of Operations Research, Springer, vol. 328(2), pages 1495-1522, September.
    6. Yücel, E. & Salman, F.S. & Arsik, I., 2018. "Improving post-disaster road network accessibility by strengthening links against failures," European Journal of Operational Research, Elsevier, vol. 269(2), pages 406-422.
    7. Maya Duque, Pablo A. & Dolinskaya, Irina S. & Sörensen, Kenneth, 2016. "Network repair crew scheduling and routing for emergency relief distribution problem," European Journal of Operational Research, Elsevier, vol. 248(1), pages 272-285.

  15. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    2. LUYTEN, Jeroen & KESSELS, Roselinde & GOOS, Peter & BEUTELS, Philippe, 2013. "Public preferences for prioritizing preventive and curative health care interventions: A discrete choice experiment," Working Papers 2013032, University of Antwerp, Faculty of Business and Economics.
    3. Axel C. Mühlbacher & Andrew Sadler & Yvonne Jordan, 2022. "Population preferences for non-pharmaceutical interventions to control the SARS-CoV-2 pandemic: trade-offs among public health, individual rights, and economics," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(9), pages 1483-1496, December.
    4. Marcel F. Jonker & Bas Donkers & Esther de Bekker‐Grob & Elly A. Stolk, 2019. "Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 350-363, March.
    5. KUPFER, Franziska & KESSELS, Roselinde & GOOS, Peter & VAN DE VOORDE, Eddy & VERHETSEL, Ann, 2013. "A discrete choice approach for analysing the airport choice for freighter operations in Europe," Working Papers 2013028, University of Antwerp, Faculty of Business and Economics.

  16. CASTRO, Marco & SÖRENSEN, Kenneth & VANSTEENWEGEN, Pieter & GOOS, Peter, 2012. "A simple GRASP+VND for the travelling salesperson problem with hotel selection," Working Papers 2012024, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).

  17. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. GOOS, Peter & JONES, Bradley & SYAFITRI, Utami, 2013. "I-optimal mixture designs," Working Papers 2013033, University of Antwerp, Faculty of Business and Economics.
    2. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    3. Yahaya, Ahmad Zubair & Somalu, Mahendra Rao & Muchtar, Andanastuti & Sulaiman, Shaharin Anwar & Wan Daud, Wan Ramli, 2019. "Effect of particle size and temperature on gasification performance of coconut and palm kernel shells in downdraft fixed-bed reactor," Energy, Elsevier, vol. 175(C), pages 931-940.
    4. Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi, 2014. "A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1193-1207.
    5. Marcin Dutka & Mario Ditaranto & Terese Løvås, 2015. "Application of a Central Composite Design for the Study of NO x Emission Performance of a Low NO x Burner," Energies, MDPI, vol. 8(5), pages 1-22, April.
    6. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.
    7. Elena Holl & Anastasia Oskina & Urs Baier & Andreas Lemmer, 2023. "Optimization of Thermodynamic Parameters of the Biological Hydrogen Methanation in a Trickle-Bed Reactor for the Conditioning of Biogas to Biomethane," Energies, MDPI, vol. 16(12), pages 1-13, June.
    8. Borrotti, Matteo & Sambo, Francesco & Mylona, Kalliopi, 2023. "Multi-objective optimisation of split-plot designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 163-172.

  18. SCHOEN, Eric D. & SARTONO, Bagus & GOOS, Peter, 2012. "Optimal blocking for general resolution-3 designs," Working Papers 2012025, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. SCHOEN, Eric D. & VO-THANH, Nha & GOOS, Peter, 2016. "Orthogonal blocking arrangements for 24-run and 28-run two-level designs," Working Papers 2016002, University of Antwerp, Faculty of Business and Economics.
    2. VO-THANH, Nha & GOOS, Peter & SCHOEN, Eric D., 2016. "Integer programming approaches to find row-column arrangements of two-level orthogonal experimental designs," Working Papers 2016010, University of Antwerp, Faculty of Business and Economics.

  19. MACHARIA, Harrison & GOOS, Peter, 2010. "D-optimal and D-efficient equivalent-estimation second-order split-plot designs," Working Papers 2010011, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    2. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.
    3. Xiaodong Li & Xu He & Yuanzhen He & Hui Zhang & Zhong Zhang & Dennis K. J. Lin, 2017. "The Design and Analysis for the Icing Wind Tunnel Experiment of a New Deicing Coating," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1417-1429, October.
    4. Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi, 2014. "A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1193-1207.
    5. MYLONA, Kalliopi & MACHARIA, Harrison & GOOS, Peter, 2011. "Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs," Working Papers 2011010, University of Antwerp, Faculty of Business and Economics.
    6. Borrotti, Matteo & Sambo, Francesco & Mylona, Kalliopi, 2023. "Multi-objective optimisation of split-plot designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 163-172.

  20. SCHOEN, Eric D. & JONES, Bradley & GOOS, Peter, 2010. "Split-plot experiments with factor-dependent whole-plot sizes," Working Papers 2010001, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.
    2. Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi, 2014. "A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1193-1207.

  21. DE KETELAERE, Bart & GOOS, Peter & BRIJS, Kristof, 2010. "Prespecified factor-level combinations in the optimal design of mixture-process variable experiments," Working Papers 2011001, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.

  22. ARNOUTS, Heidi & GOOS, Peter, 2008. "Update formulas for split-plot and block designs," Working Papers 2008022, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2013. "An iterated local search algorithm for the construction of large scale D-optimal experimental designs," Working Papers 2013006, University of Antwerp, Faculty of Business and Economics.
    2. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.
    3. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    4. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.

  23. SALEHIPOUR, Amir & SÖRENSEN, Kenneth & GOOS, Peter & BRÄYSY, Olli, 2008. "An efficient GRASP+VND metaheuristic for the traveling repairman problem," Working Papers 2008008, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Samuel Nucamendi-Guillén & Iris Martínez-Salazar & Francisco Angel-Bello & J Marcos Moreno-Vega, 2016. "A mixed integer formulation and an efficient metaheuristic procedure for the k-Travelling Repairmen Problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(8), pages 1121-1134, August.
    2. Rivera, Juan Carlos & Murat Afsar, H. & Prins, Christian, 2016. "Mathematical formulations and exact algorithm for the multitrip cumulative capacitated single-vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 249(1), pages 93-104.
    3. Juan Rivera & H. Afsar & Christian Prins, 2015. "A multistart iterated local search for the multitrip cumulative capacitated vehicle routing problem," Computational Optimization and Applications, Springer, vol. 61(1), pages 159-187, May.
    4. Yu, Mingzhu & Qi, Xiangtong, 2014. "A vehicle routing problem with multiple overlapped batches," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 40-55.
    5. Zhang, Zizhen & Qin, Hu & Zhu, Wenbin & Lim, Andrew, 2012. "The single vehicle routing problem with toll-by-weight scheme: A branch-and-bound approach," European Journal of Operational Research, Elsevier, vol. 220(2), pages 295-304.

  24. ARNOUTS, Heidi & GOOS, Peter, 2008. "Staggered designs for experiments with more than one hard-to-change factor," Working Papers 2008018, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.

  25. GOOS, Peter & VERMEULEN, Bart & VANDEBROEK, Martina, 2008. "D-optimal conjoint choice designs with no-choice options for a nested logit model," Working Papers 2008020, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2008. "Models and optimal designs for conjoint choice experiments including a no-choice option," International Journal of Research in Marketing, Elsevier, vol. 25(2), pages 94-103.

  26. BRADLEY, Jones & GOOS, Peter, 2007. "D-optimal design of split-split-plot experiments," Working Papers 2007017, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    2. ARNOUTS, Heidi & GOOS, Peter, 2009. "Design and analysis of industrial strip-plot experiments," Working Papers 2009007, University of Antwerp, Faculty of Business and Economics.
    3. Xiaodong Li & Xu He & Yuanzhen He & Hui Zhang & Zhong Zhang & Dennis K. J. Lin, 2017. "The Design and Analysis for the Icing Wind Tunnel Experiment of a New Deicing Coating," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1417-1429, October.
    4. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "ARMA-Design: Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Jan 2025.
    5. Murat Kulahci & John Tyssedal, 2017. "Split-plot designs for multistage experimentation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(3), pages 493-510, February.
    6. Loeza-Serrano, S. & Donev, A.N., 2014. "Construction of experimental designs for estimating variance components," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1168-1177.
    7. Alexandre Bohyn & Eric D. Schoen & Chee Ping Ng & Kristina Bishard & Manon Haarmans & Sebastian J. Trietsch & Peter Goos, 2024. "Design and Analysis of a Microplate Assay in the Presence of Multiple Restrictions on the Randomization," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(4), pages 745-765, December.
    8. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.
    9. Borrotti, Matteo & Sambo, Francesco & Mylona, Kalliopi, 2023. "Multi-objective optimisation of split-plot designs," Econometrics and Statistics, Elsevier, vol. 28(C), pages 163-172.
    10. Lin, Chang-Yun & Yang, Po, 2019. "Data-driven multistratum designs with the generalized Bayesian D-D criterion for highly uncertain models," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 222-238.

  27. GARROI, Jean-Jacques & GOOS, Peter & SÖRENSEN, Kenneth, 2006. "A variable-neighbourhood search algorithm for finding optimal run orders in the presence of serial correlation and time trends," Working Papers 2006026, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. SYAFITRI, Utami & SARTONO, Bagus & GOOS, Peter, 2015. "D- and I-optimal design of mixture experiments in the presence of ingredient availability constraints," Working Papers 2015003, University of Antwerp, Faculty of Business and Economics.
    2. VÁZQUEZ-ALCOCER, Alan & GOOS, Peter & SCHOEN, Eric D., 2016. "Two-level designs constructed by concatenating orthogonal arrays of strenght three," Working Papers 2016011, University of Antwerp, Faculty of Business and Economics.

  28. GOOS, Peter, "undated". "The usefulness of optimal design for generating blocked and split-plot response surface experiments," Working Papers 2005033, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.

  29. JONES, Bradley & GOOS, Peter, "undated". "A candidate-set-free algorithm for generating D-optimal split-plot designs," Working Papers 2006006, University of Antwerp, Faculty of Business and Economics.

    Cited by:

    1. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.
    2. ARNOUTS, Heidi & GOOS, Peter, 2013. "Staggered-level designs for response surface modeling," Working Papers 2013027, University of Antwerp, Faculty of Business and Economics.
    3. ARNOUTS, Heidi & GOOS, Peter, 2009. "Design and analysis of industrial strip-plot experiments," Working Papers 2009007, University of Antwerp, Faculty of Business and Economics.
    4. ARNOUTS, Heidi & GOOS, Peter, 2008. "Update formulas for split-plot and block designs," Working Papers 2008022, University of Antwerp, Faculty of Business and Economics.
    5. Moein Saleh & Ming-Hung Kao & Rong Pan, 2017. "Design D-optimal event-related functional magnetic resonance imaging experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 73-91, January.
    6. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.
    7. Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi, 2014. "A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1193-1207.
    8. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    9. MYLONA, Kalliopi & MACHARIA, Harrison & GOOS, Peter, 2011. "Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs," Working Papers 2011010, University of Antwerp, Faculty of Business and Economics.
    10. SCHOEN, Eric D. & JONES, Bradley & GOOS, Peter, 2010. "Split-plot experiments with factor-dependent whole-plot sizes," Working Papers 2010001, University of Antwerp, Faculty of Business and Economics.
    11. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.

Articles

  1. Yuanzhi Huang & Steven G. Gilmour & Kalliopi Mylona & Peter Goos, 2020. "Optimal Design of Experiments for Hybrid Nonlinear Models, with Applications to Extended Michaelis–Menten Kinetics," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 601-616, December.

    Cited by:

    1. Elham Yousefi & Werner G. Müller, 2023. "Impact of the Error Structure on the Design and Analysis of Enzyme Kinetic Models," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 31-56, April.
    2. Hans-Peter Piepho & Robert J. Tempelman & Emlyn R. Williams, 2020. "Guest Editors’ Introduction to the Special Issue on “Recent Advances in Design and Analysis of Experiments and Observational Studies in Agriculture”," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 453-456, December.
    3. Chen, Ping-Yang & Chen, Ray-Bing & Chen, Yu-Shi & Wong, Weng Kee, 2023. "Numerical Methods for Finding A-optimal Designs Analytically," Econometrics and Statistics, Elsevier, vol. 28(C), pages 155-162.

  2. Aiste Ruseckaite & Dennis Fok & Peter Goos, 2020. "Flexible Mixture-Amount Models Using Multivariate Gaussian Processes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 257-271, April.

    Cited by:

    1. S. Van Cranenburgh & S. Wang & A. Vij & F. Pereira & J. Walker, 2021. "Choice modelling in the age of machine learning -- discussion paper," Papers 2101.11948, arXiv.org, revised Nov 2021.

  3. Goos, P. & Syafitri, U. & Sartono, B. & Vazquez, A.R., 2020. "A nonlinear multidimensional knapsack problem in the optimal design of mixture experiments," European Journal of Operational Research, Elsevier, vol. 281(1), pages 201-221.

    Cited by:

    1. Chakraborty, Sourabh & Dunford, Nurhan Turgut & Goad, Carla, 2021. "A kinetic study of microalgae, municipal sludge and cedar wood co-pyrolysis," Renewable Energy, Elsevier, vol. 165(P1), pages 514-524.

  4. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.

    Cited by:

    1. Boonaert, Eva & Hoyweghen, Kaat Van & Feyisa, Ashenafi Duguma & Goos, Peter & Maertens, Miet, 2021. "Twofold Gendered Preferences in the Quantity-Quality Trade-Off Impact the Demographic Transition in Ethiopia," 2021 Conference, August 17-31, 2021, Virtual 315224, International Association of Agricultural Economists.
    2. Timmer, Sebastian & Merfeld, Katrin & Henkel, Sven, 2023. "Exploring motivations for multimodal commuting: A hierarchical means-end chain analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).

  5. Kessels, Roselinde & Jones, Bradley & Goos, Peter, 2019. "Using Firth's method for model estimation and market segmentation based on choice data," Journal of choice modelling, Elsevier, vol. 31(C), pages 1-21.

    Cited by:

    1. Mouter, Niek & de Ruijter, Annamarie & Ardine de Wit, G. & Lambooij, Mattijs S & van Wijhe, Maarten & van Exel, Job & Kessels, Roselinde, 2022. "“Please, you go first!” preferences for a COVID-19 vaccine among adults in the Netherlands," Social Science & Medicine, Elsevier, vol. 292(C).

  6. Yuanzhi Huang & Steven G. Gilmour & Kalliopi Mylona & Peter Goos, 2019. "Optimal design of experiments for non‐linear response surface models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(3), pages 623-640, April.

    Cited by:

    1. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    2. Ul Hassan, Mahmood & Miller, Frank, 2021. "An exchange algorithm for optimal calibration of items in computerized achievement tests," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    3. Yuanzhi Huang & Steven G. Gilmour & Kalliopi Mylona & Peter Goos, 2020. "Optimal Design of Experiments for Hybrid Nonlinear Models, with Applications to Extended Michaelis–Menten Kinetics," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 601-616, December.

  7. Eric D. Schoen & Nha Vo-Thanh & Peter Goos, 2017. "Two-Level Orthogonal Screening Designs With 24, 28, 32, and 36 Runs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1354-1369, July.

    Cited by:

    1. Emanuele Borgonovo & Elmar Plischke & Giovanni Rabitti, 2022. "Interactions and computer experiments," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1274-1303, September.
    2. Singh, Rakhi & Stufken, John, 2024. "Factor selection in screening experiments by aggregation over random models," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
    3. VÁZQUEZ-ALCOCER, Alan & SCHOEN, Eric D. & GOOS, Peter, 2018. "A mixed integer optimization approach for model selection in screening experiments," Working Papers 2018007, University of Antwerp, Faculty of Business and Economics.
    4. Eendebak, Pieter T. & Schoen, Eric D. & Vazquez, Alan R. & Goos, Peter, 2023. "Systematic enumeration of two-level even-odd designs of strength 3," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).

  8. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2017. "Bayesian D-optimal choice designs for mixtures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 363-386, February.
    See citations under working paper version above.
  9. Kupfer, Franziska & Kessels, Roselinde & Goos, Peter & Van de Voorde, Eddy & Verhetsel, Ann, 2016. "The origin–destination airport choice for all-cargo aircraft operations in Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 53-74.

    Cited by:

    1. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
    2. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    3. Budd, Lucy & Ison, Stephen, 2017. "The role of dedicated freighter aircraft in the provision of global airfreight services," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 34-40.
    4. Zhang, Canrong & Xie, Fanrui & Huang, Kun & Wu, Tao & Liang, Zhe, 2017. "MIP models and a hybrid method for the capacitated air-cargo network planning and scheduling problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 158-173.
    5. Van Asch, Thomas & Dewulf, Wouter & Kupfer, Franziska & Cárdenas, Ivan & Van de Voorde, Eddy, 2020. "Cross-border e-commerce logistics – Strategic success factors for airports," Research in Transportation Economics, Elsevier, vol. 79(C).
    6. Dziedzic, Marcin & Njoya, Eric T. & Warnock-Smith, David & Hubbard, Nick, 2020. "Determinants of air traffic volumes and structure at small European airports," Research in Transportation Economics, Elsevier, vol. 79(C).
    7. Tanrıverdi, Gökhan & Ecer, Fatih & Durak, Mehmet Şahin, 2022. "Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology," Journal of Air Transport Management, Elsevier, vol. 105(C).
    8. Karanki, Fecri & Bilotkach, Volodymyr & Gao, Yi & Lu, Chien-Tsung, 2024. "The economic impact of E-commerce on the U.S. airports: Cost savings and productivity growth," Journal of Air Transport Management, Elsevier, vol. 118(C).
    9. Lotti, Raoni & Caetano, Mauro, 2018. "The airport choice of exporters for fruit from Brazil," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 104-112.
    10. Deng, Yu & Zhang, Yahua & Wang, Kun, 2022. "An analysis of the Chinese scheduled freighter network during the first year of the COVID-19 pandemic," Journal of Transport Geography, Elsevier, vol. 99(C).
    11. Polater, Abdüssamet, 2020. "Airports’ role as logistics centers in humanitarian supply chains: A surge capacity management perspective," Journal of Air Transport Management, Elsevier, vol. 83(C).

  10. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    See citations under working paper version above.
  11. Peter Goos & Bradley Jones & Utami Syafitri, 2016. "I-Optimal Design of Mixture Experiments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 899-911, April.

    Cited by:

    1. Wanida Limmun & Boonorm Chomtee & John J. Borkowski, 2023. "Generating Robust Optimal Mixture Designs Due to Missing Observation Using a Multi-Objective Genetic Algorithm," Mathematics, MDPI, vol. 11(16), pages 1-33, August.
    2. Carlos de la Calle-Arroyo & Miguel A. González-Fernández & Licesio J. Rodríguez-Aragón, 2023. "Optimal Designs for Antoine’s Equation: Compound Criteria and Multi-Objective Designs via Genetic Algorithms," Mathematics, MDPI, vol. 11(3), pages 1-16, January.
    3. Hao, Honghua & Zhu, Xiaoyuan & Zhang, Xinfeng & Zhang, Chongqi, 2021. "R-optimal design of the second-order Scheffé mixture model," Statistics & Probability Letters, Elsevier, vol. 173(C).
    4. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.
    5. Belmiro P. M. Duarte, 2023. "Exact Optimal Designs of Experiments for Factorial Models via Mixed-Integer Semidefinite Programming," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    6. Haosheng Jiang & Chongqi Zhang, 2022. "Construction of Full Order-of-Addition Generalization Simplex-Centroid Designs by the Directed Graph Approach," Mathematics, MDPI, vol. 10(3), pages 1-13, January.
    7. Rios, Nicholas & Winker, Peter & Lin, Dennis K.J., 2022. "TA algorithms for D-optimal OofA Mixture designs," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    8. Lenka Filová & Radoslav Harman, 2020. "Ascent with quadratic assistance for the construction of exact experimental designs," Computational Statistics, Springer, vol. 35(2), pages 775-801, June.

  12. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    See citations under working paper version above.
  13. Maya Duque, P.A. & Castro, M. & Sörensen, K. & Goos, P., 2015. "Home care service planning. The case of Landelijke Thuiszorg," European Journal of Operational Research, Elsevier, vol. 243(1), pages 292-301.

    Cited by:

    1. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    2. Delaet, Arne & Ramaekers, Katrien & Hirsch, Patrick & Molenbruch, Yves & Braekers, Kris, 2024. "A matheuristic for integrated medium-term home healthcare planning," European Journal of Operational Research, Elsevier, vol. 319(2), pages 543-556.
    3. de Aguiar, Ana Raquel Pena & Ramos, Tânia Rodrigues Pereira & Gomes, Maria Isabel, 2023. "Home care routing and scheduling problem with teams’ synchronization," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    4. Pahlevani, Delaram & Abbasi, Babak & Hearne, John W. & Eberhard, Andrew, 2022. "A cluster-based algorithm for home health care planning: A case study in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    5. Isabel Méndez-Fernández & Silvia Lorenzo-Freire & Ignacio García-Jurado & Julián Costa & Luisa Carpente, 2020. "A heuristic approach to the task planning problem in a home care business," Health Care Management Science, Springer, vol. 23(4), pages 556-570, December.
    6. Braekers, Kris & Hartl, Richard F. & Parragh, Sophie N. & Tricoire, Fabien, 2016. "A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience," European Journal of Operational Research, Elsevier, vol. 248(2), pages 428-443.
    7. Mendoza-Alonzo, Jennifer & Zayas-Castro, José & Charkhgard, Hadi, 2020. "Office-based and home-care for older adults in primary care: A comparative analysis using the Nash bargaining solution," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    8. Stavropoulou, F. & Repoussis, P.P. & Tarantilis, C.D., 2019. "The Vehicle Routing Problem with Profits and consistency constraints," European Journal of Operational Research, Elsevier, vol. 274(1), pages 340-356.
    9. Naderi, Bahman & Begen, Mehmet A. & Zaric, Gregory S. & Roshanaei, Vahid, 2023. "A novel and efficient exact technique for integrated staffing, assignment, routing, and scheduling of home care services under uncertainty," Omega, Elsevier, vol. 116(C).
    10. Laura Malagodi & Ettore Lanzarone & Andrea Matta, 2021. "Home care vehicle routing problem with chargeable overtime and strict and soft preference matching," Health Care Management Science, Springer, vol. 24(1), pages 140-159, March.
    11. Nikzad, Erfaneh & Bashiri, Mahdi & Abbasi, Babak, 2021. "A matheuristic algorithm for stochastic home health care planning," European Journal of Operational Research, Elsevier, vol. 288(3), pages 753-774.
    12. Grenouilleau, Florian & Legrain, Antoine & Lahrichi, Nadia & Rousseau, Louis-Martin, 2019. "A set partitioning heuristic for the home health care routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 275(1), pages 295-303.
    13. Osman Atilla Yazır & Çağrı Koç & Eda Yücel, 2023. "The multi-period home healthcare routing and scheduling problem with electric vehicles," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(3), pages 853-901, September.
    14. Mosquera, Federico & Smet, Pieter & Vanden Berghe, Greet, 2019. "Flexible home care scheduling," Omega, Elsevier, vol. 83(C), pages 80-95.
    15. Makboul, Salma & Kharraja, Said & Abbassi, Abderrahman & El Hilali Alaoui, Ahmed, 2024. "A multiobjective approach for weekly Green Home Health Care routing and scheduling problem with care continuity and synchronized services," Operations Research Perspectives, Elsevier, vol. 12(C).
    16. Lin, Meiyan & Ma, Lijun & Ying, Chengshuo, 2021. "Matching daily home health-care demands with supply in service-sharing platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    17. Paola Cappanera & Maria Grazia Scutellà, 2022. "Addressing consistency and demand uncertainty in the Home Care planning problem," Flexible Services and Manufacturing Journal, Springer, vol. 34(1), pages 1-39, March.
    18. Mustafa Demirbilek & Juergen Branke & Arne Strauss, 2019. "Dynamically accepting and scheduling patients for home healthcare," Health Care Management Science, Springer, vol. 22(1), pages 140-155, March.
    19. Sacramento Quintanilla & Francisco Ballestín & Ángeles Pérez, 2020. "Mathematical models to improve the current practice in a Home Healthcare Unit," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 43-74, March.
    20. Gang Du & Xi Liang & Chuanwang Sun, 2017. "Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows," Sustainability, MDPI, vol. 9(2), pages 1-22, February.
    21. Yadav, Niteesh & Tanksale, Ajinkya, 2022. "An integrated routing and scheduling problem for home healthcare delivery with limited person-to-person contact," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1100-1125.
    22. Biao Yuan & Zhibin Jiang, 2017. "Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    23. Cinar, Ahmet & Salman, F. Sibel & Bozkaya, Burcin, 2021. "Prioritized single nurse routing and scheduling for home healthcare services," European Journal of Operational Research, Elsevier, vol. 289(3), pages 867-878.
    24. Restrepo, María I. & Rousseau, Louis-Martin & Vallée, Jonathan, 2020. "Home healthcare integrated staffing and scheduling," Omega, Elsevier, vol. 95(C).
    25. Meiyan Lin & Kwai Sang Chin & Lijun Ma & Kwok Leung Tsui, 2020. "A comprehensive multi-objective mixed integer nonlinear programming model for an integrated elderly care service districting problem," Annals of Operations Research, Springer, vol. 291(1), pages 499-529, August.

  14. Roselinde Kessels & Bradley Jones & Peter Goos, 2015. "An improved two‐stage variance balance approach for constructing partial profile designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 626-648, September.

    Cited by:

    1. Luyten, Jeroen & Kessels, Roselinde & Atkins, Katherine E. & Jit, Mark & van Hoek, Albert Jan, 2019. "Quantifying the public's view on social value judgments in vaccine decision-making: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 228(C), pages 181-193.
    2. Großmann, Heiko, 2019. "A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    3. Luyten, Jeroen & Beutels, Philippe & Vandermeulen, Corinne & Kessels, Roselinde, 2022. "Social preferences for adopting new vaccines in the national immunization program: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 303(C).
    4. Bansal, Prateek & Kessels, Roselinde & Krueger, Rico & Graham, Daniel J., 2022. "Preferences for using the London Underground during the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 45-60.
    5. Meyerhoff, Jürgen & Oehlmann, Malte, 2023. "The performance of full versus partial profile choice set designs in environmental valuation," Ecological Economics, Elsevier, vol. 204(PA).
    6. Van Acker, Veronique & Kessels, Roselinde & Palhazi Cuervo, Daniel & Lannoo, Steven & Witlox, Frank, 2020. "Preferences for long-distance coach transport: Evidence from a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 759-779.
    7. Verelst, Frederik & Willem, Lander & Kessels, Roselinde & Beutels, Philippe, 2018. "Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives," Social Science & Medicine, Elsevier, vol. 207(C), pages 106-116.
    8. Kotzab, Herbert & Yumurtacı Hüseyinoğlu, Işık Özge & Şen, Irmak & Mena, Carlos, 2024. "Exploring home delivery service attributes: Sustainability versus delivery expectations during the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).

  15. Palhazi Cuervo, Daniel & Goos, Peter & Sörensen, Kenneth & Arráiz, Emely, 2014. "An iterated local search algorithm for the vehicle routing problem with backhauls," European Journal of Operational Research, Elsevier, vol. 237(2), pages 454-464.
    See citations under working paper version above.
  16. Maya Duque, Pablo A. & Coene, Sofie & Goos, Peter & Sörensen, Kenneth & Spieksma, Frits, 2013. "The accessibility arc upgrading problem," European Journal of Operational Research, Elsevier, vol. 224(3), pages 458-465.
    See citations under working paper version above.
  17. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.

    Cited by:

    1. Robert Turner, 2013. "Using contingent choice surveys to inform national park management," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 3(2), pages 120-138, June.
    2. Rungie, Cam & Scarpa, Riccardo & Thiene, Mara, 2014. "The influence of individuals in forming collective household preferences for water quality," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 161-174.
    3. Andreas Falke & Harald Hruschka, 2017. "A Monte Carlo study of design-generating algorithms for the latent class mixed logit model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1035-1053, October.
    4. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    5. Sardaro, Ruggiero & La Sala, Piermichele & De Pascale, Gianluigi & Faccilongo, Nicola, 2021. "The conservation of cultural heritage in rural areas: Stakeholder preferences regarding historical rural buildings in Apulia, southern Italy," Land Use Policy, Elsevier, vol. 109(C).
    6. John Gibson & Riccardo Scarpa & Halahingano Rohorua, 2013. "Respiratory Health of Pacific Island Immigrants and Preferences for Indoor Air Quality Determinants in New Zealand," Working Papers in Economics 13/09, University of Waikato.
    7. Sardaro, Ruggiero & Faccilongo, Nicola & Roselli, Luigi, 2019. "Wind farms, farmland occupation and compensation: Evidences from landowners’ preferences through a stated choice survey in Italy," Energy Policy, Elsevier, vol. 133(C).
    8. Curtis, John & Grilli, Gianluca & Lynch, Muireann Á, 2024. "Residential renovations: understanding cost-disruption trade-offs," Papers WP776, Economic and Social Research Institute (ESRI).
    9. Jia Wang & Jiaoju Ge & Zhifeng Gao, 2018. "Consumers’ Preferences and Derived Willingness-to-Pay for Water Supply Safety Improvement: The Analysis of Pricing and Incentive Strategies," Sustainability, MDPI, vol. 10(6), pages 1-16, May.
    10. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2014. "Bayesian D-Optimal Choice Designs for Mixtures," Tinbergen Institute Discussion Papers 14-057/III, Tinbergen Institute.
    11. Ruggiero Sardaro & Nicola Faccilongo & Francesco Contò & Piermichele La Sala, 2021. "Adaption Actions to Cope with Climate Change: Evidence from Farmers’ Preferences on an Agrobiodiversity Conservation Programme in the Mediterranean Area," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    12. Begoña A. Farizo & John Joyce & Mario Soliño, 2014. "Dealing with Heterogeneous Preferences Using Multilevel Mixed Models," Land Economics, University of Wisconsin Press, vol. 90(1), pages 181-198.
    13. Gracia, Azucena & Barreiro-Hurlé, Jesús & Pérez y Pérez, Luis, 2012. "Can renewable energy be financed with higher electricity prices? Evidence from a Spanish region," Energy Policy, Elsevier, vol. 50(C), pages 784-794.
    14. Curtis, John & Grilli, Gianluca & Lynch, Muireann, 2024. "Residential renovations: Understanding cost-disruption trade-offs," Energy Policy, Elsevier, vol. 192(C).
    15. Ruokamo, Enni, 2016. "Household preferences of hybrid home heating systems – A choice experiment application," Energy Policy, Elsevier, vol. 95(C), pages 224-237.
    16. Ladenburg, Jacob & Skotte, Maria, 2022. "Heterogeneity in willingness to pay for the location of offshore wind power development: An application of the willingness to pay space model," Energy, Elsevier, vol. 241(C).
    17. Park, Dojin, 2021. "The Valuation of Soil Health Improvements and Ecosystem Services among Crop Producers in the U.S," 2021 Annual Meeting, August 1-3, Austin, Texas 314032, Agricultural and Applied Economics Association.
    18. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 27, pages 661-674, Edward Elgar Publishing.
    19. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    20. Campbell, Danny & Hensher, David A. & Scarpa, Riccardo, 2012. "Cost thresholds, cut-offs and sensitivities in stated choice analysis: Identification and implications," Resource and Energy Economics, Elsevier, vol. 34(3), pages 396-411.
    21. Danley, Brian & Sandorf, Erlend Dancke & Campbell, Danny, 2021. "Putting your best fish forward: Investigating distance decay and relative preferences for fish conservation," Journal of Environmental Economics and Management, Elsevier, vol. 108(C).

  18. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.

    Cited by:

    1. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
    2. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    3. Jason Soria & Shelly Etzioni & Yoram Shiftan & Amanda Stathopoulos & Eran Ben-Elia, 2022. "Microtransit adoption in the wake of the COVID-19 pandemic: evidence from a choice experiment with transit and car commuters," Papers 2204.01974, arXiv.org.
    4. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    5. Onesun Steve Yoo & Tingliang Huang & Kenan Arifoğlu, 2021. "A Theoretical Analysis of the Lean Start-up Method," Marketing Science, INFORMS, vol. 40(3), pages 395-412, May.
    6. Vishva Danthurebandara & Jie Yu & Martina Vandebroek, 2015. "Designing choice experiments by optimizing the complexity level to individual abilities," Quantitative Marketing and Economics (QME), Springer, vol. 13(1), pages 1-26, March.
    7. Basem Al-Omari & Joviana Farhat & Mujahed Shraim, 2023. "The Role of Web-Based Adaptive Choice-Based Conjoint Analysis Technology in Eliciting Patients’ Preferences for Osteoarthritis Treatment," IJERPH, MDPI, vol. 20(4), pages 1-15, February.
    8. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.
    9. Vishva Danthurebandara & Jie Yu & Martina Vandebroek, 2011. "Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay," Quantitative Marketing and Economics (QME), Springer, vol. 9(4), pages 429-448, December.
    10. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    11. van Cranenburgh, Sander & Rose, John M. & Chorus, Caspar G., 2018. "On the robustness of efficient experimental designs towards the underlying decision rule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 50-64.
    12. Denis Sauré & Juan Pablo Vielma, 2019. "Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis," Operations Research, INFORMS, vol. 67(2), pages 315-338, March.

  19. Roselinde Kessels & Peter Goos & Bradley Jones & Martina Vandebroek, 2011. "Rejoinder: the usefulness of Bayesian optimal designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 197-203, May.

    Cited by:

    1. Collewet, Marion & Fairley, Kim & Kessels, Roselinde & Knoef, Marike & van Vliet, Olaf, 2024. "The design of welfare: unraveling taxpayers' preferences," OSF Preprints 4am7e, Center for Open Science.
    2. Prateek Bansal & Roselinde Kessels & Rico Krueger & Daniel J Graham, 2021. "Face masks, vaccination rates and low crowding drive the demand for the London Underground during the COVID-19 pandemic," Papers 2107.02394, arXiv.org.
    3. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    4. Kara R. Grant & R. Karina Gallardo & Jill J. McCluskey, 2021. "Consumer preferences for foods with clean labels and new food technologies," Agribusiness, John Wiley & Sons, Ltd., vol. 37(4), pages 764-781, October.
    5. Kessels, Roselinde & Jones, Bradley & Goos, Peter, 2019. "Using Firth's method for model estimation and market segmentation based on choice data," Journal of choice modelling, Elsevier, vol. 31(C), pages 1-21.
    6. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    7. De Bauw, Michiel & Franssens, Samuel & Vranken, Liesbet, 2022. "Trading off environmental attributes in food consumption choices," Food Policy, Elsevier, vol. 112(C).
    8. Mohd Zuhair & Ram Babu Roy, 2022. "Eliciting relative preferences for the attributes of health insurance schemes among rural consumers in India," International Journal of Health Economics and Management, Springer, vol. 22(4), pages 443-458, December.
    9. Black, Michael A. & Woodward, Richard T. & Morgan, Cristine & Bagnall, Dianna & Kiella, Erin & Cisneros, Marissa & McIntosh, William Alex, 2020. "An empirical estimate of value of manageable soil quality," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304430, Agricultural and Applied Economics Association.
    10. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    11. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    12. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    13. T. Lehnert & O. H. Günther & A. Hajek & S. G. Riedel-Heller & H. H. König, 2018. "Preferences for home- and community-based long-term care services in Germany: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(9), pages 1213-1223, December.
    14. C. M. Dieteren & I. Bonfrer & W. B. F. Brouwer & J. Exel, 2023. "Public preferences for policies promoting a healthy diet: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(9), pages 1429-1440, December.
    15. van Cranenburgh, Sander & Collins, Andrew T., 2019. "New software tools for creating stated choice experimental designs efficient for regret minimisation and utility maximisation decision rules," Journal of choice modelling, Elsevier, vol. 31(C), pages 104-123.
    16. Luyten, Jeroen & Kessels, Roselinde & Atkins, Katherine E. & Jit, Mark & van Hoek, Albert Jan, 2019. "Quantifying the public's view on social value judgments in vaccine decision-making: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 228(C), pages 181-193.
    17. KESSELS, Roselinde & VAN HERCK, Pieter & DANCET, Eline & ANNEMANS, Lieven & SERMEUS, Walter, 2014. "How to reform western care payment systems according to physicians, policy makers, healthcare executives and researchers: A discrete choice experiment," Working Papers 2014022, University of Antwerp, Faculty of Business and Economics.
    18. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.
    19. Mehrnoosh Asadi & James I. Price & Roselinde Kessels & Pallab Mozumder, 2024. "Hurricane-Induced Power Disruptions: Household Preferences for Improving Infrastructure Resilience," Economics of Disasters and Climate Change, Springer, vol. 8(2), pages 235-261, July.
    20. Srivastava, Aman & Van Passel, Steven & Kessels, Roselinde & Valkering, Pieter & Laes, Erik, 2020. "Reducing winter peaks in electricity consumption: A choice experiment to structure demand response programs," Energy Policy, Elsevier, vol. 137(C).
    21. Eric Nyarko, 2021. "Optimal $$2^K$$ 2 K paired comparison designs for third-order interactions," Statistical Papers, Springer, vol. 62(5), pages 2067-2082, October.
    22. Joalland, Olivier & Mahieu, Pierre-Alexandre, 2023. "Developing large-scale offshore wind power programs: A choice experiment analysis in France," Ecological Economics, Elsevier, vol. 204(PA).
    23. Großmann, Heiko, 2019. "A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    24. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Steven Passel, 2024. "Farmers’ preferences and willingness to pay for improved irrigation water supply program: a discrete choice experiment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27277-27300, November.
    25. Srivastava, A. & Van Passel, S. & Valkering, P. & Laes, E.J.W., 2021. "Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    26. Frischknecht, Bart D. & Eckert, Christine & Geweke, John & Louviere, Jordan J., 2014. "A simple method for estimating preference parameters for individuals," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 35-48.
    27. Kar Ho Lim & Wuyang Hu, 2023. "Contextual reference price in choice experiments," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1288-1306, August.
    28. Luyten, Jeroen & Beutels, Philippe & Vandermeulen, Corinne & Kessels, Roselinde, 2022. "Social preferences for adopting new vaccines in the national immunization program: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 303(C).
    29. Mouter, Niek & de Ruijter, Annamarie & Ardine de Wit, G. & Lambooij, Mattijs S & van Wijhe, Maarten & van Exel, Job & Kessels, Roselinde, 2022. "“Please, you go first!” preferences for a COVID-19 vaccine among adults in the Netherlands," Social Science & Medicine, Elsevier, vol. 292(C).
    30. Bansal, Prateek & Kessels, Roselinde & Krueger, Rico & Graham, Daniel J., 2022. "Preferences for using the London Underground during the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 45-60.
    31. Van Acker, Veronique & Kessels, Roselinde & Palhazi Cuervo, Daniel & Lannoo, Steven & Witlox, Frank, 2020. "Preferences for long-distance coach transport: Evidence from a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 759-779.
    32. Jeroen Luyten & Sandy Tubeuf & Roselinde Kessels, 2022. "Rationing of a scarce life‐saving resource: Public preferences for prioritizing COVID‐19 vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 342-362, February.
    33. Kotzab, Herbert & Yumurtacı Hüseyinoğlu, Işık Özge & Şen, Irmak & Mena, Carlos, 2024. "Exploring home delivery service attributes: Sustainability versus delivery expectations during the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).

  20. Roselinde Kessels & Bradley Jones & Peter Goos & Martina Vandebroek, 2011. "The usefulness of Bayesian optimal designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 173-188, May.

    Cited by:

    1. Collewet, Marion & Fairley, Kim & Kessels, Roselinde & Knoef, Marike & van Vliet, Olaf, 2024. "The design of welfare: unraveling taxpayers' preferences," OSF Preprints 4am7e, Center for Open Science.
    2. Prateek Bansal & Roselinde Kessels & Rico Krueger & Daniel J Graham, 2021. "Face masks, vaccination rates and low crowding drive the demand for the London Underground during the COVID-19 pandemic," Papers 2107.02394, arXiv.org.
    3. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    4. Kara R. Grant & R. Karina Gallardo & Jill J. McCluskey, 2021. "Consumer preferences for foods with clean labels and new food technologies," Agribusiness, John Wiley & Sons, Ltd., vol. 37(4), pages 764-781, October.
    5. Kessels, Roselinde & Jones, Bradley & Goos, Peter, 2019. "Using Firth's method for model estimation and market segmentation based on choice data," Journal of choice modelling, Elsevier, vol. 31(C), pages 1-21.
    6. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    7. De Bauw, Michiel & Franssens, Samuel & Vranken, Liesbet, 2022. "Trading off environmental attributes in food consumption choices," Food Policy, Elsevier, vol. 112(C).
    8. Mohd Zuhair & Ram Babu Roy, 2022. "Eliciting relative preferences for the attributes of health insurance schemes among rural consumers in India," International Journal of Health Economics and Management, Springer, vol. 22(4), pages 443-458, December.
    9. Black, Michael A. & Woodward, Richard T. & Morgan, Cristine & Bagnall, Dianna & Kiella, Erin & Cisneros, Marissa & McIntosh, William Alex, 2020. "An empirical estimate of value of manageable soil quality," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304430, Agricultural and Applied Economics Association.
    10. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    11. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    12. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    13. T. Lehnert & O. H. Günther & A. Hajek & S. G. Riedel-Heller & H. H. König, 2018. "Preferences for home- and community-based long-term care services in Germany: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(9), pages 1213-1223, December.
    14. C. M. Dieteren & I. Bonfrer & W. B. F. Brouwer & J. Exel, 2023. "Public preferences for policies promoting a healthy diet: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(9), pages 1429-1440, December.
    15. van Cranenburgh, Sander & Collins, Andrew T., 2019. "New software tools for creating stated choice experimental designs efficient for regret minimisation and utility maximisation decision rules," Journal of choice modelling, Elsevier, vol. 31(C), pages 104-123.
    16. Luyten, Jeroen & Kessels, Roselinde & Atkins, Katherine E. & Jit, Mark & van Hoek, Albert Jan, 2019. "Quantifying the public's view on social value judgments in vaccine decision-making: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 228(C), pages 181-193.
    17. KESSELS, Roselinde & VAN HERCK, Pieter & DANCET, Eline & ANNEMANS, Lieven & SERMEUS, Walter, 2014. "How to reform western care payment systems according to physicians, policy makers, healthcare executives and researchers: A discrete choice experiment," Working Papers 2014022, University of Antwerp, Faculty of Business and Economics.
    18. Zijlstra, Toon & Goos, Peter & Verhetsel, Ann, 2019. "A mixture-amount stated preference study on the mobility budget," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 230-246.
    19. Mehrnoosh Asadi & James I. Price & Roselinde Kessels & Pallab Mozumder, 2024. "Hurricane-Induced Power Disruptions: Household Preferences for Improving Infrastructure Resilience," Economics of Disasters and Climate Change, Springer, vol. 8(2), pages 235-261, July.
    20. Srivastava, Aman & Van Passel, Steven & Kessels, Roselinde & Valkering, Pieter & Laes, Erik, 2020. "Reducing winter peaks in electricity consumption: A choice experiment to structure demand response programs," Energy Policy, Elsevier, vol. 137(C).
    21. Eric Nyarko, 2021. "Optimal $$2^K$$ 2 K paired comparison designs for third-order interactions," Statistical Papers, Springer, vol. 62(5), pages 2067-2082, October.
    22. Joalland, Olivier & Mahieu, Pierre-Alexandre, 2023. "Developing large-scale offshore wind power programs: A choice experiment analysis in France," Ecological Economics, Elsevier, vol. 204(PA).
    23. Großmann, Heiko, 2019. "A practical approach to designing partial-profile choice experiments with two alternatives for estimating main effects and interactions of many two-level attributes," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    24. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Steven Passel, 2024. "Farmers’ preferences and willingness to pay for improved irrigation water supply program: a discrete choice experiment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27277-27300, November.
    25. Srivastava, A. & Van Passel, S. & Valkering, P. & Laes, E.J.W., 2021. "Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    26. Frischknecht, Bart D. & Eckert, Christine & Geweke, John & Louviere, Jordan J., 2014. "A simple method for estimating preference parameters for individuals," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 35-48.
    27. Kar Ho Lim & Wuyang Hu, 2023. "Contextual reference price in choice experiments," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1288-1306, August.
    28. Luyten, Jeroen & Beutels, Philippe & Vandermeulen, Corinne & Kessels, Roselinde, 2022. "Social preferences for adopting new vaccines in the national immunization program: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 303(C).
    29. Mouter, Niek & de Ruijter, Annamarie & Ardine de Wit, G. & Lambooij, Mattijs S & van Wijhe, Maarten & van Exel, Job & Kessels, Roselinde, 2022. "“Please, you go first!” preferences for a COVID-19 vaccine among adults in the Netherlands," Social Science & Medicine, Elsevier, vol. 292(C).
    30. Bansal, Prateek & Kessels, Roselinde & Krueger, Rico & Graham, Daniel J., 2022. "Preferences for using the London Underground during the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 45-60.
    31. Van Acker, Veronique & Kessels, Roselinde & Palhazi Cuervo, Daniel & Lannoo, Steven & Witlox, Frank, 2020. "Preferences for long-distance coach transport: Evidence from a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 759-779.
    32. Verelst, Frederik & Willem, Lander & Kessels, Roselinde & Beutels, Philippe, 2018. "Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives," Social Science & Medicine, Elsevier, vol. 207(C), pages 106-116.
    33. Jeroen Luyten & Sandy Tubeuf & Roselinde Kessels, 2022. "Rationing of a scarce life‐saving resource: Public preferences for prioritizing COVID‐19 vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 342-362, February.
    34. Kotzab, Herbert & Yumurtacı Hüseyinoğlu, Işık Özge & Şen, Irmak & Mena, Carlos, 2024. "Exploring home delivery service attributes: Sustainability versus delivery expectations during the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).

  21. Arnouts, Heidi & Goos, Peter, 2010. "Update formulas for split-plot and block designs," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3381-3391, December.
    See citations under working paper version above.
  22. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.

    Cited by:

    1. Nicolas Depraetere & Martina Vandebroek, 2017. "A comparison of variational approximations for fast inference in mixed logit models," Computational Statistics, Springer, vol. 32(1), pages 93-125, March.
    2. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    3. Akinc, Deniz & Vandebroek, Martina, 2018. "Bayesian estimation of mixed logit models: Selecting an appropriate prior for the covariance matrix," Journal of choice modelling, Elsevier, vol. 29(C), pages 133-151.
    4. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
    5. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2014. "Bayesian D-Optimal Choice Designs for Mixtures," Tinbergen Institute Discussion Papers 14-057/III, Tinbergen Institute.
    6. Prateek Bansal & Vahid Keshavarzzadeh & Angelo Guevara & Shanjun Li & Ricardo A Daziano, 2022. "Designed quadrature to approximate integrals in maximum simulated likelihood estimation [Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariat," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 301-321.
    7. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.
    8. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    9. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    10. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.

  23. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2010. "Obtaining more information from conjoint experiments by best-worst choices," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1426-1433, June.

    Cited by:

    1. André de Palma & Karim Kilani, 2017. "Identities for maximum, minimum, and maxmin random utility models," Post-Print hal-03719024, HAL.
    2. Paudel, Bindu & Zhou, Mo, 2024. "Are consumers “green” enthusiasts or skeptics? Evidence from nontimber forest products," Forest Policy and Economics, Elsevier, vol. 168(C).
    3. Yangui, Ahmed & Akaichi, Faical & Costa-Font, Montserrat & Gil, Jose Maria, 2019. "Comparing results of ranking conjoint analyses, best–worst scaling and discrete choice experiments in a nonhypothetical context," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.
    4. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    5. Denise Doiron & Jane Hall & Patricia Kenny & Deborah J. Street, 2014. "Job preferences of students and new graduates in nursing," Applied Economics, Taylor & Francis Journals, vol. 46(9), pages 924-939, March.
    6. Balcombe, Paul & Rigby, Dan & Azapagic, Adisa, 2014. "Investigating the importance of motivations and barriers related to microgeneration uptake in the UK," Applied Energy, Elsevier, vol. 130(C), pages 403-418.
    7. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    8. Phillips, Yvonne, 2011. "When the Tide is High: Estimating the Welfare Impact of Coastal Erosion Management," 2011 Conference, August 25-26, 2011, Nelson, New Zealand 115414, New Zealand Agricultural and Resource Economics Society.

  24. Jie Yu & Peter Goos & Martina Vandebroek, 2009. "Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity," Marketing Science, INFORMS, vol. 28(1), pages 122-135, 01-02.

    Cited by:

    1. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
    2. Chang Wang & Dries Goossens & Martina Vandebroek, 2018. "The Impact of the Soccer Schedule on TV Viewership and Stadium Attendance," Journal of Sports Economics, , vol. 19(1), pages 82-112, January.
    3. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    4. Andreas Falke & Harald Hruschka, 2017. "A Monte Carlo study of design-generating algorithms for the latent class mixed logit model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1035-1053, October.
    5. Timo Fischer & Gaétan de Rassenfosse, 2011. "Debt Financing of High-growth Startups," DRUID Working Papers 11-04, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    6. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    7. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
    8. Qing Liu & Neeraj Arora, 2011. "Efficient Choice Designs for a Consider-Then-Choose Model," Marketing Science, INFORMS, vol. 30(2), pages 321-338, 03-04.
    9. Nedka Dechkova Nikiforova & Rossella Berni & Jesús Fernando López‐Fidalgo, 2022. "Optimal approximate choice designs for a two‐step coffee choice, taste and choice again experiment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1895-1917, November.
    10. Apurba Shee & Calum G. Turvey & Ana Marr, 2021. "Heterogeneous Demand and Supply for an Insurance‐linked Credit Product in Kenya: A Stated Choice Experiment Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(1), pages 244-267, February.
    11. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
    12. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    13. Qing Liu & Yihui (Elina) Tang, 2015. "Construction of Heterogeneous Conjoint Choice Designs: A New Approach," Marketing Science, INFORMS, vol. 34(3), pages 346-366, May.
    14. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2014. "Bayesian D-Optimal Choice Designs for Mixtures," Tinbergen Institute Discussion Papers 14-057/III, Tinbergen Institute.
    15. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    16. Fischer, Timo & Henkel, Joachim, 2013. "Complements and substitutes in profiting from innovation—A choice experimental approach," Research Policy, Elsevier, vol. 42(2), pages 326-339.
    17. Hillebrand, Sebastian & Teichert, Thorsten, 2020. "Successor selection in times of continuity and renewal - A discrete choice-experiment," WiSo-HH Working Paper Series 59, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    18. Andreas Falke & Harald Hruschka, 2017. "Setting prices in mixed logit model designs," Marketing Letters, Springer, vol. 28(1), pages 139-154, March.
    19. Frischknecht, Bart D. & Eckert, Christine & Geweke, John & Louviere, Jordan J., 2014. "A simple method for estimating preference parameters for individuals," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 35-48.
    20. Falke Andreas & Hruschka Harald, 2016. "A Monte Carlo Study of Design Procedures for the Semi-parametric Mixed Logit Model," Review of Marketing Science, De Gruyter, vol. 14(1), pages 21-67, June.
    21. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.
    22. Raphael Thomadsen & Robert P. Rooderkerk & On Amir & Neeraj Arora & Bryan Bollinger & Karsten Hansen & Leslie John & Wendy Liu & Aner Sela & Vishal Singh & K. Sudhir & Wendy Wood, 2018. "How Context Affects Choice," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 3-14, March.
    23. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.
    24. Hoenig, Daniel & Henkel, Joachim, 2015. "Quality signals? The role of patents, alliances, and team experience in venture capital financing," Research Policy, Elsevier, vol. 44(5), pages 1049-1064.
    25. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    26. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    27. van Cranenburgh, Sander & Rose, John M. & Chorus, Caspar G., 2018. "On the robustness of efficient experimental designs towards the underlying decision rule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 50-64.
    28. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.
    29. Denis Sauré & Juan Pablo Vielma, 2019. "Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis," Operations Research, INFORMS, vol. 67(2), pages 315-338, March.
    30. Rossella Berni & Nedka Dechkova Nikiforova & Patrizia Pinelli, 2024. "An Optimal Design through a Compound Criterion for Integrating Extra Preference Information in a Choice Experiment: A Case Study on Moka Ground Coffee," Stats, MDPI, vol. 7(2), pages 1-16, June.

  25. Bradley Jones & Peter Goos, 2009. "D-optimal design of split-split-plot experiments," Biometrika, Biometrika Trust, vol. 96(1), pages 67-82.
    See citations under working paper version above.
  26. Steven G. Gilmour & Peter Goos, 2009. "Analysis of data from non‐orthogonal multistratum designs in industrial experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 467-484, September.

    Cited by:

    1. Aiste Ruseckaite & Dennis Fok & Peter Goos, 2016. "Flexible Mixture-Amount Models for Business and Industry using Gaussian Processes," Tinbergen Institute Discussion Papers 16-075/III, Tinbergen Institute.
    2. Vasiliki Koutra & Steven G. Gilmour & Ben M. Parker & Andrew Mead, 2023. "Design of Agricultural Field Experiments Accounting for both Complex Blocking Structures and Network Effects," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 526-548, September.
    3. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.

  27. Kessels, Roselinde & Jones, Bradley & Goos, Peter & Vandebroek, Martina, 2009. "An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 279-291.

    Cited by:

    1. Chang Wang & Dries Goossens & Martina Vandebroek, 2018. "The Impact of the Soccer Schedule on TV Viewership and Stadium Attendance," Journal of Sports Economics, , vol. 19(1), pages 82-112, January.
    2. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    3. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    4. Andreas Falke & Harald Hruschka, 2017. "A Monte Carlo study of design-generating algorithms for the latent class mixed logit model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1035-1053, October.
    5. Kessels, Roselinde & Jones, Bradley & Goos, Peter, 2019. "Using Firth's method for model estimation and market segmentation based on choice data," Journal of choice modelling, Elsevier, vol. 31(C), pages 1-21.
    6. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    7. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
    8. Qing Liu & Neeraj Arora, 2011. "Efficient Choice Designs for a Consider-Then-Choose Model," Marketing Science, INFORMS, vol. 30(2), pages 321-338, 03-04.
    9. Sándor Zsolt, 2013. "Monte Carlo Simulation in Random Coefficient Logit Models Involving Large Sums," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 1(1), pages 85-108, July.
    10. GOOS, Peter & VERMEULEN, Bart & VANDEBROEK, Martina, 2008. "D-optimal conjoint choice designs with no-choice options for a nested logit model," Working Papers 2008020, University of Antwerp, Faculty of Business and Economics.
    11. Nedka Dechkova Nikiforova & Rossella Berni & Jesús Fernando López‐Fidalgo, 2022. "Optimal approximate choice designs for a two‐step coffee choice, taste and choice again experiment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1895-1917, November.
    12. Sanko, Nobuhiro & Yamamoto, Toshiyuki, 2013. "Estimation efficiency of RP/SP models considering SP design and error structures," Journal of choice modelling, Elsevier, vol. 6(C), pages 60-73.
    13. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
    14. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    15. Qing Liu & Yihui (Elina) Tang, 2015. "Construction of Heterogeneous Conjoint Choice Designs: A New Approach," Marketing Science, INFORMS, vol. 34(3), pages 346-366, May.
    16. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2014. "Bayesian D-Optimal Choice Designs for Mixtures," Tinbergen Institute Discussion Papers 14-057/III, Tinbergen Institute.
    17. Rakhi Singh & Angela Dean & Ashish Das & Fangfang Sun, 2021. "A-optimal designs under a linearized model for discrete choice experiments," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(4), pages 445-465, May.
    18. KESSELS, Roselinde & JONES, Bradley & GOOS, Peter, 2013. "An argument for preferring Firth bias-adjusted estimates in aggregate and individual-level discrete choice modeling," Working Papers 2013013, University of Antwerp, Faculty of Business and Economics.
    19. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Experimental designs in triangular simultaneous equations models," Statistical Papers, Springer, vol. 56(2), pages 273-290, May.
    20. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    21. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2010. "Obtaining more information from conjoint experiments by best-worst choices," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1426-1433, June.
    22. Andreas Falke & Harald Hruschka, 2017. "Setting prices in mixed logit model designs," Marketing Letters, Springer, vol. 28(1), pages 139-154, March.
    23. Frischknecht, Bart D. & Eckert, Christine & Geweke, John & Louviere, Jordan J., 2014. "A simple method for estimating preference parameters for individuals," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 35-48.
    24. Falke Andreas & Hruschka Harald, 2016. "A Monte Carlo Study of Design Procedures for the Semi-parametric Mixed Logit Model," Review of Marketing Science, De Gruyter, vol. 14(1), pages 21-67, June.
    25. Jie Yu & Peter Goos & Martina Vandebroek, 2009. "Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity," Marketing Science, INFORMS, vol. 28(1), pages 122-135, 01-02.
    26. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    27. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.
    28. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    29. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.
    30. Dellaert, Benedict G.C. & Arentze, Theo & Horeni, Oliver & Timmermans, Harry J.P., 2017. "Deriving attribute utilities from mental representations of complex decisions," Journal of choice modelling, Elsevier, vol. 22(C), pages 24-38.
    31. Denis Sauré & Juan Pablo Vielma, 2019. "Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis," Operations Research, INFORMS, vol. 67(2), pages 315-338, March.
    32. J. DeShazo & Trudy Cameron & Manrique Saenz, 2009. "The Effect of Consumers’ Real-World Choice Sets on Inferences from Stated Preference Surveys," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 319-343, March.
    33. Rossella Berni & Nedka Dechkova Nikiforova & Patrizia Pinelli, 2024. "An Optimal Design through a Compound Criterion for Integrating Extra Preference Information in a Choice Experiment: A Case Study on Moka Ground Coffee," Stats, MDPI, vol. 7(2), pages 1-16, June.

  28. Kessels, Roselinde & Goos, Peter & Vandebroek, Martina, 2008. "Optimal designs for conjoint experiments," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2369-2387, January.

    Cited by:

    1. Stefano Ciliberti & Simone Del Sarto & Angelo Frascarelli & Giulia Pastorelli & Gaetano Martino, 2020. "Contracts to Govern the Transition towards Sustainable Production: Evidence from a Discrete Choice Analysis in the Durum Wheat Sector in Italy," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    2. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    3. Eunae Son & Song Soo Lim, 2021. "Consumer Acceptance of Gene-Edited versus Genetically Modified Foods in Korea," IJERPH, MDPI, vol. 18(7), pages 1-17, April.
    4. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    5. Apostolakis, George & van Dijk, Gert & Kraanen, Frido & Blomme, Robert J., 2018. "Examining socially responsible investment preferences: A discrete choice conjoint experiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 83-96.
    6. GOOS, Peter & VERMEULEN, Bart & VANDEBROEK, Martina, 2008. "D-optimal conjoint choice designs with no-choice options for a nested logit model," Working Papers 2008020, University of Antwerp, Faculty of Business and Economics.
    7. Jiyeon Jung & Yoonmo Koo, 2018. "Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    8. Frode Alfnes & Maren Bachke & Mette Wik, 2012. "Eliciting donor preferences," Artefactual Field Experiments 00098, The Field Experiments Website.
    9. Lukas Kornher & Martin Schellhorn & Saskia Vetter, 2019. "Disgusting or Innovative-Consumer Willingness to Pay for Insect Based Burger Patties in Germany," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    10. Santos, Jair Carvalho Dos, 2006. "Estimativa De Custo De Coleta E Rentabilidade Para Sistema Extrativo De Latex De Seringueira Na Amazonia," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 145689, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    11. Ronny Baierl, 2018. "Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis," SAGE Open, , vol. 8(2), pages 21582440187, May.
    12. Verhetsel, Ann & Kessels, Roselinde & Goos, Peter & Zijlstra, Toon & Blomme, Nele & Cant, Jeroen, 2015. "Location of logistics companies: a stated preference study to disentangle the impact of accessibility," Journal of Transport Geography, Elsevier, vol. 42(C), pages 110-121.
    13. Sahan T. M. Dissanayake & Amy W. Ando, 2014. "Valuing Grassland Restoration: Proximity to Substitutes and Trade-offs among Conservation Attributes," Land Economics, University of Wisconsin Press, vol. 90(2), pages 237-259.
    14. Philippe Le Coent & Raphaële Préget & Sophie Thoyer, 2016. "Compensating environmental losses versus creating environmental gains: implications for biodiversity offsets," Post-Print hal-02742411, HAL.
    15. ARNOUTS, Heidi & GOOS, Peter, 2008. "Update formulas for split-plot and block designs," Working Papers 2008022, University of Antwerp, Faculty of Business and Economics.
    16. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
    17. A. Cristina Mihale-Wilson & Jan Zibuschka & Oliver Hinz, 2019. "User preferences and willingness to pay for in-vehicle assistance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 37-53, March.
    18. KESSELS, Roselinde & JONES, Bradley & GOOS, Peter, 2013. "An argument for preferring Firth bias-adjusted estimates in aggregate and individual-level discrete choice modeling," Working Papers 2013013, University of Antwerp, Faculty of Business and Economics.
    19. KESSELS, Roselinde & VAN HERCK, Pieter & DANCET, Eline & ANNEMANS, Lieven & SERMEUS, Walter, 2014. "How to reform western care payment systems according to physicians, policy makers, healthcare executives and researchers: A discrete choice experiment," Working Papers 2014022, University of Antwerp, Faculty of Business and Economics.
    20. Rocha, Luiz Eduardo Vasconcelos & Santos, Gilnei Costa & Bastos, Patricia de Melo Abrita, 2006. "Evolução Da Distribuição Da Renda E Da Pobreza Das Famílias Ocupadas E Residentes No Meio Rural Do Estado De Minas Gerais, De 1981 A 2003," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 148649, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    21. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    22. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2010. "Obtaining more information from conjoint experiments by best-worst choices," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1426-1433, June.
    23. Nguyen, Ly & Gao, Zhifeng & Anderson, James L., 2022. "Regulating menu information: What do consumers care and not care about at casual and fine dining restaurants for seafood consumption?," Food Policy, Elsevier, vol. 110(C).
    24. Dong, Songting & Ding, Min & Huber, Joel, 2010. "A simple mechanism to incentive-align conjoint experiments," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 25-32.
    25. Chiambaretto, Paul, 2021. "Air passengers’ willingness to pay for ancillary services on long-haul flights," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    26. Leite, Sheila Cristina Ferreira & De Figueiredo, Margarida Garcia, 2006. "Fluxos De Algodão Em Pluma Para Exportação No Estado Da Bahia: Uma Aplicação De Programação Linear," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 149116, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    27. Mahirah Kamaludin & Muhd Azrin Shah Razali & Nazatul Faizah Haron & A. A. Azlina, 2021. "Energy Efficiency Labelling: Investigating Students Preferences and Awareness on the Energy-efficient Electrical Appliances in Hostel," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 300-308.
    28. Balaine, Lorraine & Gallai, Nicola & Del Corso, Jean-Pierre & Kephaliacos, Charilaos, 2020. "Trading off environmental goods for compensations: Insights from traditional and deliberative valuation methods in the Ecuadorian Amazon," Ecosystem Services, Elsevier, vol. 43(C).
    29. Li, Xiaogu & Clark, Christopher D. & Jensen, Kimberly L. & Yen, Steven T., 2013. "The Effect of Mail-in Utility Rebates on Willingness-to-Pay for ENERGY STAR® Certified Refrigerators," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 159795, Southern Agricultural Economics Association.
    30. Kallas, Zein & Maria Gil, Jose, 2011. "A Dual Response Choice Experiments (DRCE) design to assess rabbit meat preference in Catalonia: A Heteroescedatistic Extreme-Value Model," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114779, European Association of Agricultural Economists.
    31. Ponce Oliva, Roberto D. & Vasquez-Lavín, Felipe & San Martin, Valeska A. & Hernández, José Ignacio & Vargas, Cristian A. & Gonzalez, Pablo S. & Gelcich, Stefan, 2019. "Ocean Acidification, Consumers' Preferences, and Market Adaptation Strategies in the Mussel Aquaculture Industry," Ecological Economics, Elsevier, vol. 158(C), pages 42-50.
    32. Gensler, Sonja & Hinz, Oliver & Skiera, Bernd & Theysohn, Sven, 2012. "Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs," European Journal of Operational Research, Elsevier, vol. 219(2), pages 368-378.
    33. KUPFER, Franziska & KESSELS, Roselinde & GOOS, Peter & VAN DE VOORDE, Eddy & VERHETSEL, Ann, 2013. "A discrete choice approach for analysing the airport choice for freighter operations in Europe," Working Papers 2013028, University of Antwerp, Faculty of Business and Economics.
    34. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.
    35. Massuquetti, Angelica, 2006. "Algumas Reflexões Acerca Do Espaço De Investigação Sobre O," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 149051, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    36. Alves, Maria Odete & Valente, Airton Saboya Jr, 2006. "Comunicação Rural Entre Três Atores Nas Áreas De Concentração De Fruteiras No Nordeste Brasileiro:," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 148515, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    37. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
    38. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.
    39. Candel, Math J.J.M. & Van Breukelen, Gerard J.P., 2010. "D-optimality of unequal versus equal cluster sizes for mixed effects linear regression analysis of randomized trials with clusters in one treatment arm," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1906-1920, August.
    40. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    41. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.
    42. Li, Xiaogu & Jensen, Kimberly L. & Clark, Christopher D. & Lambert, Dayton M., 2015. "Consumer Willingness-to-Pay for Non-taste Attributes in Beef Products," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196719, Southern Agricultural Economics Association.
    43. J. DeShazo & Trudy Cameron & Manrique Saenz, 2009. "The Effect of Consumers’ Real-World Choice Sets on Inferences from Stated Preference Surveys," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 319-343, March.
    44. Xiaogu Li & Christopher Clark & Kimberly Jensen & Steven Yen, 2014. "Will consumers follow climate leaders? The effect of manufacturer participation in a voluntary environmental program on consumer preferences," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 16(1), pages 69-87, January.

  29. Vermeulen, Bart & Goos, Peter & Vandebroek, Martina, 2008. "Models and optimal designs for conjoint choice experiments including a no-choice option," International Journal of Research in Marketing, Elsevier, vol. 25(2), pages 94-103.

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    1. Stefano Ciliberti & Simone Del Sarto & Angelo Frascarelli & Giulia Pastorelli & Gaetano Martino, 2020. "Contracts to Govern the Transition towards Sustainable Production: Evidence from a Discrete Choice Analysis in the Durum Wheat Sector in Italy," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    2. Asinyaka Michael, 2019. "Willingness to Pay for Energy Efficient Refrigerating Appliances in Accra, Ghana: A Choice Experiment Approach," Review of Economics, De Gruyter, vol. 70(1), pages 15-39, April.
    3. Eunae Son & Song Soo Lim, 2021. "Consumer Acceptance of Gene-Edited versus Genetically Modified Foods in Korea," IJERPH, MDPI, vol. 18(7), pages 1-17, April.
    4. Meixner, Oliver & Kubinger, Magdalena & Haghirian, Parissa & Haas, Rainer, 2018. "Empirical Research in Foreign Cultures: The Case of Japanese Rice," 2018 International European Forum (163rd EAAE Seminar), February 5-9, 2018, Innsbruck-Igls, Austria 276881, International European Forum on System Dynamics and Innovation in Food Networks.
    5. Apostolakis, George & van Dijk, Gert & Kraanen, Frido & Blomme, Robert J., 2018. "Examining socially responsible investment preferences: A discrete choice conjoint experiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 83-96.
    6. Jiyeon Jung & Yoonmo Koo, 2018. "Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    7. Frode Alfnes & Maren Bachke & Mette Wik, 2012. "Eliciting donor preferences," Artefactual Field Experiments 00098, The Field Experiments Website.
    8. Lukas Kornher & Martin Schellhorn & Saskia Vetter, 2019. "Disgusting or Innovative-Consumer Willingness to Pay for Insect Based Burger Patties in Germany," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    9. Koistinen, Laura & Pouta, Eija & Heikkila, Jaakko & Forsman-Hugg, Sari & Kotro, Jaana & Makela, Jarmo & Niva, M., 2011. "Impact of meat type, methods of production, fat content, price and carbon footprint information on meat choice," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114710, European Association of Agricultural Economists.
    10. Santos, Jair Carvalho Dos, 2006. "Estimativa De Custo De Coleta E Rentabilidade Para Sistema Extrativo De Latex De Seringueira Na Amazonia," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 145689, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    11. Ronny Baierl, 2018. "Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis," SAGE Open, , vol. 8(2), pages 21582440187, May.
    12. Philippe Le Coent & Raphaële Préget & Sophie Thoyer, 2016. "Compensating environmental losses versus creating environmental gains: implications for biodiversity offsets," Post-Print hal-02742411, HAL.
    13. Nordén, Anna & Coria, Jessica & Jönsson, Anna Maria & Lagergren, Fredrik & Lehsten, Veiko, 2015. "Divergence in Stakeholders’ Preferences: Evidence from a Choice Experiment on Forest Landscapes Preferences in Sweden," Working Papers in Economics 616, University of Gothenburg, Department of Economics.
    14. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
    15. A. Cristina Mihale-Wilson & Jan Zibuschka & Oliver Hinz, 2019. "User preferences and willingness to pay for in-vehicle assistance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 37-53, March.
    16. Daniel R. Cavagnaro & Richard Gonzalez & Jay I. Myung & Mark A. Pitt, 2013. "Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach," Management Science, INFORMS, vol. 59(2), pages 358-375, February.
    17. Rocha, Luiz Eduardo Vasconcelos & Santos, Gilnei Costa & Bastos, Patricia de Melo Abrita, 2006. "Evolução Da Distribuição Da Renda E Da Pobreza Das Famílias Ocupadas E Residentes No Meio Rural Do Estado De Minas Gerais, De 1981 A 2003," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 148649, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    18. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    19. Ward, David O. & Clark, Christopher D. & Jensen, Kimberly L. & Yen, Steven T. & Russell, Clifford S., 2011. "Factors influencing willingness-to-pay for the ENERGY STAR® label," Energy Policy, Elsevier, vol. 39(3), pages 1450-1458, March.
    20. Nguyen, Ly & Gao, Zhifeng & Anderson, James L., 2022. "Regulating menu information: What do consumers care and not care about at casual and fine dining restaurants for seafood consumption?," Food Policy, Elsevier, vol. 110(C).
    21. Dong, Songting & Ding, Min & Huber, Joel, 2010. "A simple mechanism to incentive-align conjoint experiments," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 25-32.
    22. Chiambaretto, Paul, 2021. "Air passengers’ willingness to pay for ancillary services on long-haul flights," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    23. Leite, Sheila Cristina Ferreira & De Figueiredo, Margarida Garcia, 2006. "Fluxos De Algodão Em Pluma Para Exportação No Estado Da Bahia: Uma Aplicação De Programação Linear," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 149116, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    24. Mahirah Kamaludin & Muhd Azrin Shah Razali & Nazatul Faizah Haron & A. A. Azlina, 2021. "Energy Efficiency Labelling: Investigating Students Preferences and Awareness on the Energy-efficient Electrical Appliances in Hostel," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 300-308.
    25. Balaine, Lorraine & Gallai, Nicola & Del Corso, Jean-Pierre & Kephaliacos, Charilaos, 2020. "Trading off environmental goods for compensations: Insights from traditional and deliberative valuation methods in the Ecuadorian Amazon," Ecosystem Services, Elsevier, vol. 43(C).
    26. Li, Xiaogu & Clark, Christopher D. & Jensen, Kimberly L. & Yen, Steven T., 2013. "The Effect of Mail-in Utility Rebates on Willingness-to-Pay for ENERGY STAR® Certified Refrigerators," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 159795, Southern Agricultural Economics Association.
    27. Kallas, Zein & Maria Gil, Jose, 2011. "A Dual Response Choice Experiments (DRCE) design to assess rabbit meat preference in Catalonia: A Heteroescedatistic Extreme-Value Model," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114779, European Association of Agricultural Economists.
    28. Ponce Oliva, Roberto D. & Vasquez-Lavín, Felipe & San Martin, Valeska A. & Hernández, José Ignacio & Vargas, Cristian A. & Gonzalez, Pablo S. & Gelcich, Stefan, 2019. "Ocean Acidification, Consumers' Preferences, and Market Adaptation Strategies in the Mussel Aquaculture Industry," Ecological Economics, Elsevier, vol. 158(C), pages 42-50.
    29. Gensler, Sonja & Hinz, Oliver & Skiera, Bernd & Theysohn, Sven, 2012. "Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs," European Journal of Operational Research, Elsevier, vol. 219(2), pages 368-378.
    30. Massuquetti, Angelica, 2006. "Algumas Reflexões Acerca Do Espaço De Investigação Sobre O," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 149051, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    31. Alves, Maria Odete & Valente, Airton Saboya Jr, 2006. "Comunicação Rural Entre Três Atores Nas Áreas De Concentração De Fruteiras No Nordeste Brasileiro:," 44th Congress, July 23-27, 2006, Fortaleza, Ceará, Brazil 148515, Sociedade Brasileira de Economia, Administracao e Sociologia Rural (SOBER).
    32. Ida, Takanori & Takemura, Kosuke & Sato, Masayuki, 2015. "Inner conflict between nuclear power generation and electricity rates: A Japanese case study," Energy Economics, Elsevier, vol. 48(C), pages 61-69.
    33. Li, Xiaogu & Jensen, Kimberly L. & Clark, Christopher D. & Lambert, Dayton M., 2015. "Consumer Willingness-to-Pay for Non-taste Attributes in Beef Products," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196719, Southern Agricultural Economics Association.
    34. Xiaogu Li & Christopher Clark & Kimberly Jensen & Steven Yen, 2014. "Will consumers follow climate leaders? The effect of manufacturer participation in a voluntary environmental program on consumer preferences," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 16(1), pages 69-87, January.

  30. Bradley Jones & Peter Goos, 2007. "A candidate‐set‐free algorithm for generating D‐optimal split‐plot designs," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(3), pages 347-364, May.
    See citations under working paper version above.
  31. Peter Goos, 2006. "Optimal versus orthogonal and equivalent‐estimation design of blocked and split‐plot experiments," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 361-378, August.

    Cited by:

    1. JONES, Bradley & GOOS, Peter, 2012. "I-optimal versus D-optimal split-plot response surface designs," Working Papers 2012002, University of Antwerp, Faculty of Business and Economics.
    2. Xiaodong Li & Xu He & Yuanzhen He & Hui Zhang & Zhong Zhang & Dennis K. J. Lin, 2017. "The Design and Analysis for the Icing Wind Tunnel Experiment of a New Deicing Coating," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1417-1429, October.
    3. Sambo, Francesco & Borrotti, Matteo & Mylona, Kalliopi, 2014. "A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1193-1207.
    4. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    5. MYLONA, Kalliopi & MACHARIA, Harrison & GOOS, Peter, 2011. "Three-level equivalent-estimation split-plot designs based on subset and supplementary difference set designs," Working Papers 2011010, University of Antwerp, Faculty of Business and Economics.
    6. Kessels, Roselinde & Goos, Peter & Vandebroek, Martina, 2008. "Optimal designs for conjoint experiments," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2369-2387, January.
    7. CUERVO, Daniel Palhazi & GOOS, Peter & SÖRENSEN, Kenneth, 2016. "An algorithmic framework for generating optimal two-stratum experimental designs," Working Papers 2016003, University of Antwerp, Faculty of Business and Economics.

  32. Goos, P. & Donev, A.N., 2006. "Blocking response surface designs," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1075-1088, November.

    Cited by:

    1. Eugene C. Ukaegbu & Polycarp E. Chigbu, 2017. "Evaluation of Orthogonally Blocked Central Composite Designs with Partial Replications," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(1), pages 112-141, May.
    2. ARNOUTS, Heidi & GOOS, Peter, 2009. "Design and analysis of industrial strip-plot experiments," Working Papers 2009007, University of Antwerp, Faculty of Business and Economics.
    3. Rodney N. Edmondson, 2020. "Multi-level Block Designs for Comparative Experiments," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 500-522, December.
    4. VO-THANH, Nha & GOOS, Peter & SCHOEN, Eric D., 2016. "Integer programming approaches to find row-column arrangements of two-level orthogonal experimental designs," Working Papers 2016010, University of Antwerp, Faculty of Business and Economics.
    5. Georgiou, Stelios D. & Stylianou, Stella & Aggarwal, Manohar, 2014. "A class of composite designs for response surface methodology," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1124-1133.
    6. Belmiro P. M. Duarte, 2023. "Exact Optimal Designs of Experiments for Factorial Models via Mixed-Integer Semidefinite Programming," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    7. Loeza-Serrano, S. & Donev, A.N., 2014. "Construction of experimental designs for estimating variance components," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1168-1177.
    8. Peter Goos & Alexander Donev, 2007. "$$\mathcal{D}$$ -optimal Minimum Support Mixture Designs in Blocks," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 65(1), pages 53-68, February.
    9. Peter Goos, 2006. "Optimal versus orthogonal and equivalent‐estimation design of blocked and split‐plot experiments," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 60(3), pages 361-378, August.

  33. Goos, Peter & Kobilinsky, Andre & O'Brien, Timothy E. & Vandebroek, Martina, 2005. "Model-robust and model-sensitive designs," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 201-216, April.

    Cited by:

    1. Kiselák, Jozef & Stehlík, Milan, 2008. "Equidistant and D-optimal designs for parameters of Ornstein-Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1388-1396, September.
    2. Werner Müller & Milan Stehlík, 2009. "Issues in the optimal design of computer simulation experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(2), pages 163-177, March.
    3. Smucker, Byran J. & Castillo, Enrique del & Rosenberger, James L., 2012. "Model-robust designs for split-plot experiments," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4111-4121.
    4. Ruggoo, Arvind & Vandebroek, Martina, 2006. "Model-sensitive sequential optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1089-1099, November.

  34. Goos, Peter & Vandebroek, Martina, 2001. "-optimal response surface designs in the presence of random block effects," Computational Statistics & Data Analysis, Elsevier, vol. 37(4), pages 433-453, October.

    Cited by:

    1. Das, Rabindra Nath & Kim, Jinseog & Park, Jeong-Soo, 2015. "Robust D-optimal designs under correlated error, applicable invariantly for some lifetime distributions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 92-100.
    2. GOOS, Peter & VERMEULEN, Bart & VANDEBROEK, Martina, 2008. "D-optimal conjoint choice designs with no-choice options for a nested logit model," Working Papers 2008020, University of Antwerp, Faculty of Business and Economics.
    3. Goos, P. & Donev, A.N., 2006. "Blocking response surface designs," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1075-1088, November.
    4. ARNOUTS, Heidi & GOOS, Peter, 2008. "Update formulas for split-plot and block designs," Working Papers 2008022, University of Antwerp, Faculty of Business and Economics.
    5. Tack, Lieven & Vandebroek, Martina, 2004. "Trend-resistant and cost-efficient cross-over designs for mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 721-746, July.
    6. Rodney N. Edmondson, 2020. "Multi-level Block Designs for Comparative Experiments," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 500-522, December.
    7. Payne, Roger W., 2003. "General balance, large data sets and extensions to unbalanced treatment structures," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 297-304, October.
    8. Kessels, Roselinde & Goos, Peter & Vandebroek, Martina, 2008. "Optimal designs for conjoint experiments," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2369-2387, January.
    9. Graßhoff, Ulrike & Schwabe, Rainer, 2003. "On the analysis of paired observations," Statistics & Probability Letters, Elsevier, vol. 65(1), pages 7-12, October.

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