A perceptual-behavioural approach with non-parametric experimental coefficient for urban parking business design

• Autorzy: Ferrarese M.

Identyfikatory

DOI

10.5604/08669546.1203200

• Języki publikacji: EN

Abstrakty

EN

Transportation science and integrated logistics of passengers in the cities provide a detailed study of the movements both on entry to the urban areas than within them. Parking lots are, very often, places of exchange between the motorized and the pedestrian or cycling mode, or between individual and collective motorized modes. As the modern urban civilization is known by its impetuous car parking expansion it becomes essential to design the parking lots bearing in mind the needs of those who will really use them and not referring to the political lobbies in the city administration. The study of parking lot in terms of business and financial design, planning and management after the construction needs is a more accurate determination of the experimental parameters, which enable choice of the model to minimize the uncertainty of the data that will define the revenues according to the Project Financing procedures.

Słowa kluczowe

EN

parking choice; market for parking; study of movements; modern urban civilization; parking modelling

PL

parkingi; projektowanie parkingów; analiza ruchu; nowoczesna cywilizacja miejska; modelowanie

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2016
• Tom: Vol. 37, iss. 1
• Strony: 15--30
• Opis fizyczny: Bibliogr. 37 poz., fot., rys., tab., wzory

Twórcy

autor

Ferrarese M.

• University of Verona, Verona, Italy
• International Expert, REPRISE-Ministry of Education, Universities and Research, Italy

Bibliografia

• [1] ABDELWAHAB, W., 1998. Elasticities mode choice probabilities and market elasticities of demand: evidence from a simultaneous mode choice/shipment-sizefreight transport model. Transport Research, 34 (4), pp. 257-266.
• [2] ARMSTRONG, G., KOTLER, P., & HE, Z., 2000. Marketing: an introduction. From http://www.amazon.co.uk/Marketing-An-Introduction-Gary-Armstrong/dp/0273762605.
• [3] ARNOTT, R., 2006. Spatial competition between parking garages and downtown parking policy. Transport Policy, 13(6), pp. 458-469.
• [4] BIENIEK, M., 2014. Service level in model of inventory location with stochastic demand. Archives of Transport, 31(3), pp. 7-21.
• [5] BRDULAK, J., & ZAKRZEWSKI, B., 2013. Methods for Calculating the Efficiency of Logistics Centres. Archives of Transport, 27-28(3-4), 25-43.
• [6] COHEN, M., 2015. Risk perception, risk attitude, and decision: a rank-dependent analysis. Mathematical Population Studies, 22(1), pp. 53-70.
• [7] CORRAO, S., 2005. Il focus group (Vol. 25). Milano: Franco Angeli.
• [8] DE DIOS ORTUZAR, J., & WILLUMSEN, L. G., 2011. Modelling transport. John Wiley & Sons.
• [9] DEDE, G., KAMALAKIS, T., & SPHICOPOULOS, T., 2015. Convergence properties and practical estimation of the probability of rank reversal in pairwise comparisons for multi-criteria decision making problems. European Journal of Operational Research, 241(2), pp. 458-468.
• [10] FEENEY, B.P., 1989. A review of the impact of parking policy measures on travel demand. Transportation Planning and Technology, 13, pp. 229–244.
• [11] FERRARESE, M., 2015. A Spatial-temporal Epistemology of Four-dimension Transportation Issue. Universal Journal of Applied Science, HRPC, 3(1), pp. 6 - 12.
• [12] GREEN, P. E., KRIEGER, A. M., & WIND, Y., 2001. Thirty years of conjoint analysis: Reflections and prospects. Interfaces, 31(3_supplement), pp. 56-73.
• [13] HESS, S., & CHORUS, C. G., 2015. Utility Maximisation and Regret Minimisation: A Mixture of a Generalisation. In: RASOULI, S. & TIMMERMANS H., Bounded Rational Choice Behaviour: Applications in Transport. Bingley UK: Emerald, pp.31-48 .
• [14] JOHN, P. W. J., 1998. Statistical Design and Analysis of Experiments (Classics in Applied Mathematics vol. 22). New York: SIAM.
• [15] JOURDAN, A., 2015. Space-filling orthogonal arrays of strength two. Journal of Statistical Computation and Simulation, 85(7), pp. 1382-1397.
• [16] LEONARDI, G., 1985. Equivalenza Asintotica tra la Teoria delle Utilità Casuali e la Massimizzazione dell'Entropia. In: REGGIANI A., Territorio e Trasporti e della mobilità, Franco Angeli, pp. 27-26.
• [17] LI DONNI V., 1991. Manuale di Economia dei Trasporti e della mobilità. Roma: NIS.
• [18] LOUVIERE, J.J., 1988. Conjoint analysis modelling of stated preferences. Journal of Transport Economics and Policy, 22 (1) pp. 93-120.
• [19] MARCACCI, F., 2015. History of Science, Epistemology, and Ontology. In: ALAI, M., BUZZONI, M., & TAROZZI, G., Science Between Truth and Ethical Responsibility. Springer International Publishing, pp. 231-241.
• [20] MENON, R. G., & SIGURDSSON, V., 2015. Conjoint Analysis for Social Media Marketing Experimentation: Choice, Utility Estimates and Preference Ranking. Managerial and Decision Economics.
• [21] MIEŚCICKI J., DASZCZUK W.B., 2013. Proposed benchmarks for PRT networks simulation, The Archives of Transport, 27-28(3-4), pp. 123-133.
• [22] MOM, G., 2015. The Crisis of Transport History: A Critique and a Vista. Mobility in History, 6(1), pp. 7-19.
• [23] NAPOLITANO, E. M., 1999. La qualità nell'impresa sociale: strumenti per il non profit (Vol. 381). Milano: FrancoAngeli.
• [24] NORMANN, R., 1985. La gestione strategica dei servizi. Milano: Etas Libri.
• [25] O’KELLY, M., 2010. Entropy-Based Spatial Interaction Models for Trip Distribution. Geographical Analysis, 42, pp. 472-487.
• [26] OPPENHEIMER, D. M., & KELSO, E., 2015. Information Processing as a Paradigm for Decision Making. Annual review of psychology, 66, pp. 277-294.
• [27] OTTOMANELLI, M., DELL'ORCO, M., & SASSANELLI, D., 2011. Modelling parking choice behaviour using Possibility Theory. Transportation Planning and Technology, 34(7), pp. 647-667.
• [28] PLESKAC, T. J., DIEDERICH, A., & WALLSTEN, T. S., 2015. Models of Decision Making under Risk and Uncertainty. In: BUSEMEYER, J.R., WANG, Z., EIDELS, A., & TOWNSEND, J.T., The Oxford Handbook of Computational and Mathematical Psychology. New York: Oxford University Press, pp. 209-231.
• [29] RAO V.R., 2014. Applied Conjoint Analysis. Springer Berlin Heidelberg.
• [30] REISCH, L. A., & THØGERSEN, J., 2015. Research on ustainable consumption: Introduction and overview. In: REISCH, L.A. & THØGERSEN, J.: Handbook of research on sustainable consumption. Cheltenham UK: Edward Elgar Publishing Limited, pp. 1-16.
• [31] SHAW, M. J., SUBRAMANIAM, C., TAN, G. W., & WELGE, M. E., 2001. Knowledge management and data mining for marketing. Decision support systems, 31(1), pp. 127-137.
• [32] TESTA, F., 2001. Qualità e valore nelle imprese di servizi pubblici locali. Economia e Diritto del Terziario. Milano: Franco Angeli.
• [33] TIDWELL, P., 2015. Compensatory Versus Non-Compensatory Choice Strategies in Limited Problem Solving Consumer Behavior: Engel-Kollat-Blackwell Versus Howard Models. Proceedings of the 1996 Academy of Marketing Science (AMS) Annual Conference. Springer International Publishing, pp. 220-224.
• [34] XU, Z., 2015. Uncertain Multi-Attribute Decision Making: Methods and Applications. Springer International Publishing.
• [35] WATLING, D. P., & CANTARELLA, G. E., 2014. Model representation & decision-making in an ever-changing world: the role of stochastic process models of transportation systems. Networks and Spatial Economics, 15(3), pp. 843-882.
• [36] WEINBERGER, R. R., & KARLIN-RESNICK, J., 2015. Parking in Mixed-Use Us Districts: Oversupplied No Matter How You Slice the Pie 2. Transportation Research Board 94th Annual Meeting (No. 15-5064).
• [37] VRIENS, M., 1994. Solving marketing problems with conjoint analysis. Journal of Marketing Management, 10(1-3), pp. 37-55.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.