Johnston R J, Kissling C C. Establishment use patterns within central places. Australian Geographical Studies, 1971, 9(2): 116-132.
[2]
Pacione M. Redevelopment of a medium-sized central shopping area: A case study of Clydebank. Tijdschrift voor Economische en Sociale Geografie, 1980, 71(3): 159-168.
[3]
Lorch, B J, Smith M J. Pedestrian movement and the downtown enclosed shopping centre. Journal of the American Planning Association, 1993, 59(1): 75-86.
[4]
Recker W W, Kostyniuk L P. Factors influencing destination choice for the urban grocery shopping trip. Transportation, 1978, 7(1): 19-33.
[5]
Timmermans H, Borgers A. Choice set constrains and spatial decision-making processes. Sistemi Urbani, 1985, 3: 211-220.
[6]
Fotheringham A S, Trew R. Chain image and store-choice modeling: the effects of income and race. Environment and Planning A, 1993, 25(2): 179-196.
[7]
Oppewal H, Timmermans H J P. Modelling the effects of shopping centre size and store variety on consumer choice behavior. Environment and Planning A, 1997, 29 (6): 1073-1090.
[8]
Van der Waerden P, Borgers A, Timmermans H. The impact of the parking situation in shopping centers on store choice behavior. GeoJournal, 1998, 45(4): 309-315.
Kitamura R. Incorporating trip chaining into analysis of destination choice. Transportation Research B, 1984, 18 (1): 67-81.
[11]
Arentze T, Borgers A, Timmermans H. A model of multi-purpose shopping trip behaviour. Papers in Regional Science, 1993, 72(3): 239-256.
[12]
Dellaert B G C, Arentze T A, Bierlaire M, et al. Investigating consumers’tendency to combine multiple shopping purposes and destinations. Journal of Marketing Research, 1998, 35(2): 177-188.
[13]
Arentze T A, Timmermans H J P. A multipurpose shopping trip model to assess retail agglomeration effects. Journal of Marketing Research, 2005, 42(1): 109-115.
Saito S, Ishibashi K. A Markov Chain model with covariates to forecast consumer’s shopping trip chain within a central commercial district. FourthWorld Congress of Regional Science Association International, Mallorca, Spain.
Zhu W, Timmermans H, Wang D. Temporal variation in consumer spatial behavior in shopping streets. Journal of Urban Planning and Development, 2006, 132(3): 166-171.
[22]
Borgers A W J, Timmermans H J P. Modeling pedestrian behavior in downtown shopping areas//Proceedings of the 9th International Conference on Computers in Urban Planning and Urban Management, London, 2005: http://128.40.111.250/cupum/searchpapers/detail.asp?pID=83.
[23]
Borgers A W J, Kemperman A D A M, Timmermans H J P. Pedestrian behaviour in down-town shopping areas: Differentiating between hedonic and utilitarian shoppers// Proceedings of the 12th RARSS Conference, Orlando, 2005.
[24]
Dijkstra J, Timmermans H, de Vries B. Empirical estimation of agent shopping patterns for simulating pedestrian movement//Proceedings of the 10th International Conference on Computers in Urban Planning and Urban Management, Igguasu Falls, Brazil, 2007.
[25]
Antonini G, Bierlaire M, Weber M. Discrete choice models of pedestrian walking behavior. Transportation Research B, 2006, 40(8): 667-687.
[26]
Borgers A W J, Smeets I M E, Kemperman A D A M, et al. Simulation of micro pedestrian behaviour in shopping streets//van Leeuwen J P H, Timmermans J P. Progress in Design & Decision Support Systems. Heeze, The Netherlands, 2006: 101-116.
[27]
O’Sullivan D, Haklay M. Agent-based models and individualism: Is the world agent-based? Environment and Planning A, 2000, 32(8): 1409-1425.
[28]
Dijkstra J, Jessurun J, Timmermans H J P. A multi-agent cellular automata model of pedestrian movement// Schreckenberg M, Sharma S D. Pedestrian and Evacuation Dynamics, Berlin: Springer-Verlag, 2001: 173-181.
[29]
Dijkstra J, Timmermans H. Towards a multi-agent model for visualizing simulated user behavior to support the assessment of design performance. Automation in Construction, 2002, 11(2): 135-145.
[30]
Kerridge J, Hine J, Wigan M. Agent-based modeling of pedestrian movements: The question that need to be asked and answered. Environment and Planning B, 2001, 28(3): 327-341.
[31]
Fortheringham A S, Trew R. Chain Image and Store-choice Modeling: The Effects of Income and Race. Environment and Planning A, 1993, 25(2): 179-196.
[32]
O’Kelly M E. A model of the demand for retail facilities incorporation multistop, multipurpose trips. Geographical Analysis, 1981, 13(2): 134-148.
[33]
Borgers A W J, Timmermans H J P. A model of pedestrian route choice and demand for retail facilities within innercity shopping areas. Geographical Analysis, 1986, 18 (2): 115-128.
[34]
Wilson A G. A family of spatial interaction models, and associated developments. Environment and Planning A, 1971, 3(1): 1-32.
[35]
Gibson M, Pullen M. Retail turnover in the East Midlands: A regional application of a gravity model. Regional Studies, 1972, 6(2): 183-196.
[36]
Ghosh A. Parameter nonstationarity in retail choice models. Journal of Business Research, 1984, 12(4): 425-436.
[37]
Guy C M. Recent advances in spatial interaction modelling: An application to the forecasting of shopping travel. Environment and Planning A, 1987, 19(2): 173-186.
[38]
Scott A J. A theoretical model of pedestrian flow. SocioEconomic Planning Sciences, 1974, 8(6): 317-322.
[39]
Hagishima S, Mitsuyoshi K, Kurose S. Estimation of pedestrian shopping trips in a neighborhood by using a spatial interaction model. Environment and Planning A, 1987, 19(9): 1139-1152.
[40]
Fotheringham A S. A new set of spatial-interaction models: The theory of competing destinations. Environment and Planning A, 1983, 15(1): 15-36.
[41]
Fotheringham A S. Some theoretical aspects of destination choice and their relevance to production-constrained gravity models. Environment and Planning A, 1983, 15 (8): 1121-1132.
[42]
Fotheringham A S. Modelling hierarchical destination choice. Environment and Planning A, 1986, 18 (3): 401-418.
[43]
Fortheringham A S, Trew R. Chain Image and Store-choice Modeling: The Effects of Income and Race. Environment and Planning A, 1993, 25(2): 179-196.
[44]
O’Kelly M E. A model of the demand for retail facilities incorporation multistop, multipurpose trips. Geographical Analysis, 1981, 13(2): 134-148.
[45]
Borgers A W J, Timmermans H J P. A model of pedestrian route choice and demand for retail facilities within innercity shopping areas. Geographical Analysis, 1986, 18 (2): 115-128.
[46]
Kurose S, Hagishima S. A method for identifying accessibility properties of pedestrian shopping networks. Journal of Retailing and Consumer Services, 1995, 2(2): 111-118.
[47]
Borgers A W J, Timmermans H J P. City centre entry points, store location patterns and pedestrian route choice behaviour: A microlevel simulation model. Socio-Economic Planning Sciences, 1986, 20(1): 25-31.
[48]
McFadden D. Conditional logit analysis of qualitative choice behavior//Zarembka P. Frontiers in Econometrics. New York: Academic Press, 1974: 105-142.
[49]
Ben-Akiva M, Lerman S. Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, US: The MIT Press, 1985.
[50]
Train K E. Discrete Choice Methods with Simulation. Cambridge, UK: Cambridge University Press, 2003.
[51]
McFadden D. Modeling the choice of residential location// Karlqvist A, Lundqvist L, Snickars F, et al. Weibull Spatial Interaction Theory and Planning Models. Amsterdam: North-Holland, 1978: 75-96.
[52]
Borgers AW J, Timmermans H J P. Choice model specification, substitution, and spatial structure effects: A simulation experiment. Regional Science and Urban Economics, 1987, 17(1): 29-47.
[53]
Borgers AW J, Timmermans H J P. Spatial choice, substitutability and spatial structure effects: An extended multinomial logit model//Wieber J C. Analyse de Systemes et Modeles Mathematiques. Paris: Les Belles Lettres, 1987: 35-40.
[54]
Borgers A W J, Timmermans H J P. A context-sensitive model of spatial choice behavior//Golledge R G, Timmermans H J P. Behavioural Modelling in Geography and Planning, London: Croom Helm, 1988: 159-178.
[55]
Fotheringham A S. Consumer store choice and choice set definition. Marketing Science, 1988, 7(3): 299-310.
[56]
Walmsley D J, Lewis G J. The pace of pedestrian flows in cities. Environment and Behavior, 1989, 21(2): 123-150.
[57]
Willis A, Gjersoe N, Havard C, et al. Human movement behaviour in urban spaces: Implications for the design and modeling of effective pedestrian environments. Environment and Planning B, 2004, 31(2): 805-828.
[58]
Lee J Y S, Lam W H K. Variation of walking speeds on a unidirectional walkway and on a bidirectional stairway. Transportation Research Record, 2006, 1982: 122-131.
[59]
Haklay M, O’Sullivan D, Thurstain-Goodwin M.‘So go downtown’: Simulating pedestrian movement in town centers. Environment and Planning B, 2001, 28(3): 343-359.
[60]
Silverman B G, Johns M, Cornwell J, et al. Human behavior models for agents in simulators and games part I: Enabling science with PMFserv. Presence, 2006, 15(2): 139-162.
[61]
Silverman B G, Bharathy G, O’Brien K, et al. Human behavior models for agents in simulators and games part II: Gamebot engineering with PMFserv. Presence, 2006, 15 (2): 163-185.
[62]
Lee J Y S, Lam W H K, Wong S C. Pedestrian simulation model for Hong Kong underground stations//Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, Oakland, US, 2001: 554-558.
[63]
Batty M, Desyllas J, Duxbury E. The discrete dynamics of small-scale spatial events: Agent-based models of mobility in carnivals and street parades. International Journal of Geographical Information Science, 2003, 17(7): 673-698.
[64]
Johansson A, Helbing D. Pedestrian flow optimization with a genetic algorithm based on boolean grids//Waldau N, Gattermann P, Knoflacher H, et al. Pedestrian and Evacuation Dynamics 2005. Berlin: Springer, 2007: 267-272.
Borgers A W J, Kemperman A D A M, Timmermans H J P, et al. Alternative ways of measuring activities and movement patterns of transients in urban areas: International experiences//Proceedings ICTSC Conference, Annecy, France, 2008-5-25
Handerson L F. On the fluid mechanics of human crowd motion. Transportation Research, 1974, 8(6): 509-515.
[71]
Helbing D, Molnar P. Social force model for pedestrian dynamics. Physical Review E, 1995, 51(5): 4282-4286.
[72]
Schadschneider A. Cellular automaton approach to pedestrian dynamics: Theory//Schreckenberg M, Sharma S. Pedestrian and Evacuation Dynamics. Berlin: Springer, 2001: 75-86.
[73]
Johnston R J, Kissling C C. Establishment use patterns within central places. Australian Geographical Studies, 1971, 9(2): 116-132.
[74]
Pacione M. Redevelopment of a medium-sized central shopping area: A case study of Clydebank. Tijdschrift voor Economische en Sociale Geografie, 1980, 71(3): 159-168.
[75]
Lorch, B J, Smith M J. Pedestrian movement and the downtown enclosed shopping centre. Journal of the American Planning Association, 1993, 59(1): 75-86.
[76]
Wilson A G. A family of spatial interaction models, and associated developments. Environment and Planning A, 1971, 3(1): 1-32.
[77]
Gibson M, Pullen M. Retail turnover in the East Midlands: A regional application of a gravity model. Regional Studies, 1972, 6(2): 183-196.
[78]
Ghosh A. Parameter nonstationarity in retail choice models. Journal of Business Research, 1984, 12(4): 425-436.
[79]
Guy C M. Recent advances in spatial interaction modelling: An application to the forecasting of shopping travel. Environment and Planning A, 1987, 19(2): 173-186.
[80]
Scott A J. A theoretical model of pedestrian flow. SocioEconomic Planning Sciences, 1974, 8(6): 317-322.
[81]
Hagishima S, Mitsuyoshi K, Kurose S. Estimation of pedestrian shopping trips in a neighborhood by using a spatial interaction model. Environment and Planning A, 1987, 19(9): 1139-1152.
[82]
Fotheringham A S. A new set of spatial-interaction models: The theory of competing destinations. Environment and Planning A, 1983, 15(1): 15-36.
[83]
Fotheringham A S. Some theoretical aspects of destination choice and their relevance to production-constrained gravity models. Environment and Planning A, 1983, 15 (8): 1121-1132.
[84]
Fotheringham A S. Modelling hierarchical destination choice. Environment and Planning A, 1986, 18 (3): 401-418.
[85]
Kurose S, Hagishima S. A method for identifying accessibility properties of pedestrian shopping networks. Journal of Retailing and Consumer Services, 1995, 2(2): 111-118.
[86]
Borgers A W J, Timmermans H J P. City centre entry points, store location patterns and pedestrian route choice behaviour: A microlevel simulation model. Socio-Economic Planning Sciences, 1986, 20(1): 25-31.
[87]
McFadden D. Conditional logit analysis of qualitative choice behavior//Zarembka P. Frontiers in Econometrics. New York: Academic Press, 1974: 105-142.
[88]
Ben-Akiva M, Lerman S. Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, US: The MIT Press, 1985.
[89]
Train K E. Discrete Choice Methods with Simulation. Cambridge, UK: Cambridge University Press, 2003.
[90]
McFadden D. Modeling the choice of residential location// Karlqvist A, Lundqvist L, Snickars F, et al. Weibull Spatial Interaction Theory and Planning Models. Amsterdam: North-Holland, 1978: 75-96.
[91]
Recker W W, Kostyniuk L P. Factors influencing destination choice for the urban grocery shopping trip. Transportation, 1978, 7(1): 19-33.
[92]
Timmermans H, Borgers A. Choice set constrains and spatial decision-making processes. Sistemi Urbani, 1985, 3: 211-220.
[93]
Borgers AW J, Timmermans H J P. Choice model specification, substitution, and spatial structure effects: A simulation experiment. Regional Science and Urban Economics, 1987, 17(1): 29-47.
[94]
Borgers AW J, Timmermans H J P. Spatial choice, substitutability and spatial structure effects: An extended multinomial logit model//Wieber J C. Analyse de Systemes et Modeles Mathematiques. Paris: Les Belles Lettres, 1987: 35-40.
[95]
Borgers A W J, Timmermans H J P. A context-sensitive model of spatial choice behavior//Golledge R G, Timmermans H J P. Behavioural Modelling in Geography and Planning, London: Croom Helm, 1988: 159-178.
[96]
Fotheringham A S. Consumer store choice and choice set definition. Marketing Science, 1988, 7(3): 299-310.
[97]
Fotheringham A S, Trew R. Chain image and store-choice modeling: the effects of income and race. Environment and Planning A, 1993, 25(2): 179-196.
[98]
Oppewal H, Timmermans H J P. Modelling the effects of shopping centre size and store variety on consumer choice behavior. Environment and Planning A, 1997, 29 (6): 1073-1090.
[99]
Van der Waerden P, Borgers A, Timmermans H. The impact of the parking situation in shopping centers on store choice behavior. GeoJournal, 1998, 45(4): 309-315.
Kitamura R. Incorporating trip chaining into analysis of destination choice. Transportation Research B, 1984, 18 (1): 67-81.
[102]
Arentze T, Borgers A, Timmermans H. A model of multi-purpose shopping trip behaviour. Papers in Regional Science, 1993, 72(3): 239-256.
[103]
Dellaert B G C, Arentze T A, Bierlaire M, et al. Investigating consumers’tendency to combine multiple shopping purposes and destinations. Journal of Marketing Research, 1998, 35(2): 177-188.
[104]
Arentze T A, Timmermans H J P. A multipurpose shopping trip model to assess retail agglomeration effects. Journal of Marketing Research, 2005, 42(1): 109-115.
Saito S, Ishibashi K. A Markov Chain model with covariates to forecast consumer’s shopping trip chain within a central commercial district. FourthWorld Congress of Regional Science Association International, Mallorca, Spain.
Zhu W, Timmermans H, Wang D. Temporal variation in consumer spatial behavior in shopping streets. Journal of Urban Planning and Development, 2006, 132(3): 166-171.
[113]
Borgers A W J, Timmermans H J P. Modeling pedestrian behavior in downtown shopping areas//Proceedings of the 9th International Conference on Computers in Urban Planning and Urban Management, London, 2005: http://128.40.111.250/cupum/searchpapers/detail.asp?pID=83.
[114]
Borgers A W J, Kemperman A D A M, Timmermans H J P. Pedestrian behaviour in down-town shopping areas: Differentiating between hedonic and utilitarian shoppers// Proceedings of the 12th RARSS Conference, Orlando, 2005.
[115]
Dijkstra J, Timmermans H, de Vries B. Empirical estimation of agent shopping patterns for simulating pedestrian movement//Proceedings of the 10th International Conference on Computers in Urban Planning and Urban Management, Igguasu Falls, Brazil, 2007.
[116]
Antonini G, Bierlaire M, Weber M. Discrete choice models of pedestrian walking behavior. Transportation Research B, 2006, 40(8): 667-687.
[117]
Borgers A W J, Smeets I M E, Kemperman A D A M, et al. Simulation of micro pedestrian behaviour in shopping streets//van Leeuwen J P H, Timmermans J P. Progress in Design & Decision Support Systems. Heeze, The Netherlands, 2006: 101-116.
[118]
O’Sullivan D, Haklay M. Agent-based models and individualism: Is the world agent-based? Environment and Planning A, 2000, 32(8): 1409-1425.
[119]
Dijkstra J, Jessurun J, Timmermans H J P. A multi-agent cellular automata model of pedestrian movement// Schreckenberg M, Sharma S D. Pedestrian and Evacuation Dynamics, Berlin: Springer-Verlag, 2001: 173-181.
[120]
Dijkstra J, Timmermans H. Towards a multi-agent model for visualizing simulated user behavior to support the assessment of design performance. Automation in Construction, 2002, 11(2): 135-145.
[121]
Kerridge J, Hine J, Wigan M. Agent-based modeling of pedestrian movements: The question that need to be asked and answered. Environment and Planning B, 2001, 28(3): 327-341.
[122]
Walmsley D J, Lewis G J. The pace of pedestrian flows in cities. Environment and Behavior, 1989, 21(2): 123-150.
[123]
Willis A, Gjersoe N, Havard C, et al. Human movement behaviour in urban spaces: Implications for the design and modeling of effective pedestrian environments. Environment and Planning B, 2004, 31(2): 805-828.
[124]
Lee J Y S, Lam W H K. Variation of walking speeds on a unidirectional walkway and on a bidirectional stairway. Transportation Research Record, 2006, 1982: 122-131.
[125]
Haklay M, O’Sullivan D, Thurstain-Goodwin M.‘So go downtown’: Simulating pedestrian movement in town centers. Environment and Planning B, 2001, 28(3): 343-359.
[126]
Silverman B G, Johns M, Cornwell J, et al. Human behavior models for agents in simulators and games part I: Enabling science with PMFserv. Presence, 2006, 15(2): 139-162.
[127]
Silverman B G, Bharathy G, O’Brien K, et al. Human behavior models for agents in simulators and games part II: Gamebot engineering with PMFserv. Presence, 2006, 15 (2): 163-185.
[128]
Lee J Y S, Lam W H K, Wong S C. Pedestrian simulation model for Hong Kong underground stations//Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, Oakland, US, 2001: 554-558.
[129]
Batty M, Desyllas J, Duxbury E. The discrete dynamics of small-scale spatial events: Agent-based models of mobility in carnivals and street parades. International Journal of Geographical Information Science, 2003, 17(7): 673-698.
[130]
Johansson A, Helbing D. Pedestrian flow optimization with a genetic algorithm based on boolean grids//Waldau N, Gattermann P, Knoflacher H, et al. Pedestrian and Evacuation Dynamics 2005. Berlin: Springer, 2007: 267-272.
Borgers A W J, Kemperman A D A M, Timmermans H J P, et al. Alternative ways of measuring activities and movement patterns of transients in urban areas: International experiences//Proceedings ICTSC Conference, Annecy, France, 2008-5-25
[135]
[2010-3-
[136]
Handerson L F. On the fluid mechanics of human crowd motion. Transportation Research, 1974, 8(6): 509-515.
[137]
Helbing D, Molnar P. Social force model for pedestrian dynamics. Physical Review E, 1995, 51(5): 4282-4286.
[138]
Schadschneider A. Cellular automaton approach to pedestrian dynamics: Theory//Schreckenberg M, Sharma S. Pedestrian and Evacuation Dynamics. Berlin: Springer, 2001: 75-86.
