Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities

References

• Aaker, D. A., & Jones, J. M. (1971). Modeling store choice behavior. Journal of Marketing Research (JMR), 8(1), 38–42. doi: 10.2307/3149723
   Web of Science ®Google Scholar
• Adler, T., & Ben-Akiva, M. (1979). A theoretical and empirical model of trip chaining behavior. Transportation Research Part B: Methodological, 13(3), 243–257. doi: 10.1016/0191-2615(79)90016-X
   Web of Science ®Google Scholar
• Arentze, T. A., Borgers, A., & Timmermans, H. J. P. (1993). A model of multi-purpose shopping trip behavior. Papers in Regional Science, 72(3), 239–256. doi: 10.1007/BF01434275
   Google Scholar
• Arentze, T., Ettema, D., & Timmermans, H. (2011). Location choice in the context of multi-day activity-travel patterns: Model development and empirical results. Transportmetrica, 9(April 2014), 1–17. doi:10.1080/18128602.2010.538870
   Web of Science ®Google Scholar
• Arentze, T. A., Oppewal, H., & Timmermans, H. J. P. (2005). A multipurpose shopping trip model to assess retail agglomeration effects. Journal of Marketing Research (JMR), 42(1), 109–115. doi: 10.1509/jmkr.42.1.109.56884
   Web of Science ®Google Scholar
• Arentze, T. A., & Timmermans, H. J. P. (2000). Albatross: A learning based transportation oriented simulation system. Eindhoven: Eirass.
   Google Scholar
• Arentze, T. A., & Timmermans, H. J. P. (2001). Deriving performance indicators from models of multipurpose shopping behavior. Journal of Retailing and Consumer Services, 8(6), 325–334. doi: 10.1016/S0969-6989(00)00038-2
   Google Scholar
• Arentze, T., & Timmermans, H. J. P. (2009). A need-based model of multi-day, multi-person activity generation. Transportation Research Part B: Methodological, 43(2), 251–265. doi: 10.1016/j.trb.2008.05.007
   Web of Science ®Google Scholar
• Bacon, R. W. (1995). Combined trips and the frequency of shopping. Journal of Retailing and Consumer Services, 2(3), 175–183. doi: 10.1016/0969-6989(95)00034-8
   Google Scholar
• Baker, R. G. V. (1996). Multi-purpose shopping behaviour at planned suburban shopping centres: A space-time analysis. Environment and Planning A, 28(4), 611–630. doi: 10.1068/a280611
   Web of Science ®Google Scholar
• Balasubramanian, S., Raghunathan, R., & Mahajan, V. (2005). Consumers in a multichannel environment: Product utility, process utility, and channel choice. Journal of Interactive Marketing, 19(2), 12–30. doi: 10.1002/dir.20032
   Google Scholar
• Bawa, K., & Ghosh, A. (1999). A model of household grocery shopping behavior. Marketing Letters, 10(2), 149–160. doi: 10.1023/A:1008093014534
   Google Scholar
• Bell, D. R., Ho, T.-H., & Tang, C. S. (1998). Determining where to shop: Fixed and variable costs of shopping. Journal of Marketing Research (JMR), 352–369. doi: 10.2307/3152033
   Web of Science ®Google Scholar
• Bell, D. R., & Lattin, J. M. (1998). Shopping behavior and consumer preference for store price format: Why “large basket” shoppers prefer EDLP. Marketing Science, 17(1), 66–88. doi: 10.1287/mksc.17.1.66
   Web of Science ®Google Scholar
• Bellman, S., Lohse, G. L., & Johnson, E. J. (1999). Predictors of online buying behavior. Communications of the ACM, 42(12), 32–38. doi: 10.1145/322796.322805
   Web of Science ®Google Scholar
• Ben-Akiva, M., & Lerman, S. R. (1985). Discrete choice analysis: Theory and application to travel demand. Journal of Business & Economic Statistics, 6. doi:10.2307/1391567
   Web of Science ®Google Scholar
• Ben-Akiva, M., Morikawa, T., & Shiroishi, F. (1991). Analysis of the reliability of preference ranking data. Journal of Business Research, 23(3), 253–268. doi: 10.1016/0148-2963(91)90033-T
   Web of Science ®Google Scholar
• Beynon, M., Griffiths, B., & Marshall, D. (2002). A prototype store choice and location modelling system using Dempster–Shafer theory. Expert Systems, 19(5), 273–284. doi: 10.1111/1468-0394.00214
   Web of Science ®Google Scholar
• Bhat, C. R. (1998a). Accommodating flexible substitution patterns in multi-dimensional choice modeling: Formulation and application to travel mode and departure time choice. Transportation Research Part B: Methodological, 32(7), 455–466. doi: 10.1016/S0191-2615(98)00011-3
   Web of Science ®Google Scholar
• Bhat, C. R. (1998b). Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling. Transportation Research Part A: Policy and Practice, 32(7), 495–507. doi: 10.1016/S0965-8564(98)00011-1
   Web of Science ®Google Scholar
• Bhat, C. R. (1998c). Analysis of travel mode and departure time choice for urban shopping trips. Transportation Research Part B: Methodological, 32(6), 361–371. doi: 10.1016/S0191-2615(98)00004-6
   Web of Science ®Google Scholar
• Bhat, C. R. (2000). Incorporating observed and unobserved heterogeneity in urban work travel mode choice modeling. Transportation Science, 34(2), 228–238. doi: 10.1287/trsc.34.2.228.12306
   Web of Science ®Google Scholar
• Bhat, C. R., & Castelar, S. (2002). A unified mixed logit framework for modeling revealed and stated preferences: Formulation and application to congestion pricing analysis in the San Francisco Bay area. Transportation Research Part B: Methodological, 36(7), 593–616. doi: 10.1016/S0191-2615(01)00020-0
   Web of Science ®Google Scholar
• Bhat, C. R., Frusti, T., Zhao, H., Schönfelder, S., & Axhausen, K. W. (2004). Intershopping duration: An analysis using multiweek data. Transportation Research Part B: Methodological, 38(1), 39–60. doi: 10.1016/S0191-2615(02)00093-0
   Web of Science ®Google Scholar
• Bhat, C. R., & Koppelman, F. S. (1999). Activity-based modeling of travel demand. In Randolph Hall (Ed.), Handbook of transportation science (Vol. 56, pp. 35–61). New York, US: Springer.
   Google Scholar
• Bhat, C. R., Sivakumar, A., & Axhausen, K. W. (2003). An analysis of the impact of information and communication technologies on non-maintenance shopping activities. Transportation Research Part B: Methodological, 37(10), 857–881. doi: 10.1016/S0191-2615(02)00062-0
   Web of Science ®Google Scholar
• Bhatnagar, A., & Ratchford, B. T. (2004). A model of retail format competition for non-durable goods. International Journal of Research in Marketing, 21(1), 39–59. doi: 10.1016/j.ijresmar.2003.05.002
   Web of Science ®Google Scholar
• Black, W. C. (1984). Choice-set definition in patronage modeling. Journal of Retailing, 60(2), 63–85.
   Web of Science ®Google Scholar
• Blaylock, J. R. (1989). An economic model of grocery shopping frequency. Applied Economics, 21(6), 843–852. doi: 10.1080/758520277
   Web of Science ®Google Scholar
• Borgers, A., & Timmermans, H. J. P. (1987). Choice model specification, substitution and spatial structure effects: A simulation experiment. Regional Science and Urban Economics, 17(1), 29–47. doi: 10.1016/0166-0462(87)90067-6
   Web of Science ®Google Scholar
• Bosnjak, M., Galesic, M., & Tuten, T. (2007). Personality determinants of online shopping: Explaining online purchase intentions using a hierarchical approach. Journal of Business Research, 60(6), 597–605. doi: 10.1016/j.jbusres.2006.06.008
   Web of Science ®Google Scholar
• Boyle, K. J., Holmes, T. P., Teisl, M. F., & Roe, B. (2001). A comparison of conjoint analysis response formats. American Journal of Agricultural Economics, 83(2), 441–454. doi: 10.1111/0002-9092.00168
   Web of Science ®Google Scholar
• Broekhuizen, T. L. J., & Jager, W. (2004). A conceptual model of channel choice: Measuring online and offline shopping value perceptions. Groningen, The Netherlands: University of Groningen.
   Google Scholar
• Brooks, C. M., Kaufmann, P. J., & Lichtenstein, D. R. (2008). Trip chaining behavior in multi-destination shopping trips: A field experiment and laboratory replication. Journal of Retailing, 84(1), 29–38. doi: 10.1016/j.jretai.2008.01.009
   Web of Science ®Google Scholar
• Bucchioni, P., Liu, X., & Weidenhamer, D. (2015). Retail E-commerce sales. US Census Bureau of the Department of Commerce.
   Google Scholar
• Burnett, P. (1977). Tests of a linear learning model of destination choice: Applications to shopping travel by heterogeneous population groups. Geografiska Annaler. Series B, Human Geography, 59(2), 95–108. doi: 10.2307/490961
   Web of Science ®Google Scholar
• Burnett, P. (1978). Markovian models of movement within urban spatial structures. Geographical Analysis, 10(2), 142–153.
   Web of Science ®Google Scholar
• Cadwallader, M. (1975). A behavioral model of consumer spatial decision making. Economic Geography, 339–349. doi: 10.2307/142918
   Web of Science ®Google Scholar
• Cairns, S. (1998). Promises and problems: Using GIS to analyse shopping travel. Journal of Transport Geography, 6(4), 273–284. doi: 10.1016/S0966-6923(98)00026-X
   Google Scholar
• Campbell, L. (2012). Amazon partners with co-op for collection lockers. The Bookseller.
   Google Scholar
• Cao, X. J. (2010). E-Shopping, spatial attributes, and personal travel. Transportation Research Record: Journal of the Transportation Research Board, 2135(1), 160–169. doi:10.3141/2135-19
   Web of Science ®Google Scholar
• Cao, X. J. (2012). The relationships between e-shopping and store shopping in the shopping process of search goods. Transportation Research Part A: Policy and Practice, 46(7), 993–1002. doi: 10.1016/j.tra.2012.04.007
   Web of Science ®Google Scholar
• Cao, X. J., Douma, F., & Cleaveland, F. (2010). Influence of E-shopping on shopping travel. Transportation Research Record: Journal of the Transportation Research Board, 2157(1), 147–154. doi: 10.3141/2157-18
   Web of Science ®Google Scholar
• Cao, X. J., Xu, Z., & Douma, F. (2012). The interactions between e-shopping and traditional in-store shopping: An application of structural equations model. Transportation, 39(5), 957–974. doi: 10.1007/s11116-011-9376-3
   Web of Science ®Google Scholar
• Carey, H. C. (1867). Principles of social science (Vol. 3). Philadelphia: JB Lippincott & Company.
   Google Scholar
• Casey, H. J. (1955). Applications to traffic engineering of the law of retail gravitation. Traffic Quarterly, 9(1), 23–35.
   Google Scholar
• Cervero, R. (1989). Land-use mixing and suburban mobility. Berkeley: University of California Transportation Center.
   Google Scholar
• Cervero, R. (1996). Mixed land-uses and commuting: Evidence from the American housing survey. Transportation Research Part A: Policy and Practice, 30(5 PART A), 361–377. doi: 10.1016/0965-8564(95)00033-X
   Web of Science ®Google Scholar
• Chang, M. K., Cheung, W., & Lai, V. S. (2005). Literature derived reference models for the adoption of online shopping. Information and Management, 42(4), 543–559. doi: 10.1016/S0378-7206(04)00051-5
   Web of Science ®Google Scholar
• Chintagunta, P. K., Chu, J., & Cebollada, J. (2012). Quantifying transaction costs in online/off-line grocery channel choice. Marketing Science, 31(1), 96–114. doi: 10.1287/mksc.1110.0678
   Web of Science ®Google Scholar
• Chocarro, R., Cortiñas, M., & Villanueva, M.-L. (2013). Situational variables in online versus offline channel choice. Electronic Commerce Research and Applications, 12(5), 347–361. doi: 10.1016/j.elerap.2013.03.004
   Web of Science ®Google Scholar
• Circella, G., & Mokhtarian, P. L. (2010). Complementarity or substitution of online and in-store shopping: An empirical analysis from Northern California. In Transportation Research Board 89th Annual Meeting.
   Google Scholar
• Corpus, G., & Peachman, J. (2003). Measuring the impacts of internet usage on travel behaviour in the Sydney Household Travel Survey. In Australasia Transport Research Forum Conference, Wellington, October.
   Google Scholar
• Couclelis, H. (2009). Rethinking time geography in the information age. Environment and Planning A, 41(7), 1556. doi: 10.1068/a4151
   Web of Science ®Google Scholar
• Crocco, F., Eboli, L., & Mazzulla, G. (2013). Individual attitudes and shopping mode characteristics affecting the use of E-shopping and related travel. Transport and Telecommunication, 14(1), 45–56. doi:10.2478/ttj-2013-0006
   Google Scholar
• Cullinane, S. L. (2009). From bricks to clicks: The impact of online retailing on transport and the environment. Transport Reviews, 29(6), 759–776. doi: 10.1080/01441640902796364
   Web of Science ®Google Scholar
• DCLG. (2014). Planning practice guidance: Ensuring the vitality of town centres. London: Department for Communities and Local Government.
   Google Scholar
• Dellaert, B. G. C., Arentze, T. A., Bierlaire, M., Borgers, A., & Timmermans, H. J. P. (1998). Investigating consumers’ tendency to combine multiple shopping purposes and destinations. Journal of Marketing Research (JMR), 35(2), 177–188. doi: 10.2307/3151846
   Web of Science ®Google Scholar
• Department for Transport. (2017). National Travel Survey, 2002-2015. [data collection]. 11th Edition. UK Data Service. SN: 5340, https://doi.org/10.5255/UKDA-SN-5340-7.
   Google Scholar
• Dholakia, U. M., Kahn, B. E., Reeves, R., Rindfleisch, A., Stewart, D., & Taylor, E. (2010). Consumer behavior in a multichannel, multimedia retailing environment. Journal of Interactive Marketing, 24(2), 86–95. doi: 10.1016/j.intmar.2010.02.005
   Web of Science ®Google Scholar
• Dholakia, R. R., Zhao, M., & Dholakia, N. (2005). Multichannel retailing: A case study of early experiences. Journal of Interactive Marketing, 19(2), 63–74. doi: 10.1002/dir.20035
   Google Scholar
• Ding, C., Xie, B., Wang, Y., Lin, Y., Chuan, D., Binglei, X., … Yaoyu, L. (2014). Modeling the joint choice decisions on urban shopping destination and travel-to-shop mode: A comparative study of different structures. Discrete Dynamics in Nature and Society, 2014, doi:10.1155/2014/492307
   Web of Science ®Google Scholar
• Dunn, R., & Wrigley, N. (1985). Beta-logistic models of urban shopping center choice. Geographical Analysis, 17(2), 95–113. doi: 10.1111/j.1538-4632.1985.tb00831.x
   Web of Science ®Google Scholar
• Etherington, D. (2016). Daimler begins testing Smart car trunk delivery service with DHL. Tech Crunch.
   Google Scholar
• Farag, S. (2006). E-shopping and its interactions with in-store shopping. Utrecht: Utrecht University.
   Google Scholar
• Farag, S., Krizek, K. J., & Dijst, M. (2006). E-shopping and its relationship with in-store shopping: Empirical evidence from the Netherlands and the USA. Transport Reviews, 26(1), 43–61. doi: 10.1080/01441640500158496
   Web of Science ®Google Scholar
• Farag, S., Schwanen, T., Dijst, M., & Faber, J. (2007). Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping. Transportation Research Part A: Policy and Practice, 41(2), 125–141. doi: 10.1016/j.tra.2006.02.003
   Web of Science ®Google Scholar
• Ferrell, C. E. (2005). The effects of teleshopping on travel behavior and urban form. Berkeley: University of California.
   Google Scholar
• Fotheringham, A. S. (1983). A new set of spatial-interaction models: The theory of competing destinations. Environment and Planning A, 15(1), 15–36. doi: 10.1068/a150015
   Web of Science ®Google Scholar
• Fotheringham, A. S. (1988). Note – consumer store choice and choice set definition. Marketing Science, 7(3), 299–310. doi: 10.1287/mksc.7.3.299
   Web of Science ®Google Scholar
• Fox, E. J., Montgomery, A. L., & Lodish, L. M. (2004). Consumer shopping and spending across retail formats. The Journal of Business, 77(S2), S25–S60. doi: 10.1086/381518
   Web of Science ®Google Scholar
• Ghosh, A. (1986). The value of a mall and other insights from a revised central place model. Journal of Retailing, 62(1), 79–97.
   Web of Science ®Google Scholar
• Gibson, M., & Pullen, M. (1972). Retail turnover in the East Midlands: A regional application of a gravity model. Regional Studies, 6(2), 183–196. doi: 10.1080/09595237200185161
   Web of Science ®Google Scholar
• Gijsbrechts, E., Campo, K., & Nisol, P. (2008). Beyond promotion-based store switching: Antecedents and patterns of systematic multiple-store shopping. International Journal of Research in Marketing, 25(1), 5–21. doi: 10.1016/j.ijresmar.2007.07.001
   Web of Science ®Google Scholar
• Girard, T., Korgaonkar, P., & Silverblatt, R. (2003). Relationship of type of product, shopping orientations, and demographics with preference for shopping on the internet. Journal of Business and Psychology, 18(1), 101–120. doi: 10.1023/A:1025087021768
   Web of Science ®Google Scholar
• Goldfingle, G. (2014). Amazon launches click-and-collect lockers in London Tube stations. Retail Week.
   Google Scholar
• Golob, T. F., & Regan, A. C. (2001). Impacts of information technology on personal travel and commercial vehicle operations: Research challenges and opportunities. Transportation Research Part C: Emerging Technologies, 9(2), 87–121. doi: 10.1016/S0968-090X(00)00042-5
   Web of Science ®Google Scholar
• Gonzalez-Benito, O. (2002). Overcoming data limitations for store choice modelling. Exploiting retail chain choice data by means of aggregate logit models. Journal of Retailing and Consumer Services, 9(5), 259–268. doi: 10.1016/S0969-6989(01)00035-2
   Google Scholar
• Gonzalez-Benito, O. (2005). Spatial competitive interaction of retail store formats: Modeling proposal and empirical results. Journal of Business Research, 58(4), 457–466. doi: 10.1016/j.jbusres.2003.09.001
   Web of Science ®Google Scholar
• Gould, J., & Golob, T. F. (1997). Shopping without travel or travel without shopping? An investigation of electronic home shopping. Transport Reviews, 17(4), 355–376. doi: 10.1080/01441649708716991
   Web of Science ®Google Scholar
• Gustafsson, A., Herrmann, A., & Huber, F. (2013). Conjoint measurement: Methods and applications. New York: Springer Science & Business Media.
   Google Scholar
• Guy, C. M. (1987). Recent advances in spatial interaction modelling: An application to the forecasting of shopping travel. Environment and Planning A, 19(2), 173–186. doi: 10.1068/a190173
   Web of Science ®Google Scholar
• Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571. doi: 10.1016/j.jbusres.2008.06.016
   Web of Science ®Google Scholar
• Handy, S. L. (1992). Regional versus local accessibility: Neo-traditional development and its implications for non-work travel. Built Environment (1978), 18, 253–267.
   Google Scholar
• Handy, S. L. (1993). Regional versus local accessibility: Implications for nonwork travel. Berkeley: University of California Transportation Center.
   Google Scholar
• Handy, S. L. (1996). Methodologies for exploring the link between urban form and travel behavior. Transportation Research Part D: Transport and Environment, 1(2), 151–165. doi: 10.1016/S1361-9209(96)00010-7
   Web of Science ®Google Scholar
• Handy, S. L., & Clifton, K. J. (2001). Local shopping as a strategy for reducing automobile travel. Transportation, 28(4), 317–346. doi: 10.1023/A:1011850618753
   Web of Science ®Google Scholar
• Hawkins, A. J. (2016). Uber wants to be your express delivery service for everything. The Verge.
   Google Scholar
• Haynes, K. E., & Fotheringham, A. S. (1984). Gravity and spatial interaction models (Vol. 2). Beverly Hills: Sage.
   Google Scholar
• Hensher, D. A., & Bradley, M. (1993). Using stated response choice data to enrich revealed preference discrete choice models. Marketing Letters, 4(2), 139–151. doi: 10.1007/BF00994072
   Google Scholar
• Hjorthol, R. J. (2002). The relation between daily travel and use of the home computer. Transportation Research Part A: Policy and Practice, 36(5), 437–452. doi: 10.1016/S0965-8564(01)00012-X
   Web of Science ®Google Scholar
• Horowitz, J. L. (1993). Semiparametric estimation of a work-trip mode choice model. Journal of Econometrics, 58(1–2), 49–70. doi: 10.1016/0304-4076(93)90113-J
   Web of Science ®Google Scholar
• Hsiao, M.-H. H. (2009). Shopping mode choice: Physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review, 45(1), 86–95. doi: 10.1016/j.tre.2008.06.002
   Web of Science ®Google Scholar
• Huang, Y., & Oppewal, H. (2006). Why consumers hesitate to shop online: An experimental choice analysis of grocery shopping and the role of delivery fees. International Journal of Retail and Distribution Management, 34(4/5), 334–353. doi: 10.1108/09590550610660260
   Google Scholar
• Huff, D. L. (1963). A probabilistic analysis of shopping center trade areas. Land Economics, 81–90. doi: 10.2307/3144521
   Web of Science ®Google Scholar
• Ibrahim, M. F., & McGoldrick, P. J. (2003). Shopping choices with public transport options: An agenda for the 21st century. Ann Arbor: Ashgate.
   Google Scholar
• Jiao, J., Moudon, A. V., & Drewnowski, A. (2011). Grocery shopping. Transportation Research Record: Journal of the Transportation Research Board, 2230(1), 85–95. doi: 10.3141/2230-10
   PubMed Web of Science ®Google Scholar
• Johnson, E. J., & Meyer, R. J. (1984). Compensatory choice models of noncompensatory processes: The effect of varying context. Journal of Consumer Research, 528–541. doi: 10.1086/208989
   Web of Science ®Google Scholar
• Keskinen, A., Delache, X., Cruddas, J., Lindjord, J. E., & Iglesias, C. (2001). A purchase and a chain. Impacts of E-commerce on transport and the environment. Report of Working Group, 3.
   Google Scholar
• Kim, B.-D., & Park, K. (1997). Studying patterns of consumer’s grocery shopping trip. Journal of Retailing, 73(4), 501–517. doi: 10.1016/S0022-4359(97)90032-4
   Web of Science ®Google Scholar
• Kitamura, R. (1984). Incorporating trip chaining into analysis of destination choice. Transportation Research Part B: Methodological, 18(1), 67–81. doi: 10.1016/0191-2615(84)90007-9
   Web of Science ®Google Scholar
• Koppelman, F. S., & Bhat, C. R. (2006). A self instructing course in mode choice modeling: Multinomial and nested logit models.
   Google Scholar
• Koppelman, F. S., & Hauser, J. R. (1978). Destination choice behavior for non-grocery-shopping trips. Transportation Research Record: Journal of the Transportation Research Board, 673, 157–165.
   Google Scholar
• Kumar, A., & Levinson, D. (1995). Temporal variations on allocation of time. Transportation Research Record: Journal of the Transportation Research Board, 1493, 118–127.
   Google Scholar
• Lakshmanan, J. R., & Hansen, W. G. (1965). A retail market potential model. Journal of the American Institute of Planners, 31(2), 134–143. doi: 10.1080/01944366508978155
   Google Scholar
• Lee, D. J.-H., & Ross, C. L. (2016). Bringing freight components into statewide and regional travel demand forecasting. Atlanta: Georgia Tech Research Corporation.
   Google Scholar
• Lee, R. J., Sener, I. N., Mokhtarian, P. L., & Handy, S. L. (2017). Relationships between the online and in-store shopping frequency of Davis, California residents. Transportation Research Part A: Policy and Practice, 100, 40–52. doi: 10.1016/j.tra.2017.03.001
   Web of Science ®Google Scholar
• Lee, K. S., & Tan, S. J. (2003). E-retailing versus physical retailing: A theoretical model and empirical test of consumer choice. Journal of Business Research, 56(11), 877–885. doi: 10.1016/S0148-2963(01)00274-0
   Web of Science ®Google Scholar
• Liao, Z., & Cheung, M. T. (2001). Internet-based e-shopping and consumer attitudes: An empirical study. Information and Management, 38(5), 299–306. doi: 10.1016/S0378-7206(00)00072-0
   Web of Science ®Google Scholar
• Limanond, T., Niemeier, D. A., & Mokhtarian, P. L. (2005). Specification of a tour-based neighborhood shopping model. Transportation, 32(2), 105–134. doi: 10.1007/s11116-004-6992-1
   Web of Science ®Google Scholar
• Liu, C., & Forsythe, S. (2011). Examining drivers of online purchase intensity: Moderating role of adoption duration in sustaining post-adoption online shopping. Journal of Retailing and Consumer Services, 18(1), 101–109. doi: 10.1016/j.jretconser.2010.10.004
   Google Scholar
• Louviere, J. J. (1988). Conjoint analysis modelling of stated preferences: A review of theory, methods, recent developments and external validity. Journal of Transport Economics and Policy, 22, 93–119.
   Web of Science ®Google Scholar
• Louviere, J. J., Flynn, T. N., & Carson, R. T. (2010). Discrete choice experiments are not conjoint analysis. Journal of Choice Modelling, 3(3), 57–72. doi: 10.1016/S1755-5345(13)70014-9
   Web of Science ®Google Scholar
• Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated choice methods: Analysis and application. Journal of Applied Econometrics, 17(6), 701–704. doi:10.1002/jae.701
   Web of Science ®Google Scholar
• Louviere, J. J., & Meyer, R. J. (1981). A composite attitude-behavior model of traveler decision making. Transportation Research Part B: Methodological, 15(6), 411–420. doi: 10.1016/0191-2615(81)90025-4
   Web of Science ®Google Scholar
• Lowe, M. (2005). The regional shopping centre in the inner city: A study of retail-led urban regeneration. Urban Studies, 42(3), 449–470. doi: 10.1080/00420980500035139
   Web of Science ®Google Scholar
• Lundevaller, E. H. (2009). The effect of travel cost on frequencies of shopping and recreational trips in Sweden. Journal of Transport Geography, 17(3), 208–215. doi: 10.1016/j.jtrangeo.2008.05.002
   Web of Science ®Google Scholar
• MarkerJr, J. T., & Goulias, K. (2007). Framework for the analysis of grocery teleshopping. Transportation Research Record: Journal of the Transportation Research Board, 1725(1), 1–8. doi:10.3141/1725-01
   Google Scholar
• McFadden, D., Talvitie, A., Cosslett, S., Hasan, I., Johnson, M., Reid, F., & Train, K. E. (1977). Demand model estimation and validation (Vol. 5). Berkeley: Institute of Transportation Studies, University of California.
   Google Scholar
• Messinger, P. R., & Narasimhan, C. (1997). A model of retail formats based on consumers’ economizing on shopping time. Marketing Science, 16(1), 1–23. doi: 10.1287/mksc.16.1.1
   Web of Science ®Google Scholar
• Miller, E. J., & O’Kelly, M. E. (1983). Estimating shopping destination models from travel diary data. The Professional Geographer, 35(4), 440–449. doi: 10.1111/j.0033-0124.1983.00440.x
   Web of Science ®Google Scholar
• Mokhtarian, P. L. (1990). A typology of relationships between telecommunications and transportation. Transportation Research Part A: General, 24(3), 231–242. doi: 10.1016/0191-2607(90)90060-J
   Google Scholar
• Mokhtarian, P. L. (2002). Telecommunications and travel. The case for complementarity. Journal of Industry Ecology, 6(2), 43–57. doi: 10.1162/108819802763471771
   Google Scholar
• Mokhtarian, P. L. (2004). A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3), 257–284. doi: 10.1023/B:PORT.0000025428.64128.d3
   Web of Science ®Google Scholar
• Mokhtarian, P. L. (2009). If telecommunication is such a good substitute for travel, why does congestion continue to get worse? Transportation Letters, 1(1), 1–17. doi: 10.3328/TL.2009.01.01.1-17
   Web of Science ®Google Scholar
• Mokhtarian, P. L., Salomon, I., & Handy, S. L. (2004). A taxonomy of leisure activities: The role of ICT.
   Google Scholar
• Mokhtarian, P. L., & Salomon, I. (1997). Chapter 7: Emerging travel patterns: Do telecommunications make a difference? In Hani S. Mahmassani (Ed.), Perpetual Motion: Travel Behaviour Research Opportunities and Application Challenges (pp. 143–182). Pergamon Press/Elsevier, 2002.
   Google Scholar
• Mokhtarian, P. L., & Tang, W. L. (2013). Trivariate probit models of pre-purchase/purchase shopping channel choice: Clothing purchases in Northern California. Choice Modelling: The State of the Art and the State of Practice, Chapter 12, 243–273.
   Google Scholar
• Nagurney, A., Dong, J., & Mokhtarian, P. L. (2001). Teleshopping versus shopping: A multicriteria network equilibrium framework. Mathematical and Computer Modelling, 34(7), 783–798. doi: 10.1016/S0895-7177(01)00099-1
   Google Scholar
• Office for National Statistics. (2015). Retail sales 2014.
   Google Scholar
• Ortúzar, J., & Willumsen, L. G. (1994). Modelling transport. Sussex, England: Wiley.
   Google Scholar
• Pattabhiraman, V. R. (2012). A needs-based approach to activity generation for travel demand analysis. Cambridge, MA: Massachusetts Institute of Technology.
   Google Scholar
• Pauwels, K., & Neslin, S. A. (2011). Building with bricks and mortar: The revenue impact of opening physical stores in a multichannel environment. Working Paper, 603, 1–29. doi:10.1016/j.jretai.2015.02.001
   Google Scholar
• Pendyala, R. M., Kitamura, R., Kikuchi, A., Yamamoto, T., & Fujii, S. (2005). Florida activity mobility simulator: Overview and preliminary validation results. Transportation Research Record: Journal of the Transportation Research Board, 1921(1), 123–130. doi: 10.3141/1921-14
   Web of Science ®Google Scholar
• Pinjari, A. R., & Bhat, C. R. (2011). Activity-based travel demand analysis. A Handbook of Transport Economics, 10, 213–248.
   Google Scholar
• Popkowski Leszczyc, P. T. L., Sinha, A., & Sahgal, A. (2004). The effect of multi-purpose shopping on pricing and location strategy for grocery stores. Journal of Retailing, 80(2), 85–99. doi: 10.1016/j.jretai.2004.04.006
   Web of Science ®Google Scholar
• Popkowski Leszczyc, P. T. L., & Timmermans, H. J. P. (2001). Experimental choice analysis of shopping strategies. Journal of Retailing, 77(4), 493–509. doi: 10.1016/S0022-4359(01)00054-9
   Web of Science ®Google Scholar
• Porojan, A. (2001). Trade flows and spatial effects: The gravity model revisited. Open Economies Review, 12(3), 265–280. doi: 10.1023/A:1011129422190
   Web of Science ®Google Scholar
• Rasouli, S., & Timmermans, H. J. P. (2013). Assessment of model uncertainty in destinations and travel forecasts of models of complex spatial shopping behaviour. Journal of Retailing and Consumer Services, 20(2), 139–146. doi: 10.1016/j.jretconser.2012.05.001
   Google Scholar
• Recker, W. W., & Golob, T. F. (1979). A non-compensatory model of transportation behavior based on sequential consideration of attributes. Transportation Research Part B: Methodological, 13(4), 269–280. doi: 10.1016/0191-2615(79)90019-5
   Web of Science ®Google Scholar
• Recker, W. W., & Kostyniuk, L. P. (1978). Factors influencing destination choice for the urban grocery shopping trip. Transportation, 7(1), 19–33. doi: 10.1007/BF00148369
   Web of Science ®Google Scholar
• Recker, W. W., & Schuler, H. J. (1981). Destination choice and processing spatial information: Some empirical tests with alternative constructs. Economic Geography, 57(4), 373–383. doi: 10.2307/144216
   Web of Science ®Google Scholar
• Recker, W. W., & Stevens, R. F. (1976). Attitudinal models of modal choice: The multinomial case for selected nonwork trips. Transportation, 5(4), 355–375. doi: 10.1007/BF00151097
   Web of Science ®Google Scholar
• Reilly, W. J. (1931). The law of retail gravitation. New York: Knickerbocker Press.
   Google Scholar
• Reutterer, T., & Teller, C. (2009). Store format choice and shopping trip types. International Journal of Retail and Distribution Management, 37(8), 695–710. doi: 10.1108/09590550910966196
   Google Scholar
• Rhee, H.-S., Riggins, F. J., & Kim, C. (2009). The impact of product type and perceived characteristics of the web on multifaceted online shopping behavior. Journal of Organizational Computing and Electronic Commerce, 19(1), 1–29. doi: 10.1080/10919390802198907
   Web of Science ®Google Scholar
• Richards, M. G., & Ben-Akiva, M. (1974). A simultaneous destination and mode choice model for shopping trips. Transportation, 3(4), 343–356. doi: 10.1007/BF00167965
   Web of Science ®Google Scholar
• Roorda, M. J., Miller, E. J., & Habib, K. (2008). Validation of TASHA: A 24-h activity scheduling microsimulation model. Transportation Research Part A: Policy and Practice, 42(2), 360–375. doi: 10.1016/j.tra.2007.10.004
   Web of Science ®Google Scholar
• Rotem-Mindali, O. (2014). E-Commerce: Implications for travel and the environment. In Handbook of sustainable travel (pp. 293–305). London: Springer.
   Google Scholar
• Rotem-Mindali, O., & Salomon, I. (2007). The impacts of E-retail on the choice of shopping trips and delivery: Some preliminary findings. Transportation Research Part A: Policy and Practice, 41(2), 176–189. doi: 10.1016/j.tra.2006.02.007
   Web of Science ®Google Scholar
• Rotem-Mindali, O., & Salomon, I. (2009). Modeling consumers’ purchase and delivery choices in the face of the information age. Environment and Planning B: Planning and Design, 36(2), 245. doi: 10.1068/b34013t
   Google Scholar
• Rotem-Mindali, O., & Weltevreden, J. W. J. (2013). Erratum to: Transport effects of e-commerce: What can be learned after years of research? Transportation, 40(5), 867. doi: 10.1007/s11116-013-9457-6
   Web of Science ®Google Scholar
• Rust, R. T., & Donthu, N. (1995). Capturing geographically localized misspecification error in retail store choice models. Journal of Marketing Research (JMR), 32(1), 103–110.
   Web of Science ®Google Scholar
• Salomon, I. (1985). Telecommunications and travel: Substitution or modified mobility? Journal of Transport Economics and Policy, 219–235. doi:10.1080/09595238100185051
   Web of Science ®Google Scholar
• Salomon, I. (1986). Telecommunications and travel relationships: A review. Transportation Research Part A: General, 20(3), 223–238. doi: 10.1016/0191-2607(86)90096-8
   Google Scholar
• Salomon, I., & Koppelman, F. S. (1988). A framework for studying teleshopping versus store shopping. Transportation Research Part A: General, 22(4), 247–255. doi: 10.1016/0191-2607(88)90003-9
   Google Scholar
• Santos, A., McGuckin, N., Nakamoto, H. Y., Gray, D., & Liss, S. (2011). Summary of travel trends: 2009 national household travel survey, Washington: US Department of Transportation.
   Google Scholar
• Schiraldi, P., Seiler, S., & Smith, H. (2011). Supermarket choice with multi-store shopping: Measuring the effect of format regulation, London: Unpublished manuscript.
   Google Scholar
• Schmöcker, J. D., Quddus, M., Noland, R. B., & Bell, M. G. H. (2008). Mode choice of older and disabled people: A case study of shopping trips in London. Journal of Transport Geography, 16(4), 257–267. doi: 10.1016/j.jtrangeo.2007.07.002
   Web of Science ®Google Scholar
• Schoenbachler, D. D., & Gordon, G. L. (2002). Multi-channel shopping: Understanding what drives channel choice. Journal of Consumer Marketing, 19(1), 42–53. doi: 10.1108/07363760210414943
   Google Scholar
• Schonfelder, S., & Axhausen, K. W. (2001). Analysing the rhythms of travel using survival analysis. Transportation Research Board 80th Annual Meeting, 137–162.
   Google Scholar
• Schröder, H., & Zaharia, S. (2008). Linking multi-channel customer behavior with shopping motives: An empirical investigation of a German retailer. Journal of Retailing and Consumer Services, 15(6), 452–468. doi: 10.1016/j.jretconser.2008.01.001
   Google Scholar
• Sivakumar, A. (2007). Modelling transport: A synthesis of transport modelling methodologies. London: Imperial College of London.
   Google Scholar
• Soopramanien, D. G. R., & Robertson, A. (2007). Adoption and usage of online shopping: An empirical analysis of the characteristics of “buyers” “browsers” and “non-internet shoppers”. Journal of Retailing and Consumer Services, 14(1), 73–82. doi: 10.1016/j.jretconser.2006.04.002
   Google Scholar
• Steed, J., & Bhat, C. (2000). On modeling departure-time choice for home-based social/recreational and shopping trips. Transportation Research Record: Journal of the Transportation Research Board, 1706, 152–159. doi: 10.3141/1706-18
   Web of Science ®Google Scholar
• Strathman, J. G., Dueker, K. J., & Davis, J. S. (1994). Effects of household structure and selected travel characteristics on trip chaining. Transportation, 21(1), 23–45. doi: 10.1007/BF01119633
   Web of Science ®Google Scholar
• Suárez, A., del Bosque, I. R. d. B., Rodrı̗guez-Poo, J. M., & Moral, I. (2004). Accounting for heterogeneity in shopping centre choice models. Journal of Retailing and Consumer Services, 11(2), 119–129. doi: 10.1016/S0969-6989(03)00011-0
   Google Scholar
• Suel, E. (2016). Modelling the relationship between multi-channel retail and personal mobility behaviour (PhD Dissertation). Imperial College London.
   Google Scholar
• Suel, E., Daina, N., & Polak, J. W. (2016). A hazard-based approach to modelling effects of online shopping on inter-shopping duration. In Universities’ Transport Study Group (UTSG) Conference January 2016. Bristol.
   Google Scholar
• Suel, E., Le Vine, S., & Polak, J. W. (2015). Empirical application of expenditure diary instrument to quantify relationships between in-store and online grocery shopping: Case study of greater London. Transportation Research Record: Journal of the Transportation Research Board, 2496, 45–54. doi: 10.3141/2496-06
   Web of Science ®Google Scholar
• Swait, J. D., & Ben-Akiva, M. (1987). Empirical test of a constrained choice discrete model: Mode choice in São Paulo, Brazil. Transportation Research Part B: Methodological, 21(2), 103–115. doi: 10.1016/0191-2615(87)90010-5
   Web of Science ®Google Scholar
• Teltzrow, M., Meyer, B., & Lenz, H.-J. (2007). Multi-channel consumer perceptions. Journal of Electronic Commerce Research, 8(308277), 18–31.
   Google Scholar
• Thill, J., & Thomas, I. (1987). Toward conceptualizing trip-chaining behavior: A review. Geographical Analysis, 19(1), 1–17. doi: 10.1111/j.1538-4632.1987.tb00110.x
   Web of Science ®Google Scholar
• Thill, J.-C., & Wheeler, A. (2000). Knowledge discovery and induction of decision trees in spatial decision problems. In Spatial economic science. Advances in Spatial Science. (pp. 188–205). Berlin, Heidelberg: Springer.
   Google Scholar
• Thomas, C. J., & Bromley, R. D. F. (2003). Retail revitalization and small town centres: The contribution of shopping linkages. Applied Geography, 23(1), 47–71. doi: 10.1016/S0143-6228(02)00068-1
   Web of Science ®Google Scholar
• Timmermans, H. J. P. (1981). Multiattribute shopping models and ridge regression analysis. Environment and Planning A, 13(1), 43–56. doi: 10.1068/a130043
   Web of Science ®Google Scholar
• Timmermans, H. J. P. (1982). Consumer choice of shopping centre: An information integration approach. Regional Studies, 16(3), 171–182. doi: 10.1080/09595238200185201
   Web of Science ®Google Scholar
• Timmermans, H. J. P. (1984). Discrete Choice Models versus Decompositional Multiattribute Preference Models: A Comparative Analysis of Model Performance in the Context of Spatial Shopping-behaviour. In: D. E. Pitfield (Ed.), Discrete choice models in regional science (pp. 88–102). London: Pion, ISBN 0-85086-113-6. (British section of the Regional Science Association annual conference; 1993).
   Google Scholar
• Timmermans, H. J. P. (1996). A stated choice model of sequential mode and destination choice behaviour for shopping trips. Environment and Planning A, 28(1), 173–184. doi: 10.1068/a280173
   Web of Science ®Google Scholar
• Timmermans, H. J. P., Borgers, A., & van der Waerden, P. (1992). Mother logit analysis of substitution effects in consumer shopping destination choice. Journal of Business Research, 24(2), 177–189. doi: 10.1016/0148-2963(92)90060-O
   Google Scholar
• Timmermans, H. J. P., Van der Heuden, R., & Westerveld, H. (1982). The identification of factors influencing destination choice: An application of the repertory grid methodology. Transportation, 11(2), 189–203. doi: 10.1007/BF00167931
   Web of Science ®Google Scholar
• Timmermans, H. J. P., Van Der Heijden, R., & Westerveld, H. (1984). Decision making between multi attribute choice alternatives: A model of spatial shopping-behaviour using conjoint measurements. Environment and Planning A, 16(3), 377–387. doi: 10.1068/a160377
   Web of Science ®Google Scholar
• Train, K. E. (1980). A structured logit model of auto ownership and mode choice. The Review of Economic Studies, 47(2), 357–370. doi: 10.2307/2296997
   Web of Science ®Google Scholar
• Train, K. E. (2009). Discrete choice methods with simulation. Cambridge: Cambridge University Press.
   Google Scholar
• Tversky, A. (1972). Elimination by aspects: A theory of choice. Psychological Review, 79(4), 281. doi: 10.1037/h0032955
   Web of Science ®Google Scholar
• Uncles, M. D. (1987). A beta-logistic model of mode choice: Goodness of fit and intertemporal dependence. Transportation Research Part B: Methodological, 21(3), 195–205. doi: 10.1016/0191-2615(87)90003-8
   Web of Science ®Google Scholar
• Visser, E., & Lanzendorf, M. (2004). Mobility and accessibility effects of B2C e-commerce: A literature review. Tijdschrift Voor Economische En Sociale Geografie, 95(2), 189–205. doi: 10.1111/j.0040-747X.2004.00300.x
   Web of Science ®Google Scholar
• Weltevreden, J. W. J. (2007). Substitution or complementarity? How the internet changes city centre shopping. Journal of Retailing and Consumer Services, 14(3), 192–207. doi: 10.1016/j.jretconser.2006.09.001
   Google Scholar
• Weltevreden, J. W. J., & Rotem-Mindali, O. (2008). Mobility effects of b2c and c2c e-commerce: A literature review and assessment. In Third international specialist meeting on ICT, everyday life and urban change (pp. 16–19). Briston, UK.
   Google Scholar
• Weltevreden, J. W. J., & Rotem-Mindali, O. (2009). Mobility effects of b2c and c2c e-commerce in the Netherlands: A quantitative assessment. Journal of Transport Geography, 17(2), 83–92. doi: 10.1016/j.jtrangeo.2008.11.005
   Web of Science ®Google Scholar
• Wilson, A. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. doi: 10.1068/a030001
   Web of Science ®Google Scholar
• Winter, C. (2014, February 27). Volvo wants your parked car to accept deliveries. Bloomberg. Retrieved from https://www.bloomberg.com.
   Google Scholar
• Wrigley, N. (1988). Store choice, store location and market analysis. London: Routledge.
   Google Scholar
• Yun, D.-S., & O’Kelly, M. E. (1997). Modeling the day-of-the-week shopping activity and travel patterns. Socio-Economic Planning Sciences, 31(4), 307–319. doi: 10.1016/S0038-0121(97)00010-4
   Google Scholar
• Zhai, Q., Cao, X., Mokhtarian, P. L., & Zhen, F. (2016). The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods. Transportation, 1–20. doi:10.1007/s11116-016-9683-9
   PubMed Web of Science ®Google Scholar
• Zhen, F., Cao, X. J., Mokhtarian, P. L., & Xi, G. (2016). Associations between online purchasing and store purchasing for four types of products in Nanjing, China. Transportation Research Record: Journal of the Transportation Research Board, 2566, 93–101. doi: 10.3141/2566-10
   Web of Science ®Google Scholar
• Zhou, Y., & Wang, X. C. (2014). Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data. Transportation Research Part A: Policy and Practice, 70, 1–9. doi: 10.1016/j.tra.2014.09.014
   Web of Science ®Google Scholar