Detection and Measurement of Latent and Manifest Heterogeneity of Familiarity, Perceptions, and Attractiveness of Places Using Multilevel Analysis

Spatial choice models are increasingly becoming the focus of research for transportation applications (Ferguson and Kanaroglou, 1995, Pellegrini and Fotherigham, 2002, Hunt et al., 2004; Paleti et al., 2013).  Adding components of attitudes and perceptions to spatial discrete choice models allows building simulated decision makers that are more realistically heterogeneous. This is accomplished via latent factors within an integrated system of structural equations with discrete choice models (Ben Akiva et al., 2002a, 2002b; Bhat and Dubey, 2014).  Capturing, measuring, and incorporating emotional connections between people and place(s) such as the multiple dimensions of  Sense of Place Deutsch and Goulias (2010) and Deutsch et al. (2013a) can help us advance one step further to explain variation in activity and travel behavior choices.  Along these lines of new model development, in a recent study Santa Barbara, CA, residents linked destinations to a variety of location attributes such as distance and cost, comfort, security, but also included decision making styles and interactions among persons engaging in the same activity and selecting locations to visit (Deutsch-Burgner et al., 2014).  In this context, we have been able to identify important concepts of decision making related to activity patterns and subjective well-being.  The psychological and emotional aspects of a destination have been shown to be at times equally or even more heavily influential on decisions of destination selection than objective measures such as cost, time and distance. In this same research, we were able to create an individualized index of attraction for four different aspects of place (Deutsch and Goulias, 2013b, Deutsch-Burgner et al., 2014).  These aspects, attractiveness, opportunities available, familiarity, and perception of safety were used as a basis for the development of a heat map like surface of attraction.  The weighted scores by individuals provide not only an analysis of the respondents' views of the region, but also the degree to which each aspect matters.  We were also able to refine these concepts examining various types of activities to capture the varying degree of importance in decision-making.  Individuals have different expectations and criteria to evaluate a destination, and therefore an activity episode.  However, this is not sufficient to understand spatial choice.  A more detailed analysis of added latent constructs on a joint person-by-person and location-by-location basis of  attractiveness, opportunities available, familiarity, and perception of safety  and the correlations of these aspects with objective indicators of land use and urban form as well as personal characteristics can reveal hidden patterns in this type of information.   In this paper we use data from the GeoTRIPS ( G eography of TR avel, I nterests, P laces and S ocial ties ) survey, a web-based survey that was conducted during the period of May 2012 through July 2012.  We are using the data from an interactive mapping exercise of this survey in which respondents were asked to agree/ disagree on a seven point likert-like scale to statements on attractiveness, opportunities available, familiarity, and perception of safety regarding mini-regions of Santa Barbara.  Regions were delineated by a hexagonal tessellated grid in Figure 1 that also shows an example of the relationship among perception of opportunities available in each hexagon, attraction of each hexagon, and the size of the circles representing the counted number of business establishments in each hexagon. (supplementary file displays the figure correctly) Figure 1 Perceived Opportunity Correlated with Stated Attractiveness and Observed Number of Business Establishments in GeoTRIPS Survey In this paper using two analytical techniques, i.e., a repeated measures latent class ordered regression model and a multilevel structural ordered regression model system, we explore the relationships among perceived opportunity to participate in activities in each hexagon, stated attractiveness for each hexagon, perceived danger, and familiarity with each of these areas.  These are the four endogenous variables in the different model systems.  We consider as exogenous variables at the respondent level, characteristics such as age, gender, employment, income, education, marital status, car ownership, number of children in the household, and number of years in current residence.  At the spatial (hexagon) lower level we use as exogenous variables the presence and size of business establishments classified by the 2-digit SIC to capture objective presence of activity opportunities, average centrality of the highway links within each hexagon to capture urban form, and adjacent to each hexagon perceived attraction, perception of opportunities, and familiarity to capture spatial dependency and correlation of ratings.  the estimated models show positive correlations between perceived and objective existence of opportunities and attractiveness of locations driven by leisure and entertainment businesses establishments.  Urban form measured by roadway centrality is also found to be significant contributor to perceptions.    We also find substantial differences among latent groups of the 561 respondents of this survey.  There are also a few surprises in the lack of significant influence of a few social and demographic indicators that we will present in more detail in the forthcoming paper.   References Ben-Akiva, M., D. 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R. Bhat, R. M. Pendyala, and K. G. Goulias. (2013) Modeling of Household Vehicle Type Choice Accommodating Spatial Dependence Effects. Transportation Research Record: Journal of the Transportation Research Board 2343, no. 1: 86-94.