Destination Choice Behavior Research Articles

화물자동차기반 대도시 화물수요모형 구축을 위한 화물자동차 통행특성 분석

The purpose of the study is to analyze the travel characteristics of freight trucks in metropolitan areas, focusing on activity generation, destination choice, and trip chaining behaviors. The results showed that the number of service companies at departure areas has a primary influence on the activity generation pattern and destination choice behavior of trucks in metropolitan areas. The number of trips within a trip chain is largest, in case where the prevailing industry in destination areas is wholesale or retail and the shipment item is food or beverage. These results imply that for the reasonable estimation of truck travel demand both the trip chaining behaviors and the industrial compositions in departure and destination areas should be separately considered for each type of commodity.

Synthetic Environment to Evaluate Alternative Trip Distribution Models

In this paper an environment is synthesized to incorporate spatial distributions of population and employees and to simulate travelers’ destination choice behaviors following utility-maximization decision rules. In this synthetic environment, two alternative trip distribution models—the destination choice model and the gravity model—are evaluated by comparing estimated model coefficients and trip matrices against their true counterparts. The destination choice model provides reasonable model coefficients and trip matrix when the average trip length is much greater than the zone size. However, when the average trip length comes closer to the zone size as a result of significant spatial aggregation errors the model coefficients appear more biased, and more errors occur in trip matrix estimation. In the gravity model, linear regression does not provide consistent coefficients for trip attraction variables and therefore cannot accurately estimate trip attractions. It is not optional but necessary to apply the destination choice model for consistently estimating the trip attraction and trip matrix in trip distribution.

Dynamic Analysis of Japanese Tourists’ Three Stage Choices

Finding ways to encourage people to participate in domestic tourism has been a central political issue in Japan for many years. One issue is the unbalanced regional trend in domestic tourist destinations. Various transport policies have been proposed. Under such policy considerations, jointly representing tourism participation, destination choice, and travel mode choice becomes important. However, tourism demand shows monthly variations. To date, the above three aspects have not been satisfactorily analyzed in a dynamic fashion. This study seeks to gain a better understanding of interrelated tourist behavior and provide a scientific tool to support tourism policy decisions by jointly analyzing these choice aspects to build a dynamic nested logit model while taking the influence of state dependence into account. Empirical analysis confirmed the effectiveness of the model with the use of retrospective panel survey data collected from 1,253 respondents in Japan in 2010. To the authors’ best knowledge, this was the first panel survey in Japan to investigate tourists’ behavior over the course of 1 year on a monthly basis. Model estimation results confirmed significantly negative effects of state dependence with respect to tourism participation behavior (implying a decreasing tendency of continuous tourism participation at the monthly level), but positive effects with respect to destination and travel mode choice behaviors. The positive value of state dependence for the travel mode choice behavior suggests that people prefer to use the same type of travel modes when they travel. The influence of travel mode choice on destination choice shows largely regional variations. Results also clarified effects of tourism motivation, individual characteristics, destination-specific attributes, and travel mode–specific attributes on the three choice aspects. Implications of model estimations for policy decisions are discussed.

Going round in circles: mobility, destination and experience

This paper addresses the changing approaches to transport in urban tourism as seen through the move from functional sectoral accounts towards a perspective informed by the experience economy. By reviewing the traditional service offers, it is possible to unpack what lies within the service dominant logics that lead to co-creation of value and the realisation of quality tourism experiences. The paper then considers the adoption and adaptation of traditional forms of transport within the value proposition in urban tourism. Mobility in tourism is a strangely new focus of attention, strangely because without it there would be no tourism to speak of. However mobility requires a framework of civil and legal entitlements that allow people to move and a transport infrastructure that allows those rights to be realised in both working and leisure time situations. This article will address the construction of the tourism transport infrastructure by examining the ways in which the transportation elements in mobility have been re-thought within tourism. The first part of the paper will re-construct an account of transport and mobility which deals with it in terms of the functions and logistics of delivery, both between points of origin and destinations, and within destinations. These perspectives can be seen in the texts which shape the basic tourism curriculum (Cooper et al, 2008; Page, 2009) and explain how tourism and transport have developed over the years by integrating the opportunities provided by the new technologies – motorised vehicles (both cars and coaches), trains, ships and aeroplanes – to allow for the development of a range of destinations. Lumsdon and Page (2004) introduced a new approach to transport and tourism by distinguishing between transport for tourism and transport as tourism, which provides a linkage between the first and second parts of this article. The second part will develop an account of mobility in tourism that demonstrates how their uniqueness derives from what the ‘Service-dominant (S-D) logic’ (Vargo and Lush, 2004; Vargo and Morgan, 2005; Vargo and Lush 2006) would call value co-creation. Hyde and Laesser (2008) emphasised the important role of transport in the tourist decision-making process associated with destination choice behaviour but it is necessary to move beyond this construction of the interconnections (Andersson, 2007). These elements of transport were generally considered to be “goods” or “products” including both tangible and intangible factors. Physical goods become one element among others in a total service offering, from an exhibition to a living performance or a concert and transportation has become an integral part of that experience if not of the offer.

Modeling Destination Choice Behavior Incorporating Spatial Factors, Individual Sociodemographics, and Travel Mode

Destination choice studies have been primarily carried out in developed countries. However in China, a typical developing country, few studies about destination choice exist. In this paper, we propose nonlinear-in-parameters multinomial logit models to investigate the influences of spatial factors on both work and intermediate stop destination choices. We use individual sociodemographics, travel-activity attributes, and land-use characteristics as exogeneous variables. Individual’s destination choice behaviors with different sociodemographics and travel modes are examined as well. The models are applied to data collected in the city of Shangyu, China. Compared with previous studies, this research further distinguishes the size variables influencing destination choices for work and intermediate stop in the type and the extent to which each type of size variables exerts influence. Besides, the preferences to destination choices are more clearly illustrated, resulting from the typical occupation characteristics and commuting modes of China.

Choices of Metropolitan Destinations by the 1995-2000 New Immigrants Born in Mexico and India: Characterization and Multivariate Explanation

Using the confidential long-form records of the 2000 population census, we study the choices of metropolitan destinations made by the Mexican-born and Indian-born immigrants who arrived in the United States in 1995-2000. Based on the application of a multinomial logit model to the data of each of these two ethnic groups, our main findings are as follows. The destination choice behaviors of both ethnic groups were in general consistent with the major theories of immigration. Both groups were subject to (1) the attraction of co-ethnic communities and (2) the positive effects of wage level and total employment growth. With respect to the job increases in different wage deciles, both ethnic groups share the pattern that the less educated were subject to the pull of increase in low-wage jobs, whereas the better educated were subject to the pull of increase in high-wage jobs. With respect to the possibility of competitions against other foreign-born ethnics, both ethnic groups were found to be more prone to selecting destinations where their co-ethnics represented a relatively high proportion of the foreign-born population. The main differences in destination choice behaviors between the two ethnic groups resulted partly from the fact that the relative explanatory powers of our chosen explanatory factors differed substantially between the two ethnic groups. The Mexican-born were more subject to the attractions of (1) larger co-ethnic communities, (2) greater overall employment growth, (3) more job increases in low wage deciles, and (4) greater share of the foreign-born population by co-ethnics. In contrast, the Indian-born were more attracted by (1) higher wage level, and (2) more job increases in high wage deciles.

Optimization of the Distribution of Shopping Center to Manage the Shopping Trips in a China's City

In order to manage the transportation demand through land use planning, we developed a model to optimize the distribution of shopping centers in a Chinese city. In the model the location behavior of shopping centers and the destination selection behavior of the shoppers are considered. It is a p-median style model, in which we considered the modal split model. Respective models based on road network and super transportation network are structured. The objective of both models is to decrease the distance of shopping trip. With survey data of Dalian city we calibrated the two models and verified their validity. After that, genetic algorithm with dynamic parameters is designed in order to solve this nonlinear programming problem. Numerical test is conducted using the data for Dalian of China. 1. BACKGROUND Studies on the distribution of shopping centers involve the location choice behavior of owners and the destination choice behavior of consumers. Location models considering the consumer behaviors were studied and the corresponding algorithms to solve them were also developed (Daniel 2001, Tammy 2002 and Stefno 2002). Concerning the destination choice behavior of the consumers, as early as 1929 Reilly explained it with gravity theory and then Casey and Huff simulated the behavior with stochastic gravity model (David 1981). Afterwards, Nakanishi and Cooper analyzed the behavior with the MCI (multiplicative competitive interaction) model (Cooper, et al. 1988). In China, most studies on the distribution of the shopping centers are qualitative rather than quantities. Recently, as the advance of the GIS and optimal algorithm, the distribution of the shopping centers was studied with the optimizing model and the corresponding algorithm. Nobuaki (1998) forecasted the scales of the shopping center in the zones level with Huff and regression models, but he could not give the detailed locations. Yang (2002a) analyzed the supplied quality of each house and the environment sustainability of each store, and further selected the optimal distribution among the candidate alternatives with AHP. Yang (2002b) studied the optimal distribution of shopping centers aiming to minimize the total car trip distance. Among the existing literatures, few studies integrated the urban traffic demand and the distribution of the shopping centers, thus it is necessary to develop a method to optimize the distribution of the shopping centers in China’s cities.

DECONSTRUCTING DESTINATION IMAGE IN THE INFORMATION AGE

The substantial increases in the volume of tourist information available as a consequence of rapid technological change, globalization, and the blurring boundaries of competition are the main reasons that both consumers and destinations face complexity. These forces combined have caused a process that is “reengineering” the tourism industry. Particularly destination image, influenced by the proliferation of communicated destination identities, as driven by the online revolution, holds many innovation promises in terms of destination marketing and positioning. As it is difficult for tourists to form a clear image of a destination without the actual experience, the multimedia interactive nature of the Web can add a whole new dimension to destination marketing. But how are those image attributes that have the largest impact on consumer perception and therefore destination choice identified and measured? Through empirical data this article shows that the present multiattribute destination image research is inadequate in predicting destination choice behavior. A subsequent discussion of the results asserts that the deconstruction of traditional destination image theory is unavoidable. In its place, it is concluded, emerges a new information technology-based destination image measurement paradigm.

Visiting Propensity Predicted by Destination Image

In destination market positioning, the destination image plays a pivotal role. Due to the interrelationship between destination choice behavior and image, there is an increased interest in the destination image as a predictor variable in a destination choice model. The research presents a binary logistic model to evaluate factors affecting the propensity of potential German travelers visiting the U.S. The overall impression, perceptive image, sociodemographic variables and previous visits are examined in a visiting propensity context. Empirical results of this study showed that the overall image is the most significant factor in influencing destination choice, along with the perceptive image based on destination attributes. The relative importance of the destination image was assessed as being higher than other factors.

RESEARCH NOTE: An Examination of Destination-Originated (Pull) Factors

Travelers from six countries/regions who were vacationing in one of the six vacation destinations of Mugla, Turkey, were interviewed in order to identify the destination-originated (pull) factors that are likely to influence travelers' destination choice behavior. Results indicated six destination-originated (pull) factors had significant impact on travelers' decision to choose Turkey as the vacation destination over other possible vacation destinations. These significant destination-originated (pull) factors are: the perception of the cost of accommodations, cost of others such as souvenirs, type of accommodations offered, quality of food, environmental concerns at the lodging facilities, and historical and cultural attractions. Five of the destination-originated (pull) factors had positive impact on travelers' decision to choose Turkey as a vacation destination while the cost of others such as souvenirs had a negative impact.

Simulation of Destination Choice under Huge Choice Sets: Application of Markov Chain Monte Carlo Algorithms

A destination choice model is developed, using a coordinates-based methodology, to resolve the problems arising from zone systems on which most models developed so far are based. To evaluate destination choice probabilities and simulate choice behavior efficiently with huge choices sets, the MCMC method is applied. The distribution of destination locations obtained by a simulation on a hypothetical uniform area is almost identical to the theoretical distribution, suggesting the validity of the MCMC method. From the result of a simulation run in Kyoto, it is confirmed that the MCMC method is a useful technique as a method of forecasting destination choice behavior with huge choice sets.

Maximum car ownership under constraints of road capacity and parking space

This paper presents a model for determining the maximum number of cars by zones in view of the capacity of the road network and the number of parking spaces available. In other words, the proposed model is to examine whether existing road network and parking supply is capable of accommodating future zonal car ownership growth (or the reserve capacity in each zone); i.e. the potential maximum zonal car ownership growth that generates the road traffic within the network capacity and parking space constraints. In the proposed model, the vehicular trip production and attraction are dependent on the car ownership, available parking spaces and the accessibility measures by traffic zones. The model is formulated as a bi-level programming problem. The lower-level problem is an equilibrium trip distribution/assignment problem, while the upper-level problem is to maximize the sum of zonal car ownership by considering travellers’ route and destination choice behaviour and satisfying the network capacity and parking space constraints. A sensitivity analysis based heuristic algorithm is developed to solve the proposed bi-level car ownership problem and is illustrated with a numerical example.

Modeling of Bicycle Route and Destination Choice Behavior for Bicycle Road Network Plan

A new modeling method that describes bicycle route or destination choice behavior is presented. Although there are numerous bicycle users in Japan, the urban transportation planning process often treats bicycles and pedestrians as a single mode. Therefore, a methodology by which to evaluate and analyze bicycle demand needs to be developed. A bicycle route choice model that describes the relationship between route choice behavior and facility characteristics (e.g., road width or sidewalk) has been proposed. This model can be applied to the planning of bicycle road networks. The data from a bicycle trip survey conducted in Japan are used to study the characteristics of the model. The model is applied to study access railway station choice (destination choice). The model can produce a better fit than can a conventional model.

Tourism information and pleasure motivation

This paper focuses on motivational and emotional aspects of destination choice behavior. In a marketing context, a conceptual model using push, pull, and hedonic factors is developed for research on evaluations of destination attributes. In this context tourists are pushed by their emotional needs and pulled by the emotional benefits. Consequently, emotional and experiential needs are relevant in pleasure-seeking and choice behavior. From an information processing point of view, it is suggested that mental imagery is an anticipating and motivating force that mediates emotional experiences, evaluations, and behavioral intentions. The conceptual model is relevant for managers who want to know the affective and motivational reaction of customers to promotional stimuli.

Analysis of Demand for Road-Based Transport Facilities: A Bi-Level Programming Approach

A bi-level programming model is presented for determining the number of parking spaces and road-capacity expansions that are required to satisfy road traffic and parking demand. The lower-level problem is an equilibrium trip-distribution/assignment problem, and the upper-level problem is to maximize the net user benefit (or consumer surplus) by considering travelers’ route and destination choice behavior and by satisfying the network capacity and attraction-end parking supply constraints. The use of consumer surplus in the objective function reflects an economic tradition that public investment in transport facilities (parking spaces and road capacities) should be operated in a way that maximizes the facilities’ social benefits. A sensitivity-analysis-based heuristic algorithm is developed to solve the proposed bi-level problem and is illustrated with numerical examples.

Predicting destination choice — A discussion of destination loyalty

Successfully predicting tourism destination choice by potential travellers would be an invaluable advantage to managers and marketers. This paper reviews the literature on brand loyalty, destination choice and repeat visitation behaviour. Based on this review it argues that previous destination choice over a long time period would provide the necessary information to segment (potential) tourists into loyalty segments which in turn will provide destination marketers with valuable information for more cost-effective target marketing. While this article does not test the predictive value of the loyalty typology, it suggests that there is a close linkage between previous destination purchase history and future purchase behaviour.

Traveler Destination Choice Behavior: Effects of Time of Day, Activity Duration, and Home Location

Multinomial logit destination choice models are developed and the following hypotheses are examined: ( a) time of day affects destination choice behavior, ( b) the duration of stay at the destination affects destination choice, and ( c) home location affects non-home-based destination choice. The statistical results offer strong evidence in support of the hypotheses.

Segmentation of the Nordic Winter Sun Seekers Market

This research, based on 617 residents of Ottawa, was carried out to segment the Canadian winter sun travellers market. Six segments were identified on the basis of sought product benefits. They were named Entertainment, Active Sun and Fun, Culture Patron, Value for the Money, Sun and Comfort and Achievers. The segments were described using demographic and psychographic data and their destination choice and media usage behavior were examined to provide insights into the managerial actions that tourism marketers may undertake to attract them to specific sun destinations.

Panel Attrition and the Correcting Method for its Biases

This paper aims to analyze the sample attrition problem peculiar to a panel survey, especially related to multi-wave attrition biases. The paper also intends to develop a correcting method for those attrition biases and empirically examines an applicability of this method to shopping destination choice behavior. First of all, attrition models are calibrated for several waves in Kofu shopper panels in order to identify the difference in decision structure between the first attrition and the following-step attritions. Secondly, the ordered logit model corresponding to multi-wave attrition process is formulated, and the weighting method for shopping destination choice behavior with those attrition biases is also developed. As a result, it is found from an empirical application that the proposed method is useful for correcting those biases.

Emissiveness and destination choice behavior of Shanghainese in their weekend recreation

Based on questionnaire survey and cross-tabulation analysis, the authors discussed relationships between emissiveness and socio-economic elements of Shanghainese in their weekend trips, including emissivenesses of different age group, income per month, occupations, education and family structure. Visiting rates of recreationists to destinations demonstrated different levels even being under a same emissiveness. In the second part of the paper, the authors described three different spatial scales of destination choice behavior of Shanghainese to tourist sites from which situated in urban area, to which located in suburb area and in neighboring provinces. The authors also observed the perceptive evaluation of Shanghainese to those sites they had visited or would visit in the future. Some proposals about sustainable urban tourism development were put forward at the end of this paper.