Soil texture prediction via reduced K-means Principal Component Multinomial Regression

Texture is one of the most important physical property of the soils for its influence on other fundamental properties. It is defined according to particle size distribution, that can be accurately measured in laboratory. However, these measurements are costly and very time consuming, therefore valid alternatives are necessary. In last years some statistical techniques have been used to predict textural classification using values of reflectance spectrometry as explicative variables. The estimation of the model parameters can be not too accurate, affecting prediction when there is multicollinearity among predictors. Another issue can be the great number of explicative variables usually necessary to explain the response. In order to improve the accuracy of the prediction in classification problems under multicollinearity and to reduce the dimension of the problem with continuous covariates, in this paper we introduce a new technique, based on classification and dimension reduction methods. We show how the new proposal can improve the accuracy of prediction, considering a problem concerning the textural classification of soils of Campania region.     

Market segmentation analysis for airport access mode choice modeling with mixed logit

Accessing airports can be considered as a crucial issue since passengers need not miss their flights. This issue makes the mode choice to access the airports important to study on and develop policies regarding it. Many studies show destination type as domestic or international affects the airport access mode choice, along with other factors. In this study, we investigate the effect of destination type of mode choice using mixed logit, using market segmentation approach. Market segmentation regarding destination type as domestic or international is a first in airport access mode choice modeling. Revealed-preference data was collected by face-to-face passenger surveys at Ataturk International Airport in Istanbul, Turkey, in 2015. We did market segmentation analysis for Multinomial Logit (MNL) and Mixed Logit (ML) models. When MNL and ML models were compared, it was observed that ML was superior to MNL. Further, results of market segmentation analysis revealed that using segmented models produced more accurate results than using the pooled model; both in MNL and ML. This finding was also supported by the value of time estimates; there were significant differences between domestic and international travel markets in terms of airport access mode choice. These results showed that different transportation policies may be introduced for domestic and international traveler segments, which also were explained.     

Transnational corporations’ localization strategies via retail attributes: Focus on Chinese market

We explored the localization strategy of the transnational corporations (TNCs) in China by employing retail store attributes within the fast-changing Chinese retail market to select stores. We applied the multinomial logit (MNL) model based on McFadden’s (1974) random utility theory to proceed with this study. A questionnaire survey was conducted in nine areas in China. Surveys targeted people who had used Tesco, Walmart, and RT-Mart. 950 questionnaires were distributed, and 909 valid samples were obtained. The analysis results indicated that RT-Mart and Walmart, top players in the Chinese distribution industry, showed higher customer satisfaction in all sectors than Tesco, and statistically, all variables were significant. Customers of RT-Mart and Walmart were more satisfied compared with Tesco's customers in all variables, such as product quality, price, location, convenience, atmosphere, and staff service. In comparison to RT-Mart, Walmart had lower prices, fewer branches and convenience facilities, and lesser brand awareness, but the model estimates indicated that customer satisfaction was high regarding product quality, atmosphere, and employee service. In this study, various behavior factors were reviewed in consideration of consumer selection of stores; this aspect is significant because we have added attributes pertaining to the brand in our study.     

A border effect in airport choice: Evidence from Western Europe

Some commentators suggest that air travelers are reluctant to use a foreign airport as a point of departure for their journey. Such reluctance has implications for marketing and policy measures, especially in border regions and in smaller countries, such as the Netherlands and Belgium. In this study, we tested this supposed barrier effect of national borders with empirical data.Our research is based on a subsample (n = 4083) of a large-scale survey among German, Dutch and Belgian adults. Participants were asked about their most recent flight, preferences regarding long-distance travel, and general travel behavior. The survey information about the most recent trip was linked to the Official Airline Guide with data from 18 airports in the Western European region. On average, however, only 10 airports offered a direct connection to the destination of the respondents’ most recent flight. A conditional logit model with varying choice sets allowed us to model only the relevant airports per respondent, while accounting for other known determinants in airport choice, such as travel time, airline competition, and number of available flights.The model results confirmed our expectations: people strongly prefer a departure airport situated in their own country. The model predictions suggest that without the border effect the share of people in our sample departing abroad would rise from 7.7% to 18.7%. Experience (with multiple airports as a point of departure) mitigates the barrier effect of the border. The performance of our model is good: the median probabilitie for the chosen alternative is 68%. Our research stresses the importance of the barrier effect of borders in airport choice: even when traveling across borders in the European sky, national borders remain important.     

A weighted logit freight mode-choice model

The paper describes the estimation of a weighted discrete choice model applicable for analysing choice of mode and crossing for freight in the Oresund region. The study finds that, by applying a weighted logit approach, it is possible to establish a suitable decoupling of agents and shipments. Moreover, by assessing preferences on the basis of a representative baseline OD matrix it is possible to better reflect the dependence between mode substitution effects and geography/infrastructure. The paper presents demand elasticities with respect to monetary cost and travel time as well as value-of-time estimates for five modes and thirteen commodity groups.     

MICROFINANCE PENETRATION AND ITS INFLUENCE ON CREDIT CHOICE IN INDONESIA: EVIDENCE FROM A HOUSEHOLD PANEL SURVEY

This paper studies empirical determinants of how heterogeneous households are matched to different types of loan products in a credit market in Indonesia. A unique situation arose when a microfinance institution launched operations in our survey area during the survey period, and we utilized its market entry for conducting mixed logit analysis of households’ credit choices. Time-varying choice sets help us identify parameters regarding preferences for various credit attributes. Our results show that the new availability of small-scale loans without collateral requirement greatly increases households’ probability of obtaining credit overall. Households in self-employed business prefer formal credit as a stable financing source but are impeded in receiving it when they locate in a rural area, probably because of large transaction costs. The poorest households, however, might not be able to exploit new credit opportunities as much as richer households, even if the scale of credit is very small.     

Nested logit model formation to analyze airport parking behavior based on stated preference survey studies

The rapid growth of private car ownership and utilization has resulted in significant parking-related congestion problems at large-scale international airports. Parking facilities located in the peripheral areas of airports could be more efficiently used to mitigate congestion and reduce delays due to dramatically increasing traffic demands and inferiorly designed parking lot configurations. In order to analyze the travelers' parking choice preferences for the off-site airport parking activities, a stated preference survey study was conducted around Terminal 3 at Beijing Capital International Airport. Two nested logit models were formulated to analyze the correlation between travelers' parking behavior and their travel characteristics. The research results indicate that travelers prefer to choose off-site parking facilities for long-term parking. A free and fast operation of connections should be provided in consideration of the long-distance layouts of parking facilities. A classification analysis of travelers with different preferences was conducted and the potential changes in travelers' parking choices to off-site parking lots were quantified. The research findings are helpful for traffic management agencies to develop practical guidelines for the establishment of new parking facilities with multiple access points at airports.     

Medical Insurance Effects on Household Durable Goods Consumption: Evidence from China

In this article, we employ the China Health and Nutrition Survey (CHNS) data to investigate the effect of medical insurance on household durable goods consumption, which is closely related to China’s future rapid economic growth. We apply a logit regression model and find that medical insurance significantly promotes household durable goods consumption. Moreover, urban and rural households have different consumption choices when they are covered by medical insurance. To be more specific, urban households with medical insurance augment their consumption of refrigerators, washing machines, and air conditioners; rural households with medical insurance increase their purchases of color TVs, refrigerators, washing machines, air conditioners, and computers.     

Consumer willingness to pay for traditional food products

Reflecting the growing interest from both consumers and policymakers, and building on recent developments in Willingness to Pay (WTP) methodologies, we evaluate consumer preferences for an archetypal traditional food product. Specifically we draw on stated preference data from a discrete choice experiment, considering the traditional Hungarian mangalitza salami. A WTP space specification of the generalized multinomial logit model is employed, which accounts for not only heterogeneity in preferences but also differences in the scale of the idiosyncratic error term. Results indicate that traditional food products can command a substantial premium, albeit contingent on effective quality certification, authentic product composition and effective choice of retail outlet. Promising consumer segments and policy implications are identified.