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Journal articles on the topic 'Integrated Choice and Latent Variable'

Author: Grafiati

Published: 6 September 2023

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1

Chen, Jian, and Shoujie Li. "Mode Choice Model for Public Transport with Categorized Latent Variables." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/7861945.

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Mode choice model for public transport, which integrates structural equation model (SEM) and discrete choice model (DCM) with categorized latent variables, was presented in this paper. Apart from identifying those important latent variables that affect mode choice for public transport, the objective of this study was also to develop an improved disaggregative model that better explains travel behavior of those decision-makers in choosing public transport. After extensive observations, selective latent variable sets which consist of latent variable components were chosen together with explicit variables in formulating the utility functions. Data collected in Chengdu city, China, were used to calibrate and validate the model. Results showed that the impact of fare on mode choice of public transport escalated in the SEM-DCM integrated model compared with the traditional logit model. The goodness of fit for the integrated model with latent variable sets is 0.201 higher than that of the traditional logit model, which proves that latent variables have an obvious impact on mode choice behavior, and the SEM-DCM integrated model has higher accuracy and stronger explanatory ability. The results are especially helpful for public transport operators to achieve higher mode share split by improving the service quality of public transport in terms of providing more convenience and better service environment for public transport users.

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Mahpour, Alireza, Amirreza Mamdoohi, Taha HosseinRashidi, Basil Schmid, and Kay W. Axhausen. "Shopping destination choice in Tehran: An integrated choice and latent variable approach." Transportation Research Part F: Traffic Psychology and Behaviour 58 (October 2018): 566–80. http://dx.doi.org/10.1016/j.trf.2018.06.045.

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3

Politis, Ioannis, Panagiotis Papaioannou, and Socrates Basbas. "Integrated Choice and Latent Variable Models for evaluating Flexible Transport Mode choice." Research in Transportation Business & Management 3 (August 2012): 24–38. http://dx.doi.org/10.1016/j.rtbm.2012.06.007.

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4

Soto, Jose J., Luis Márquez, and Luis F. Macea. "Accounting for attitudes on parking choice: An integrated choice and latent variable approach." Transportation Research Part A: Policy and Practice 111 (May 2018): 65–77. http://dx.doi.org/10.1016/j.tra.2018.03.003.

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Chen, Ching-Fu, Chiang Fu, and Pei-Ya Siao. "Exploring electric moped sharing preferences with integrated choice and latent variable approach." Transportation Research Part D: Transport and Environment 121 (August 2023): 103837. http://dx.doi.org/10.1016/j.trd.2023.103837.

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6

Sohn, Keemin. "An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model." Transportation Science 51, no. 3 (August 2017): 946–67. http://dx.doi.org/10.1287/trsc.2016.0696.

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Vij, Akshay, and Joan L. Walker. "How, when and why integrated choice and latent variable models are latently useful." Transportation Research Part B: Methodological 90 (August 2016): 192–217. http://dx.doi.org/10.1016/j.trb.2016.04.021.

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Mohiuddin, Hossain, Md Musfiqur Rahman Bhuiya, Shaila Jamal, and Zhi Chen. "Exploring the Choice of Bicycling and Walking in Rajshahi, Bangladesh: An Application of Integrated Choice and Latent Variable (ICLV) Models." Sustainability 14, no. 22 (November 9, 2022): 14784. http://dx.doi.org/10.3390/su142214784.

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Bangladesh has emphasized active transportation in its transportation policies and has encouraged its population, especially the youth and students, towards bicycling. However, there is a scarcity of studies that have examined the factors important to the choice of active transportation that can be referenced to support the initiative. To address this research gap, in this study, we explore the influence of sociodemographics and latent perceptions of a built environment on the choice to walk and bicycle among students and nonstudents in Rajshahi, Bangladesh. In Rajshahi, we conducted a household survey between July and August, 2017. We used a modeling framework that integrated choice and latent variable (ICLV) models to effectively incorporate the latent perception variables in the choice model, addressing measurement error and endogeneity bias. Our models show that students are influenced by perceptions of safety from crime, while nonstudents are influenced by their perceptions of the walkability of a built environment when choosing a bicycle for commuting trips. For recreational bicycle trips, students are more concerned about the perceptions of road safety, whereas nonstudents are concerned about safety from crime. We find that road safety perception significantly and positively influences walking behavior among nonstudents. Structural equation models of the latent perception variables show that females are more likely to provide lower perceptions of neighborhood walkability, road safety, and safety from crime. Regarding active transportation decisions, overall, we find there is a difference between student and nonstudent groups and also within these groups. The findings of this study can assist in developing a sustainable active transportation system by addressing the needs of different segments of the population. In this study, we also provide recommendations regarding promoting active transportation in Rajshahi.

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Chae, Dasol, Jaeyoung Jung, and Keemin Sohn. "Facilitating an expectation-maximization (EM) algorithm to solve an integrated choice and latent variable (ICLV) model with fully correlated latent variables." Journal of Choice Modelling 26 (March 2018): 64–79. http://dx.doi.org/10.1016/j.jocm.2017.08.001.

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10

Yeh, Ching-Hua, Monika Hartmann, Matthew Gorton, Barbara Tocco, Virginie Amilien, and Kamilla Knutsen Steinnes. "Looking behind the choice of organic: A cross-country analysis applying Integrated Choice and Latent Variable Models." Appetite 167 (December 2021): 105591. http://dx.doi.org/10.1016/j.appet.2021.105591.

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Sok, Jaap, Ivo A. van der Lans, Henk Hogeveen, Armin R. W. Elbers, and Alfons G. J. M. Oude Lansink. "Farmers’ Preferences For Bluetongue Vaccination Scheme Attributes: An Integrated Choice and Latent Variable Approach." Journal of Agricultural Economics 69, no. 2 (November 21, 2017): 537–60. http://dx.doi.org/10.1111/1477-9552.12249.

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12

Jiao, Pengpeng, Meiqi Liu, and Jin Guo. "Integrated Model of Joint Residence-Workplace Location Choice and Commute Behavior Using Latent Class and Mixed Logit Methods." Discrete Dynamics in Nature and Society 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/251781.

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With the rapid development of urbanization and motorization, urban commute trips are becoming increasingly serious due to the unbalanced distribution of residence and workplace land-use types in most Chinese cities. To explore the inherent interrelations among residence location, workplace, and commute trip, an integrated model framework of joint residence-workplace location choice and commute behavior is put forward based on the personal trip survey data of Beijing in 2005. First, to extract households’ different choice characteristics, this paper presents a latent class model, clusters all households into several groups, and analyzes the conditional probability of each group. Second, the paper integrates the residence location and workplace together as the joint choice alternative, employs the socioeconomic factors, individual attributes, household attributes, and trip characteristics as explanatory variables, and formulates the joint residence-workplace location choice model using mixed logit method. Estimations of the latent class model show that four latent groups fit the data best. Further results of the joint residence-workplace location choice model indicate that there exist significantly different choice characteristics in each latent group. Generally, the integrated model framework outperforms traditional location choice methods.

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Kim, Junghwan, and Bumsoo Lee. "Campus commute mode choice in a college town: An application of the integrated choice and latent variable (ICLV) model." Travel Behaviour and Society 30 (January 2023): 249–61. http://dx.doi.org/10.1016/j.tbs.2022.10.002.

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Kamargianni, Maria, Subodh Dubey, Amalia Polydoropoulou, and Chandra Bhat. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model." Transportation Research Part A: Policy and Practice 78 (August 2015): 473–88. http://dx.doi.org/10.1016/j.tra.2015.06.011.

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Jing, Yun, Wanglin Xu, Siye Guo, and Yingjin Zhang. "Analysis of Choice Behaviors of Railway Shippers for Freight Services Based on a Fuzzy Integrated Choice and Latent Variable Model." IEEE Access 8 (2020): 64399–410. http://dx.doi.org/10.1109/access.2020.2984626.

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Cheng, Long, Xuewu Chen, William H. K. Lam, Shuo Yang, and Pengfei Wang. "Improving Travel Quality of Low-Income Commuters in China." Transportation Research Record: Journal of the Transportation Research Board 2605, no. 1 (January 2017): 99–108. http://dx.doi.org/10.3141/2605-10.

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Low-income residents can depend on fewer travel options and have restricted mobility. This paper analyzes low-income commuters’ mode choice behavior by using data from an activity-based travel survey in Fushun, China. An integrated choice and latent variable model is presented. The model uses the following latent attitudes: comfort, convenience, reliability, flexibility, safety, and environmental preferences. The inclusion of attitudes captures unobserved heterogeneity of the choice process with a better understanding of travel demands. Postestimation of the integrated model is applied to assess the responsiveness of preferences for various transportation modes to changes in policy-relevant variables. This assessment is done by calculating the elasticity and marginal effects of choice probabilities for the relevant attributes of travel preferences. The analysis indicates that individuals with high comfort preferences care more about walking environment, and they need solutions to enhance their walking experience. However, travelers preferring reliability are more likely to travel by public transit, and measures to inform commuters of real-time bus operation information were proposed. Commuters who emphasize environmental preference are more apt to cycle; therefore, probike strategies are recommended. Results of the analysis indicate that different actions should be taken to serve different preferences. The findings should be useful information for policy makers and transportation planners wanting to improve low-income commuters’ travel quality.

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Li, Jun, Shunping Jia, Sijia Zhang, and Yuqiong Wang. "Modeling and Analysis of Ticketing Channel Choice for Intercity Bus Passengers: A Case Study in Beijing, China." Journal of Advanced Transportation 2019 (August 8, 2019): 1–14. http://dx.doi.org/10.1155/2019/8198346.

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Buses represent the main mode for intercity passenger transportation in China. In recent years, a multichannel ticketing strategy has been widely employed in the bus passenger transportation industry. However, the mechanisms and key drivers of the channels through which bus passengers purchase tickets are underexplored. Thus, the aim of this study is to empirically apply an integrated choice and latent variable (ICLV) approach to analyze ticketing channel choice behavior and the heterogeneous preferences of bus passengers. The variables incorporated in the model include the socioeconomic characteristics of passengers, trip attributes, and latent attitudes with 12 ordinal indicators. Based on the data of 1800 participants collected from the city of Beijing, China, this study develops a ticketing channel choice ICLV model merging a discrete choice model with a structural equation model. The key factors that affect the channel preference are further discussed through a comparison with a conventional multinomial logit (MNL) model. The results reveal that the three attitudinal variables have a significant influence on ticketing channel choice. Furthermore, this study indicates that perceptual differences exist due to various socioeconomic and trip characteristics. Personal privacy is a major obstacle that prevents passengers from choosing online channels, especially for older passengers and those with lower education.

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Bergantino, Angela S., Mauro Capurso, Thijs Dekker, and Stephane Hess. "Allowing for Heterogeneity in the Consideration of Airport Access Modes: The Case of Bari Airport." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 8 (February 7, 2019): 50–61. http://dx.doi.org/10.1177/0361198118825126.

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Mode choice models traditionally assume that all objectively available alternatives are considered. This might not always be a reasonable assumption, even when the number of alternatives is limited. Consideration of alternatives, like many other aspects of the decision-making process, cannot be observed by the analyst, and can only be imperfectly measured. As part of a stated choice survey aimed at unveiling air passengers’ preferences for access modes to Bari International Airport in Italy, we collected a wide set of indicators that either directly or indirectly measure respondents’ consideration of the public transport alternatives. In our access mode choice model, consideration of public transport services was treated as a latent variable, and entered the utility function for this mode through a “discounting” factor. The proposed integrated choice and latent variable approach allows the analyst not only to overcome potential endogeneity and measurement error issues associated with the indicators, but also makes the model suitable for forecasting. As a result of accounting for consideration effects, we observed an improvement in fit that also held in a validation sample; moreover, the effects of policy changes aimed at improving the modal share of public transport were considerably reduced.

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19

Enam, Annesha, Karthik C. Konduri, Abdul R. Pinjari, and Naveen Eluru. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choices." Journal of Choice Modelling 26 (March 2018): 80–100. http://dx.doi.org/10.1016/j.jocm.2017.07.003.

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20

Otter, Thomas, Greg M. Allenby, and Trish Van Zandt. "An Integrated Model of Discrete Choice and Response Time." Journal of Marketing Research 45, no. 5 (October 2008): 593–607. http://dx.doi.org/10.1509/jmkr.45.5.593.

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Computer and Web-based interviewing tools have made response times ubiquitous in marketing research. Practitioners use these data as an indicator of data quality, and academics use them as an indicator of latent processes related to memory, attributes, and decision making. The authors investigate a Poisson race model with choice and response times as dependent variables. The model facilitates inference about respondents' preferences for choice alternatives, their diligence in providing responses, and the accessibility of attitudes and the speed of thinking. Thus, the model distinguishes between respondents who are quick to think and those who are quick to react but do so without much thought. Empirically, the authors find support for the endogenous nature of response times and demonstrate that models that treat response times as exogenous variables may result in misleading inferences.

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21

Sarman, Igor, Riccardo Curtale, and Homa Hajibaba. "Drivers of Travel Insurance Purchase." Journal of Travel Research 59, no. 3 (May 13, 2019): 545–58. http://dx.doi.org/10.1177/0047287519843187.

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With the increasing number of critical events happening at tourism destinations, travelers engage in different strategies to reduce travel risks, and travel insurance purchase is one of these. However, little is known about travel insurance purchase behavior despite its relevance in the modern context of travelers’ heightened alert induced by potential or actual risks of critical events. The present study applies an Integrated Choice and Latent Variable (ICLV) model to investigate individual insurance purchase decisions in a leisure travel context. A mix of sociodemographic covariates, travel-related behaviors, and psychological variables is adopted in the model. Personality traits are crucial for the purchase of products that are strongly related to the psychological dimension of individuals’ choice behavior. The results show that personality traits of conscientiousness and neuroticism contribute to the determination of travel insurance purchase behavior.

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22

Fu, Xuemei, and Zhicai Juan. "Estimation of multinomial probit-kernel integrated choice and latent variable model: comparison on one sequential and two simultaneous approaches." Transportation 44, no. 1 (June 11, 2015): 91–116. http://dx.doi.org/10.1007/s11116-015-9626-x.

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23

Papadimitriou, Eleonora, Sylvain Lassarre, George Yannis, and Dimitrios I. Tselentis. "Road, Traffic, and Human Factors of Pedestrian Crossing Behavior: Integrated Choice and Latent Variables Models." Transportation Research Record: Journal of the Transportation Research Board 2586, no. 1 (January 2016): 28–38. http://dx.doi.org/10.3141/2586-04.

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24

Sandorf, Erlend Dancke, Lars Persson, and Thomas Broberg. "Using an integrated choice and latent variable model to understand the impact of “professional” respondents in a stated preference survey." Resource and Energy Economics 61 (August 2020): 101178. http://dx.doi.org/10.1016/j.reseneeco.2020.101178.

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Abate, Tenaw G., Tobias Börger, Margrethe Aanesen, Jannike Falk-Andersson, Kayleigh J. Wyles, and Nicola Beaumont. "Valuation of marine plastic pollution in the European Arctic: Applying an integrated choice and latent variable model to contingent valuation." Ecological Economics 169 (March 2020): 106521. http://dx.doi.org/10.1016/j.ecolecon.2019.106521.

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Liu, Yicong, Patrick Loa, Kaili Wang, and Khandker Nurul Habib. "Theory-driven or data-driven? Modelling ride-sourcing mode choices using integrated choice and latent variable model and multi-task learning deep neural networks." Journal of Choice Modelling 48 (September 2023): 100431. http://dx.doi.org/10.1016/j.jocm.2023.100431.

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Ma, Jie, Xin Ye, and Kun Huang. "Development of Integrated Choice and Latent Variable (ICLV) Models Using Matrix-Based Analytic Approximation and Automatic Differentiation Methods on TensorFlow Platform." Journal of Advanced Transportation 2022 (August 2, 2022): 1–19. http://dx.doi.org/10.1155/2022/6556282.

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This study further explores the multinomial probit-based integrated choice and latent variable (ICLV) models. The LDLT matrix-based analytic approximation methods, including Mendell and Elston (ME) method, bivariate ME (BME) method, and two-variate bivariate screening (TVBS) method, were adapted to calculate the multivariate cumulative normal distribution (MVNCD) function in the ICLV model because of the better performances in accuracy and computational time. Integrated with the composite marginal likelihood (CML) estimation approach, the ICLV model based on high-dimensional integration can be estimated accurately within a reasonable time. In this study, some three-alternative and four-alternative ICLV models are simulated to examine their abilities to recover model parameters. It is found that the parameter estimates and standard error estimates are acceptable for both models and the computational time is expected to decrease using tensor data structures on the TensorFlow platform. For the four-alternative ICLV models, the TVBS method has the highest level of accuracy. The BME method is also a good alternative to TVBS if computational time is of great concern. The application of the automatic differentiation (AD) technique in the model can free researchers from coding analytical gradients of log-likelihood functions and thereby greatly reduce the workload of researchers.

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Jiang, Rui, Zhen Li, Yuhang Jia, Siyu Li, and Shengquan Chen. "SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains." Cells 12, no. 4 (February 13, 2023): 604. http://dx.doi.org/10.3390/cells12040604.

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Recent advances in spatial transcriptomics have revolutionized the understanding of tissue organization. The identification of spatially variable genes (SVGs) is an essential step for downstream spatial domain characterization. Although several methods have been proposed for identifying SVGs, inadequate ability to decipher spatial domains, poor efficiency, and insufficient interoperability with existing standard analysis workflows still impede the applications of these methods. Here we propose SINFONIA, a scalable method for identifying spatially variable genes via ensemble strategies. Implemented in Python, SINFONIA can be seamlessly integrated into existing analysis workflows. Using 15 spatial transcriptomic datasets generated with different protocols and with different sizes, dimensions and qualities, we show the advantage of SINFONIA over three baseline methods and two variants via systematic evaluation of spatial clustering, domain resolution, latent representation, spatial visualization, and computational efficiency with 21 quantitative metrics. Additionally, SINFONIA is robust relative to the choice of the number of SVGs. We anticipate SINFONIA will facilitate the analysis of spatial transcriptomics.

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Potoglou, Dimitris, Juan-Francisco Palacios, and Claudio Feijóo. "An integrated latent variable and choice model to explore the role of privacy concern on stated behavioural intentions in e-commerce." Journal of Choice Modelling 17 (December 2015): 10–27. http://dx.doi.org/10.1016/j.jocm.2015.12.002.

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30

Mao, Biqi, Changlin Ao, Yang Cheng, Nan Jiang, and Lishan Xu. "Exploring the role of public risk perceptions on preferences for air quality improvement policies: An integrated choice and latent variable approach." Journal of Cleaner Production 269 (October 2020): 122379. http://dx.doi.org/10.1016/j.jclepro.2020.122379.

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31

Alemu, Mohammed H., and Søren B. Olsen. "Linking Consumers’ Food Choice Motives to their Preferences for Insect-based Food Products: An Application of Integrated Choice and Latent Variable Model in an African Context." Journal of Agricultural Economics 70, no. 1 (July 12, 2018): 241–58. http://dx.doi.org/10.1111/1477-9552.12285.

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Yeh, Ching-Hua, and Monika Hartmann. "To Purchase or Not to Purchase? Drivers of Consumers’ Preferences for Animal Welfare in Their Meat Choice." Sustainability 13, no. 16 (August 13, 2021): 9100. http://dx.doi.org/10.3390/su13169100.

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This study investigates the relevance of psychological constructs in determining consumer intention to buy and Willingness-To-Pay (WTP) for a processed meat product, cured ham, differentiated by the attributes of animal welfare, ham variety, and price. Data obtained from an online survey conducted in Germany was used to estimate an integrated choice and latent variable (ICLV) model, which is based on an extension of the Theory of Planned Behavior (TPB) framework. There are two consumer segments that are identified: one that is highly price sensitive in its product choice and one that gives roughly equal weight to the animal welfare, ham variety, and price attributes. The ICLV model shows consistency across the two groups regarding the importance of psychological constructs—moral norms, attitude, and perceived behavioral control—in explaining respondent intentions to buy cured ham and their stated product choice. Subjective norms, however, are only a significant determinant of consumer intention to buy cured ham for the price sensitive consumer group.

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Ding, Chuan, Chao Liu, Yaoyu Lin, and Yaowu Wang. "The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis." PROMET - Traffic&Transportation 26, no. 2 (April 26, 2014): 109–19. http://dx.doi.org/10.7307/ptt.v26i2.1332.

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Reducing car trips and promoting green commuting modes are generally considered important solutions to reduce the increase of energy consumption and transportation CO2 emissions. One potential solution for alleviating transportation CO2 emissions has been to identify a role for the employer through green commuter programs. This paper offers an approach to assess the effects of employer attitudes towards green commuting plans on commuter mode choice and the intermediary role car ownership plays in the mode choice decision process. A mixed method which extends the traditional discrete choice model by incorporating latent variables and mediating variables with a structure equation model was used to better understand the commuter mode choice behaviour. The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process. The results found in this paper provide helpful information for transportation and planning policymakers to test the transportation and planning policies effects and encourage green commuting reducing transportation CO2 emissions.

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Zudhy Irawan, Muhammad, Prawira Fajarindra Belgiawan, and Tri Basuki Joewono. "Investigating the effects of individual attitudes and social norms on students’ intention to use motorcycles – An integrated choice and latent variable model." Travel Behaviour and Society 28 (July 2022): 50–58. http://dx.doi.org/10.1016/j.tbs.2022.02.009.

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Soto, Jose, Mauricio Orozco-Fontalvo, and Sergio A. Useche. "Public transportation and fear of crime at BRT Systems: Approaching to the case of Barranquilla (Colombia) through integrated choice and latent variable models." Transportation Research Part A: Policy and Practice 155 (January 2022): 142–60. http://dx.doi.org/10.1016/j.tra.2021.11.001.

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36

Shah, Bharvi A., L. B. Zala, and Nipa A. Desai. "An integrated estimation approach to incorporate latent variables through SEM into discrete mode choice models to analyze mode choice attitude of a rider." Transportation Research Interdisciplinary Perspectives 19 (May 2023): 100819. http://dx.doi.org/10.1016/j.trip.2023.100819.

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37

Chao, Zeng, Cui Zihao, and Qiao Hao. "Time-Domain Characteristics of Residential Parking and SEM-BL Integration Model of Parking Method Choice Behaviour." Mathematical Problems in Engineering 2022 (July 5, 2022): 1–15. http://dx.doi.org/10.1155/2022/5164257.

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Correct understanding of the residential parking characteristics and parking behavioral regularities is important to the planning of parking facilities, the selection of parking equipment, and the formulation of parking management measures in residential areas. There are few in-depth reports on the time domain characteristics of the residential parking and the parking choice behavior of developers and drivers. Besides, the influence of developers’ potential demands and drivers’ mental latent variables on the results of parking choice has been ignored. To address the gap, in this paper, we propose the concept of latent variables for parking choice based on the analysis of the time domain characteristics of residential parking in different cities and areas. We construct the SEM-BL integrated model for developers and drivers that considers the combined effect of both manifest and latent variables for the actual residential situation and analyze the factors influencing the choice of stereoscopic parking facilities from the perspective of developers and drivers in residential areas. The results show that the type of residential area, floor space, and plot ratio have a critical impact on parking choice. Residential drivers are most concerned about factors such as walking distance after parking, access convenience, pick-up time, pedestrian access, and environment, while developers choose a stereoscopic parking garage with more concern for economy, ignoring the consideration of drivers for walking distance after parking and convenience of accessing the car. Therefore, the mismatch between the needs of both sides is one of the important factors that make it difficult to solve the problem of parking in residential areas. Based on these results, we put forward a proposal for residential parking planning and equipment selection that takes into account the common needs of both developers and drivers.

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Polydoropoulou, Amalia, Dinesh A. Gopinath, and Moshe Ben-Akiva. "Willingness To Pay for Advanced Traveler Information Systems: SmarTraveler Case Study." Transportation Research Record: Journal of the Transportation Research Board 1588, no. 1 (January 1997): 1–9. http://dx.doi.org/10.3141/1588-01.

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The issue of travelers' adoption of an advanced traveler information system (ATIS) and willingness to pay for such information services is addressed. A case study is presented of SmarTraveler, an ATIS that provides, via telephone, real-time location-specific traffic and transit information in the greater Boston area. The model is an integrated system of discrete choice and latent variable models. It predicts travelers' frequency of use and subscription under varying pricing scenarios. Two models are presented: one for current SmarTraveler users, and one for nonusers. The SmarTraveler usage rate is modeled as a function of payment method and pricing, travelers' travel and socioeconomic characteristics, and their attitudes and perceptions toward ATIS. The data used in model estimation included willingness-to-pay scenarios involving two methods of payment: a flat monthly fee, and a charge per call. It was found that for nonusers, the higher the expected benefit from an ATIS, the higher the willingness to pay. This expected benefit is a latent variable indicated via the importance placed by individuals on ATIS attributes such as reliability, relevance, and coverage. For users, the utility of SmarTraveler is affected strongly by the users' level of satisfaction with the service. A modeling framework is developed that captures response biases and presents figures on willingness to pay for an innovative ATIS actually implemented in the market.

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Rahimi, Alireza, Ghazaleh Azimi, and Xia Jin. "What Drives Commuters to Pay for Autonomous Vehicles?" Transportation Research Record: Journal of the Transportation Research Board 2676, no. 4 (December 4, 2021): 267–80. http://dx.doi.org/10.1177/03611981211058095.

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Although commuters have been identified as potential early adopters of autonomous vehicles (AVs) that can boost the adoption rate of this technology, there is a lack of knowledge on their willingness to pay (WTP) for this technology and the attitude that influences this decision. Using data from a consumer survey conducted in the United States, this study presents a comprehensive analysis of the decision to pay for AVs among commuters. An integrated choice and latent variable (ICLV) model was applied in this study, considering its robust performance in modeling choice behavior for integrating users’ attitudes. The results showed that commuters with a favorable view toward multitasking tended to put a higher value on driverless cars. On the other hand, although a favorable view toward technology motivated commuters to pay more for AVs, data privacy and trust issues with the technology could outweigh this factor and discourage commuters from adopting and paying for AVs. This study also provides in-depth insights and comprehensive views on the impacts of commuters’ socioeconomic and demographic attributes on the decision to pay for AVs. Notably, although age and educational attainment did not directly affect WTP behavior, they played important roles in this decision, with significant effects mediated through latent attitudes. These in-depth analyses provide useful insights that can help develop customized marketing strategies for different market segments according to their specific and unique preferences and concerns.

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Friedmann, Enav, and Oded Lowengart. "The context of choice as boundary condition for gender differences in brand choice considerations." European Journal of Marketing 52, no. 5/6 (May 14, 2018): 1280–304. http://dx.doi.org/10.1108/ejm-08-2017-0524.

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Purpose Marketers often assume that functional, hedonic and socially conspicuous utilities in choosing a brand differ for men and women, thus different marketing strategies are required for each gender. To date, most of the research studies have used self-reported measures when shopping in general or in regard to a single product. The purpose of this research is to examine this question using two different contexts of brand choice: single choice evaluation (SCE) and brand selection context (BSC). This assessment will clarify whether male and female utilities when choosing a brand are indeed inherent and consistent. Design/methodology/approach Data were collected using surveys in three studies (N = 923). Conjoint analysis and ICLV (integrated choice and latent variables) models were examined. Findings BSC analysis that more closely mimics real-life contexts revealed that the consideration of these utilities is generally similar for men and women, while the SCE analysis showed significant gender differences. Practical implications In the context of choosing between brands, stereotypical gender targeting may be ineffective and might not be the best allocation of resources for marketers. Social implications Gender stereotypes in advertising seem to reconstruct differences that are not significant in a realistic brand selection context. Originality/value The context of choice was found to be a condition boundary for gender differences in brand choice considerations. Gender differences are not evolutionary or inherent.

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Tsirimpa, Athena, and Amalia Polydoropoulou. "The Impact of Traffic Information Acquisition on the Traffic Conditions of the Athens Greater Area." International Journal of Operations Research and Information Systems 5, no. 2 (April 2014): 1–20. http://dx.doi.org/10.4018/ijoris.2014040101.

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The main objective of this article is to gain fundamental understanding on the effect of real time information acquisition, on the traffic conditions of the Athens greater area. Activity scheduling is a dynamic process, where individuals often need to modify their schedule, as a result of new insights. Research so far hasn't analyzed the effect of traffic information acquisition, in activity scheduling, although several studies have been conducted to capture the factors that influence the rescheduling of activities. An integrated latent variable model has been estimated, that predicts the probability of rescheduling activities as a function of flexibility, mode choice constraints and travel information. The analysis of the results indicates that one of the biggest impacts of traffic information acquisition is reflected in the rescheduling of activities. Therefore, traffic information not only can significantly improve the travel experience of individuals but may directly affect the performance of the transportation system.

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Kornilova, T. V. "Latent Profiles of Personality and Decision Making Regulation Styles." Консультативная психология и психотерапия 30, no. 2 (2022): 126–45. http://dx.doi.org/10.17759/cpp.2022300208.

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Decision making (DM) generally assumes that the person is performing a choice between a multitude of alternatives under uncertainty and possible risk. According to the concept of dynamic regulative systems (Kornilova, 2016), preferred or most relied on DM strategies are linked in an integrative way with a variety of personality traits that can be at the top of the hierarchy. These include risk readiness, rationality, and Dark Triad traits as reflective of a generally unstable personality core. Decision-Making Tendency Inventory (DMTI; Misuraca et al., 2015) defined DM characteristics via maximization, satisficing and minimization. However, the relationships between DM characteristics captured by DMTI and the listed personality traits have not been explored before. The goal of the current study was establishing latent personality profiles in a person-centered approach that integrates DM “tendencies” and the listed personality traits by identifying relatively homogenous subgroups of individuals with similar profiles. Methods. 625 individuals in the age from 17 to 39 years (М = 20,17, SD = 3,02; 84% females) participated in the study. We used DMTI, Dirty Dozen, and LFR questionnaires to measure DM tendencies, Dark Triad traits, and risk readiness/rationality, respectively. Latent profile analysis was performed in VarSelLCM for R. Results. The results indicated the presence of three latent profiles in the data after adjustments for age and sex. Risk readiness and Dark Triad traits were positively related with maximizing and satisficing, forming one latent class. In another class lower rationality, on the other hand, was linked with minimization. In the third class higher rationality accompanied lower Dark Triad traits. Conclusions. The results provide evidence in favor of the general hypothesis that latent profiles of personality traits are associated with distinct preferences for specific DM tendencies. Higher levels of maximizing, satisficing, and minimizing were not related to subclinical psychopathy or Machiavellianism. Higher narcissism and risk readiness, generally unrelated, are nonetheless characteristic of the latent class that prefers maximizing and satisficing. Preference for minimization of effort during DM was associated with lower rationality. Latent class or latent profile analysis is a powerful technique that sheds new light on the relationships between personality and DM, beyond the contributions of variable-centered approaches such as correlational analysis.

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Urach, S., CMW Gaasterland, M. Posch, B. Jilma, K. Roes, G. Rosenkranz, JH Van der Lee, and R. Ristl. "Statistical analysis of Goal Attainment Scaling endpoints in randomised trials." Statistical Methods in Medical Research 28, no. 6 (June 19, 2018): 1893–910. http://dx.doi.org/10.1177/0962280218777896.

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Goal Attainment Scaling is an assessment instrument to evaluate interventions on the basis of individual, patient-specific goals. The attainment of these goals is mapped in a pre-specified way to attainment levels on an ordinal scale, which is common to all goals. This approach is patient-centred and allows one to integrate the outcomes of patients with very heterogeneous symptoms. The latter is of particular importance in clinical trials in rare diseases because it enables larger sample sizes by including a broader patient population. In this paper, we focus on the statistical analysis of Goal Attainment Scaling outcomes for the comparison of two treatments in randomised clinical trials. Building on a general statistical model, we investigate the properties of different hypothesis testing approaches. Additionally, we propose a latent variable approach to generate Goal Attainment Scaling data in a simulation study, to assess the impact of model parameters such as the number of goals per patient and their correlation, the choice of discretisation thresholds and the type of design (parallel group or cross-over). Based on our findings, we give recommendations for the design of clinical trials with a Goal Attainment Scaling endpoint. Furthermore, we discuss an application of Goal Attainment Scaling in a clinical trial in mastocytosis.

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Bourassa, J. Eli, Rafael N. Alexander, Michael Vasmer, Ashlesha Patil, Ilan Tzitrin, Takaya Matsuura, Daiqin Su, et al. "Blueprint for a Scalable Photonic Fault-Tolerant Quantum Computer." Quantum 5 (February 4, 2021): 392. http://dx.doi.org/10.22331/q-2021-02-04-392.

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Photonics is the platform of choice to build a modular, easy-to-network quantum computer operating at room temperature. However, no concrete architecture has been presented so far that exploits both the advantages of qubits encoded into states of light and the modern tools for their generation. Here we propose such a design for a scalable fault-tolerant photonic quantum computer informed by the latest developments in theory and technology. Central to our architecture is the generation and manipulation of three-dimensional resource states comprising both bosonic qubits and squeezed vacuum states. The proposal exploits state-of-the-art procedures for the non-deterministic generation of bosonic qubits combined with the strengths of continuous-variable quantum computation, namely the implementation of Clifford gates using easy-to-generate squeezed states. Moreover, the architecture is based on two-dimensional integrated photonic chips used to produce a qubit cluster state in one temporal and two spatial dimensions. By reducing the experimental challenges as compared to existing architectures and by enabling room-temperature quantum computation, our design opens the door to scalable fabrication and operation, which may allow photonics to leap-frog other platforms on the path to a quantum computer with millions of qubits.

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Danthurebandara, Vishva Manohara, Martina Vandebroek, and Jie Yu. "Integrated mixed logit and latent variable models." Marketing Letters 24, no. 3 (October 31, 2012): 245–59. http://dx.doi.org/10.1007/s11002-012-9213-2.

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Zhou, Jing, Wei Lan, and Yingkai Tang. "The value of institutional shareholders." Management Decision 54, no. 1 (February 8, 2016): 44–65. http://dx.doi.org/10.1108/md-10-2014-0615.

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Purpose – By integrating agency theory with the institution-based view, the purpose of this paper is to examine whether-and if so, how-the likelihood of completion of cross-border acquisitions (CBAs) is influenced by institutional shareholders, in interaction with institutional quality and constraints both at the country and firm levels. Design/methodology/approach – After controlling for endogeneity by the latent instrumental variable (LIV) approach, the authors test the hypotheses using a sample of CBAs undertaken by Chinese listed firms during the period 2002-2012. Findings – The authors find that as institutional shareholders tend to enhance the quality of corporate governance, an overseas acquisition attempt undertaken by acquiring firm with greater institutional ownership is more likely to be completed. This relation is more prominent when the acquisition is exposed to inferior institutional context, such as when the target firm is domiciled in countries with weaker institutional quality, the acquiring firm is state-controlled, or the target is publicly traded in stock markets. Research limitations/implications – An additional focus on the share-price reaction to the announcement or long-term alliance performance of such CBAs may reveal the relative importance of institutional shareholders in CBAs. The potential varying effects between domestic and foreign institutional investors deserve to be tested. Other factors, for instance antitrust laws, could be further studied. Practical implications – The results will better inform and enhance governance and internationalization strategies of Chinese firms that are expected to undertake CBAs activities in areas such as the cooperation with institutional shareholders, the choice of target domiciled location, the reform of ownership structure, and the selection of target’s types in host country. In addition, given a broadly similar pattern of legal evolution between China and many other emerging countries since the 1990s (Peng and Heath, 1996), China’s experience may also provide valuable lessons and insights for firms from other emerging economies when undertaking CBAs activities in their internationalization strategies. Originality/value – This study develops a theoretical link of firm-specific characteristics and country-level factors into an integrated analytical framework by applying agency theory in interaction with institution theory into literature on CBAs. This theoretical framework varies from most of extant studies often using a single theory into their analysis and would thus provide a new analytical train of thought for future studies.

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Yazdanpanah, Mahdi, and Mansour Hadji Hosseinlou. "The Impact of Perception toward the Built Environment in Airport Access Mode Choice Using Hybrid Choice Modeling." Journal of Advanced Transportation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/8268701.

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Built environment (BE), as an objective variable, plays a substantial role in urban residents’ behavior. However, the perception toward a BE, as a subjective variable, varies among people. To identify the role of perception toward BE, we used a stated preference (SP) survey conducted in January–February 2015 at the Imam Khomeini International Airport (IKIA), Tehran, Iran. The data was drawn from 641 individuals; 359 of them were residents of Tehran. For the estimation of the model, a hybrid discrete choice model was used to capture the latent variable, in addition to mode attributes and trip conditions, with 1795 SP observations. Psychometric questions concerned the perception of ease in access to main streets or highways and good traffic conditions within their residential areas. The results showed that the latent variable (positive perception toward built environment or PBE) had a significant positive effect on people’s willingness to park at the airport. Moreover, the gender, age, marital status, level of education, experience living in a foreign country, and income level also influenced the formation of perception toward the BE and airport transportation mode choice.

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Shabbir, Tayyeb. "Multinomial Logit Model of Occupational Choice: A Latent Variable Approach." Pakistan Development Review 32, no. 4II (December 1, 1993): 687–98. http://dx.doi.org/10.30541/v32i4iipp.687-698.

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Economists and other social scientists have had a long-standing interest in studying the different aspects of an individual's occupational choice. An important issue in this regard is an econometric analysis of the determinants of occupational choice. A rather well-known example of such a work is Schmidt and Strauss (1975) which uses a maximum likelihood procedure to estimate a multinomial logit model (MNL) where occupational choice is determined by an individual's education, experience, race and sex. Regarding the above genre of models (as, in fact, in the parallel and closely related literature on earnings functions), one is often interested in ascertaining the unbiased marginal effect of education on the dependent variable. Not only these estimates allow tests of the human capital theory against alternative hypotheses, they also have important public policy implications particularly for the developing countries which are typically contemplating expansion of their educational sectors. However, these estimates may become biased in the event that a relevant regressor is left out of the specification. Particularly difficult problems arise when such an excluded variable is a latent (or unobserved) one.

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Lewbel, Arthur. "Semiparametric Estimation of Location and Other Discrete Choice Moments." Econometric Theory 13, no. 1 (February 1997): 32–51. http://dx.doi.org/10.1017/s0266466600005636.

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Latent variable discrete choice model estimation and interpretation depend on the density function of the latent variable's unobserved random component. This paper provides a simple semiparametric estimator of the moments of this density. The results can be used as starting values for parametric estimators, to estimate the appropriate location and scaling for semiparametric estimators, for specification testing including tests of latent error skewness and kurtosis, and to estimate coefficients of discrete explanatory variables in the model.

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Madakyaru, Muddu, Mohamed N. Nounou, and Hazem N. Nounou. "Integrated Multiscale Latent Variable Regression and Application to Distillation Columns." Modelling and Simulation in Engineering 2013 (2013): 1–17. http://dx.doi.org/10.1155/2013/730456.

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Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions), which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR) techniques, such as principal component regression (PCR), partial least squares (PLS), and regularized canonical correlation analysis (RCCA). Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR) modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

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