scholarly journals Research on the Choice Behavior of Taxis and Express Services Based on the SEM-Logit Model

2019 ◽  
Vol 11 (10) ◽  
pp. 2974 ◽  
Author(s):  
Yang Si ◽  
Hongzhi Guan ◽  
Yuchao Cui
Keyword(s):  
Latent Variables ◽  
Logit Model ◽  
Latent Variable ◽  
Structural Equation ◽  
Choice Behavior ◽  
Online Survey ◽  
Mode Choice ◽  
Explanatory Power ◽  
Equation Model ◽  
Internet Technology

With the development of Internet technology, online car-hailing is booming in China, which has profoundly affected people’s travel structures. In order to seek the sustainable development of taxi and online car-hailing services from the perspective of passenger mode choice behavior, the mechanism of passengers’ decision-making procedures and their travel mode choice behaviors were analyzed. To study the influence of latent variable factors on passenger choice behavior, this paper firstly designed a questionnaire, and a structural equation model (SEM) was established for the preliminary study of the relationship between the latent variables and the behavioral intentions using the online survey data. Then, the latent variables were introduced into the Logit model, setting up the SEM-Logit model to explore the mode choice patterns between taxis and online car services. The results showed that the SEM-Logit model with the latent variables is better than a general Logit model in terms of the model precision and hit ratio. Meanwhile, after introducing the latent variables, it was found that convenience, comfort, and economy factors have a significant influence on the model, and the explanatory power of the model increases accordingly.

Sequenced Ordered Logit Model Considering Latent Variables for Determining Trip Satisfaction of Metro Passengers

2020 ◽  
Vol 2674 (9) ◽  
pp. 755-766
Author(s):  
Tara Saeidi ◽  
Mahmoud Mesbah ◽  
Meeghat Habibian
Keyword(s):  
Public Transportation ◽  
Latent Variables ◽  
Logit Model ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Model ◽  
Access Time ◽  
Ordered Logit ◽  
Ordered Logit Model ◽  
Passenger Satisfaction

Improving the public transportation system to compete with the private modes requires an understanding of passenger perceptions of the service quality (SQ). In the literature, various models have been developed to identify effective SQ attributes and to assess their relationship with passenger satisfaction. However, most of them either ignore the socioeconomic and trip characteristics or consider them by a market segmentation approach. Since these variables can affect passenger perceptions, it is important to include them in the model. This paper aims to capture the effect of socioeconomic and trip variables by combining them with SQ attributes in a satisfaction analysis. An ordered logit model considering SQ latent variables is calibrated to model passenger satisfaction. The measurement part of a Structural Equation Model (SEM) is applied to construct latent variable structures. The case study was on the Tehran metro. The SQ attributes were used to form five SQ latent variables: “comfort,”“information,”“cleanliness,”“service,” and “safety/security.” The results indicate that socioeconomic and trip characteristics, as well as the SQ latent variables, had a significant effect on passenger satisfaction. From the results of this study, “service” and “comfort” were found to be the most effective contributors to satisfaction levels among the SQ latent variables. Among socioeconomic and trip characteristics, gender, education, driving license, egress mode, access time, and trip origin type (i.e., work, education, etc.) were also important in passenger satisfaction.

scholarly journals Impact of Market Orientation Components on Organizational Performance of SMEs. The single-industry approach " Food and Beverage Sector"

2021 ◽  
Vol 8 (5) ◽  
pp. 504-516
Author(s):  
Akram Abdulsamad ◽  
Noor Azman ALI ◽  
Anuar Shah Bali Mahomed ◽  
Haslinda Hashim ◽  
Abdulwahab Jandab ◽  
...  
Keyword(s):  
Organizational Performance ◽  
Market Orientation ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Customer Orientation ◽  
Equation Model ◽  
Food And Beverage ◽  
Competitor Orientation ◽  
Main Components

This study examines the direct effect of the three main components of the market orientation on the organizational performance of SMEs in Yemen. Four variables are used in the research, are competitor orientation, customer orientation, and inter-functional coordination, as the exogenous latent variables, whereas organizational performance, as the endogenous latent variable. The quantitative approach is applied in this study with causal and descriptive research. The single-sector method is adopted, is the food and beverage sector, by using random sample sampling, the sample size was 640 managers/owners. only 459 samples were valid to conduct the analysis by using the Structural Equation Model (SEM) in SmartPLS Software version 3.0. The findings of the study reveal that the three main components of the market orientation have a positive and significant impact on SMEs' organizational performance. However, the effect size of customer orientation on organizational performance was more than competitor orientation and inter-functional coordination.

scholarly journals Using psychometric data from the stated preference (SP) experiments to search explanatory power for appropriateness of congestion charging policy

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Sofyan M. Saleh ◽  
Sugiarto Sugiarto ◽  
Cut Mutiawati ◽  
Renni Angraini ◽  
Muhammad Isya
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Stated Preference ◽  
Explanatory Power ◽  
Path Coefficient ◽  
Annual Income ◽  
Positive Correlation ◽  
Psychological Determinants ◽  
Psychometric Data

Comprehensive stated preference (SP) experiment was conducted in Jakarta (a capital of Indonesia), where proposal for congestion charge (CC) has been considered as a way to reduce acute traffic congestion. With the government planning a CC scheme, public support is regarded as a prerequisite for its implementation. Therefore, a framework of structural equation model (SEM) is used to search explanatory power for the appropriateness of CC considering unobserved variable (latent variable) from psychometric data obtained from SP questionare.  Causal paths among psychological determinants and their strength are measured and analyzed along with proposal acceptability from a psychological perspective. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the acceptability of the proposed scheme. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the appropriateness of the proposed scheme. Latent variables representing the validity of the CC scheme, such as ACE, APC and REC appear to have a significant explanation. These emerge as psychological determinants contributing a positive correlation with enhancement of appropriateness CC policy. Empirical result further shows that males have positive scores for the latent variables of car dependency (CDC) and inhibition freedom of movement (IFM). Furthermore, the variable of annual income, it has a positive correlation with recognition of the effects of CC in mitigating congestion and environmental problems (REC), car dependency (CDC) and awareness of the problems of cars in society (APC). This means that respondents with higher incomes are more concerned with the problems manifested by motorization while, on the contrary, the path coefficient between annual income (AI) and car dependency (CDC) has a value of 0.270. This discloses an automobile dependency. These findings should provide insight that designing a more acceptable policy in respecting to the acceptance of public in large.

scholarly journals Products of Variables in Structural Equation Models: Multiplicative Reticular Action Models

2019 ◽  
Author(s):  
Steven M. Boker ◽  
Timo von Oertzen ◽  
Andreas Markus Brandmaier
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Equation Model ◽  
Random Coefficients ◽  
Action Model ◽  
Action Models ◽  
Special Case ◽  
General Method

A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands. The result is a new category of SEM which we call a Multiplicative Reticular Action Model (XRAM). XRAM can include interactions between latent variables, multilevel random coefficients, latent variable moderators, and novel constructs such as factors of paths and twin genetic decomposition of multilevel random coefficients. The method relies on an assumption that all variance sources in a model can be decomposed into linear combinations of independent normal standardized variables. Although the distribution of a variable that is an outcome of multiplication between other variables is not normal, the assumption is that it can be decomposed into sources that are normal if one takes into account the non-normality induced by the multiplication. The method is applied to an example to show how in a special case it is equivalent to known unbiased and efficient estimators in the statistical literature. Two simulations are presented that demonstrate the precision of the approximation and implement the method to estimate parameters in a multilevel autoregressive framework.

scholarly journals Determinants of school attendance in elementary school students in Japan: a structural equation model

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Hiromi Nakamura-Thomas ◽  
Nobuyuki Sano ◽  
Donald Maciver
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
School Attendance ◽  
Subjective Health ◽  
Equation Model ◽  
Positive Perception ◽  
Negative Effects ◽  
School Teachers ◽  
School Students

Abstract Background Managing school nonattendance is a priority worldwide. Frequent school nonattendance in early school years has immediate and long-term negative effects. Although strategies to address nonattendance are being developed and implemented, the number of students with school nonattendance issues is increasing. In this study, we explored students’ feelings and perceptions about attending school and the potential determinants of a positive attitude towards attending school. Methods We hypothesized that a positive perception towards attending school was influenced by relationships, perceptions of current circumstances, subjective health, and having someone to share experiences and thoughts with. For examining the hypothesized model, an original questionnaire with 14 items was developed, including perceptions towards school attendance (an item), relationships with friends and school teachers (5 items), current circumstances (4 items), subjective health (3 items), and the individuals available to share experiences and thoughts with (1 item). In total, 6860 children submitted the questionnaire (85.3% response rate) and 6841 responses were included to examine the model. Children were 10 or 11 years old, and selected from 111 state-run schools in 8 randomly selected school districts. Results The final model demonstrated good fit and showed that the latent variable of relationships with friends and school teachers directly impacted on how children felt about attending school. The latent variable of subjective health also directly impacted on how children felt about attending school but not strongly. Other latent variables were not significant. Conclusions The importance of positive relationships with friends and teachers in overcoming school nonattendance has been emphasized in previous studies. This study has provided evidence that these relationships impacted children’s positive perception about attending school in a large sample of students aged 10–11 years. The latent variable of subjective health may require more items to capture mental health.

The Impact of Green Attributes From Suppliers on Supply Chain Performance

2019 ◽  
pp. 1216-1232
Author(s):  
Jose Roberto Mendoza Fong ◽  
Jorge Luis García-Alcaraz ◽  
Aidé Aracely Maldonado-Macías ◽  
Cuauhtémoc Sánchez Ramírez ◽  
Valeria Martínez Loya
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Manufacturing Industry ◽  
Descriptive Analysis ◽  
Equation Model ◽  
Ciudad Juarez ◽  
Senior Managers ◽  
Positive Effects ◽  
The Impact

Nowadays, green supplier selection (GSS) is one of the most important activities for companies. Therefore, this research aims to demonstrate the relationship that exists between GSS and the marketing benefits of companies. The chapter proposes a structural equation model that integrates three latent variables. The two independent latent variables concern preproduction green attributes and process green attributes, and they are associated with a dependent latent variable: marketing indexes. Thus, three hypotheses are proposed to relate these latent variables. To validate such hypotheses, a survey is administered to 253 middle and senior managers from the manufacturing industry of Ciudad Juárez. Similarly, a descriptive analysis of the sample and the items is carried out. Results show direct and positive effects among the analyzed variables. However, the highest impact is caused by preproduction green attributes over production process green attributes.

scholarly journals ANALISIS KEKAMBUHAN ORANG DENGAN SKIZOFRENIA MENGGUNAKAN METODE PARTIAL LEAST SQUARE STRUCTURAL EQUATION MODEL

2019 ◽  
Vol 8 (3) ◽  
pp. 222
Author(s):  
IRA INDRIYANTI ◽  
G.K. GANDHIADI ◽  
MADE SUSILAWATI
Keyword(s):  
Family Support ◽  
Structural Equation Model ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Model ◽  
Medication Compliance ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square

Schizophrenia is a psychotic disorder characterized by major disorders in the mind and emotions. People with schizophrenia (ODS) can experience recurrence if they do not receive proper care. The latent variable used in this study was ODS reccurence. One method that can determine the relationship between latent variables and latent variables with the indicator is the partial least square structural equation model (PLS-SEM). This study was conducted to see how the structural model of ODS recurrence data and to know the factors that most influence ODS recurrence. The results of this study concluded that the resulting model was good enough with a large R-square value of 0.8577, but not all variables used in this study had a significant effect on ODS recurrence. ODS recurrence is significantly influenced by family support and community social support variables. While medication compliance and physician control regularity will not have a significant effect without family support. The worse treatment of families and communities around ODS recurrence will occur more often.

scholarly journals Analysis of Travel Mode Choice Behavior Considering the Indifference Threshold

2019 ◽  
Vol 11 (19) ◽  
pp. 5495 ◽  
Author(s):  
Zhang ◽  
Guan ◽  
Zhu ◽  
Zhu
Keyword(s):  
Public Transportation ◽  
Traffic Management ◽  
Structural Equation ◽  
Choice Behavior ◽  
Latent Class ◽  
Mode Choice ◽  
Latent Class Model ◽  
Equation Model ◽  
Travel Choice ◽  
Travel Costs

An effective way to optimize traffic structures is by changing travel costs, thereby moving travelers from private transportation to public transportation. However, according to the existing studies, the traveler will not transfer from one mode to another unless the change in travel utility is greater than the indifference threshold. Therefore, the “indifference threshold” is one of the most important factors influencing a traveler’s choice of behavior. This study defines the “indifference threshold” as the traveler’s sensitivity to changes in travel utilities. In the framework of the theory of planned behavior (TPB), a structural equation model (SEM) considering the indifference threshold is established to analyze a traveler’s mode choice behavior. The analysis results showed that a travelers’ sensitivity to changes in travel utilities has the greatest impact on mode-choice behavior intentions and mode choice behavior. Perceptual behavior control has the strongest influence on travel choice behavior. In addition, in order to further explore the heterogeneity of a traveler’s behavior, the travelers were subdivided into four types, by establishing a latent class model (LCM) considering the indifference threshold. Finally, different traffic management suggestions are proposed for different types of travelers.

scholarly journals Modeling the Effective Factors on Bank Loans Default Rate UsingDelphi, SEM and Tobit Techniques (Evidence from Iran)

2017 ◽  
Vol 11 (4) ◽  
pp. 13
Author(s):  
Hamid Safaynikou ◽  
Mohammad Taher Ahmadi Shadmehri ◽  
Ahmad Sabahi ◽  
Mohammad Javad Razmi
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Credit Scoring ◽  
Equation Model ◽  
Bank Loans ◽  
Medium Size ◽  
Effective Factors ◽  
Default Rate

Banks entering a developing market face a lot of uncertainty about the risks involved in lending. This paper models the effective factors on default rate (DR) loans to small and medium size enterprises (SMEs) in Iran based on the case study of branches of Melli Bank in Khorasan Razavi province. For this purpose a set of data about loans made to 300 SMEs between years 2004 to 2015 and Delphi, SEM and Tobit models were applied. Results of Delphi technique indicated that 48 factors affect the DR. The structural equation model (SEM) estimations showed that between 10 latent variables which describe the DR, the “loans properties” latent variable have the most effect. Also, findings of Tobit econometric model stated that between 48 variables which affect the DR, “loan volume” variable has the most effect. These and other factors emphasize the need for SMEs credit scoring in developing countries.

scholarly journals Health, Security and Participation: A Structural Relationship Modeling among the Three Pillars of Active Ageing in China

2020 ◽  
Vol 17 (19) ◽  
pp. 7255
Author(s):  
Yinan Yang ◽  
Yingying Meng ◽  
Pengtao Dong
Keyword(s):  
Older People ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Negative Impact ◽  
Positive Impact ◽  
Equation Model ◽  
Active Ageing ◽  
Security Level ◽  
The Impact

This paper explores and tests the impact of health and security on the participation of Chinese older people using data from the China Longitudinal Ageing Social Survey (CLASS) in 2014. Based on the framework of Active Ageing, the exogenous latent variables “health” and “security” are assumed to directly affect the endogenous latent variable “participation”, and indirectly affect it via mediating the function of “willingness”. The estimation results of the structural equation model show that health has a significant positive impact, while security has a significant negative impact on participation. In addition, health and security can significantly enhance the willingness of older people to participate. After the opposite effects of health and security are offset, their net effect on participation is generally negative. According to these empirical results, this paper concludes that the optimization of health coupled with the moderation of security level is more beneficial for promoting the participation of older people.

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