scholarly journals Modeling factors affecting the choice of telework and its impact on demand in transportation networks

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Rambod Vakilian ◽  
Ali Edrisi
Keyword(s):  
Logistic Regression ◽  
Time Delay ◽  
Logistic Regression Model ◽  
Transportation Networks ◽  
University Staff ◽  
Transportation Demand ◽  
Factors Affecting ◽  
On Demand ◽  
Study Population ◽  
Travel Distances

This research estimates the extent of using teleworking to mean the feasibility and appropriateness of this method of work for employees and professors according to their characteristics and features of career. The study population included university staff and professors in Tehran and data collection was carried out through 447 questionnaires. A logistic regression model was used to investigate the transport demand caused by teleworking. The results showed that various factors including history and percentage of telework and after that, the time delay of home-to-work and trave distance affected the model of transportation demand of professor’s members. For the staffing community, it had the greatest impact on teleworking, history and percentage of telework, followed by travel distances, latency from work to home, and latency from home to work.

scholarly journals Modeling Factors Affecting the Choice of Telework and its Impact on Demand in Transportation Networks

2020 ◽  
Vol 16 (1) ◽  
pp. 21-29
Author(s):  
Rambod Vakilian ◽  
Ali Edrisi
Keyword(s):  
Logistic Regression ◽  
Time Delay ◽  
Logistic Regression Model ◽  
Transportation Networks ◽  
University Staff ◽  
Transportation Demand ◽  
Factors Affecting ◽  
On Demand ◽  
Study Population ◽  
Travel Distances

AbstractThis research estimates the extent of using teleworking to mean the feasibility and appropriateness of this method of work for employees and professors according to their characteristics and features of career. The study population included university staff and professors in Tehran, and data collection was carried out through 447 questionnaires. A logistic regression model was used to investigate the transport demand caused by teleworking. The results showed that various factors, including history and percentage of telework, and after that, the time delay of home-to-work and travel distance, affected the model of transportation demand of professor’s members. For the staffing community, it had the most significant impact on teleworking, history and percentage of telework, followed by travel distances, latency from work to home, and latency from home to work.

scholarly journals Factors Affecting Mortality in Patients Admitted to the Hospital by Emergency Physicians despite Disagreement with Other Specialties

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Engin Ozakin ◽  
Arif Alper Cevik ◽  
Filiz Baloglu Kaya ◽  
Nurdan Acar ◽  
Fikri M. Abu-Zidan
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Systolic Blood Pressure ◽  
Logistic Regression Model ◽  
Admission Diagnosis ◽  
Emergency Physicians ◽  
Factors Affecting ◽  
Admission Decisions ◽  
Service Departments ◽  
Significant Factors

Background. Emergency physicians (EPs) face critical admission decisions, and their judgments are questioned in some developing systems. This study aims to define the factors affecting mortality in patients admitted to the hospital by EPs against in-service departments’ decision and evaluate EPs’ admission diagnosis with final discharge diagnosis. Methods. This is a retrospective analysis of prospectively collected data of ten consecutive years (2008–2017) of an emergency department of a university medical center. Adult patients (≥18 years-old) who were admitted to the hospital by EPs against in-service departments’ decision were enrolled in the study. Significant factors affecting mortality were defined by the backward logistic regression model. Results. 369 consecutive patients were studied, and 195 (52.8%) were males. The mean (SD) age was 65.5 (17.3) years. The logistic regression model showed that significant factors affecting mortality were intubation (p<0.0001), low systolic blood pressure (p=0.006), increased age (p=0.013), and having a comorbidity (p=0.024). There was no significant difference between EPs’ primary admission diagnosis and patient’s final primary diagnosis at the time of disposition from the admitted departments (McNemar–Bowker test, p=0.45). 96% of the primary admission diagnoses of EPs were correct. Conclusions. Intubation, low systolic blood pressure on presentation, increased age, and having a comorbidity increased the mortality. EPs admission diagnoses were highly correlated with the final diagnosis. EPs make difficult admission decisions with high accuracy, if needed.

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

scholarly journals Effects of the Agri-environmental Program Implemented in Sultan Reeds Area of Kayseri, Turkey

2019 ◽  
Vol 7 (12) ◽  
Author(s):  
Ismet Boz
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Agricultural Practices ◽  
Farm Size ◽  
Chi Square ◽  
Factors Affecting ◽  
Environmental Program ◽  
Chi Square Test ◽  
Sustainable Agricultural Practices

This study was initiated to evaluate the effects of agri-environment program implemented in the Sultan reeds area of Kayseri province, Turkey. The specific objectives of the study were to compare the farmers who enrolled in the program with those who didn’t enroll regarding their application of different sustainable agricultural practices, and to determine factors affecting their enrolment in the program. The main comparative indicators were selected from different sustainable agricultural practices either promoted by the agri-environmental program or not promoted but considered very useful for the locality. Two stratified samples of farmers (enrolled and not enrolled) were selected based on their farm size. Chi-square tests of independence were used to compare farmers on the selected sustainable agricultural practices. Logistic regression model was used to determine factors affecting the enrolment of the agri-environment program. The findings of the chi-square test showed that enrolled farmers use grow more forage legumes, are more conscious about pesticides use and chemical applications, and they use more pressurized irrigation systems. Findings of the logistic regression model sowed that using rental land negatively, but contacts with extension personnel, and using long term loans for farming investments positively influenced the enrolment of the agri-environment program. Governmental effort must concentrate on these issues when promoting agri-environmental programs in the region.

FACTORS AFFECTING CLIENT INFLUENCE ON PROPERTY VALUATION IN MALAYSIA: DO CLIENT SIZE AND SIZE OF VALUE ADJUSTMENT MATTER?

2015 ◽  
Vol 75 (10) ◽  
Author(s):  
Kamalahasan Achu ◽  
Lim Wan Chin ◽  
Burhaida Burhan ◽  
Muhammad Faris Nordin
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Logistic Regression Model ◽  
Client Characteristics ◽  
Factors Affecting ◽  
The Real Estate ◽  
Property Valuation ◽  
Behavioural Research ◽  
Behavioural Experiment ◽  
Client Pressure

Client influence on property valuation has been an emerging theme of behavioural research in the real estate discipline. Studies on valuers’ decision-making behaviour imply that client influence is an important source of judgemental bias. Academic interest in client influence research has evolved from identifying the existence of client pressure to studies that explain the mechanism of client influence. A questionnaire survey was administered to valuers to measure their perception with regard to factors affecting client influence in Malaysia. The effect of client size and size of value adjustment requested by clients on valuation were also tested in a behavioural experiment. The survey revealed that valuers in Malaysia perceived client characteristics and valuer characteristics as some of the most important factors affecting client influence on valuations. It was found that factors such as type of client, size of client, integrity of valuer and experience of valuer could potentially impact on the amount and type of influence exerted on valuations. The results of the logistic regression model indicated that neither the client size nor magnitude of value adjustment requested by client affected the decisions of valuers to alter valuation outcome. 

scholarly journals The Factors Affecting Eye Patients (Cataract) In Jordan by Using the Logistic Regression Model

2017 ◽  
Vol 11 (8) ◽  
pp. 38
Author(s):  
Adeeb Ahmed Ali AL Rahamneh ◽  
Omar M. Hawamdeh
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Likelihood Ratio Test ◽  
Logistic Regression Model ◽  
Ratio Test ◽  
Response Variable ◽  
Factors Affecting ◽  
Independent Variables ◽  
Lemeshow Test ◽  
The Right

This study aims to use the logistic regression model to classify patients as infected and without cataracts. The independent variables were used to represent the gender, the age, the pressure in the right eye, the pressure in the left eye, HbA1C, and the anemia, representative variables for the study of Cataract disease affects the eyes, based on a random sample of (116) patients. The results proved that the used logistic regression model is an efficient and representative for data that shows through (Likelihood Ratio Test) and (Hosmer and Lemeshow test), and the study proved that the value of (R Square Nagelkerke=1) this means that 100% of the change in the occurred changes in the response variable explained through the Logistic regression model.

scholarly journals EFEKTIVITAS DISTRIBUSI RASKIN DI PEDESAAN DAN PERKOTAAN INDONESIA

2012 ◽  
Vol 13 (1) ◽  
pp. 132
Author(s):  
Jamhari Jamhari
Keyword(s):  
Logistic Regression ◽  
Logistic Regression Model ◽  
Factors Affecting ◽  
Quantity Index ◽  
Accuracy Index ◽  
The Poor ◽  
Rural And Urban ◽  
Economic Survey ◽  
To Receive ◽  
Floor Condition

This research aims to investigate effectiveness of rice for the poor program (Raskin) in rural and urban Indonesia based on the National Socio Economic Survey data (Susenas) collected by Central Bureau of Statistic (BPS) in 2007. Number of sample was 52,370 households. Effectiveness of Raskin Program was measured by target, quantity and price accuracy indexes. Logistic regression model was used to identify factors affecting probability of a household to receive raskin or not. The results of analysis show that raskin distribution was not yet accurately reach the target beneficiaries. Raskin distribution was also not accurate in quantity and price. Quantity accuracy index was 58 percent in rural, 53 percent in urban and 57 percent in Indonesia. Price quantity index was 68 percent in rural, 63 percent in urban and 67 percent in Indonesia. Probability of a household to receive raskin was affected by education, gender, age, household member, income, employment, floor condition and location.

scholarly journals Factors Affecting Postnatal Care in Bangladesh: Clustered Data Analysis

2018 ◽  
Vol 66 (1) ◽  
pp. 59-65
Author(s):  
Mehejabeen Mahbub ◽  
Most Fatima Tuz Zahura
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Data Analysis ◽  
Antenatal Care ◽  
Regression Model ◽  
Birth Order ◽  
Postnatal Care ◽  
Logistic Regression Model ◽  
Wealth Index ◽  
Factors Affecting

The study aims to determine the factors affecting postnatal care in Bangladesh using the data extracted from Bangladesh Demographic and Health Survey (BDHS), 2014. For the purpose of regression analysis, mixed logistic regression model has been utilized to take into account the possible correlation among subjects within clusters. It is found that region, place of residence, mother’s education, wealth index, access to media, birth order and antenatal care visits have significant association with postnatal care. Dhaka Univ. J. Sci. 66(1): 59-65, 2018 (January)

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