scholarly journals Modeling the effect of days and road type on peak period travels using structural equation modeling and big data from radio frequency identification for private cars and taxis

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Tina Dzigbordi Wemegah ◽  
Shunying Zhu ◽  
Charles Atombo
Keyword(s):  
Big Data ◽  
Structural Equation Modeling ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Structural Equation ◽  
Equation Modeling ◽  
Peak Period ◽  
Frequency Identification ◽  
Road Type

scholarly journals Assessing hospital readiness for radio frequency identification device implementation in Iran: a conceptual model

2019 ◽  
Vol 12 (6) ◽  
pp. 245-254
Author(s):  
Malihe Sadeghi ◽  
Pakzad Rahmati ◽  
Zahra Ramezani Pour ◽  
Elham Goharinejad ◽  
Mehdi Kahouei
Keyword(s):  
Human Resources ◽  
Radio Frequency ◽  
Human Resource ◽  
Radio Frequency Identification ◽  
New Technologies ◽  
Organizational Factors ◽  
Organizational Readiness ◽  
Equation Modeling ◽  
Frequency Identification ◽  
Radio Frequency Identification Device

AbstractBackgroundTo avoid possible failures and ineffective use of economic resources, necessary infrastructure must be provided before implementing new technologies in a developing country like Iran.ObjectivesTo assess the degree of readiness for implementing a radio frequency identification device (RFID) system in hospitals in Iran.MethodsWe adopted a descriptive design and structural equation modeling (LISREL statistical software package) to analyze data collected from the hospitals affiliated with the Semnan University of Medical Sciences. All managers, physicians, residents, nurses, and staff members of the medical records and information technology sectors participated in this study. A questionnaire was designed by the investigators to collect ideas from the participants about organizational readiness, cultural readiness, and human resource readiness in implementing RFID.ResultsWe found a significant positive correlation between the variables studied. Human resource readiness significantly predicted RFID implementation, with cultural readiness playing the role of a mediator variable. Cultural readiness itself was influenced by organizational readiness (P < 0.01). We found 0.346 (standard deviation: 0.374) changes in an arbitrary unit of the possibility of RFID implementation was attributed to human resources and cultural readiness.ConclusionsPaying attention to cultural factors, which play an important role in implementing technological projects such as RFID in developing countries like Iran, can reduce the risk of failure. Hospitals should strengthen organizational factors and improve the support of top rank managers when implementing technological projects. By so doing, they will promote cultural readiness, prepare human resources, and win the cooperation of personnel for such projects.

scholarly journals The Role of Big Data Predictive Analytics and Radio Frequency Identification in the Pharmaceutical Industry

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 9013-9021 ◽  
Author(s):  
Muhammad Noman Shafique ◽  
Muhammad Mahboob Khurshid ◽  
Haji Rahman ◽  
Ashish Khanna ◽  
Deepak Gupta
Keyword(s):  
Big Data ◽  
Pharmaceutical Industry ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Predictive Analytics ◽  
Frequency Identification

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

The Measurement Invariance of the Short Dark Triad

2020 ◽  
Vol 41 (4) ◽  
pp. 207-218
Author(s):  
Mihaela Grigoraș ◽  
Andreea Butucescu ◽  
Amalia Miulescu ◽  
Cristian Opariuc-Dan ◽  
Dragoș Iliescu
Keyword(s):  
Structural Equation Modeling ◽  
Item Response ◽  
Structural Equation ◽  
Dark Triad ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Scale Level ◽  
High Stake ◽  
Differential Functioning ◽  
Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

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