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What is Factor Analysis

Chapter 18
Handbook of Research on Holistic Optimization Techniques in the Hospitality, Tourism, and Travel Industry
A statistical method used to describe the variability among observed variables in terms of a potentially lower number of unobserved variables called factors.
Published in Chapter:
Young Tourists' Perceptions of Hotel Disintermediation: Evidence from Italy
Giacomo Del Chiappa (University of Sassari, Italy), Mariella Pinna (University of Sassari, Italy), and Marcello Atzeni (University of Cagliari, Italy)
Copyright: © 2017 |Pages: 19
DOI: 10.4018/978-1-5225-1054-3.ch018
Abstract
Generation Y has been considered to be a sizeable new market. This study, based on a sample of 1131 Italian travellers from Gen Y, investigates their views for and against disintermediation, and analyses how their choices are influenced by user generated content (UGC), rather than by information provided by high street travel agencies. The factor analysis uncovers three dimensions: “Benefits of Travel Agency”, “Benefits of Online Reservation”, and “Online Trust & Search Behaviour”. Further, a series of statistical tests indicate that demographics such as age and education have a significant influence on the respondents' perceptions. Our findings suggest that hotel managers and travel agencies should monitor Gen Y perceptions of the benefits and constraints of using the Internet, UGC and travel agencies for hotel booking. Further, accommodation providers should use online channels to create affective commitment in their young customers. Limitations of the study are discussed and suggestions for further research are given.
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Chapter 6
Using Tests to Study People's Responses: What Do the Scores Mean?
A type of structural equation modeling that is used to study the relationship between observed indictors (items) and latent variables (factors). The most well-known models are exploratory factor analysis and confirmatory factor analysis.
Published in Chapter: Using Tests to Study People's Responses: What Do the Scores Mean?; From: Cases on Developing Effective Research Plans for Communications and Information Science
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Chapter 10
Framework for Enhancing Organizational Performance: Haryana Government Departments, India
A statistical technique used to reduce large number of variables into fewer numbers of factors or dimensions. The technique extracts common variance in variables and assemble them into a common segmentation.
Published in Chapter: Framework for Enhancing Organizational Performance: Haryana Government Departments, India; From: Handbook of Research on Civic Engagement and Social Change in Contemporary Society
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Chapter 1
Understanding E-Skills in the FLT Context
Data-reduction technique used to interpret underlying dimensions in a construct.
Published in Chapter: Understanding E-Skills in the FLT Context; From: Handbook of Research on E-Learning Methodologies for Language Acquisition
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Chapter 132
Independent Subspaces
A set of samples is described by a linear model x = Ay + µ + e, where µ is a constant, y and e are both from Gaussian and mutually uncorrelated, and components of y are called factors and mutually uncorrelated. Typically, the model is estimated by the maximum likelihood principle
Published in Chapter: Independent Subspaces; From: Encyclopedia of Artificial Intelligence
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Chapter 15
Millennial's Involvement in Corporate Social Responsibility
A statistical method used to describe variability between the observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.
Published in Chapter: Millennial's Involvement in Corporate Social Responsibility; From: Customer Satisfaction and Sustainability Initiatives in the Fourth Industrial Revolution
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Chapter 21
Mining Spatial Patterns of Distribution of Uranium in Surface and Ground Waters in Ukraine
Statistical methods which reduce a set of source variables to a smaller number of new variables, where each new variable is a function of one or more of the original variables.
Published in Chapter: Mining Spatial Patterns of Distribution of Uranium in Surface and Ground Waters in Ukraine; From: Handbook of Research on Geographic Information Systems Applications and Advancements
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Chapter 5
Offline vs. Online Quality Dimension: The Relationship Between Shopping Mall Quality Dimensions and Customer Loyalty
A statistical method used to describe variability between the observed correlated variables in terms of a potentially lower number of unobserved variables called factors.
Published in Chapter: Offline vs. Online Quality Dimension: The Relationship Between Shopping Mall Quality Dimensions and Customer Loyalty; From: Strategies and Tools for Managing Connected Consumers
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Chapter 1
A Primer on Survey Research
Advanced statistical analysis used to explore or confirm the internal structure of a questionnaire.
Published in Chapter: A Primer on Survey Research; From: Handbook of Research on Advancements in Organizational Data Collection and Measurements: Strategies for Addressing Attitudes, Beliefs, and Behaviors
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Chapter 4
Economic Impacts and Management of the COVID-19 Global Crisis: A Study of the Tourism Industry
A process in which the values of observed data are expressed as functions of a number of possible causes in order to find which are the most important.
Published in Chapter: Economic Impacts and Management of the COVID-19 Global Crisis: A Study of the Tourism Industry; From: Emerging Trends and Insights on Economic Inequality in the Wake of Global Crises
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Chapter 5
Theory Development in Information Systems Research Using Structural Equation Modeling: Evaluation and Recommendations
A statistical approach that can be used to analyze interrelationships among a large number of variables and to explain these variables in terms of their common underlying dimensions (factor)
Published in Chapter: Theory Development in Information Systems Research Using Structural Equation Modeling: Evaluation and Recommendations; From: Handbook of Research on Contemporary Theoretical Models in Information Systems
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Chapter 19
Measuring Clergy Effectiveness: The Development of the Clergy Effectiveness Scale
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Chapter 702
Usability of CAPTCHA in Online Communities and Its Link to User Satisfaction
Factor analysis is a statistical method for data reduction that describes variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.
Published in Chapter: Usability of CAPTCHA in Online Communities and Its Link to User Satisfaction; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 6
The Effect of the Festivals on the Development of Tourism With the Support of Residents: The Case Study of Zeytinli Rockfest in Edremit
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Chapter 9
Predictive Analytics of Workplace Bullying and Bad Leadership Practices: An Exploratory Empirical Study
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Chapter 44
Structural Equation Modeling for Systems Biology
A statistical method for describing variability among observed variables.
Published in Chapter: Structural Equation Modeling for Systems Biology; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 29
The Study of Developing a Financial Literacy Scale for University Students in the Digital Era: Evidence From Inonu University
It is a method for condensing a large number of variables into a smaller number of factors. This method takes the broadest common variance from all variables and converts it to a single score. We can use this score as an index of all variables for further analysis.
Published in Chapter: The Study of Developing a Financial Literacy Scale for University Students in the Digital Era: Evidence From Inonu University; From: Handbook of Research on Digital Violence and Discrimination Studies
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Chapter 10
Critical Success Factors for Organizational Agility: Q-Study and the Place of IT
A statistical technique used to uncover the latent structure of a set of variables. It reduces attribute space from a larger number of variables to a smaller number of factors.
Published in Chapter: Critical Success Factors for Organizational Agility: Q-Study and the Place of IT; From: Achieving Organizational Agility, Intelligence, and Resilience Through Information Systems
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Chapter 6
Statistical Analysis of Women's Labor Force Data of OECD Countries
A statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors.
Published in Chapter: Statistical Analysis of Women's Labor Force Data of OECD Countries; From: Handbook of Research on Unemployment and Labor Market Sustainability in the Era of Globalization
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Chapter 18
Major Components of Green Urbanization and Their Relative Importance: A Study on Some Districts of West Bengal (India)
It is a statistical process in which the values of observed data are expressed as functions of a number of possible causes in order to find which are the most important. Factor analysis is a technique that is used to reduce a large number of variables into fewer numbers of factors. This technique extracts maximum common variance from all variables and puts them into a common platform.
Published in Chapter: Major Components of Green Urbanization and Their Relative Importance: A Study on Some Districts of West Bengal (India); From: Handbook of Research on Economic and Political Implications of Green Trading and Energy Use
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Chapter 12
Taxonomies of Debiasing Methods in Procurement Processes
The statement describes an analysis method that transforms data within a relationship into independent data structures, bringing variables together to create more meaningful new variables (Karagöz and Kösterelioglu, 2008).
Published in Chapter: Taxonomies of Debiasing Methods in Procurement Processes; From: Overcoming Cognitive Biases in Strategic Management and Decision Making
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Chapter 43
Assessing Critical Success Factors of ERP Implementation
Any of several methods for reducing co-relational data to a smaller number of dimensions or factors; beginning with a correlation matrix a small number of components or factors are extracted that are regarded as the basic variable that account for the interrelations observed in the data.
Published in Chapter: Assessing Critical Success Factors of ERP Implementation; From: Encyclopedia of Information Science and Technology, Second Edition
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Chapter 1
Q Methodology: A Concise Overview
A statistical technique used to reduce many observed variables into a few unobserved ones-factors, so that data can be easily managed.
Published in Chapter: Q Methodology: A Concise Overview; From: Methodological Innovations in Research and Academic Writing
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Chapter 31
Associations Between Driving Forces to Adopt ICT and Benefits Derived from that Adoption in Medical Practices in Australia
A statistical method used to describe variability among observed variables in terms of fewer unobserved variables called factors.
Published in Chapter: Associations Between Driving Forces to Adopt ICT and Benefits Derived from that Adoption in Medical Practices in Australia; From: Handbook of Research on Developments in E-Health and Telemedicine: Technological and Social Perspectives
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Chapter 11
Clustering Methods for Gene-Expression Data
Factor analysis is a statistical technique in which the correlation between the variables is approximated by the linear dependence of the latter on a set of unobservable (latent) variables.
Published in Chapter: Clustering Methods for Gene-Expression Data; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 106
Understanding the Dimensions of the Broadband Gap: More than a Penetration Divide
A multivariate technique that can be used to either identify the underlying dimensions for a set of variables, or to determine whether the information can be summarized in a smaller number of factors.
Published in Chapter: Understanding the Dimensions of the Broadband Gap: More than a Penetration Divide; From: Encyclopedia of E-Business Development and Management in the Global Economy
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Chapter 15
The Impact of School Leadership and Professional Development on Professional Commitment: A Hierarchical Linear Modeling Approach
This is a statistical technique that allows researchers to reduce a large number of variables to smaller number of variables. It is a data reduction technique that uses associations among variables to build cluster of items.
Published in Chapter: The Impact of School Leadership and Professional Development on Professional Commitment: A Hierarchical Linear Modeling Approach; From: Handbook of Research on Global Issues in Next-Generation Teacher Education
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Chapter 45
Health-Related Quality of Life Measures in the Information Age
A statistical method used to classify large numbers of interrelated measurements into a smaller selection of factors that represent larger underlying constructs.
Published in Chapter: Health-Related Quality of Life Measures in the Information Age; From: Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare
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Chapter 30
Visualization Tools for Big Data Analytics in Quantitative Chemical Analysis: A Tutorial in Chemometrics
A process in which the values of observed data are expressed as functions of a number of possible causes in order to find which are the most important.
Published in Chapter: Visualization Tools for Big Data Analytics in Quantitative Chemical Analysis: A Tutorial in Chemometrics; From: Handbook of Research on Big Data Storage and Visualization Techniques
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Chapter 6
Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite
A quantitative statistical analysis approach to identify underlying (latent) factors or components in observed or survey data to understand the most influential factors on a construct.
Published in Chapter: Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite; From: Online Survey Design and Data Analytics: Emerging Research and Opportunities
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Chapter 13
The Development of the Occupational Work Ethic for K-20 Education
Is a statistical method used to explain variability among observed variables in terms of fewer unobserved variables called factors. The observed variables are modeled as linear combinations of the factors, plus “error” terms. The information gained about the interdependencies can be used later to reduce the set of variables in a dataset.
Published in Chapter: The Development of the Occupational Work Ethic for K-20 Education; From: Handbook of Research on Teaching and Learning in K-20 Education
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Chapter 10
Junior High School Pupils' Perceptions and Self-Efficacy of Using Mobile Devices in the Learning Procedure
A procedure to describe variability among observed variables, in terms of a potentially lower number of unobserved variables.
Published in Chapter: Junior High School Pupils' Perceptions and Self-Efficacy of Using Mobile Devices in the Learning Procedure; From: Handbook of Research on Integrating ICTs in STEAM Education
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Chapter 3
Youth Aspirations Towards Industry 4.0 Job Requirements: The Example of the Serbian Labor Market
– refers to statistical method used to describe variability among correlated variables. Its logic relies on reducing a large set of variables to smaller number of factors that have some common characteristics and are easily understandable.
Published in Chapter: Youth Aspirations Towards Industry 4.0 Job Requirements: The Example of the Serbian Labor Market; From: Developing Skills and Competencies for Digital and Green Transitions
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Chapter 11
Educational Technology Assessment: A Model for Analyzing Online Psychometric Tests for Course Evaluations
A statistical factorial model used in this study is derived from Agbetsiafa (2010) , and Field (2009) . Concisely, factor analysis allows the delineation of an essential or hidden configuration in a data set. It accelerates the analysis of the configuration of the associations (correlation) among an outsized number of variables by describing a set of shared essential measurements, commonly termed factors ( Agbetsiafa, 2010 ).
Published in Chapter: Educational Technology Assessment: A Model for Analyzing Online Psychometric Tests for Course Evaluations; From: Handbook of Research on Educational Technology Integration and Active Learning
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Chapter 46
Psychometric Methods for Work Ethic Research: Factor Analysis and Structural Equation Modeling
is a statistical method used to explain variability among observed variables in terms of fewer unobserved variables called factors. The observed variables are modeled as linear combinations of the factors, plus “error” terms. The information gained about the interdependencies can be used later to reduce the set of variables in a dataset.
Published in Chapter: Psychometric Methods for Work Ethic Research: Factor Analysis and Structural Equation Modeling; From: Handbook of Research on E-Learning Applications for Career and Technical Education: Technologies for Vocational Training
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