Exploratory Factor Analysis (EFA) Programs in R
In: Structural equation modeling: a multidisciplinary journal, Volume 26, Issue 5, p. 819-826
ISSN: 1532-8007
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In: Structural equation modeling: a multidisciplinary journal, Volume 26, Issue 5, p. 819-826
ISSN: 1532-8007
In: International journal of academic research in business and social sciences: IJ-ARBSS, Volume 12, Issue 12
ISSN: 2222-6990
In: International journal of academic research in business and social sciences: IJ-ARBSS, Volume 13, Issue 12
ISSN: 2222-6990
In: International journal of academic research in business and social sciences: IJ-ARBSS, Volume 14, Issue 1
ISSN: 2222-6990
In: International journal of academic research in business and social sciences: IJ-ARBSS, Volume 12, Issue 5
ISSN: 2222-6990
Construction sector productivity is substantial significance for the government and policymakers because it creates a competitive industry environment as well as determines a nation's expectancy. Addressing the factors influencing productivity especially in Green Construction Project (GCP) is essential and its significantly need to align with the target goal in Malaysia Green Technology Master Plan (2017–2030). In lieu to the scenario, this research aims to identify the important factors affecting the productivity of GCP, by evaluating the criticality factors that may contribute to project productivity. Based on the previous studies, five (5) key component factors were identified with a total of forty-four (44) associated items. The key component factors can be broadly categorized into i) Project, ii) Manpower, iii) Management, iv) Technical and v) External aspect. These factors with their associated items, are then used to develop questionnaire survey to gather data. The Exploratory Factor Analysis (EFA) was employed to the collected data which emphasize to the five (5) component factors with forty-four (44) items affecting green construction productivity with the total variance percentage is 72.113%. Each of the components consists of at least seven (7) variables, so the components complied with the requirement that each component must have at least three variables. According to the findings, the KOM (Kaiser-Meyer-Olkin Measure of Sampling Adequacy) is 9, which is very similar to 1. Each factor loading variable is greater than 0.4 indicating that all components satisfied the Factor Analysis rule. The highest Eigenvalue is on Project Factors (18.175), and the lowest is External Factors (1.154). It is important to understand all key factors affecting the construction productivity, so that the industry practitioners can effectively strategies a plan to improve the productivity in GCP, for prompt delivery of construction projects with lower cost, higher quality and remarking sustainability.
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In: International journal of academic research in business and social sciences: IJ-ARBSS, Volume 11, Issue 4
ISSN: 2222-6990
In: Humanities & Social Sciences Reviews, eISSN: 2395-6518, Vol 8, No 3, 2020, pp 1295-1309, https://doi.org/10.18510/hssr.2020.83132
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In: Organizational research methods: ORM, Volume 6, Issue 2, p. 147-168
ISSN: 1552-7425
The authors surveyed exploratory factor analysis (EFA) practices in three organizational journals from 1985 to 1999 to investigate purposes for conducting EFA and to update and extend Ford, MacCallum, and Tait's (1986) review. Ford et al. surveyed the same journals from 1975 to 1984, concluding that researchers often applied EFA poorly (e.g., relying too heavily on principal components analysis [PCA], eigenvalues greater than 1 to choose the number of factors, and orthogonal rotations). Fabrigar, Wegener, MacCallum, and Strahan (1999) reached a similar conclusion based on a much smaller sample of studies. This review of 371 studies shows reason for greater optimism. The tendency to use multiple number-of-factors criteria and oblique rotations has increased somewhat. Most important, the authors find that researchers tend to make better decisions when EFA plays a more consequential role in the research. They stress the importance of careful and thoughtful analysis, including decisions about whether and how EFA should be used.
Exploratory factor analysis (EFA) is usually necessary to uncover the right items for inclusion in a research instrument. As a result, this research adapts and modifies an instrument on the risk intelligence construct within small and medium enterprises (SMEs) in Nigeria. The study uses Hawley's risk theory of profit and employs the EFA to validate the instrument. Our study differs significantly from prior studies regarding SMEs' socio-economic, political, and cultural statuses, among other factors. More importantly, most past research focused on larger firms or used different dimensions. However, the current study uniquely integrates risk perception, risk-taking propensity, and insurance literacy within Nigerian SMEs to close the literature gap. The study adopts a cross-sectional research approach using quantitative data obtained through a structured survey from 370 SMEs across Nigeria's six geopolitical regions. The study tested the validity and reliability of the constructs used and refined the 27 items used. The EFA result finally reduced the items to 24; risk perception (6 items), risk-taking propensity (9 items) and insurance literacy (9 items).
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Innovation has nowadays become the main force to cope with challenging times in the fast-changing world. The influence of public sector innovation (PSI) in resolving dynamic economical and societal challenges is undisputable. Regardless of the numerous advantages of innovation in the public sector (PS) which have been recognised worldwide, the concept of public sector innovation is still novel for the Federation of Bosnia and Herzegovina (FBiH). Moreover, there is limited empirical evidence which would facilitate the understanding of public sector innovation performance. The purpose of this paper is to identify main components of PSI performance. The primary research data was obtained through a survey with close-ended questions which was completed by the public sector institution employees in FBiH. The exploratory factor analysis (EFA) was used in order to determine the principal components of measuring public sector innovation performance. The EFA returned the factor-structures for all four suggested constructs, innovation capabilities, wider sector conditions for innovation, sources of information and the share of creative occupation, explaining between 65% and 78% of the variance of the innovation performance measurement construct. The results from the exploratory factor analysis provided a distinct estimation on the factor structure of measuring PSI. The paper has provided and analysed the first instrument in measuring public sector innovation performance in FBiH.
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The article presents the data on the exploratory analysis of factors involved in employees' effectiveness for responding to crisis in Iran׳s military hospitals. This research was a descriptive exploratory study. The statistical population included the 561 medical and nonmedical staff of three military hospitals. Two researcher-made questionnaires were used to collect data, and reliability and validity of the questionnaires were confirmed. The exploratory factor analysis (EFA) method was used to classify, clarify, and explain study factors and the infrastructural structure. At the end, 473 questionnaires were found appropriate for the final analysis. Based on results of the exploratory factor analysis (EFA), 8 criteria were identified as the main factors involved in employees' effectiveness for responding to crisis. According to Friedman test results, organizational factors were the most important factors influencing employees' effectiveness with a mean score of 3.76 of 5. Responding to crisis was the most important variable factor involved response to crisis with a mean score of 3.74 of 5.
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In: Canadian journal of family and youth: CJFY, Volume 15, Issue 1, p. 90-110
ISSN: 1718-9748
With the advent of technology, learning becomes more accessible. With the pandemic brought about by Covid 19, the educational system in the Philippines shifted from traditional face-to-face to online learning. Not being prepared for the sudden shift, many students are being affected. In this study, significant factors affecting students' e-learning are determined. Exploratory Factor Analysis (EFA) was used to determine the factors that affect University students' e-learning. This statistical technique used to reduce data to a smaller set of summary variables and investigate the phenomenon's underlying theoretical structure, and determine the form of the variable-respondent relationship. Data sets were gathered through Google Form with twenty-two (22) observable variables. A subset of the entire data is the factors affecting students' e-learning activities. Based on the results, there are three underlying factors namely (F1) App Used, Course Content and Design, and Faculty/Student's Capability Factors, (F2) E-learning, Mental Health and Home Environment Problems, (F3) Social/Media Influence and Student's Mannerism Factors. Different goodness of fit tests was employed to validate the final model. The final model satisfies all the criteria needed for model validation. Hence, the model is accurate and fits with the variables considered in the study.
In: Advances in social work, Volume 22, Issue 3, p. 1174-1193
ISSN: 2331-4125
Practical measures to screen for high levels of pre-divorce conflict offer a unique opportunity for early intervention by forensic social work professionals in divorces where children are at risk of being exposed to high levels of interparental conflict and subsequent maladjustment. There is a lack of validated short screening instruments specifically addressing pre-divorce conflict for parents with at least one minor child. An instrument of this nature would support those in the forensic social work field in identifying families that may be at risk for a high-conflict divorce process. Accordingly, this study describes the development of a self-report measure to assess conflict in parenting couples who are in the process of divorce. An Exploratory Factor Analysis (EFA) was conducted with data from a sample of parents in the process of divorce (n=114), and multiple factor structures were examined. The EFA confirmed that a one-factor model offered the best fit. The short 8-item Parents Divorcing Conflict Scale (PDCS) is a promising measure for use in forensic social work, research, and clinical and policy settings as it captures pertinent themes of conflict, including communication, social network, parent characteristics, satisfaction with agreements, and mistrust, and can inform early intervention strategies that will serve to support healthy communication practices amongst divorcing couples throughout the marriage dissolution process.
In: Problems & perspectives in management, Volume 22, Issue 2, p. 299-312
ISSN: 1810-5467
Research in the field of entrepreneurship has become an intriguing area for further investigation. In an era where digital advancements are ubiquitous, previous researchers have identified a gap: the lack of a specific instrument to identify digital entrepreneur skills. Therefore, this study aims to determine the constructs of students' digital entrepreneur skills. The analysis techniques include confirmatory factor analysis (CFA), exploratory factor analysis (EFA), Pearson correlation, Kendall's, Spearman's, and Cronbach's alpha. The study was conducted over five phases with 235 participants from university students in Indonesia who run or own a business. The results revealed strong instrument validity with robustness ranging from significant Pearson, Kendall's, and Spearman's analyses (<0.05) and Cronbach's alpha (>0.60). The exploratory factor analysis indicated a Kaiser-Meyer-Olkin value of 0.954 (>0.05) and Bartlett's test (0.000 < 0.05), with all items having values of anti-image (>0.50), communalities (> 0.50), and factor loadings (> 0.40), uncovering three components. Lastly, the CFA demonstrated an overall good fit model, with high first-order factor loadings (>0.60) and a second-order construct digital entrepreneur skills comprising three components: interpersonal digital skills with a factor loading of 0.890, idea and technology management skills (0.920), and adaptation and innovation skills (1.020). The study highlights the critical need for students to develop digital entrepreneurial skills encompassing interpersonal digital skills, ideation, and technology management, as well as adaptation and innovation abilities to thrive in the digital economy and enhance their personal and professional growth.
AcknowledgmentI want to thank all those who have helped make this research a success, especially for Sebelas Maret University as a place of affiliation and all respondents willing to participate in my study.