A Factor Analysis Methodology for Analyzing the Competencies Affecting Entrepreneurs of SMEs

2019 ◽  
Author(s):  
Ankita Bajpai ◽  
Gajendra Singh
Keyword(s):  
Factor Analysis ◽  
Analysis Methodology

DEVELOPING A TAXONOMY FOR IDENTIFYING ENTREPRENEURIAL RISK: AN EMPIRICAL STUDY ON ENTREPRENEURIAL RISK PATTERNS OF BUSINESS ENTERPRISES

2014 ◽  
Vol 19 (01) ◽  
pp. 1450002 ◽  
Author(s):  
D. ANTHONY MILES
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Predictor Variable ◽  
Multivariate Regression Analysis ◽  
The Body ◽  
Business Failure ◽  
Behavioral Characteristics ◽  
Industry Type ◽  
Analysis Methodology ◽  
Business Enterprises

Most of the prior research on entrepreneurial risk concentrates on entrepreneur behavioral characteristics, personality traits and characteristics. Very little of the body of research examines the market behavior of the firm and its risk patterns that can cause business failure. The purpose of this research was to develop a taxonomy of entrepreneurial risk behaviors and examine their effect on small business enterprises (SME). The study was the development and administration of the Entrepreneurial Risk Survey (ERS) instrument. ERS was used to empirically examine a sample (N = 201) of SMEs across 11 industries for the proposed taxonomy of 22 risk variables. An exploratory factor analysis methodology was conducted for the study. The principle component analysis was conducted and resulted in an eight-factor solution. A multivariate regression analysis was also used to measure the industry type as a predictor variable. The results of the exploratory factor analysis (EFA) indicated there are eight factors of entrepreneurial risk that affect SMEs.

scholarly journals The Factors Impact on the Service Quality of People’s Credit Funds: The Case of Mekong Delta River in Vietnam

2017 ◽  
Vol 6 (2) ◽  
pp. 150
Author(s):  
Tran Thi Thanh Tu ◽  
Do Hong Nhung ◽  
Dang Ngoc Duc
Keyword(s):  
Factor Analysis ◽  
Service Quality ◽  
Mekong Delta ◽  
Analysis Methodology ◽  
Explanatory Factor Analysis

The paper used results of the survey of 100 clients from 24 PCFs in 3 provinces in the Mekong Delta River in Vietnam. By applying Explanatory Factor Analysis methodology, the result of study showed that  tangibles (TAN), responsiveness (RES), reliability (REL), assurances (ASS), and empathy (EMP)affecting to the service quality of PCFs in Mekong Delta River in Vietnam. The research found that PCFs’ service quality would be increased if their empathy and tangibility improved. Then, PCFs’ managers should pay more on creating incentives for credit officers to improve their sympathy and understanding customers needs as well as enhancing appearances of PCF staffs and transaction offices.

scholarly journals Hierarchical Factor Analysis Methodology for Intelligent Manufacturing

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hyun Sik Sim
Keyword(s):  
Factor Analysis ◽  
Product Quality ◽  
Structural Model ◽  
Product Yield ◽  
Intelligent Manufacturing ◽  
Difficult Problem ◽  
Process Equipment ◽  
Key Factors ◽  
Analysis Methodology ◽  
Hierarchical Factor Analysis

To realize intelligent manufacturing, a controllable factory must be built, and manufacturing competitiveness must be achieved through the improvement of product quality and yield. The yield in the micromanufacturing process is gaining importance as a management factor used in deciding the production cost and product quality as product functions becomes more sophisticated. Because the micromanufacturing process involves manufacturing products through multiple steps, it is difficult to determine the process or equipment that has encountered failure, which can lead to difficulty in securing high yields. This study presents a structural model for building a factory integration system to analyze big data at manufacturing sites and a hierarchical factor analysis methodology to increase product yield and quality in an intelligent manufacturing environment. To improve the product yield, it is necessary to analyze the fault factors that cause low yields and locate and manage the critical processes and equipment factors that affect these fault factors. However, yield management is a difficult problem because there exists a correlation between equipment, and in the sequence of process equipment that the lot passed through, the downstream and the upstream cause complex faults. This study used data-mining techniques to identify suspected processes and equipment that affect the yield of products in the manufacturing process and to analyze the key factors of the equipment. Ultimately, we propose a methodology to find the key factors of the suspected process and equipment that directly affect the implementation of the intelligent manufacturing scheme and the yield of the product. To verify the effect of key parameters of critical processes and equipment on the yield, the proposed methodology was applied to actual manufacturing sites.

Factor Analysis of Measures of Articulation, Language, Auditory Processing, Reading-Spelling, and Maxillofacial Structure

1977 ◽  
Vol 20 (2) ◽  
pp. 319-324
Author(s):  
Anita F. Johnson ◽  
Ralph L. Shelton ◽  
William B. Arndt ◽  
Montie L. Furr
Keyword(s):  
Factor Analysis ◽  
Clinical Judgment ◽  
Auditory Processing

This study was concerned with the correspondence between the classification of measures by clinical judgment and by factor analysis. Forty-six measures were selected to assess language, auditory processing, reading-spelling, maxillofacial structure, articulation, and other processes. These were applied to 98 misarticulating eight- and nine-year-old children. Factors derived from the analysis corresponded well with categories the measures were selected to represent.

Evidence-based subtypes in functional dyspepsia with confirmatory factor analysis: Psychosocial and physiopathological correlates

2001 ◽  
Vol 120 (5) ◽  
pp. A51-A52 ◽  
Author(s):  
B FISCHLER ◽  
J VANDENBERGHE ◽  
P PERSOONS ◽  
V GUCHT ◽  
D BROEKAERT ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Functional Dyspepsia ◽  
Evidence Based ◽  
Confirmatory Factor

The French Version of the Revised Child Anxiety and Depression Scale (RCADS) in a Nonclinical Sample

2015 ◽  
Vol 74 (3) ◽  
pp. 119-127 ◽  
Author(s):  
Martine Bouvard ◽  
Anne Denis ◽  
Jean-Luc Roulin
Keyword(s):  
Factor Analysis ◽  
Anxiety Disorder ◽  
Confirmatory Factor Analysis ◽  
Generalized Anxiety Disorder ◽  
Child Anxiety ◽  
Depression Scale ◽  
Anxiety And Depression ◽  
Generalized Anxiety ◽  
French Version ◽  
Confirmatory Factor

This article investigates the psychometric properties of the Revised Child Anxiety and Depression Scale (RCADS). A group of 704 adolescents completed the questionnaires in their classrooms. This study examines potential confirmatory factor analysis factor models of the RCADS as well as the relationships between the RCADS and the Screen for Child Anxiety Related Emotional Disorders-Revised (SCARED-R). A subsample of 595 adolescents also completed an anxiety questionnaire (Fear Survey Schedule for Children-Revised, FSSC-R) and a depression questionnaire (Center for Epidemiological Studies Depression Scale, CES-D). Confirmatory factor analysis of the RCADS suggests that the 6-factor model reasonably fits the data. All subscales were positively intercorrelated, with rs varying between .48 (generalized anxiety disorder-major depression disorder) and .65 (generalized anxiety disorder-social phobia/obsessive-compulsive disorder). The RCADS total score and all the RCADS scales were found to have good internal consistency (> .70). The correlations between the RCADS subscales and their SCARED-R counterparts are generally substantial. Convergent validity was found with the FSSC-R and the CES-D. The study included normal adolescents aged 10 to 19. Therefore, the findings cannot be extended to children under 10, nor to a clinical population. Altogether, the French version of the RCADS showed reasonable psychometric properties.

Measuring Impact of Stress in Sandwich Generation Caring for Demented Parents

GeroPsych ◽  
2014 ◽  
Vol 27 (4) ◽  
pp. 171-179 ◽  
Author(s):  
Laurence M. Solberg ◽  
Lauren B. Solberg ◽  
Emily N. Peterson
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Social Worker ◽  
Resource Availability ◽  
Well Being ◽  
Sandwich Generation ◽  
Item Questionnaire ◽  
Significant Difference ◽  
Adult Caregivers ◽  
The Impact

Stress in caregivers may affect the healthcare recipients receive. We examined the impact of stress experienced by 45 adult caregivers of their elderly demented parents. The participants completed a 32-item questionnaire about the impact of experienced stress. The questionnaire also asked about interventions that might help to reduce the impact of stress. After exploratory factor analysis, we reduced the 32-item questionnaire to 13 items. Results indicated that caregivers experienced stress, anxiety, and sadness. Also, emotional, but not financial or professional, well-being was significantly impacted. There was no significant difference between the impact of caregiver stress on members from the sandwich generation and those from the nonsandwich generation. Meeting with a social worker for resource availability was identified most frequently as a potentially helpful intervention for coping with the impact of stress.

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