CONCEPTUALISING COMMUNICATION MEDIA AND FARMER’S REACTION IN PROBLEM SOLVING

2018 ◽  
Vol 6 (1) ◽  
pp. 01-07
Author(s):  
Idris Bin Ismail ◽  
Rosidayu Sabran ◽  
Yahya Bin Mohamed Ariffin
Keyword(s):  
Factor Analysis ◽  
Problem Solving ◽  
Exploratory Factor Analysis ◽  
Common Factor ◽  
Quantitative Measure ◽  
Information Delivery ◽  
Communication Media ◽  
Local Context ◽  
Governance Reform ◽  
New Research

Purpose: Agricultural Extension Services (AES) under structural governance reform that aimed to curb AES situational problem like insufficient of information delivery, suggested communication media principally radio as a tool for farmers to keep up with newest idea and information about agriculture technology and practices. It shows that, radio role is still pertinent on delivery of information for production output. Beyond that, this study is to examine radio as new concept that allow feedback and influence farmer’s information behavior in dealing with AES problem. Methodology: This study propose the reaction of Malaysian paddy farmers could be shape to view insufficient of information delivery within AES as being intervention in increasing farmers’ utilization of communication media such radio. Drawing upon Kim and Grunig (2011) Situational Theory Problem Solving (STOPS) as the framework, aside from looking at the perception of publics towards certain problem. This study  construct a quantitative measure of radio through exploratory factor analysis using principal components with varimax rotation to assess the performance of each item in measuring their respective variables and to be examined within STOPS. An extensive reviews of literature then produced preliminary factor and items that were tested through a survey distributed among 110 respondents. Findings: Exploratory factor analysis found the items fell into common factor group and finalized with seven (7) items of measurement for future study. Practical Implications: These results offer initial guidance into the relevance of radio effected farmer’s reaction in problem solving within the proposed model of the STOPS especially at local context. Social Implications: Study forwarded the idea of communication method that assisted public to be connected towards identified problem. Radio can be used to create awareness, share information and give a voice to the community Research Limitations: New research to further investigate other needs of famers through the use of combination of media not specifically on radio only. Originality Value: Study examined the role of radio in farmer’s reaction in problem solving towards insufficient information delivery to fill the gap of knowledge within the framework of the STOPS.

Exploratory Factor Analysis

2018 ◽  
Author(s):  
Brian D. Haig
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Common Factor ◽  
Methodological Issues ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Scientific Inference ◽  
Confirmatory Factor ◽  
The Common

Chapter 6 argues that exploratory factor analysis is an abductive method of theory generation that exploits a principle of scientific inference known as the principle of the common cause. Factor analysis is an important family of multivariate statistical methods that is widely used in the behavioral and social sciences. The best known model of factor analysis is common factor analysis, which has two types: exploratory factor analysis and confirmatory factor analysis. A number of methodological issues that arise in critical discussions of exploratory factor analysis are considered. It is suggested that exploratory factor analysis can be profitably employed in tandem with confirmatory factor analysis.

scholarly journals The Novel Paradigm of Economics Driven for Local Smart Sustain Cities Modeling Using Exploratory Factor Analysis and Planning Technique Using Fuzzy Evaluation Decision Making

2020 ◽  
Vol 12 (3) ◽  
pp. 793
Author(s):  
Mode Vasuaninchita ◽  
Varin Vongmanee ◽  
Wanchai Rattanawong
Keyword(s):  
Decision Making ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Smart City ◽  
Smart Cities ◽  
Local Context ◽  
Fuzzy Evaluation ◽  
Analysis Technique ◽  
Planning Technique ◽  
Evaluation Decision

The Smart Cities (SCs) models currently widely employed are identical and inconsiderate of Economics Driven (ED), Local Context (LC), and Sustainability (St) factors. These are key factors to driving, constructing, and developing smart cities. This paper presents a process wherein “the Local Smart Sustain Cities Model (LSSCsM)” is combined and modeled with Exploratory Factor Analysis technique (EFA) to design a smart city that fits the local features of a given area. This particular process creates a Smart Cities Model (SCsM) that has unique sustainability and local context factors. This paper also presents the smart cities Priority Action Ranking (PAR) process using Fuzzy Logic Decision Making (FLDM) to evaluate the strengths and weaknesses of each smart city economics driver and characteristic and prioritize the direction planning of each factor and characteristic. The resulting smart cities model can then be used as the foundation of sustainable smart cities that avoid the pitfall of using incompatible smart cities models as the base and consequently failing, thus avoiding the extravagant costs associated with an unsuccessful project of such scale.

scholarly journals Application of Financial Cloud in the Sustainable Development of Smart Cities

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Yangchun Cao ◽  
Guangyu Zhang ◽  
Chunyao Ou
Keyword(s):  
Sustainable Development ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Structural Equation ◽  
Comprehensive Evaluation ◽  
Smart Cities ◽  
Evaluation Model ◽  
Common Factor ◽  
The Sustainable Development ◽  
Evaluation Score

This article first investigates the status of financial cloud development in smart cities and studies the sustainable development of smart cities. Secondly, it investigates the construction of the evaluation model, using the power of the financial cloud, through exploratory factor analysis, selecting the principal component analysis method to extract the factors, for screening and dimensionality reduction of the indicators, and making hypotheses. We used confirmatory factor analysis to establish the structural equation. The measurement model analyzes and validates the assumptions of the previous stage and finally determines the sustainable development evaluation index system. Then, starting from the scoring coefficient matrix of the exploratory factor analysis of the final model, the variance contribution rate of each common factor is weighted to construct a comprehensive evaluation model to calculate the comprehensive evaluation score. For the comprehensive evaluation score of the sustainable development level of the smart city, SPSS software performs cluster analysis, performs regional clustering, and determines the level of urban development. Finally, by comparing the sustainable development levels of smart cities, the related causes of the gaps are analyzed. Key factors affecting the sustainable development of smart cities are identified, and corresponding countermeasures are proposed.

scholarly journals Cross-cultural adaptation and exploratory factor analysis of the Person-centred Practice Inventory - Staff (PCPI-S) questionnaire among Malaysian primary healthcare providers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nur Zahirah Balqis-Ali ◽  
Pui San Saw ◽  
Anis Syakira Jailani ◽  
Weng Hong Fun ◽  
Noridah Mohd Saleh ◽  
...  
Keyword(s):  
Primary Care ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Internal Consistency ◽  
Healthcare Providers ◽  
Local Context ◽  
Care Practice ◽  
Underlying Structure ◽  
Expert Committee ◽  
Local Practice

Abstract Background The Person-centred Practice Inventory-Staff (PCPI-S) instrument was developed to measure healthcare providers’ perception towards their person-centred practice. The study aimed to explore the influence of culture, context, language and local practice towards the PCPI-S instrument adaptation process for use among public primary care healthcare providers in Malaysia. Methods The original PCPI-S was reviewed and adapted for cultural suitability by an expert committee to ensure conceptual and item equivalence. The instrument was subsequently translated into the local Malay language using the forward-backward translation by two independent native speakers, and modified following pre-tests involving cognitive debriefing interviews. The psychometric properties of the corresponding instrument were determined by assessing the internal consistency, test-retest reliability, and correlation of the instrument, while the underlying structure was analysed using exploratory factor analysis. Results Review by expert committee found items applicable to local context. Pre-tests on the translated instrument found multiple domains and questions were misinterpreted. Many translations were heavily influenced by culture, context, and language discrepancies. Results of the subsequent pilot study found mean scores for all items ranged from 2.92 to 4.39. Notable ceiling effects were found. Internal consistency was high (Cronbach’s alpha > 0.9). Exploratory factor analysis found formation of 11 components as opposed to the original 17 constructs. Conclusion The results of this study provide evidence regarding the reliability and underlying structure of the PCPI-S instrument with regard to primary care practice. Culture, context, language and local practice heavily influenced the adaptation as well as interpretation of the underlying structure and should be given emphasis when translating person-centred into practice.

scholarly journals Cross-Cultural Adaptation and Exploratory Factor Analysis of The Person-Centred Practice Inventory-Staff (PCPI-S) Questionnaire Among Malaysian Primary Healthcare Providers

2020 ◽  
Author(s):  
Nur Zahirah Balqis-Ali ◽  
Pui San Saw ◽  
Anis Syakira Jailani ◽  
Weng Hong Fun ◽  
Noridah Mohd Saleh ◽  
...  
Keyword(s):  
Primary Care ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Internal Consistency ◽  
Healthcare Providers ◽  
Local Context ◽  
Care Practice ◽  
Underlying Structure ◽  
Expert Committee ◽  
Local Practice

Abstract Background: The Person-Centred Practice Inventory-Staff (PCPI-S) instrument was developed to measure healthcare providers’ perception towards their person-centred practice. The study aimed to explore the influence of culture, context, language and local practice towards the PCPI-S instrument adaptation process for use among public primary care healthcare providers in Malaysia.Methods: The original PCPI-S was reviewed and adapted for cultural suitability by an expert committee to ensure conceptual and item equivalence. The instrument was subsequently translated into the local Malay language using the forward-backward translation by two independent native speakers, and modified following pre-tests involving cognitive debriefing interviews. The psychometric properties of the corresponding instrument were determined by assessing the internal consistency, test-retest reliability, and correlation of the instrument, while the underlying structure was analysed using exploratory factor analysis.Results: Review by expert committee found items applicable to local context. Pre-tests on the translated instrument found multiple domains and questions were misinterpreted. Many translations were heavily influenced by culture, context, and language discrepancies. Results of subsequent pilot study found mean scores for all items ranged from 2.92 to 4.39. Notable ceiling effects were found. Internal consistency was found to be high (Cronbach’s alpha > 0.9). Exploratory factor analysis found formation of 11 components as opposed to the original 17 constructs. Conclusion: The results of this study provide evidence regarding the reliability and underlying structure of the PCPI-S instrument with regard to primary care practice. Culture, context, language and local practice heavily influenced the adaptation as well interpretation of the underlying structure and should be given emphasis when translating person-centred into practice.Trial registration: NMRR-18-309-40447

scholarly journals One model to rule them all? Using machine learning algorithms to determine the number of factors in exploratory factor analysis.

2020 ◽  
Author(s):  
David Goretzko ◽  
Markus Bühner
Keyword(s):  
Machine Learning ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Learning Algorithms ◽  
Common Factor ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
New Approach ◽  
Correct Number ◽  
Number Of Factors

Determining the number of factors is one of the most crucial decisions a researcher has to face when conducting an exploratory factor analysis. As no common factor retention criterion can be seen as generally superior, a new approach is proposed - combining extensive data simulation with state-of-the-art machine learning algorithms. First, data was simulated under a broad range of realistic conditions and three algorithms were trained using specially designed features based on the correlation matrices of the simulated data sets. Subsequently, the new approach was compared to four common factor retention criteria with regard to its accuracy in determining the correct number of factors in a large-scale simulation experiment. Sample size, variables per factor, correlations between factors, primary and cross-loadings as well as the correct number of factors were varied to gain comprehensive knowledge of the efficiency of our new method. A gradient boosting model outperformed all other criteria, so in a second step, we improved this model by tuning several hyperparameters of the algorithm and using common retention criteria as additional features. This model reached an out-of-sample accuracy of 99.3% (the pre-trained model can be obtained from https://osf.io/mvrau/). A great advantage of this approach is the possibility to continuously extend the data basis (e.g. using ordinal data) as well as the set of features to improve the predictive performance and to increase generalizability.

scholarly journals Exploratory factor analysis on situational judgment data after controling for scenario effect

2013 ◽  
Vol 26 (4) ◽  
pp. 599-624
Author(s):  
JunJae Namgung ◽  
Soonmook Lee ◽  
HyoSun Kim
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Exploratory Factor Analysis ◽  
Structural Equation ◽  
Common Factor ◽  
Equation Modeling ◽  
Situational Judgment ◽  
Method Effect ◽  
Creative Personality ◽  
Judgment Data

We demonstrated how to perform exploratory factor analysis on situational judgment data of creative personality. Situational judgment test(SJT) has a long history of 80 years and has settled down in industrial/organizational settings for the last 20 years. However, we have not overcome the problem of estimating construct because item scores in SJT contain method effect generated by the scenarios as well as response scores to the substantive questions. We applied Asparouhov and Muthen’s(2009) logic of explorary structural equation modeling(ESEM) to open an approach to estimating common factor structures after controling for the method effect generated by scenarios. Using ESEM, it is possible to specify measurement error correlations in the frame of structural equation modeling and to use exploratory approach to factor analysis on the remaining part of data. As a result we could estimate a four-factor structure on data of 40 items with eight scenarios measuring creative personality of college students.

scholarly journals Development and Validation of the Readiness for End-of-Life Conversations (REOLC) Scale

2021 ◽  
Vol 12 ◽  
Author(s):  
Pia Berlin ◽  
Nico Leppin ◽  
Katharina Nagelschmidt ◽  
Carola Seifart ◽  
Winfried Rief ◽  
...  
Keyword(s):  
Factor Analysis ◽  
End Of Life ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Community Sample ◽  
Common Factor ◽  
Death And Dying ◽  
Living Will ◽  
Equation Modeling ◽  
Fear Of Progression

Background: Engaging in end-of-life care considerations is beneficial when the time is right. The purpose of this study is to provide a valid instrument to assess peoples readiness for end-of-life conversations before they are initiated.Materials and Methods: A community sample was recruited in study one for exploratory factor analysis of a 13-item questionnaire. In study two, psychometric properties were analyzed with structural equation modeling in a population affected by cancer. Convergent and discriminant validity were assessed with questionnaires measuring distress, depression, anxiety, fear of progression, and distress of death and dying.Results: In study one (N = 349) exploratory factor analysis resulted in three subscales readiness (α = 0.84), communication (α = 0.76), and values (α = 0.56) with a possible common factor (α = 0.84) for a community sample. In study two (N = 84) the three-factor solution with 13 items was not supported for cancer patients. Factor structure was adapted to 12 items with one common factor readiness (α = 0.87). Model fit was good: χ2(50) = 59.18, p>0.05 (Satorra-Bentler-correction = 1.27), with χ2/df = 1.184, rRMSEA = 0.053 (90%-CI[0.000;0.100]), and rSRMR = 0.072. Convergent validity was supported by moderate correlations to trait gratitude, ratings of readiness to provide a living will or talk with family about the end of life. Divergent validity was supported by no or small correlation with distress, depression, general and death anxiety and fear of progression, respectively.Conclusions: Results support usage of the REOLC Scale in different settings with adapted factor structure. The questionnaire is interpreted as valid and reliable instrument to assess objective readiness for end-of-life conversations.

STUDY OF SITUATIONAL THEORY OF PROBLEM SOLVING (STOPS) IN CONCEPTUALIZING FARMER’S RESPONSE TOWARDS INSUFFICIENT INFORMATION DELIVERY IN MALAYSIA

2017 ◽  
Vol 5 (2) ◽  
pp. 124-133 ◽  
Author(s):  
Idris Bin Ismail ◽  
Rosidayu Sabran ◽  
Mohd Yahya Bin Mohamed Ariffin
Keyword(s):  
Problem Solving ◽  
Future Study ◽  
Communicative Action ◽  
Governance Structure ◽  
Information Delivery ◽  
Local Context ◽  
Insufficient Information ◽  
Communicative Behavior ◽  
Upward Communication ◽  
Exploratory Data

Purpose: Insufficiency of information delivery within agricultural extension services (AES) is a worldwide concern and been recognized as unresolved debate. This issue triggered AES on governance structure demand upward communication to encourage more input at farm level to allow farmers to make a decision and improve their ability to problem-solving. Methodology:  This research includes review the literature on the issue, the theoretical arguments of STOPS and finally to test the items for the measurement of farmers’ response in this problem and identified items for future study. Items were tested through a survey distributed to 110 respondents. The exploratory data analysis was performed using principal components with varimax rotation to assess the performance of each items in measuring their respective variables. Study only retained items that loaded on the variables at .50 cut off criterion, and the Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO more than .50 Findings: Result of analysis found the items fell into factor groups as suggested by theory and finalized with 58 items of measurement for future study. Practical implications: These results offer initial guidance into the relevance of STOPS on farmers response in problem-solving towards insufficient information delivery within AES and how they react to issues that affect them. Social Implications: The investigation of STOPS on the sample in the local context of the public would provide a deeper understanding of farmers in Malaysia on their dimensions of conceptual of situational perception, communicative behavior and motivation in problem-solving towards insufficient of information delivery. Research Limitation: Evaluation of Malaysian farmer’s perception and communicative action is limited to the theoretical proposition of STOPS. Originality Value: Study unleashed farmers response in problem-solving capacity towards insufficient of information delivery which have not been fully addressed through the assumption and concept of STOPS.

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