Measurement of the Effects of Regional Policy Instruments

1980 ◽  
Vol 12 (10) ◽  
pp. 1191-1202 ◽  
Author(s):  
H Folmer
Keyword(s):  
Structural Equation Model ◽  
Measurement Errors ◽  
Structural Equation ◽  
Regional Policy ◽  
Policy Instruments ◽  
Equation Model ◽  
Policy Effects ◽  
Methodological Problems

In the literature on measuring of the effects of regional policy four methodological problems can be distinguished: First, handling the multidimensional nature of the regional profile; second, separation of policy effects from autonomous developments; third, comparison of different policy instruments; and fourth, handling theoretical constructs and measurement errors. In this paper a linear structural equation model is formulated that overcomes these problems. The paper concludes with a case study of the situation in Holland during the period 1974–1975.

Measurement of the Effects of Regional Policy Instruments by Means of Linear Structural Equation Models and Panel Data

1981 ◽  
Vol 13 (11) ◽  
pp. 1435-1448 ◽  
Author(s):  
H Folmer
Keyword(s):  
Time Series ◽  
Measurement Errors ◽  
Structural Equation ◽  
Regional Policy ◽  
Structural Equation Models ◽  
Time Series Data ◽  
Policy Instruments ◽  
Equation Model ◽  
Series Data ◽  
Cross Sectional

Two kinds of problems have generally been encountered in measuring the effects of instruments of regional policy. The first concerns the construction of an adequate method, which should (a) take explicitly into account the multidimensional character of a regional profile, (b) disentangle policy effects from autonomous developments, (c) make it possible to compare the effects of different policy instruments, and (d) be capable of dealing with theoretical constructs and measurement errors. The second problem relates to the scarcity of regional data, both concerning time-series and cross-sectional data. A linear structural equation model is presented which meets the first set of conditions. This model is then modified in such a way that it can be estimated by pooling cross-sectional and time-series data, thus increasing the number of observations. In addition, as an application the effects of regional industrialization policy on investments in the Netherlands during the period 1973–1976 are estimated.

scholarly journals Empirical Underidentification with the Bifactor Model: A Case Study

2017 ◽  
Vol 78 (5) ◽  
pp. 717-736 ◽  
Author(s):  
Samuel Green ◽  
Yanyun Yang
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Equation Model ◽  
Bifactor Model ◽  
Data Sets ◽  
Bifactor Models

Bifactor models are commonly used to assess whether psychological and educational constructs underlie a set of measures. We consider empirical underidentification problems that are encountered when fitting particular types of bifactor models to certain types of data sets. The objective of the article was fourfold: (a) to allow readers to gain a better general understanding of issues surrounding empirical identification, (b) to offer insights into empirical underidentification with bifactor models, (c) to inform methodologists who explore bifactor models about empirical underidentification with these models, and (d) to propose strategies for structural equation model users to deal with underidentification problems that can emerge when applying bifactor models.

scholarly journals THE ANTECEDENT OF CUSTOMER SATISFACTION

2020 ◽  
Author(s):  
Andala Rama Putra Barusman ◽  
Evelin Putri Rulian ◽  
Susanto Susanto
Keyword(s):  
Customer Satisfaction ◽  
Structural Equation Model ◽  
Customer Relationship Management ◽  
Structural Equation ◽  
Hospitality Industry ◽  
Relationship Management ◽  
Customer Retention ◽  
Equation Model ◽  
Customer Relationship

Taking a case study of tourism as hospitality industry in Lampung Province in Indonesia, we analyze the antecedent of customer satisfaction and its impact on customer retention. Using Structural Equation Model (SEM), we find that customer relationship management has a significant impact on service quality, customer satisfaction and customer retention.

scholarly journals Structural Equation Model on Factors Affecting Students Satisfaction towards University Library: A Case Study

2021 ◽  
Vol 6 (2) ◽  
pp. 23-33
Author(s):  
Zahayu Md Yusof ◽  
Masnita Misiran ◽  
Hasimah Sapiri ◽  
Massudi Mahmuddin
Keyword(s):  
Structural Equation Model ◽  
Undergraduate Students ◽  
Structural Equation ◽  
Equation Model ◽  
Online Services ◽  
Factors Affecting ◽  
Library Management ◽  
University Library ◽  
Students Satisfaction

Library in the university is known as the centre of knowledge. University library offers learning support, research requirement and also teaching materials. The objective of this study is to identify the most (and least) factors that contribute to students satisfaction towards university library. A case study on selected respondents consist of 266 undergraduate students was conducted. Their opinion on the library services has been recorded. Questionnaires were distributed to the respondents. Structural Equation Model was developed to display their responses. The finding concluded that online services and collections have significant relationship with the overall satisfaction towards the library, whereas facilities and library staffs do not have significant contribution to the satisfaction. As a suggestion, the library management should improve their service quality by upgrading the online services such as wireless access, library website service,  and online book renewal process to mentioned a few, which might be effective in improving the students’ satisfaction towards the library.

scholarly journals A SYSTEMATIC REVIEW OF STRUCTURAL EQUATION MODEL (SEM)

2020 ◽  
Vol 1 (2) ◽  
pp. 27-39
Author(s):  
H. O. Owolabi ◽  
J. K. Ayandele ◽  
D. D. Olaoye
Keyword(s):  
Structural Equation Model ◽  
Measurement Errors ◽  
Structural Equation ◽  
Statistical Technique ◽  
Equation Model ◽  
Equation Modeling ◽  
Weak Assumption ◽  
Multivariate Statistical ◽  
Software Packages ◽  
Complex Relationships

Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to test relationships between variables. The use of SEM to analyze relationship between variables is premised on the weak assumption of path analysis, regression analysis and so on; that variables are measured without error. This review thus sheds light on the meaning of SEM, its assumptions, steps and some of the terms used in SEM. The importance of item parcelling to SEM and its methods were briefly examined. It also dealt on the stages involved in SEM, similarities and differences between SEM and conventional statistical methods, software packages that can be used for SEM. This article employed systematic literature review method because it critically synthesized research studies and findings on structural equation modeling (SEM). It could be concluded that SEM is useful in analyzing a set of relationships between variables using diagrams. SEM can also be useful in minimizing measurement errors and in enhancing reliability of constructs. Based on this, it is recommended that SEM should be employed to test relationship between variables since it can explore complex relationships among variables such as direct, indirect, spurious, hierarchical and non-hierarchical.

scholarly journals PENGARUH KUALITAS PELAYANAN TERHADAP LOYALITAS NASABAH DENGAN KEPUASAN NASABAH SEBAGAI VARIABEL INTERVENING (PT BANK RAKYAT INDONESIA PERSERO TBK CABANG BANJARMASIN SAMUDERA)

2021 ◽  
Vol 10 (2) ◽  
pp. 24
Author(s):  
Nadia Mauliditta Septiana ◽  
Dwi Wahyu Artiningsih ◽  
Hairudinor Hairudinor
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Structural Equation Model ◽  
Customer Loyalty ◽  
Structural Equation ◽  
Hypothesis Test ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square

The purpose of this study is to analyze the Effect of Service Quality on Customer Loyalty with Customer Satisfaction (Case Study of PT Bank Rakyat Indonesia Persero Tbk Banjarmasin Samudera Branch. The type used in this research is explanatory research because this research explains the causal relationship between research variables through the hypothesis test that has been formulated previously. The analytical method uses Structural Equation Model (SEM) with Partial Least Square (PLS) Program. The results of this study prove that Service Quality has no effect on Customer Satisfaction at BRI Bank Prince Samudera Banjarmasin Branch, while Customer Satisfaction has a positive and significant effect on Customer Loyalty. And Service Quality has a positive and significant effect on Customer Loyalty.The results of this study prove that Service Quality has no effect on Customer Satisfaction at BRI Bank Prince Samudera Banjarmasin Branch, while Customer Satisfaction has a positive and significant effect on Customer Loyalty. And Service Quality has a positive and significant effect on Customer Loyalty.Keywords: Service Quality, Customer Loyalty, and Customer Satisfaction

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