Journal articles: 'Structural equation modeling technique'

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Bolla, Marianna, and Fatma Abdelkhalek. "Kalman's filtering technique in structural equation modeling." Studia Universitatis Babes-Bolyai Matematica 66, no. 1 (March 20, 2021): 179–96. http://dx.doi.org/10.24193/subbmath.2021.1.15.

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"Structural equation modeling finds linear relations between exogenous and endogenous latent and observable random vectors. In this paper, the model equations are considered as a linear dynamical system to which the celebrated R.~E.~K\'alm\'an's filtering technique is applicable. An artificial intelligence is developed, where the partial least squares algorithm of H.~Wold and the block Cholesky decomposition of H.~Kiiveri et al. are combined to estimate the parameter matrices from a training sample. Then the filtering technique introduced is capable to predict the latent variable case values along with the prediction error covariance matrices in the test sample. The recursion goes from case to case along the test sample, without having to re-estimate the parameter matrices. The algorithm is illustrated on real life sociological data."

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Rahmasari, Lisda. "Analisis Pengaruh Orientasi Kewirausahaan, Inovasi, dan Kapabilitas Pemasaran terhadap Keunggulan Bersaing pada UKM Olahan Ikan di Semarang." Jurnal Ilmiah Aset 23, no. 1 (March 31, 2021): 21–30. http://dx.doi.org/10.37470/1.23.1.174.

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This study aimed to find out the influence of entrepreneurial orientation, innovation and marketing capabilities on competitive advantage. The research population comprised Fish Processing Business in Semarang City. The sample was selected by means of the purposive sampling technique. The sample was 100 companies. The data were collected by a questionnaire, interviews, and documentation. This research uses Structural Equation Modeling (SEM) analysis technique using AMOS 24.0 analysis tool. The test results using Structural Equation Modeling (SEM) analysis techniques indicate that the model is in accordance with population data. The results of the study showed that entrepreneurship oriented , innovation and marketing capabilities had a significant positive effect on competitive advantage. Used by analyzer for example validity test, test reliabilitas, and hipotesis test use modelling equation structural (SEM).

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Razak, Nor Iza Anuar, Zamira Hasanah Zamzuri, and Nur Riza Mohd Suradi. "Bootstrapping technique in structural equation modeling: a Monte Carlo study." Journal of Physics: Conference Series 1132 (November 2018): 012072. http://dx.doi.org/10.1088/1742-6596/1132/1/012072.

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Lam, Tzeng Yih, and Douglas A. Maguire. "Structural Equation Modeling: Theory and Applications in Forest Management." International Journal of Forestry Research 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/263953.

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Forest ecosystem dynamics are driven by a complex array of simultaneous cause-and-effect relationships. Understanding this complex web requires specialized analytical techniques such as Structural Equation Modeling (SEM). The SEM framework and implementation steps are outlined in this study, and we then demonstrate the technique by application to overstory-understory relationships in mature Douglas-fir forests in the northwestern USA. A SEM model was formulated with (1) a path model representing the effects of successively higher layers of vegetation on late-seral herbs through processes such as light attenuation and (2) a measurement model accounting for measurement errors. The fitted SEM model suggested a direct negative effect of light attenuation on late-seral herbs cover but a direct positive effect of northern aspect. Moreover, many processes have indirect effects mediated through midstory vegetation. SEM is recommended as a forest management tool for designing silvicultural treatments and systems for attaining complex arrays of management objectives.

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Allison, Paul D. "Missing Data Techniques for Structural Equation Modeling." Journal of Abnormal Psychology 112, no. 4 (2003): 545–57. http://dx.doi.org/10.1037/0021-843x.112.4.545.

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Rigdon, Edward E. "Advanced Structural Equation Modeling: Issues and Techniques." Applied Psychological Measurement 22, no. 1 (March 1998): 85–87. http://dx.doi.org/10.1177/01466216980221008.

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HOSSAIN, Md Shakhawat, Md Golam MOSTAFA, and Md Alamgir HOSSAIN. "MODELING TOURISTS’ SATISFACTION IN THE NATURE-BASED TOURIST DESTINATION USING STRUCTURAL EQUATION MODELING TECHNIQUE." GeoJournal of Tourism and Geosites 37, no. 3 (September 30, 2021): 814–22. http://dx.doi.org/10.30892/gtg.37311-713.

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The goal of this study is to show how satisfied tourists is of supreme significance to the tourism industry, particularly as it affects the future of a nature-based destination and explores the relationship among destination image, service quality, perceived value, tourist satisfaction, word-of-mouth, and revisit intentions of tourists. The 292 survey data was obtained via a structured questionnaire from tourists who visited the Haor region, Bangladesh and structural equation modeling (SEM) is used to test the hypothetical paths. Six hypotheses were accepted, and one is rejected. Tourism stakeholders can find important knowledge and they can satisfy tourists, which is likely by improving destination.

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Singh, Rajwinder, H. S. Sandhu, B. A. Metri, and Rajinder Kaur. "Modeling Supply Chain Performance: A Structural Equation Approach." International Journal of Information Systems and Supply Chain Management 6, no. 4 (October 2013): 18–41. http://dx.doi.org/10.4018/ijisscm.2013100102.

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Supply chain management (SCM) has become an effective tool now a day to survive in this competitive world. Organizations do their best to improve performance by adopting better supply chain (SC) performance indicators. In this paper 19 key performance indicators (KPI) were identified based on strong literature support in consultation of practitioners and consultants in the field of non-livestock retailing (NLR). NLR is the retailing of agriculture and horticulture products. The technique of factor analysis using principal component analysis with Varimax rotation has classified KPI into four factors as; inventory metrics, customer metrics, flexibility metrics and growth and learning metrics. Structural Equation Modelling (SEM) approach was used to develop and validate a model for measuring SC performance of organized NLR industry based on KPI. The data for analysis was collected from top 10 organized NLR players operating in Punjab, Chandigarh, New Delhi and Gurgaon in India. The results were subjected to rigorous statistical tests for reliability and validity. Finally, these classified KPI were presented in the form of a model to measure SC performance of organized NLR industry using SEM.

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Mang’unyi, Eric E. "Exploring private universities service quality in Kenya: A structural equation modeling technique." Journal of Social Sciences (COES&RJ-JSS) 4, no. 1 (January 1, 2015): 578–96. http://dx.doi.org/10.25255/jss.2015.4.1.578.596.

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ZAIM, Selim, Ali TURKYILMAZ, Mehves TARIM, Bilal UCAR, and Oguz AKKAS. "MEASURING CUSTOMER SATISFACTION IN TURK TELEKOM COMPANY USING STRUCTURAL EQUATION MODELING TECHNIQUE." Journal of Global Strategic Management 1, no. 4 (June 15, 2010): 89. http://dx.doi.org/10.20460/jgsm.2010415842.

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Supandi, Epha Diana. "STRUCTURAL EQUATION MODELING WITH GENERALIZED STRUCTURED COMPONENT ANALYSIS ON THE RELATIONSHIP BETWEEN RENUMERATION AND MOTIVATION ON EMPLOYEE PERFORMANCE AT UIN SUNAN KALIJAGA YOGYAKARTA." MEDIA STATISTIKA 13, no. 2 (December 28, 2020): 136–48. http://dx.doi.org/10.14710/medstat.13.2.136-148.

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Structural equation modeling (SEM) is a multivariate statistical analysis technique that is used to analyze the structural relationships between observed variables and latent constructs. SEM has several methods one of which is Generalized Structured Component Analysis (GSCA). An empirical application concerning the relationship between renumeration and work motivation on employee performance is presented to illustrate the usefulness of the GSCA method. Data were collected by a questionnaire distributed to lecturers and staffs at UIN Sunan Kalijaga Yogyakarta. The result showed that the remuneration variable had a significant and positive impact on work motivation. Also, the work motivation variable had a significant and positive effect on employee performance.

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Meehan, Jeffrey C., and Gregory L. Stuart. "Using Structural Equation Modeling With Forensic Samples." Criminal Justice and Behavior 34, no. 12 (December 2007): 1560–87. http://dx.doi.org/10.1177/0093854807307026.

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Because of its many advantages, structural equation modeling (SEM) has been used with increasing frequency in behavioral science, and it is a set of techniques that can be useful in analyzing forensic research data. Issues in SEM, including theory, estimation method, sample size and data requirements, identification, and fit indices are discussed. Using a sample of data from men arrested for domestic violence perpetration and court referred to treatment, examples of path analysis, confirmatory factor analysis, and full structural models with latent variables are presented.

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Bell, Margaret E., and Jean A. Massey. "Structural Equation Modeling: An Alternative to Traditional Validation Techniques." Journal of Educational Technology Systems 14, no. 4 (June 1986): 345–52. http://dx.doi.org/10.2190/et14.4.j.

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Validation of the sequencing of objectives is an important step in structural design. Prior statistical techniques, such as the reproducibility coefficient, have yielded only summary information. In contrast, structural equation modeling provides both goodness-of-fit indices and effect coefficients for links or paths between time-ordered events, i.e., objectives. Discussed here is the application of structural equation modeling to a set of objectives in a senior-level cardiovascular nursing course. Consistent with the theory-based requirement of structural equation modeling, the objectives were developed using Robert Gagné's conditions of learning. Also discussed is the use of “t” values, which indicate statistical significance of the paths, for testing instructional links in the learning model.

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Kock, Ned. "Structural Equation Modeling with Factors and Composites." International Journal of e-Collaboration 13, no. 1 (January 2017): 1–9. http://dx.doi.org/10.4018/ijec.2017010101.

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Recent methodological developments building on partial least squares (PLS) techniques and related ideas have significantly contributed to bridging the gap between factor-based and composite-based structural equation modeling (SEM) methods. PLS-SEM is extensively used in the field of e-collaboration, as well as in many other fields where multivariate statistical analyses are employed. The author compares results obtained with four methods: covariance-based SEM with full information maximum likelihood (FIML), factor-based SEM with common factor model assumptions (FSEM1), factor-based SEM building on the PLS Regression algorithm (FSEM2), and PLS-SEM employing the Mode A algorithm (PLSA). The comparison suggests that FSEM1 yields path coefficients and loadings that are very similar to FIML's; and that FSEM2 yields path coefficients that are very similar to FIML's and loadings that are very similar to PLSA's.

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Warrah, Saleman Mashood, Khuan Wai Bing, and Hamidah Yusof. "DEVELOPING AND VALIDATING MODEL OF TEACHER QUALITY USING STRUCTURAL EQUATION MODELING (SEM) TECHNIQUE." Malaysian Online Journal of Educational Management 6, no. 3 (June 22, 2018): 1–28. http://dx.doi.org/10.22452/mojem.vol6no3.1.

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Jambakr, M. I., A. F. Yuzaherdi, J. Jauhari, A. Putra, and R. Efendi. "Structural Equation Modeling Technique for Social Application of Information Technology User Requirements’ Identification." Journal of Physics: Conference Series 1338 (October 2019): 012049. http://dx.doi.org/10.1088/1742-6596/1338/1/012049.

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Chow, Sy-Miin, Moon-ho R. Ho, Ellen L. Hamaker, and Conor V. Dolan. "Equivalence and Differences Between Structural Equation Modeling and State-Space Modeling Techniques." Structural Equation Modeling: A Multidisciplinary Journal 17, no. 2 (April 13, 2010): 303–32. http://dx.doi.org/10.1080/10705511003661553.

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Geng, Wei Feng. "The Application of Structural Equation Modeling in the Applied Linguistics Research." Applied Mechanics and Materials 687-691 (November 2014): 1532–35. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1532.

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Structural equation model is the only statistical methods that can simultaneously do comprehensive examination about the relationships between the multi-dimensional variables. It has broad application prospects in the field of applied linguistics. In this paper, combined with the applied linguistics article that choose structural equation modeling as the technique on academic journals over the past decades, then discussing the differences in domestic and foreign researchers from both content and form, after comparison and analysis, putting forward the suggestions for the application of SEM in our domestic applied linguistics.

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Priyatna, Dwicahyo Ramadhan, Raupong Raupong, and La Podje Talangko. "Estimasi Parameter Structural Equation Modeling Terhadap Kepuasan Pelanggan Layanan Telekomunikasi Menggunakan Metode Maximum Likelihood." ESTIMASI: Journal of Statistics and Its Application 1, no. 1 (January 31, 2020): 48. http://dx.doi.org/10.20956/ejsa.v1i1.9299.

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Structural Equation Modeling is a statistical technique that is able to analyze the pattern of simultan linear relationships between indicator variables and latent variables. In this study using structural equation modeling to analyze the relationship between perceived quality, perceived value, perceived bestscore, and customer satisfaction. The purpose of this study is to obtain the result parameter model estimation of structural equation modeling using maximum likelihood method and to obtain the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator. Data collected by distributing questionnaire. Collecting sample in this study using Proporsional Random Sampling technique. To measure the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator, the model chosen is the model used to measure Indonesian Customer Satisfaction Indeks. From the result of this study obtained in the amount of 92,04% with very satisfied criteria level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator with very satisfied criteria.

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Holipah, Holipah, I. Made Tirta, and Dian Anggraeni. "ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R." Majalah Ilmiah Matematika dan Statistika 19, no. 2 (September 1, 2019): 85. http://dx.doi.org/10.19184/mims.v19i2.17272.

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Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. Keywords: SEM, Multiple Group, R Program

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Curkovic, Natalija. "Using of Structural Equation Modeling Techniques in Cognitive Levels Validation." Interdisciplinary Description of Complex Systems 10, no. 3 (2012): 270–83. http://dx.doi.org/10.7906/indecs.10.3.5.

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Burkholder, Gary J., and Lisa L. Harlow. "Using structural equation modeling techniques to evaluate HIV risk models." Structural Equation Modeling: A Multidisciplinary Journal 3, no. 4 (January 1996): 348–68. http://dx.doi.org/10.1080/10705519609540051.

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Gandhi, Pranav K., L. Douglas Ried, I.-Chan Huang, Carole L. Kimberlin, and Teresa L. Kauf. "Assessment of response shift using two structural equation modeling techniques." Quality of Life Research 22, no. 3 (April 5, 2012): 461–71. http://dx.doi.org/10.1007/s11136-012-0171-1.

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Wei, Zhi Rong. "Application of Structural Equation Model and AMOS Software." Applied Mechanics and Materials 687-691 (November 2014): 1577–79. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1577.

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The Amos 17 is the structural equation model (Structural Equation Modeling, SEM), which is one of the important software analysis. With the application of SEM technology in depth, analysis of multi group structural equation model (Multiple-Group Analysis) has gradually attracted researcher’s attention.. Stability of deep test theoretical model by examining the effect of its regulating variable, and the method is not only suitable for fitting degree test theoretical models in the regulation of variables of different level, but also for the fitting problem to test the tracking data and theoretical model. Through a case study of their own, using Amos 17 software as the basis introduces the basic principle of multi group structural equation model analysis technique and its use method in the study of Applied Linguistics to domestic applied linguistics intends to use the method which will provide examples of reference.

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Khan, Noor Ullah, Wenya Wu, Roselina Binti Ahmad Saufi, Nur Ain Ayunni Sabri, and Ashfaq Ahmad Shah. "Antecedents of Sustainable Performance in Manufacturing Organizations: A Structural Equation Modeling Approach." Sustainability 13, no. 2 (January 17, 2021): 897. http://dx.doi.org/10.3390/su13020897.

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Sustainability is integral for organizations to manage environmental issues. Environmental awareness among stakeholders builds pressure on manufacturers to adopt green human resource management practices (GHRMPs), environmental management system (EMS), and foster organizational citizenship behavior for the environment (OCBE) to improve sustainable performance (SP). This study investigates the mediating effects of OCBE and EMS on the relationship between GHRMP and SP among ISO14001-certified manufacturing firms and SP. The quantitative design employed, and data of 227 respondents were analyzed via the SEM technique using AMOS 24™. Thus, findings revealed that GHRMP is positively related to SP, while OCBE and EMS partially mediated the relationship between GHRMP and SP among ISO14001-certified Malaysian manufacturing firms. This study makes novel academic and practical contributions to green HRM, organizational behavior, and sustainable performance. However, this study also has some limitations.

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Melati Pangestu, Sonny Indrajaya,. "Analysis of Online Purchase Decisions with Modeling Structural Equation Based on Variance." Jurnal Manajemen 25, no. 1 (February 21, 2021): 92. http://dx.doi.org/10.24912/jm.v25i1.705.

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The purpose of this study is to be able to test what can influence online purchasing decisions at PT. Go Online Goals. The independent variables obtained from the preliminary survey results are Promotion, Perception of Prices, and Image for Brands. The dependent variable is the decision on the purchase. This research method for analysis using data as well as Variance-Based Structural Equations using the Partial Least Square (PLS) tool. The population is residents who live in the DKI Jakarta area with a sample size of 200 respondents. The sampling technique uses convenience sampling. By using a quantitative descriptive approach. The results showed that promotion had a positive and significant effect on purchasing decisions, perceived price also had a significant positive effect on purchasing decisions, and for brand image there was a positive and significant effect on purchasing decisions.

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Anggriani, Rini, Anthony Anggrawan, and Irwan Cahyadi. "Structural Analysis of the Equation Model on Store Atmosphere towards Hedonic Value and Consumer Impulsive Buying (Study at Majapahit Food Center)." Jurnal Varian 4, no. 1 (September 29, 2020): 61–70. http://dx.doi.org/10.30812/varian.v4i1.851.

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This study aims to determine the analysis of Structural Equation Modeling (SEM) of store atmosphere on Hedonic Value and Impulsive Buying of Consumers at the Majapahit Food Center. This type of research uses causality research with a sample of respondents who are consumers who visited at Majapahit Food Center Mataram. The sampling technique used the accidental sampling technique. The study population was 100 visitors to the Majapahit Food Center. Sampling using the accidental sampling technique. The data collection technique used a questionnaire with a Likert scale measuring instrument. The data analysis method used is a validity test, reliability test, using SPSS, and data analysis using Structural Equation Modeling (SEM) with AMOS. The results of the study stated that the store atmosphere has a positive and significant effect on Hedonic Value and the Store Atmosphere has a positive and significant effect on Impulsive Buying and Hedonic Value has a positive and significant effect on Impulsive Buying Consumers in the Majapahit Food Center Study.

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Mhamad, Aras Jalal, and Renas Abubaker Ahmed. "Structural Equation Modeling for the Effect of Main Factors on Abortion Issue." Journal of University of Raparin 7, no. 1 (December 3, 2019): 1–13. http://dx.doi.org/10.26750/vol(7).no(1).paper1.

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Based on medical exchange and medical information processing theories with statistical tools, our study proposes and tests a research model that investigates main factors behind abortion issue. Data were collected from the survey of Maternity hospital in Sulaimani, Kurdistan-Iraq. Structural Equation Modelling (SEM) is a powerful technique as it estimates the causal relationship between more than one dependent variable and many independent variables, which is ability to incorporate quantitative and qualitative data, and it shows how all latent variables are related to each other. The dependent latent variable in SEM which have one-way arrows pointing to them is called endogenous variable while others are exogenous variables. The structural equation modeling results reveal is underlying mechanism through which statistical tools, as relationship between factors; previous disease information, food and drug information, patient address, mother’s information, abortion information, which are caused abortion problem. Simply stated, the empirical data support the study hypothesis and the research model we have proposed is viable. The data of the study were obtained from a survey of Maternity hospital in Sulaimani, Kurdistan-Iraq, which is in close contact with patients for long periods, and it is number one area for pregnant women to obtain information about the abortion issue. The results shows arrangement about factors effectiveness as mentioned at section five of the study. This gives the conclusion that abortion problem must be more concern than the other pregnancy problem.

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Lau, Ying, Tha Pyai Htun, Peng Im Lim, Sarah Ho-Lim, and Piyanee Klainin-Yobas. "Maternal, Infant Characteristics, Breastfeeding Techniques, and Initiation: Structural Equation Modeling Approaches." PLOS ONE 10, no. 11 (November 13, 2015): e0142861. http://dx.doi.org/10.1371/journal.pone.0142861.

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Agrawal, Saurabh, and Rajesh Kumar Singh. "Forecasting product returns and reverse logistics performance: structural equation modelling." Management of Environmental Quality: An International Journal 31, no. 5 (October 22, 2019): 1223–37. http://dx.doi.org/10.1108/meq-05-2019-0109.

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Purpose Forecasting product returns plays an important role in the operations of reverse logistics (RL). However, their contribution to sustainability performance is yet to be explored. The purpose of this paper is to explore the product returns in Indian electronics industry and examine the relationship of forecasting product returns with triple bottom line performance of RL. Design/methodology/approach In this study, based on past literature review, four hypotheses, relating to forecasting of product returns and its association with performance, were developed. A questionnaire was sent to 700 respondents from the Indian electronics industry. Overall, 208 received responses were found suitable for the research. The necessary statistical analysis was carried out to ensure the reliability and validity of the questionnaire. In order to test different hypotheses, partial least square path modelling (PLSPM) technique of structural equation modeling was utilized. Findings Measurement model had shown sufficient data fit for the modeling. PLSPM results reveal that the accuracy in forecasting product returns is positively associated with operational performance of RL. It also plays an important role in the sustainability efforts of an organization. Research limitations/implications Managers can utilize results of study for exploring and emphasizing issues of product returns for improving RL performance. One of the limitations is that data are collected only from Indian electronics industry. Another limitation is that only product returns are considered for the operational and TBL performance of RL. In future, study may be carried out considering different factors in other sectors and countries. Originality/value The intent of forecasting product returns is considered to be operational efficiency. It can make significant contributions to the sustainability efforts of an organization. Review of the past literature indicates that research in the field of RL is in developing stage, and issues related to forecasting product returns are under-represented. The paper adds value to the few available articles on product returns.

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Kimiyagahlam, Fatemeh, Meysam Safari, and Shaheen Mansori. "Influential Behavioral Factors on Retirement Planning Behavior: The Case of Malaysia." Journal of Financial Counseling and Planning 30, no. 2 (November 1, 2019): 244–61. http://dx.doi.org/10.1891/1052-3073.30.2.244.

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The main objective of this research is to identify the behavioral factors which have an effect on retirement planning behavior. The study applies the theory of planned behavior and time perspective theory as a basis for the analysis of data by the structural equation modeling technique from a sample of 900 adults in Kelang Valley, Malaysia. The results of structural equation modeling show that financial literacy, propensity to plan, and future orientation are directly associated with retirement planning behavior. The saving attitude is also found to partially mediate these relationships. However, family education and materialism are not associated with retirement planning. Implications for researchers and practitioners are presented.

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Owolabi, H. O., J. K. Ayandele, and D. D. Olaoye. "A SYSTEMATIC REVIEW OF STRUCTURAL EQUATION MODEL (SEM)." Open Journal of Educational Development (ISSN: 2734-2050) 1, no. 2 (November 23, 2020): 27–39. http://dx.doi.org/10.52417/ojed.v1i2.163.

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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.

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Koubaa, Yamen, Rym Srarfi Tabbane, and Rim Chaabouni Jallouli. "On the use of structural equation modeling in marketing image research." Asia Pacific Journal of Marketing and Logistics 26, no. 2 (April 8, 2014): 315–38. http://dx.doi.org/10.1108/apjml-10-2013-0113.

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Purpose – The purpose of this paper is to assess the use of structural equation modeling in one specific field of marketing research, the image research. Design/methodology/approach – A meta-analysis of a sample of image marketing works using structural equation modeling (SEM). The period of investigation is limited to the last five years to test for possible positive return of previous assessments of SEM use on the current SEM application. Findings – Following this work, three major conclusions emerged: the study of homogenous samples of SEM models is required to get to accurate assessment of using the technique; SEM application is getting better probably due to learning from SEM reviews; and the reliance on a conjoint assessment of the various SEM issues is necessary to avoid parsimonious assessments. This study has provided a concise and refreshed view on the use of SEM in one marketing field, the image research. Research limitations/implications – 47 SEM papers and 99 models along five years were examined through this research. Although the authors reviewed four of the most consulted databases in marketing, the authors might miss several interesting works not available in these databases during the investigation. It is interesting to add on the works reviewed in this study and to re-conduct the analysis. The objective is not to doubt the consistency of SEM image research but to provide writers and readers with tools that enable them to produce better quality SEM research. Moreover, the quantitative analysis could be larger. Future research can consider computing other statistics. Finally, in the standards of most of marketing journals, this paper is a bit long. But as suggested by Babin et al., journal editors should allow more space to SEM-based reviews as the nature of the discussion requires lengthening. Practical implications – Mastering the statistical tool in marketing research is as important as mastering the conceptual tool. Statistical learning and/or cooperation with statisticians is recommended. Originality/value – A multi-criteria review of works from one specific field in marketing research and across a recent period of time allowing for the test of possible positive return from previous reviews of SEM use on the quality of the current publications of SEM papers.

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Nazim, Ahmad. "Modeling The Influential Factors Of 8th Grades Student’s Mathematics Achievement In Malaysia By Using Structural Equation Modeling (SEM)." International Journal of Advances in Applied Sciences 3, no. 4 (December 1, 2014): 172. http://dx.doi.org/10.11591/ijaas.v3.i4.pp172-177.

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This research demonstrates the application of Structural Equation Modeling (SEM) method in order to obtain the best fit model for a more efficient and accurate inter-relationship among variables findings and interpretation. For the purpose of this study, secondary data of Trends in International Mathematics and Science Study (TIMSS) was used. The questionnaire were distributed by using two stage stratified cluster sampling technique to 5733 eighth grades students in Malaysia. A Confirmatory Factor Analysis (CFA), Discriminant Validity and Path Analysis had been conducted to obtain the best fit model of SEM. At the end of the study, a best fit model will be obtained for a better accuracy and precision estimation in further analysis.

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Aprianti, Rahayu, and Indira Rachmawati. "The Effect of E-Servicescape Dimensions on Repurchase Intention with Trust as an Intervening Variable." Almana : Jurnal Manajemen dan Bisnis 4, no. 3 (December 17, 2020): 309–15. http://dx.doi.org/10.36555/almana.v4i3.1339.

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This research to determine how much influence the e-servicescape dimension has on repurchase intention through trust as an intervening variable. The object of this study is the food-delivery service on mobile applications, Grab Food. The population used in this study were users of Grab Food services in Indonesia with a sample of 400 respondents who had purchased products through Grab Food in Indonesia obtained using purposive sampling techniques. Samples were obtained from distributing online questionnaires via Google Form. The independent variables used in the study are the e-servicescape dimensions, namely: aesthetic appeal, layout and functionality, and financial security. The dependent variable used in this study is repurchase intention and trust as intervening variables. The data analysis technique used in this research is Structural Equation Modeling with Covariance Based Structural Equation Modeling (CB-SEM). Based on the results of research that has been done, E-servicescape has a positive and significant effect on repurchase intention through trust variables.

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Endozo, Anatalia N. "Structural Equation Modeling of Mental Toughness Among University Learners." Global Journal of Health Science 11, no. 4 (April 1, 2019): 149. http://dx.doi.org/10.5539/gjhs.v11n4p149.

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BACKGROUND: Mental toughness is recognized as an important component towards academic success thus making its psychological qualities determine how challenges are effectively addressed during pressurized situations. Challenges facing undergraduate learners in the context of mental toughness had been broadly investigated mostly in developed countries. Most of the studies centered on sports and descriptive findings lack critical analysis. OBJECTIVE: The main objective of the current study was to investigate the level of mental toughness of university learners and the impact on the learners' academic performance. The current study also investigated whether university learners who were reported with greater mental toughness are more likely to be academically successful than those lower in mental toughness. METHODS: This quantitative study employed SmartPls 3 software to predict the significant level of motivation, self-reliance, concentration and coping with pressure on academic performance among university learners. Two universities were considered for assessing the structural equation modeling of mental toughness. Additionally, sources of data included reviews of different books on the related topics, research studies, articles, journals, newspapers, and magazines. Substantial information has been gathered from these sources thus allowing for appropriate analysis, compilation, interpretation, and structuring of the entire study. Thus, in an attempt to isolate and categorize potential attributes of mental toughness and its impact on academic performance, the available literature reviewed. This quantitative study considered adoptable in handling bias findings. A sample size of 417 considered appropriate for a variance based structural equation modeling. A total number of 417 responses gathered from Angeles University Foundation (AUF) and Baliuag University (BU), Philippines considered for this mental toughness study. RESULTS: A total of a 75 percent from the questionnaires (477) returned from a sum 600 questionnaires distributed to specified respondents. Demographic details report that female responded with round-off 60%, this implied that female strive more in education than male. Ages 17-20 occupied 55% nursing/medicine marked around of 34% to top among the six colleges investigated in this study, next was college of business and administration marked around of 20% to take second place. This study suggested that students considered more to be medical doctors, professional nurses and business practitioners in the future rather than being professional teachers or system engineers. Reliability and validity of this study reported according to the Smart-Pls algorithm factor matrix, Cronbach's alpha, rho_A, and composite reliability all above 0.7 thresholds. Also, the average variance extracted from 0.5 achieved. The discriminant validity of this study based on Fornell-Lackner criterion, factor loading at 0.6 above and Heterotrait Monotrait Ratio quality achieved. Conclusively, all supported path coefficients significant at the p-values < 0.01. In a nutshell, partial least squares algorithm reported about a 58% variance explained from the entire structured model. CONCLUSION: The adopted factors for this structural equation modeling of mental toughness for university learners achieved fifty-eight percent variance explained in the study. Future studies can be directed towards replicating the use of this model in other locations and different analytical techniques.

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Gbongli, Komlan, Yongan Xu, Komi Mawugbe Amedjonekou, and Levente Kovács. "Evaluation and Classification of Mobile Financial Services Sustainability Using Structural Equation Modeling and Multiple Criteria Decision-Making Methods." Sustainability 12, no. 4 (February 11, 2020): 1288. http://dx.doi.org/10.3390/su12041288.

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Despite the fast emergent of smartphones in day-to-day activity, the sustainable development of mobile financial services (MFS) remains low partially due to online consumer’s trust and perceived risk. This research broadens the trust and the perceived risk at the multi-dimensional for understanding and prioritizing alternatives of MFS decision. A combined methodology; structural equation modeling (SEM) with two multiple criteria decision-making (MCDM) methods such as a technique for order of preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP) were applied for data analysis. The two steps SEM-TOPSIS techniques were adopted through a two-types survey on datasets consisting of 538 MFS users, and 74 both experienced MFS users and experts in Togo. The SEM is used for causal relationships and assigning weights for the TOPSIS input. TOPSIS was applied for providing MFS alternative classification, in which the results were compared with prior research using the SEM-AHP technique on the given population. The results via SEM revealed particularly strong support for the dispositional trust and perceived privacy risk. Trust has a negative relationship with perceived risk. Except for perceived time risk, all the antecedents of perceived risk and trust validated the proposed relationship. The findings of TOPSIS uncovered that mobile money transfer (MMT) remains the core application used, followed by mobile payment (MP) and mobile banking (MB) and, therefore, consistent with AHP. However, the TOPSIS technique is better suited to the problem of MFS selection for this study field. This research offers a novel and practical modeling and classification concept for researchers, companies’ managers, and experts in the areas of information technology. The implications, limitations, and future research are provided.

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Sarbeng, Isaac Baafi. "Staff Training and Development Interventions and Teaching Performance: Application of Structural Equation Modeling." International Journal of Human Resource Studies 3, no. 4 (December 8, 2013): 159. http://dx.doi.org/10.5296/ijhrs.v3i4.4705.

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Staff training and development is an essential programme necessary for improving staff performance. The study sought to assess staff training and development programmes and performance of teaching staff at the various departments of the University of Cape Coast. A cross-sectional survey of 193 Faculty members, selected through a simple sampling technique, was conducted to assess whether the trained faculty of UCC were performing their task up to expectation. The study revealed that although the training programmes are not perceived as fair enough, it has positively affected staff professional knowledge, intellectual planning, class attendance and assessment. The respondents also believe that there has been improvement in their instructional delivery due to the training programmes of UCC. It is therefore recommended for management of the University to provide equal opportunity for staff in terms of training through a quota system. The study further recommends for wide communication of the modalities for selection of faculty for further studies.

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Cimino, Orlando, Marco Vassallo, Roberto Henke, and Francesco Vanni. "Income Diversification Strategies of Italian Peri-Urban Farms: A Structural Equation Modeling Approach." Land 10, no. 8 (July 28, 2021): 790. http://dx.doi.org/10.3390/land10080790.

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On-farm diversification in non-agricultural activities has been increasingly recognized as a rewarding farm strategy through which farmers produce on-farm non-agricultural goods and services. The main objective of this paper is to explore to what extent the condition of peri-urbanity affects farm income diversification in Italy by looking at the push and pull factors that allow peri-urban farmers to re-organize their business by developing diversification strategies that are tightly connected to the demand of goods and services coming from the urban society. A structural equation modeling (SEM) statistical technique has been applied to estimate direct and indirect causal relationships among the multiple variables involved. The SEM analytical approach allowed us to untie the complexity of the push and pull factors connections and to highlight the most significant ones. The strengths of the structural paths provide evidence on the key diversification strategies adopted by peri-urban farms.

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Djan, Ismulyana, and Fitriyanti . "THE ANALYSIS OF PRICE, PROMOTION, AND PLACE AND THEN TO EFFECT ON CONSUMER DECISION MAKING A Study of Structural Equation Modeling in Healthcare Products." Management Journal of Binaniaga 2, no. 02 (December 31, 2017): 65. http://dx.doi.org/10.33062/mjb.v2i02.243.

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The purpose of this study is to determine the customer’s purchasing decision toward the product that directly influenced by the price variable, promotion variable and place variable, included analyzing the policy of price decision, promotion implementation and how important the place to decide customer’s purchasing decision. The method used in his study is survey method using Structural equation modeling (SEM) analyzing technique through AMOS application. The result of the study shows that the price influenced the purchasing decision making as (CR) 2,399 > 1,96, and the promotion influenced the purchasing decision making as (CR) 3,493 > 1,96, and the place did not influence the purchasing decision making as (CR) 1,089 < 1,96.Keyword : Structural Equation Modeling (SEM)

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Ahmed, Shurooq H. A., and Saad M. A. Suliman. "A structure equation model of indicators driving BIM adoption in the Bahraini construction industry." Construction Innovation 20, no. 1 (January 6, 2020): 61–78. http://dx.doi.org/10.1108/ci-06-2019-0048.

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Purpose This study aims to establish an adoption model using Structural Equation Modeling (SEM) that examines the relationship between several key indicators that drive building information modeling (BIM) adoption. Design/methodology/approach The study was carried out using quantitative approaches through the Delphi method and questionnaire survey. A total of 272 completed responses were collected and analyzed through the SEM technique using SPSS 25 and AMOS software. Findings The structural model shows that “environment” and partially “people” indicators are the leading indicators driving BIM adoption with path coefficient values of 0.280 and 0.332, respectively. Originality/value It is expected that these conclusions will lead the Bahraini construction industry stakeholders to raise the level of BIM adoption.

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Gandhi, Pranav K., L. Douglas Ried, I.-Chan Huang, Carole L. Kimberlin, and Teresa L. Kauf. "Erratum to: Assessment of response shift using two structural equation modeling techniques." Quality of Life Research 22, no. 3 (August 4, 2012): 473. http://dx.doi.org/10.1007/s11136-012-0244-1.

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Duncan, Terry E., Roy Oman, and Susan C. Duncan. "Modeling Incomplete Data in Exercise Behavior Research Using Structural Equation Methodology." Journal of Sport and Exercise Psychology 16, no. 2 (June 1994): 187–205. http://dx.doi.org/10.1123/jsep.16.2.187.

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Exercise behavior research typically suffers from attrition and other forms of missing data. In studies that suffer from this common malady, several researchers have demonstrated that correct maximum likelihood estimation with missing data can be obtained under mild assumptions concerning the missing data mechanism. Model estimation with distinct missing data patterns can, in many cases, be carried out utilizing existing structural equation modeling software that allow for the simultaneous analysis of mean and covariance structures for multiple groups. Findings are discussed in relation to the utility of latent variable structural equation modeling techniques for analysis with incomplete data in the study of social-psychological determinants of exercise behavior.

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Al-Mahameed, Farah J., Xiao Qin, Robert J. Schneider, and Mohammad Razaur Rahman Shaon. "Analyzing Pedestrian and Bicyclist Crashes at the Corridor Level: Structural Equation Modeling Approach." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 7 (May 7, 2019): 308–18. http://dx.doi.org/10.1177/0361198119845353.

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Pedestrian and bicycle crashes have been increasing at an alarming pace in recent years. Between 2009 and 2016, annual U.S. pedestrian fatalities increased 46%, and bicyclist fatalities increased 34%. Crashes involving pedestrians and bicyclists, or vulnerable road users (VRUs), are negatively correlated with roadway factors, and positively correlated with environmental and socioeconomic factors. However, specific variables representing these factors are often correlated, making it difficult to accurately characterize relationships between individual variables and pedestrian and bicyclist safety. This study used the structural equation model technique to overcome this problem. Pedestrian and bicyclist crash frequency and more than 60 explanatory variables for 200 highway corridors in Wisconsin were collected. The interrelationships between observed “manifest” variables and unobserved “latent” variables were tested. The results suggest that the most important latent variables influencing the crash frequency of VRUs are bicycle/pedestrian-oriented roadway design (e.g., paved shoulders, sidewalks, and bike lanes), exposure (e.g., walking and biking activity, and employment density), and low social status (e.g., educational level, and wage percentage). The benefits of this study may help community planners, transportation researchers, and policymakers with a better understanding of the intricate interrelationship of the influential factors contributing to VRUs road crashes.

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Selvam, Dhanapal Durai Dominic Panneer, Sarit Maitra, P. Parthiban, and Abdul Zubar Hameed. "Composite Techniques of Structural Equation Modeling and Analytic Hierarchy Process for Information Technology Vendor Selection." International Journal of Information Technology & Decision Making 20, no. 04 (May 6, 2021): 1153–87. http://dx.doi.org/10.1142/s0219622021500346.

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This paper had developed an effective information technology (IT) vendor selection model for banking & financial services industries (BFSI). For any business, profitability and growth depends on the right vendor selection in their purchase process. This paper identifies ten most influencing and important criteria with 43 sub-criteria to comprehend the vendor selection process. Furthermore, the authors developed a vendor selection score model using Structural Equation Modelling (SEM) and Analytic Hierarchy Process (AHP). This article intends to inform practice and conclude with practical recommendations to BFSI for vendor selection. The proposed composite technique identified the most eligible vendor to meet up with the buyer’s strategies. This article suggests the most desirable vendor for the required benefit. Vendor 1 (Silverlake) with a score of 44% promised to be the most recommended one that also performed consistently in the sensitivity test.

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Perry, Carlos Monge, Jesús Cruz Álvarez, and Jesús Fabián López. "MANUFACTURING AND CONTINUOUS IMPROVEMENT AREAS USING PARTIAL LEAST SQUARE PATH MODELING WITH MULTIPLE REGRESSION COMPARISON." CBU International Conference Proceedings 2 (July 1, 2014): 15–26. http://dx.doi.org/10.12955/cbup.v2.442.

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Structural equation modeling (SEM) has traditionally been deployed in areas of marketing, consumer satisfaction and preferences, human behavior, and recently in strategic planning. These areas are considered their niches; however, there is a remarkable tendency in empirical research studies that indicate a more diversified use of the technique. This paper shows the application of structural equation modeling using partial least square (PLS-SEM), in areas of manufacturing, quality, continuous improvement, operational efficiency, and environmental responsibility in Mexico’s medium and large manufacturing plants, while using a small sample (n = 40). The results obtained from the PLS-SEM model application mentioned, are highly positive, relevant, and statistically significant. Also shown in this paper, for purposes of validity, reliability, and statistical power confirmation of PLS-SEM, is a comparative analysis against multiple regression showing very similar results to those obtained by PLS-SEM. This fact validates the use of PLS-SEM in areas of untraditional scientific research, and suggests and invites the use of the technique in diversified fields of the scientific research

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Setiyowati, Arbin Janu, Marthen Pali, Bambang Budi Wiyono, and Triyono Triyono. "STRUCTURAL MODEL OF COUNSELING COMPETENCE." Jurnal Cakrawala Pendidikan 38, no. 1 (February 8, 2019): 45–62. http://dx.doi.org/10.21831/cp.v38i1.21509.

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Counseling competence is a set of essential abilities which is prominent to be employed in conducting counseling. This counseling competence research took students of counseling as a counselor candidate. This study aims to analyze the correlation between basic knowledge, basic communication skill, and cultural skill to the counseling competence. This work used Ex Post Facto Causal Relationship Explanatory research design. The research subjects were 120 students of Department of Guidance and Counseling from three State Universities in Java Island. Samples were taken by using cluster random sampling technique. The data analysis was conducted through Structural Equation Modeling (SEM) technique. The research results show that there is a significant relationship between knowledge, basic attitude, basic communication skill and cultural skill to the counseling competence. The implication of this research finding to the education of the Department of Guidance and Counseling is the significance of considering the factors forming the academic counseling competence to produce the professional counselor candidate.

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Chong, Vincent K., and Kar Ming Chong. "Budget Goal Commitment and Informational Effects of Budget Participation on Performance: A Structural Equation Modeling Approach." Behavioral Research in Accounting 14, no. 1 (January 1, 2002): 65–86. http://dx.doi.org/10.2308/bria.2002.14.1.65.

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This paper examines budget goal commitment and informational effects of budget participation on performance. A structural model is proposed and tested that includes budget participation, budget goal commitment, job-relevant information, and job performance variables. The data were collected by survey questionnaires. Seventy-nine middle-level managers, drawn randomly from a cross-section of manufacturing companies in Australia, participated in the project. A structural equation modeling technique was used to test hypothesized linkages. Support was found for the effects of budget goal commitment and informational roles of budget participation on job performance.

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Nuraini, Candra, and Iskandar Ma’moen. "Effects of Entrepreneurship on The Performance of Organic Rice Farmers in Tasikmalaya Regency." E3S Web of Conferences 232 (2021): 02024. http://dx.doi.org/10.1051/e3sconf/202123202024.

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This study aims to analyzethe influence of the rice organic farmers’ entrepreneurship on the farming performance and identify the influence of farming technique or activities on the farming performance. This study used a survey method. The study was conducted in Manonjaya and Salawu sub-districts, Tasikmalaya regency, August until November 2019 which was chosen using purposive sampling technique applied to 50 samples. The respondents who were organic rice farmers were recruited using multistage purposive sampling technique. Data analysis was performed using structural equation modeling (SEM) with WarpPLS 2.0. The result show that the entrepreneurship significantly and positively affects farming techniques. Entrepreneurship has significant and positive influence on the organic rice farming performance. In addition, farming technique is significantly and positively influential on the organic rice farming performance.

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Tjokrosaputro, Miharni, and Cokki Cokki. "PERAN INNOVATIVENESS SEBAGAI MODERASI PADA KETERKAITAN PENGARUH SOSIAL TERHADAP MINAT PEMBELIAN KOPI STARBUCKS." Jurnal Muara Ilmu Ekonomi dan Bisnis 4, no. 1 (April 30, 2020): 174. http://dx.doi.org/10.24912/jmieb.v4i1.7588.

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Tujuan penelitian ini adalah untuk mengetahui apakah keinovatifan dapat memoderasi peran pengaruh sosial terhadap minat pembelian kopi Starbucks sebagai produk hijau. Penelitian ini menggunakan metode survey. Responden adalah 100 konsumen Starbucks. Teknik pengambilan sampel adalah convenience sampling. Teknik pengumpulan data menggunakan kuesioner. Teknik analisis data menggunakan Partial Least Square-Structural Equation Modeling. Hasil penelitian menunjukkan bahwa pengaruh sosial berpengaruh terhadap niat membeli kopi Starbucks dan keinovatifan konsumen tidak memoderasi peran pengaruh sosial terhadap minat pembelian kopi Starbuck sebagai produk hijau. The purpose of this study was to determine whether innovativeness can moderate the role of social influence in the purchase intention of Starbucks coffee as a green product. Respondents were 100 Starbucks consumers. The sampling technique is convenience sampling. Data collection techniques using a questionnaire by survey method. Data analysis techniques using Partial Least Square-Structural Equation Modeling. The results showed that social influence had effect on Starbucks coffee purchase intentions and consumer innovativeness did not moderate the role of social influence on the purchase intention of Starbuck coffee as a green product. This might be due to brand equity factors, collectivistic culture and limited sample size, which can be suggested for future researchers.

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Journal articles on the topic 'Structural equation modeling technique'

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