Conference PaperPDF Available

Introduction to Structural Equation Modeling: Review, Methodology and Practical Applications

Authors:

Abstract and Figures

Abstract - The paper addresses an introduction to the structural equation modeling (SEM), the insight into the methodology, and the importance of this statistical technique for practical applications. SEM is a very powerful statistical modeling tool, which incorporates the measurements models and the path models into the comprehensive covariance structure analysis framework. Herein, the exploratory analysis (EFA) and the confirmatory factor analysis (CFA) are usually employed as the intermediate stages of the modeling design. The main intent of this work is to inform the interesting readers about all the potentials, which can be conducted when use this technique. For encouraging the interested researchers, who are new in this field, the main steps and characteristics of SEM methodology are briefly presented. A short overview of applications based on this advanced statistical methodology is also provided, with emphasis on supply chain (SC) management applications, which study the impact of integration between individual players on the SC performance. An investigaton of Port Economics applications based on SEM is also inspected in this work.
Content may be subject to copyright.
A preview of the PDF is not available
... EFA is commonly employed as an initial step in research to examine the underlying constructs and gain preliminary insights into the relationships between measured variables and latent factors (Dragan & Topolšek, 2014). Its primary purpose is to uncover patterns and structures within the data without relying on preestablished hypotheses. ...
... EFA serves as a valuable tool to provide guidance for further research, particularly in informing the development of a more specific and testable theory. The EFA involves three key stages (suitability of data, factor extraction, and factor Rotation and Interpretation) (Dragan & Topolšek, 2014;Ogunsanya et al., 2022). ...
... The first stage is suitability of data which involves evaluating the data for sample size adequacy and the strength of correlations among variables. The consensus suggests that a larger sample size is preferable, with recommendations ranging from at least 150 to 300 cases (Dragan & Topolšek, 2014;Ogunsanya et al., 2022;Pallant, 2020), in this study the data were collected from 235 responses. The correlation matrix is examined for coefficients greater than 0.3 to ensure adequate interrelationships among variables (Dragan & Topolšek, 2014;Ogunsanya et al., 2022). ...
Article
Full-text available
Construction monitoring in dynamic construction site environments poses significant challenges for construction management. To overcome these challenges, the implementation of computer vision (CV) technologies for construction project monitoring has gained traction. This study focuses on investigating the factors influence the successful implementation of CV technologies in monitoring construction activities within building projects. A comprehensive methodology was employed, including a systematic review of CV technologies implemented in construction and qualitative surveys conducted with construction experts. Additionally, a quantitative questionnaire was developed, and the collected data was analysed using structural equation modelling. The findings reveal the presence of 10 factors categorized into four constructs. Notably, all 10 factors demonstrate high value factor loadings and statistical significance, and among the four constructs (device, jobsite, environment, human), device (0.82) has the highest impact on the implementation of CV-based technologies on the construction site, followed by jobsite condition (0.62), human (0.61), and environment (0.51) came in the last place. By addressing these influential factors and mitigating their effects, construction stakeholders can enhance the implementation of CV technologies for monitoring construction sites. This study contributes valuable insights that inform the implementation and optimization of CV technologies in construction projects, ultimately advancing the field of construction management.
... SEM is a statistical technique that allows researchers to evaluate and test complex relationships between variables, combining aspects of factor analysis and multiple regression analysis. SEM is particularly useful for assessing theoretical models that involve multiple, interrelated dependent relationships simultaneously [50]. For that reason, and since the study deals with the subtraction of observable variables into latent variables, structural equation modeling is used, and Figure 1 presents the conceptual model. ...
Article
Full-text available
This study investigates the entrepreneurial intention of engineering and non-engineering students to understand the potential entrepreneurial gaps among future engineers. The study specifically examines the underlying factors, especially looking at the entrepreneurial scales of mindset and attitudes. The study is a quantitative research conducted by a survey with 112 participants. The results reveal that engineering students exhibit lower levels of entrepreneurial intention compared to the non-engineering group, showing that there is a gap between groups. The two groups exhibit similar levels of entrepreneurial attitudes, while the engineering group shows lower levels of entrepreneurial mindset. The effect of mindset on intention is significant among engineering students and insignificant among non-engineering students, whereas attitudes do not demonstrate a substantial discrepancy. The study found no notable variation in the promotion of entrepreneurial perception among students. The results show that developing an entrepreneurial mindset among engineering students is vital for promoting their entrepreneurial intentions. To achieve this, the research shows that institutions should provide the necessary skills and a supportive environment. Implications for institutions consist of establishing programs that advance entrepreneurial thinking and hands-on experience, leading to a new cohort of successful engineers turned entrepreneurs.
... The items of each scale align with their theoretical dimension construction, demonstrating that the scale has good structural validity and that the items accurately reflect their intended dimensions. The cumulative variance explanation ratio of all dimensions exceeds 60%, indicating that the factor structure of the scale explains most of the variable variance, thus demonstrating good explanatory power (Dragan & Topolšek, 2014). ...
... In the fourth stage, the validity and reliability of the model were examined. When the model proved to be fit, the last step was to interpret the results of the analysis [31]. ...
Article
Full-text available
Background: Video Advertising (VI) is a powerful media tool used by several companies as a marketing strategy. During COVID-19 pandemic, there was a wide adoption of digital media, particularly VI, to promote company products. However, some changes occurred post-pandemic, which influenced customer behavior. Objective: This research aimed to explore changes in customer behavior towards VI post-pandemic. The exploration focused on understanding changes in four major factors which included Sensory Appeal (SEN), Informativeness (INF), Entertainment (ENT), and Telepresence (PRE). Methods: Data were collected using snowball sampling method, resulting in 744 responses. After deleting outliers and non-shopping customer, there were 584 analyzable data. Covariance-Based Structural Equation Model (CB SEM) method facilitated by Lisrel Application was used for data analysis. Results: The result showed that significant changes have occurred in customer behavior to VI post-pandemic. Among the 13 tested hypotheses, 11 showed significant influences, while 2 did not, indicating shifts in customer behavior. Conclusion: COVID-19 pandemic led to significant changes and imparted customer with a new understanding of VI, which became a major marketing tool. These changes were due to experiences during the pandemic, which affected SEN (72%), INF (77%), ENT (76%), and PRE (70%). Further analysis showed that ENT affected Customer Trust (CT) and Actual Purchase (APU) by 20% and 27%, while PRE caused 34% and 20% respectively, indicating a decrease in customer response from VI to CT and APU. Based on these results, further exploration should build on the identified factors and investigate additional variables that had not been considered.
Chapter
In light of the transformative effects of digital technology on education, this study presents an innovative performance management framework tailored for virtual learning environments in the metaverse era. Utilizing the Structural Equation Modeling (SEM) approach, this paper proposes a comprehensive evaluative model that integrates the Theory of Planned Behaviour (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Community of Inquiry Framework (CoI). The model incorporates five Key Performance Indicators (KPIs)—content delivery, student engagement, metaverse tool utilization, student performance, and adaptability—to thoroughly evaluate academic avatar performance in virtual educational settings. This theoretical framework represents a significant advancement in understanding and enhancing avatar effectiveness within the metaverse environment. It contributes to the ongoing discourse on performance management in digital education and lays the groundwork for future empirical research.
Article
Full-text available
Yenilikçilik (inovasyon), yeni fikirlerin veya ürünlerin benimsenmesi veya uygulanması olarak tanımlanır ve beceri gelişiminive sürekli öğrenmeyi teşvik eder. Aynı zamanda, yeni teknolojiler ve iş uygulamalarının entegrasyonunu içerirken, teknolojikgelişmeler ürün ve süreçlerin oluşturulmasını ve iyileştirilmesini sağlamaktadır. Artan rekabet ortamında sosyal ve ekonomikalanlarda teknolojik yeniliğin ve girişimciliğin önemi giderek artmakta ve toplumların hızlı bilimsel gelişmelere uyum sağlamasıgerekmektedir. Bu bağlamda, bireylerin ve toplumların bilgi edinme, girişimcilik ve yaratıcılık özellikleri de sosyoekonomikilerlemede merkezi bir role sahip olup, pek çok sektörü etkileyerek bir yenilikçilik kültürünü teşvik etmektedir. Girişimciler yenifikirler ve ürünler geliştirebildikleri için girişimcilik, ekonomik ilerlemenin anahtar itici gücü olarak öne çıkmaktadır. Yaratıcılık,kurumsal etkinlikte ve rekabetçi ortamlara uyum sağlamada önemli bir rol oynayarak yenilikçiliği beslemekte ve değişkenortamlara uyum sağlayarak performansı artırmaktadır. Bu çalışmada, yenilikçilik anlamında en çok potansiyele sahip üniversiteöğrencilerinin yenilikçilik kapasiteleri ile teknolojik yenilik eğilimleri arasındaki ilişki incelenmiştir. 836 öğrenciden temin edilenveriler yapısal eşitlik modeli ile analiz edilmiştir. Bulgular, yaratıcılığın inovasyon eğilimini en çok etkileyen faktör olduğunu, riskalma eğiliminin ise en az öneme sahip faktör olduğunu göstermektedir. Bu doğrultuda, öğrencilerin girişimcilik ve yenilikçilikkapasiteleri ile risk alabilme tutumlarını değiştirip geliştirebilmek için erken yaşlardan itibaren eğitimde hem bilgilendirici hemde teşvik edici pratik uygulamalara yer verecek politikalar geliştirilmelidir. Böylelikle ülkenin sosyo-ekonomik ve teknolojikgelişimine önemli katkılar sağlanabilecektir. (PDF) Üniversite Öğrencilerinin Yenilikçilik Kapasitelerinin Teknolojik Yenilikçilik Eğilimlerine Etkisini Ölçmeye Yönelik Bir Model Önerisi. Available from: https://www.researchgate.net/publication/387435444_Universite_Ogrencilerinin_Yenilikcilik_Kapasitelerinin_Teknolojik_Yenilikcilik_Egilimlerine_Etkisini_Olcmeye_Yonelik_Bir_Model_Onerisi [accessed Feb 04 2025].
Article
Full-text available
Artan nüfus, yoğunlaşan sanayileşme ve aşırı tüketimin yol açtığı çevresel tahribat, insan yaşamını tehdit eden boyutlara ulaşmıştır. Sürdürülebilir tüketim davranışlarının teşvik edilmesi ve mevcut tüketim davranışlarının sürdürülebilir tüketim davranışlarına dönüştürülmesi, kaynakların verimli kullanımı ve çevresel tahribatın azaltılması açısından büyük önem taşımaktadır. Bireylerin sürdürülebilir tüketim algılarının ve eğilimlerinin ölçülmesi, mevcut tüketim davranışlarını dönüştürmeyi amaçlayan kurum ve kuruluşların, hedeflerine ulaşmaları için gerekli stratejileri geliştirmelerine imkân sağlayacaktır. Bu çalışmanın amacı, sürdürülebilir tüketim algılarının ve eğilimlerinin ölçülmesine imkân tanıyan Quoquab ve Mohammad (2020) tarafından geliştirilen sürdürülebilir tüketim ölçeğinin geçerlik ve güvenirliğini inceleyerek Türkçeye uyarlamaktır. Orijinal ölçekte yer alan maddeler çeviri-ters çeviri yöntemi kullanılarak Türkçeye çevrilmiştir. Çevirisi yapılan ölçek, kolayda örneklem yöntemiyle seçilen 485 kişiye uygulanmıştır. Verilerin analizine madde toplam korelasyon analizi ile başlanmış, ardından paralel analiz yöntemi kullanılarak açımlayıcı faktör analizi (AFA) uygulanmıştır. AFA sonucu elde edilen üç faktörlü 16 maddeli yapı, doğrulayıcı faktör analizi ile incelenerek geçerli bir ölçüm modeli elde edilmiştir. Üç faktör toplam varyansın %58,12’sini açıklamaktadır. Ölçeğin tümü için iç tutarlılık katsayısı (Cronbach alfa) 0,87 olarak hesaplanmıştır. Elde edilen model, ayırıcı ve yakınsama geçerliği açısından test edilmiştir. Ulaşılan bulgular, ölçeğin Türkçe formunun geçerli ve güvenilir bir ölçüm aracı olduğunu göstermektedir. Çalışmada Türkçeye uyarlanan ölçeğin, Türk tüketicilerin sürdürülebilir tüketim eğilimlerinin ölçülmesi konusunda yapılacak çalışmalara katkı sağlaması beklenmektedir.
Article
Full-text available
ภูมิหลังและวัตถุประสงค์: การวิเคราะห์องค์ประกอบเชิงยืนยัน (Confirmatory Factor Analysis : CFA) เป็นวิธีการทางสถิติที่ใช้กันอย่างแพร่หลายในงานวิจัยทางด้านพฤติกรรมศาสตร์ สังคมศาสตร์ วัตถุประสงค์เพื่อการสํารวจและระบุองค์ประกอบร่วมที่สามารถอธิบายความสัมพันธ์ระหว่างตัวแปรสังเกตได้ ผลที่ได้คือลดตัวแปรสังเกตได้โดยสร้าง ตัวแปรใหม่ในรูปขององค์ประกอบร่วม ระเบียบวิธีการศึกษา: การศึกษาครั้งนี้เป็นการศึกษาทบทวนวรรณกรรมที่เกี่ยวข้องกับการศึกษาการวิเคราะห์องค์ประกอบเชิงยืนยัน (Confirmatory Factor Analysis : CFA) ทำการวิเคราห์เนื้อหาแล้วนำเสนอเชิงพรรณนาความตามประเด็นที่สำคัญ ผลการศึกษา พบว่า งานวิจัยทางด้านพฤติกรรมศาสตร์ สังคมศาสตร์ จะใช้การวิเคราะห์องค์ประกอบเชิงยืนยันเพื่อยืนยันโมเดลการวัดกับข้อมูลเชิงประจักษ์ โดยที่นักวิจัยมีทฤษฎี มีโมเดลการวัดแล้ว และรู้แน่ชัดล่วงหน้าว่าตัวแปรต่าง ๆ จะรวมกันเป็นกี่องค์ประกอบ ซึ่งจะนำมาจากการดำเนินการศึกษาวรรณกรรม ทฤษฎี เอกสารและงานวิจัยที่เกี่ยวข้อง กำหนดเป็นกรอบแนวคิดที่ชัดเจน สร้างโมเดลการวัด (Measurement Model) ที่ทราบชื่อและจำนวนองค์ประกอบ (Factor) และตัวแปร (Variable) มีการกำหนดความสัมพันธ์ระหว่างองค์ประกอบและตัวแปรสังเกตได้หรือตัวบ่งชี้ (Indicator) ไว้ล่วงหน้าก่อนดำเนินการวิเคราะห์ข้อมูลของโมเดลการวัดต่าง ๆ อาทิ เช่น ภาวะผู้นำการเปลี่ยนแปลง ภาวะผู้นำทางวิชาการ ภาวะผู้นำเชิงกลยุทธ์ ภาวะผู้นำเชิงวิสัยทัศน์ ภาวะผู้นำเชิงนวัตกรรม ภาวะผู้นำเพื่อการเรียนรู้ ภาวะผู้นำเชิงจริยธรรม ภาวะผู้นำเชิงสร้างสรรค์ ภาวะผู้นำแบบเหนือชั้น เป็นต้น สรุปผล: ผลการศึกษาเน้นย้ำถึงความสำคัญของการวิเคราะห์ปัจจัยยืนยันในการวิจัยด้านพฤติกรรมศาสตร์และสังคมศาสตร์ ซึ่งแบบจำลองการวัดที่กำหนดไว้ล่วงหน้าตามทฤษฎีและวรรณกรรมจะได้รับการพิสูจน์โดยใช้ข้อมูลเชิงประจักษ์ กระบวนการนี้ช่วยชี้แจงความสัมพันธ์ระหว่างประเภทความเป็นผู้นำและตัวแปรที่สังเกตได้ ทำให้มั่นใจได้ว่ากรอบแนวคิดแสดงปัจจัยพื้นฐานได้อย่างถูกต้อง
Article
Full-text available
This paper aims to identify the effect of using the maximum likelihood (ML) parameter estimation method when data do not meet the assumption of multivariate normality and are not continuous. Both ML and the diagonally weighted least squares (DWLS) procedure were applied to simulated sets of data, which have different distributions and include variables that can take different numbers of possible values. Results were also compared to the ideal situation of a data set consisting of continuous, normally distributed variables. Outcomes indicate that ML provides accurate results when data are continuous and uniformly distributed, but is not as precise with ordinal data that is not treated as continuous, especially when variables have a small number of categories and data do not meet the assumption of multivariate normality. In contrast, DWLS provides more accurate parameter estimates, and a model fit that is more robust to variable type and non-normality.
Book
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal relations directly by perceiving quantities in magnitudes and motions of causes that are conserved in the effects of causal exchanges. The author surveys the basic concepts of graph theory useful in the formulation of structural models. Focusing on SEM, he shows how to write a set of structural equations corresponding to the path diagram, describes two ways of computing variances and covariances of variables in a structural equation model, and introduces matrix equations for the general structural equation model. The text then discusses the problem of identifying a model, parameter estimation, issues involved in designing structural equation models, the application of confirmatory factor analysis, equivalent models, the use of instrumental variables to resolve issues of causal direction and mediated causation, longitudinal modeling, and nonrecursive models with loops. It also evaluates models on several dimensions and examines the polychoric and polyserial correlation coefficients and their derivation. Covering the fundamentals of algebra and the history of causality, this book provides a solid understanding of causation, linear causal modeling, and SEM. It takes readers through the process of identifying, estimating, analyzing, and evaluating a range of models.
Article
It is proposed that a firm's strategy and how it perceives environmental uncertainty can influence the need for R&D–marketing integration. Factors related to organizational design and senior management support, along with the sociocultural differences between R&D and marketing managers, can influence the level of integration achieved by an organization. Finally, it is proposed that the gap between the level of integration needed and that achieved can influence innovation success.
Article
Monte Carlo computer simulations were used to investigate the performance of three χ2 test statistics in confirmatory factor analysis (CFA). Normal theory maximum likelihood χ2 (ML), Browne's asymptotic distribution free χ2 (ADF), and the Satorra-Bentler rescaled χ2 (SB) were examined under varying conditions of sample size, model specification, and multivariate distribution. For properly specified models, ML and SB showed no evidence of bias under normal distributions across all sample sizes, whereas ADF was biased at all but the largest sample sizes. ML was increasingly overestimated with increasing nonnormality, but both SB (at all sample sizes) and ADF (only at large sample sizes) showed no evidence of bias. For misspecified models, ML was again inflated with increasing nonnormality, but both SB and ADF were underestimated with increasing nonnormality. It appears that the power of the SB and ADF test statistics to detect a model misspecification is attenuated given nonnormally distributed data.
Article
With the rapid development of Chinese manufacturing industry and economy, there is an increasing emphasis on the Chinese institutional environment. In this study, we examine the impact of the three aspects of institutional pressures – normative, mimetic, and coercive – on the two dimensions of supplier integration – system and process – and their impact in turn on financial performance. We test the relationships with data collected from 617 manufacturers in China. Our results show that normative and mimetic pressures are positively related to both system and process integration; while coercive pressures are only positively related to process integration and not significantly related to system integration. The results also indicate that both system and process integration have a positive impact on financial performance. By developing and testing a theoretical model about institutional pressures, supplier integration, and financial performance in the context of the Chinese manufacturing industry, this study contributes to both the institutional and supply chain management literature, as well as providing a better understanding of Chinese manufacturing practices.
Article
Limited research examines the effects of interorganizational trust and interdependence on the relationship quality between supply chain partners in the hospitality services. It is also not well understood how the interorganizational joint team manages the relationships between hospitality firms and their suppliers. Drawing on the social exchange theory and the resource dependence theory, we propose a model and hypotheses to articulate the mediation effect of joint teamwork on the relationships between interorganizational trust, interdependence, and relationship quality. We rigorously analyze survey data from hotel and restaurant procurement managers. Our findings confirm that interorganizational trust and interdependence have significant effects on joint teamwork. Meanwhile, the teamwork mediates the effects of interorganizational trust and interdependence on relationship quality. Our work enriches the understanding of supply chain relationships in the hospitality services, and provides meaningful insights for the hospitality firms to manage supply chains. Finally, we conclude our work with suggestions for future research.
Article
This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx. New in the fourth edition of Latent Variable Models: * a data CD that features the correlation and covariance matrices used in the exercises; * new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and * reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching. Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful. © 2004 by Lawrence Erlbaum Associates, Inc. All rights reserved.