PLS-SEM or CB-SEM: updated guidelines on which method to use

Numerous statistical methods are available for social researchers. Therefore, knowing the appropriate technique can be a challenge. For example, when considering structural equation modelling (SEM), selecting between covariance-based (CB-SEM) and variance-based partial least squares (PLS-SEM) can be challenging. This paper applies the same theoretical measurement and structural models and dataset to conduct a direct comparison. The findings reveal that when using CB-SEM, many indicators are removed to achieve acceptable goodness-of-fit, when compared to PLS-SEM. Also, composite reliability and convergent validity were typically higher using PLS-SEM, but other metrics such as discriminant validity and beta coefficients are comparable. Finally, when comparing variance explained in the dependent variable indicators, PLS-SEM was substantially better than CB-SEM. Updated guidelines assist researchers in determining whether CB-SEM or PLS-SEM is the most appropriate method to use.

Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)In view of its essential role in knowledge creation, multivariate data analysis prevails in the social sciences literature. The field of tourism is not an exception, specifically in the widely adoption of structural equation modeling (SEM), a multivariate technique, by tourism researchers over the past decade. While there are two major types of SEM including covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM), the former dominated previous tourism research. However, increasing use of PLS-SEM in tourism research has been witnessed in recent years. This upward trend is likely to persist in the near future given the growing popularity of PLS-SEM in other social sciences domains like marketing, strategic management, and management information system, as specified in the preface of the book. Indeed, PLS-SEM, in relative to CB- SEM, provides more flexibility in handling of data. For instance, PLS-SEM is well-suited for accommodating small sample sizes and complex model, fortesting a model containing both formative and reflective constructs, and for handling single-item measures. To this end, the timely introduction of the book A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) helps tourism researchers stand at the front edge of the SEM technique and make effective use of the PLS-SEM in data analysis. Additionally, the book illustrates the application of PLS-SEM with a free downloadable software namely SmartPLS which is essential to extend the application of PLS-SEM in tourism research.Authored by Hair, Hult, Ringo, and Sarstedt, the book consists of eight chapters. To equip the readers with the basic knowledge of PLS- SEM, Chapter 1 delineates the meaning of SEM and its relationship with multivariate data analysis, followed by a description of the major elements in multivariate data analysis. Then the basic elements of PLS-SEM are explained. Finally, PLS-SEM is distinguished from its counterpart namely CB-SEM while the major characteristics of PLS-SEM and the conditions where the PLS-SEM are more adequate than CB-SEM and vice versa are discussed. To step in the application of PLS- SEM, Chapter 2 firstly explicates the concepts in structural model specification including mediation, moderation, and higher-order models. Then specification of measurement model is explained with a special focus on the differences between reflective and formative measures. After that, the issues that need to be addressed after data collection are discussed. The chapter ends by creating the model in the SmartPLS is illustrated. With an established model, Chapter 3 focuses on model estimation. The chapter explains the algorithm underpinning the estimation and the statistical properties of the PLS-SEM method, as well as the options and parameter settings for running the algorithm. Following that, the issues about interpretation of results are explained. The final section illustrates the execution of model estimation in the SmartPLS.Based on the model estimation, empirical measures of the measurement and structural models are derived, where evaluation of the models takes place. Chapter 4 exhibits the major steps in model evaluation in the beginning. Thereafter, the chapter explains the evaluation of reflective measurement models according to three major criteria including internal consistency reliability, convergent validity, and discriminant validity, followed by an illustration with the SmartPLS. Chapter 5 explains the assessment of formative measurement models with respect to the criteria of convergent validity, collinearity, and significance and relevance of the formative indicators. The chapter also elucidates the basic concepts of bootstrapping which is used to examine the statistical significance of estimates in PLS- SEM. An illustration of the assessment of formative measurement model in the SmartPLS follows. Chapter 6 continues the topic on model evaluation by focusing on the assessment of structural model. …

transfer, create conditions for the establishment of farmers' behavioral psychological contracts in the process of agricultural land transfers, and guide farmers to establish relationship psychological contracts. The second is to improve the market system, properly cultivate and develop agricultural land transfer intermediaries, reduce transaction costs, and reduce the probability of farmers' psychological contracts being broken. The third is to guide farmers to establish a positive agricultural land transfer psychology based on their resource endowments such as labor force quality and cultural quality, and encourage farmers to make agricultural land transfer decisions such as subcontracting, leasing, reselling, and interchanging.

The measurement of unobservable (latent) variables has been a recent phenomenon in the manufacturing research area. Most available empirical research in manufacturing has been exploratory in nature and has borrowed its methods extensively from other fields such as psychology, sociology, and marketing. Traditional exploratory techniques have been used to provide preliminary scales and assess measurement properties. Manufacturing researchers have, however, overlooked the assessment of unidimensionality, an essential measurement property and a basic assumption of measurement theory. An explicit evaluation of unidimensionality can be accomplished with a confirmatory factor analysis (CFA) of individual measures as specified by a multiple‐indicator measurement model. A paradigm for scale evaluation incorporating CFA for the assessment of unidimensionality is outlined here along with methodology to assess other measurement properties such as convergent validity, discriminant validity, composite reliability, and average variance extracted. A measurement model is tested first followed by a structural model of interest. The hypothesized structural model relates pull production with two of its antecedents, setup improvement and preventive maintenance practices. It further relates pull production to one of its consequences, delivery dependability. Responses from 244 firms are used to test the measurement and structural model.

Customer experience (CX) has received substantial attention in empirical research in the recent past. While there has been growing research interest in customer experience, few studies have examined its relationship with other concepts such as customer loyalty, customer satisfaction and service quality. This study investigates the relationship between customer experience and customer loyalty in retail banking with multiple channels of distribution. Further, the study seeks to advance research on the relationship between customer experience and customer loyalty by exploring the mediation roles of customer satisfaction and service quality in the retail banking industry in South Africa. The South African retail banking industry is increasingly competitive and regularly confronted with new entrants. Technological innovations, regulatory requirements, changing customer expectations, demographics and new non-traditional industry entrants are disrupting the banking industry. The services offered by retail banks are highly undifferentiated and hence there is a need for banks to look for other ways to compete than through differentiation of products. When one of the banks introduces a new service to the market, other banks typically follow suit quickly by imitating it. Subsequently, core services offered by all banks tend to be very similar in nature and form. In addition, customers are highly knowledgeable and selective, and they are increasingly raising their expectations in terms of the quality of services they receive from the banks. In view of this, banks therefore need to have a clear understanding of their customers’ needs and develop relevant offerings that can retain their customers. Relationship marketing is believed to be one of the ways in which banks can create long-term relationships with their customers, thereby gaining their loyalty. Specifically, focusing their efforts on creating advantageous customer experiences, essential to forming long-term loyal relationship with the customers. Thus, this study is aimed at determining the relationship between customer experience and customer loyalty. This is achieved by exploring the influence of selected constructs, namely service quality and customer satisfaction, in order to analyse the role of customer experience as a predictor of loyalty. To achieve the objectives of the study, a quantitative descriptive research approach that was cross-sectional in nature was adopted. A non-probability convenience sampling method was followed to select a sample of 500 bank customers across the Durban region in KwaZulu-Natal, South Africa. A questionnaire was developed from validated measurement scales from previous studies and a literature review. Data was collected by means of a self-administered questionnaire that was distributed physically and online to bank customers. A total of 466 responses was received from the data collection process. The Statistical Package for the Social Sciences (SPSS) 24.0 and Smart Partial Least Square (SmartPLS4) were used to analyse the data. Using data from the survey and Partial Least Squares Structural Equation Modelling (PLS-SEM), a theoretical model was created and empirically tested. This model indicates that customer loyalty can be achieved by improving customer experiences, enhancing service quality and improving customer satisfaction. The results of descriptive statistics indicated an overall mean below 2.5. The presentation then progressed to the SEM analysis, which was done in two stages. The first stage examined the measurement model. As stated, the model in this study is a reflective hierarchical model. The CX construct is a reflective-reflective HOC, and its dimensions of feeling, behavioural, sensorial, cognitive and social are the LOCs; hence, a repeated indicator approach was used to assess the measurement model. The reliability of the reflective measurement model was assessed using indicator reliability, Cronbach’s alpha and composite reliability (rho_c). The convergent validity of the constructs was examined using AVE, while the Fornell Larker technique and the heterotrait-monotrait (HTMT) ratio were used to assess the discriminant validity of the constructs. Thus, using CFA, the validity by means of convergent and discriminant validity as well as the reliability of the model were established. After the measurement model was deemed fit, the structural model was examined by means of path coefficients, variance explained (R2 ) and predictive relevance (Q2 ). The R2 results for the structural model were above 0.65 for all variables, which is considered a substantially good fit, while the Q2 the values obtained were 0.616, 0.694 and 0.712 for customer loyalty, customer satisfaction and service quality respectively. The model was found to be satisfactory for both measurement and structural models, after which relationships among variables were tested for significance. All relationships were found to be positive and significant The results show the key role of customer experience and its impact on customer loyalty and that this relationship is mediated by customer satisfaction and service quality. These findings contribute towards improving the theoretical knowledge of the influence of customer experience on loyalty, and guide retail banks in developing and implementing appropriate customer experience strategies.

BackgroundSocial media has transformed health communication into a dynamic and interactive process, shifting from one-way dissemination by experts to user-driven content creation and sharing. However, this openness also facilitates the spread of misinformation, which poses a threat to public health behaviors. While prior research has explored dialogue paths and narrative analysis independently, there remain gaps in understanding their interactive effects and the contextual heterogeneity-such as platforms, user groups, and emotions-on health behaviors. This study addresses these gaps within China’s social media landscape.MethodsA multi-method approach was employed.Data collectionBetween January 2023 and December 2024, over 50,000 data points related to health communication were collected from prominent Chinese social media platforms, including Weibo, WeChat, Xiaohongshu, and Douyin. From this comprehensive dataset, a subsample of 300 valid user cases was identified for structural equation modeling (SEM), to ensure statistical adequacy and model robustness.Survey300 valid questionnaires assessed user perceptions and behaviors regarding health information.AnalysisDrawing upon health communication theory and narrative persuasion frameworks, a structural equation modeling (SEM) approach was employed to test the proposed conceptual model. The SEM analysis comprised two essential stages: (1) the measurement model stage, where the reliability and validity of latent constructs were evaluated through confirmatory factor analysis (CFA), including assessments of convergent and discriminant validity; and (2) the structural model stage, which examined the hypothesized relationships among dialogue path, narrative structure, engagement, and health behavior outcomes.ResultsThe results of the structural equation modeling (SEM) indicate that both dialogue pathways and narrative strategies significantly influence users’ health information behaviors. Specifically, dialogue depth exhibited a strong positive effect on information sharing behavior, while narrative consistency was significantly related to feedback intention. The measurement model confirmed good reliability and validity, with all factor loadings exceeding 0.7 and composite reliabilities surpassing 0.8. Normality tests indicated acceptable skewness and kurtosis for all observed variables. Furthermore, multi-group analysis revealed that platform type moderates the strength of these relationships, with Weibo users demonstrating more emotionally driven interaction patterns compared to WeChat users.ConclusionThis study identifies dialogue coherence, emotional narrative structure, and user engagement as significant predictors of health-related behavioral intentions within social media contexts. Notably, engagement serves as a crucial mediating variable that links both narrative and dialogic features to behavioral outcomes. These findings enhance our understanding of the mechanisms that underpin digital health communication, specifically by elucidating how narrative processes and dialogue influence user behavior. Practically, the results indicate that health communication initiatives on social media can be improved by integrating emotionally resonant narratives and ensuring coherence in dialogic exchanges, both of which are essential for fostering positive behavioral change. By analyzing dialogic interaction and narrative structure within a unified Structural Equation Modeling (SEM) framework, this research underscores the importance of considering storytelling elements alongside interactive features, thus providing a more comprehensive perspective on how users engage with and are influenced in digital health environments.

This study is very important to ensure that business organizations can formulate and plan a strategic plan to continue to ensure that their business performance remains viable and sustainable. The aim of this study is to assess the direct relationships between corporate image, employee engagement, organizational culture, employee loyalty, and business performance among private business organizations. This study is vital to be carried out because many private organizations face difficulty to maintain their business performance in the coming years. The research model of this study consists of three independent variables: corporate image, employee engagement, organizational culture, employee loyalty as a mediator, and business performance as a dependent variable. This study adopts a quantitative approach by using primary data for analysis. Primary data were utilized in this study and a survey questionnaire which was adopted and adapted from previous studies was used for data collection. 329 clean data were used in the data analysis by utilizing the structural equation modeling (SEM) technique. Smartpls3 was used in this study to run the multivariate data analysis and test the proposed hypotheses. In addition, the model measurement and structural model assessment procedures also were performed by using Smartpls3. The PLS-SEM technique was employed for this study due to its assessment ability. Initially, the convergent validity was evaluated on the measurement model by assessing the construct reliability and validity. Then, the discriminant validity was assessed and confirmed through cross-loading and Hetrotrait-Monotrait (HTMT) ratios. Subsequently, the structural model was assessed and the hypotheses testing reveals that corporate image, employee engagement, and organizational culture, have a positive and significant influence on employee loyalty and business performance was strongly affected by employee loyalty. This shows that corporate image, employee engagement, and organizational culture are very important factors and business organizations need to pay serious attention if they want to ensure that the planned business performance can be achieved.

Objective: This research aims to analyze the relationship between the use of information technology and the quality of financial reports, to analyze the relationship between public accountability and the quality of financial reports. Method: This type of research is classified as quantitative research. Quantitative research is research that emphasizes testing theory - by measuring research variables based on the philosophy of positivism, studying a certain population or sample, collecting data using research tools, analyzing quantitative/statistical data with the aim of testing a given hypothesis. Research data was obtained by distributing an online questionnaire designed using a Likert scale of 1 to 7. The independent research variables were the use of information technology and public accountability. The research sample was 450 government employee respondents. These respondents are known to know best and assess the quality of financial reports. Data analysis used partial least squares (PLS) structural equation modeling (SEM) with SmartPLS 3.0 software tools. The data analysis stage is to assess the validity and reliability of a construct. The tests carried out are Convergent Validity, Discriminant Validity, Cronbach's Alpha and Composite Reliability. The Structural Model (Inner Model) is a measurement to evaluate the level of accuracy of the model in research, the tests carried out are R-Square, F-Square and Path Analysis. Result: Based on the structural equation modeling analysis, the p value is 0.00 < 0.050 and the patch coefficient is positive so that there is a positive and significant relationship between information technology and the quality of financial reports and there is a positive and significant relationship between financial accountability and the quality of financial reports. Conclusion: Based on the results of the analysis, it is found that the use of information technology has a positive effect on the quality of financial reports, Public Accountability has a positive effect on the quality of financial reports. This means that the more accountable financial management and financial reporting, the more performance will improve. High accountability in financial management is expected to increase public trust in the government so that it can create a good investment climate. It is believed that the implementation of accountability will be able to improve the performance of government organizations. The use of information technology has a positive and significant effect on the quality of financial reports and the use of information technology has a significant positive effect on the quality of financial reports. Information technology functions as technology that processes and stores information and disseminates information. The process of processing transaction data and presenting financial reports can be accelerated by the use of good technology so that the value of the information contained in financial reports is not lost.

In this paper, we have discussed and analyzed the impact on the university library service image using questionnaire data of the college students in Zhejiang Area based on the Structural Equation Model (SEM). The determinants include the service time, the service consciousness, the service space and the service attitude. And not only that, but this study put forward tactics for the improve university library service image based on this paper's result.

This research aims to examine organizational commitment model of private university lecturers in Indonesia, using three independent variables, namely internal marketing, job satisfaction and organizational justice. Data collection was done by survey method on 200 private university (PTS) lecturers under the Higher Education Service Institutions covering 14 regions in Indonesia. Helped by PLS (Partial Least Square), SEM (Structural Equation Model) was used to process the data collected. Accordingly, to check the validity, the measurement model was evaluated based on several reflective indicators (convergent and discriminant validity as well as composite reliability). Based on the result of discriminant and convergent validity, it is known that the whole constructs are valid as both the outer loading and AVE (Average Variance Extracted) value are > 0.70, moreover, a similar good result shown in composite reliability evaluation with the value of > 0.70. Finally, the results found showed that seven hypotheses, out of nine hypotheses, were proven to be true. On the other hand, for the other hypotheses, the findings showed that organizational justice and Internal marketing had no direct effect on organizational commitment. Next, it is also known that organizational justice and job satisfaction were proven to be the mediators of in the relation between internal marketing and organizational commitment.

On Issues of Validity and Especially on the Misery of Convergent Validity

There are several points of intersections on findings of authors on social and personal characteristics which brought diverse changes in personal and professional life, impacted social organizations and human relations (Lévy, 2001). Human relations are built on cyber culture which is more evident during COVID-19. This led to new ways of thinking and communicating among the individuals. Despite the substantial body of literature concerning different management models aligned with technostress and employee’s job satisfaction in the business field have not yet grown significantly. This paper aims to analyze and establish relation between technostress and employee’s job satisfaction by fitting a structural equation modeling approach. Analyses of the measurement model confirmed its convergent validity, composite reliability and discriminant validity. The analysis of the structural model showed discrepancies in some constructs, which, to some extent, disconfirm theoretical assumptions regarding the systemic and balanced relationships among the concepts. On the other hand, the results confirm the relationship between the variables. The study revealed the variables having impact on technostress, job satisfaction and organisational commitment in different proportions. Technostress also showed to have impact on job satisfaction and organisational commitment. The study used Structural Equation Modeling (SEM) method to find the relationship between technostress creators and Job satisfaction. The findings showed a negative impact of technostress creators on job satisfaction.

Understanding Consumer's purchase intention and consumption of convenience food in an emerging economy: Role of marketing and commercial determinants

Structural equation modeling (SEM) was employed to analyze the influence of exogenous variables (research and extension (RE), marketing aspects (MA), and infrastructure development (ID)) on the endogenous variable chickpea production development (CPD) to restructure policy interventions in India. Results of the measurement model revealed that all the latent variables have construct validity (both convergent validity and discriminant validity) and composite reliability. Confirmatory factor analysis revealed that all indicators of both exogenous and endogenous variables are significant. Yield-increasing production technologies (PT), minimum support prices (MSP), and storage structures (SS) and the three exogenous variables (research and extension, marketing, and infrastructure development) are the strongest indicators. For the endogenous variable CPD, remunerative prices (RP) is the strongest indicator and also serves as a driving force for other indicators. The results of the structural model revealed that RE is the most effective construct followed by ID and MA, and they cumulatively explained 89 percent of the total variation in CPD. Among these three constructs, MSP is the key indicator of MA with the highest loading factor (0.799), and hence it should be given the highest priority for promoting CPD in India.

The utility of Structural Equation Modelling (SEM) approach into research in psychology, especially in psychometrics development have not yet been fully explored. The proportion of utilization between SEM sub models in research field (i.e. structural model and measurement model) was unbalance. Numerous researcher has used SEM only to test their structural model but avoid to use SEM to identify its measurement model. This article explain SEM function to estimate reliability of measurement. The reliability coeffcient such as composite reliability, construt reliability and maximal reliability are outlined.