Variation Sharing

2017 ◽  
Vol 8 (4) ◽  
pp. 46-68 ◽  
Author(s):  
Ned Kock ◽  
Shaun Sexton
Keyword(s):  
Measurement Error ◽  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variables ◽  
Structural Equation ◽  
Least Squares Method ◽  
Fundamental Problem ◽  
Equation Modeling ◽  
Path Coefficient ◽  
Least Squares Regression

The most fundamental problem currently associated with structural equation modeling employing the partial least squares method is that it does not properly account for measurement error, which often leads to path coefficient estimates that asymptotically converge to values of lower magnitude than the true values. This attenuation phenomenon affects applications in the field of business data analytics; and is in fact a characteristic of composite-based models in general, where latent variables are modeled as exact linear combinations of their indicators. The underestimation is often of around 10% per path in models that meet generally accepted measurement quality assessment criteria. The authors propose a numeric solution to this problem, which they call the factor-based partial least squares regression (FPLSR) algorithm, whereby variation lost in composites is restored in proportion to measurement error and amount of attenuation. Six variations of the solution are developed based on different reliability measures, and contrasted in Monte Carlo simulations. The authors' solution is nonparametric and seems to perform generally well with small samples and severely non-normal data.

To verify or not to verify: using partial least squares to predict effect of online news on panic buying during pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kim-Lim Tan ◽  
Joseph Kee-Ming Sia ◽  
Daniel Kuok Ho Tang
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Structural Equation ◽  
Least Squares Method ◽  
Online News ◽  
The Body ◽  
Equation Modeling ◽  
Initial Attempt ◽  
Content Type ◽  
Partial Least Squares Method

PurposeCoronavirus disease (COVID-19) pandemic has given rise to different dimensions of uncommon human behavior, and panic buying is one of them. Interestingly, panic buying research has not been given much attention. The purpose of this paper is threefold. Firstly, it examines the influences of the theory of planned behavior (TPB) elements (subjective norm, attitude and perceived behavior control (PBC)) on panic buying. Secondly, it investigates online news and the perceived likelihood of being affected (PLA) as antecedents to the TPB constructs. Finally, to examine online news verification as a moderator on the relationship between the TPB constructs and panic buying.Design/methodology/approachData were collected from 371 respondents and analyzed using the partial least squares method structural equation modeling (PLS-SEM). PLS predict was applied to determine the predictive power of the model further.FindingsThis study found that subjective norms and attitude influence panic buying. The results further revealed that online news has a direct influence on the PLA and attitude. However, PBC has no such effect on panic buying. Surprisingly, online news verification also has no moderating effects on the relationships between the TPB elements and panic buying.Originality/valueThis research helps to understand consumer panic buying behavior, especially during shock events such as the COVID-19 pandemic. This study is the first that extends the TPB incorporating both online news and PLA as antecedents to panic buying in the same model. Furthermore, the study serves as an initial attempt to investigate online news verification as a moderator between the link of three constructs of TPB and panic buying, contributing to existing literature. Lastly, it advances the body of knowledge on consumer behavior and contributes methodologically by introducing the PLS approach.

scholarly journals Learning Mathematics of Financial Operations during the COVID-19 Era: An Assessment with Partial Least Squares Structural Equation Modeling

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2120
Author(s):  
María del Carmen Valls Martínez ◽  
Pedro Antonio Martín-Cervantes ◽  
Ana María Sánchez Pérez ◽  
María del Carmen Martínez Victoria
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Modeling ◽  
Valuation Model ◽  
Video Tutorials ◽  
Effective Performance ◽  
Teaching Learning

The COVID-19 pandemic has affected all walks of life, including education. Universities have been forced to teach in a blended or online environment, which has led professors to adapt their traditional teaching–learning methodologies. The professors of Mathematics of Financial Operations at the University of Almeria (Spain) have created video tutorials so that students can autonomously prepare the theoretical part of the subject, leaving the face-to-face classes for practical exercises. This article aims to analyze the effectiveness of video tutorials and the autonomy finally achieved by students in their learning. For this purpose, a questionnaire was carried out in which, through 21 questions, the constructs Autonomy, Effectiveness, Depth, Format, Challenge, and Use were assessed. Based on these six latent variables, the proposed model using the Partial Least Squares Structural Equation Modeling (PLS-SEM) methodology revealed that students considered the Format and Depth of the video tutorials crucial for genuinely effective performance learning and promoting their autonomy. On the other hand, the variables Challenge and Use were poorly rated. This article presents an original valuation model, which has the virtue of achieving a prediction of 78.6% and, in addition, has high predictive power.

scholarly journals Evaluation of Preventive, Supportive and Awareness Building Measures among International Students in China in Response to COVID-19: A Structural Equation Modeling Approach

2020 ◽  
Author(s):  
Tanwne Sarker ◽  
Apurbo Sarkar ◽  
Md. Ghulam Rabbany ◽  
Milon Barmon ◽  
Rana Roy ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
International Students ◽  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variables ◽  
Convergent Validity ◽  
Structural Equation ◽  
Equation Modeling ◽  
Local Authorities ◽  
The Impact

Abstract Background The Coronavirus Disease 2019 (COVID-19) with its high mortality, stigma and panic has compelled many cities and countries to complete lockdown. The worldwide student group is one of the most affected and vulnerable communities in this situation. Our current study aimed to assess the impact of the behavior change communication among international students in China in current COVID-19 crisis.Methods In this paper, we have utilized partial least squares-structural equation modeling (PLS-SEM) to understand the health behaviour changes of international students in China in response to novel Coronavirus outbreak. We mainly analyzed the relationship among the three selected latent variables (preventive, supportive and awareness building) based on a survey among the international students (n=467) in China in February 2020. We obtained their valuable responses regarding level of awareness, satisfaction and trust in authorities (i.e., government, local authorities and institutions) during this emergency period. Results We utilized 22 indicators in the conceptual framework model with the help of Smart PLS 2.0 version software. The lowest average variance extracted (AVE) for all the constructs of our paper exceeded the minimum accepted value of 0.5, representing the adequate convergent validity. Prediction of students’ satisfaction, the key outcome degree of the model, was nearly moderate, with an R2 = 0.507 whereas the prediction of trust in authorities was above substantial, with an R2 = 0.797. Therefore, our PLS-SEM model showed a strong and significant positive association between preventive and supportive measures taken for the study population and gaining trust, awareness and satisfaction in authorities. Conclusions Integrated partial least squares-structural equation modeling (PLS-SEM) can be a great way to measure the satisfaction and trust level of various population groups over government, local authorities, and institutions in public health emergency like COVID-19 crisis. We believe that our findings are important for travel and global health perspectives. Other countries can learn and take necessary initiatives for their international students and general public to halt this deadly epidemic with gaining their satisfaction and trust as well.

scholarly journals The sampling design effect on partial least squares algorithm

2016 ◽  
Vol 5 (9) ◽  
pp. 84
Author(s):  
Hugo Serrato González ◽  
Ignacio Méndez Ramírez ◽  
Odette Lobato Calleros
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variables ◽  
Structural Equation ◽  
Sampling Design ◽  
Equation Modeling ◽  
Selection Probability ◽  
Sampling Distributions ◽  
Feasible Option ◽  
Selection Of

The objective of this article is to analyze the effect of the probability sampling’s selection on the estimated results in Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) algorithm.The idea leading this work is to estimate the satisfaction level of government service users in a large and dispersed population, for which a sample design with an equal selection probability is not a feasible option. This study is based on the analysis of the sampling distributions of estimators under different sampling designs.It is shown that the probability of selection of the units behind the sampling design affect the results of the PLS algorithm, both the scores of latent variables and the impacts between them.To the author's knowledge, this issue has not been addressed before in the literature.

scholarly journals eWOM in C2C Platforms: Combining IAM and Customer Satisfaction to Examine the Impact on Purchase Intention

2021 ◽  
Vol 16 (5) ◽  
pp. 1612-1630
Author(s):  
Salvador Bueno ◽  
M. Dolores Gallego
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Purchase Intention ◽  
Structural Equation ◽  
Source Credibility ◽  
Positive Impact ◽  
Equation Modeling ◽  
Research Model ◽  
Argument Quality ◽  
The Impact

This study is focused on communications that come from consumer-to-consumer (C2C) ecommerce relationships. This topic is directly associated with the electronic word-of-mouth (eWOM) phenomenon. eWOM is related to the set of positive or negative opinions made by potential, actual, or former customers about a seller. The present study proposes a structural equation modeling with partial least squares (PLS-SEM) research model to analyze consumers’ opinions impact on attitude toward purchasing. This model is based on the Information Adoption Model (IAM) in combination with an ecommerce satisfaction perspective, comprising five constructs: (1) service quality, (2) ecommerce satisfaction, (3) argument quality, (4) source credibility and (5) purchase intention. The model was tested by applying the Smart Partial Least Squares (SmartPLS) software for which 116 effective data from customers of the Taobao C2C platform were used. The findings reveal that all of the defined relationships were supported, confirming the positive impact of all the proposed constructs on the purchase intention. In this respect, the findings suggest that C2C platforms should strengthen the analyzed connections to grow the business and to promote transactions. Finally, implications and limitations related to the explanatory capacity and the sample are identified.

Smart shopping: the adoption of grocery shopping apps

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lee-Andra Bruwer ◽  
Nkosivile Welcome Madinga ◽  
Nqobile Bundwini
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variables ◽  
Moderating Effect ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Grocery Shopping ◽  
Intention To Use ◽  
Content Type

PurposeThe purpose of this paper is to determine the key factors influencing the adoption of grocery shopping and to examine the moderating effect of education between antecedents of the adoption of grocery shopping apps and user attitude and intention to purchase.Design/methodology/approachThis study adopted partial least squares structural equation modeling (PLS-SEM) to evaluate the relationship between the latent variables: perceived usefulness, perceived ease of use, attitude and intention to use grocery shopping apps. Partial least squares multigroup analysis (PLS-MGA) was used to examine the moderating effect of education. A total of 305 grocery shopping apps users were surveyed using a structural questionnaire.FindingsThe results indicated that all the factors considered in the framework were significant in predicting the intention to use the grocery shopping apps. The findings show that education has no significant impact on any relationship.Practical implicationsA better understanding of the factors that affect the acceptance of mobile grocery shopping apps is important for developing better strategic management plans.Originality/valueThis is one of the first studies to research the adoption of grocery shopping apps in a developing country, as well as the first to focus on consumers in South Africa.

scholarly journals Applying the Theory of Planned Behavior to Examine Pro-Environmental Behavior: The Moderating Effect of COVID-19 Beliefs

2020 ◽  
Vol 12 (24) ◽  
pp. 10556
Author(s):  
Caterina Lucarelli ◽  
Camilla Mazzoli ◽  
Sabrina Severini
Keyword(s):  
Climate Change ◽  
Theory Of Planned Behavior ◽  
Least Squares ◽  
Partial Least Squares ◽  
Planned Behavior ◽  
Structural Equation ◽  
Environmental Behavior ◽  
Group Analysis ◽  
Policy Implications ◽  
Equation Modeling

The COVID-19 pandemic and climate change issues present evident interdependencies which justify the spread of connected beliefs. We examine possible changes in individuals’ pro-environmental behavior in light of this pandemic, using the Theory of Planned Behavior (TPB) framework. A questionnaire survey was submitted to the same sample of individuals, before and during the pandemic. Our evidence, based on Partial Least Squares Structural Equation Modeling (PLS-SEM), shows that the COVID-19 pandemic has not led to a weakening in TPB construct relationships, or in related Pro-Environmental Behavior (PEB). Conversely, through our Partial Least Squares-Multi-Group Analysis (PLS-MGA), we show that individuals with greater awareness of interdependencies between the COVID-19 and climate change exhibit both higher Intention and reinforced Pro-Environmental Behaviors. This finding reveals interesting policy implications in terms of innovative behavioral drivers that should be employed to steer public support towards climate-oriented initiatives.

Sign in / Sign up

Export Citation Format

Share Document