A review of using partial least square structural equation modeling in e‐learning research

Lin, Hsiu‐Mei; Lee, Min Hsien; Liang, Jyh Chong; Chang, Hsin Yi; Huang, Pinchi; Tsai, Chin Chung

doi:10.1111/bjet.12890

Cited by 83 publications

(59 citation statements)

References 70 publications

(77 reference statements)

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“…To examine the structural relationships among the students' motivated strategies for learning, perceived immersion and attitudes toward IVR learning activity, partial least squares structural equation modeling (PLS-SEM) analysis was conducted using the SmartPLS software. The PLS-SEM technique is increasingly used in e-learning research for the reasons that it can analyze data with small sample sizes or non-normal data for focusing on prediction (Lin et al, 2019). As a result, this study adopted the PLS-SEM technique to evaluate the structural relationships among the variables.…”

Section: Discussionmentioning

confidence: 99%

Students’ motivational beliefs and strategies, perceived immersion and attitudes towards science learning with immersive virtual reality: A partial least squares analysis

Cheng

Tsai

2020

Brit J Educational Tech

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Section: Discussionmentioning

confidence: 99%

Students’ motivational beliefs and strategies, perceived immersion and attitudes towards science learning with immersive virtual reality: A partial least squares analysis

Cheng

Tsai

2020

Brit J Educational Tech

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“…It can better summarize the information of independent variables and better explain dependent variables by extracting effective comprehensive variables. PLS can overcome the problem of multivariate collinearity caused by the interaction between independent variables, thus greatly eliminating interference factors and improving the accuracy of prediction [28]. It cannot only overcome the collinearity problem, but also emphasize the interpretation and prediction function of independent variables to dependent variables when selecting the feature vectors, eliminate the influence of regression noise and make the model contain the least number of variables.…”

Section: Partial Least Squarementioning

confidence: 99%

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics

Guo

Chen

et al. 2020

Sensors

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It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.

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“…Table 3 shows that the individual item loading is higher than 0.70 and which is also significant at 0.01. Further, the reliability of the scale is assessed through the composite reliability (CR) and average variance extracted (AVE) as recommended by Benitez, Henseler, Castillob, and Schuberthc (2020) and Lin, Lee, Liang, and Chang (2020). The result highlights that CR for legal and regulatory and physical and geographical barriers are all well above the threshold point of 0.70 recommended by Henseler, Hubona, and Ray (2016) and Ali, Rasoolimanesh, Sarstedt, Ringle, and Ryu (2018).…”

Section: Resultsmentioning

confidence: 99%

Place and policy barriers of rural Nigeria's small and medium enterprises' internationalization

Mendy

Odunukan

Rahman

2021

Thunderbird Intl Bus Rev

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Despite internationalization theory's recognition that place and policy constitute fundamental barriers for the internationalization of small and medium enterprises (SMEs), research into rural‐based firms from the developing world is a much underdeveloped and neglected area. To address the need to examine this gap, the purpose of this study is to identify and compare place and policy challenges of rural SMEs' internationalization in Nigeria. We have developed a model that extends internationalization theory's overemphasis on the structural aspects of these barriers and thereby provide a resolution tool for managers. By using partial least squares (PLS) path modeling methodology, we also administered 403 questionnaires in six of Nigeria's geopolitical zones. Our three‐stage analyses reveal findings that the physical and geographical (or place barrier) challenges account for 90% whilst the traditionally neglected aspects of legal and regulatory barriers score 85%. Therefore, place related barriers should be given slightly higher priority if it is not possible to be given equal recognition in internationalization theory. These findings provide new insights into a more complex picture of SMEs' internationalization in emerging economies. It is recommended that our Human‐centric Hierarchical Model could help inform managers' decision‐making processes on what human aspects they need to prioritize when faced with policy and place barriers. It is also recommended that our model adds social value to SME businesses and provides a new lens for scholars to investigate place and policy related barriers to rural Nigeria's SMEs.

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A review of using partial least square structural equation modeling in e‐learning research

Cited by 83 publications

References 70 publications

Students’ motivational beliefs and strategies, perceived immersion and attitudes towards science learning with immersive virtual reality: A partial least squares analysis

Students’ motivational beliefs and strategies, perceived immersion and attitudes towards science learning with immersive virtual reality: A partial least squares analysis

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics

Place and policy barriers of rural Nigeria's small and medium enterprises' internationalization

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