Academic literature on the topic 'PLS–PM modeling'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'PLS–PM modeling.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "PLS–PM modeling"
1
Afthanorhan, Asyraf, Zainudin Awang, and Nazim Aimran. "Five Common Mistakes for Using Partial Least Squares Path Modeling (PLS-PM) in Management Research." Contemporary Management Research 16, no. 4 (2020): 255–78. http://dx.doi.org/10.7903/cmr.20247.
Full textAbstract:
The value of Partial Least Squares Path Modeling (PLS-PM) in management research has now been acknowledged, although the PLS-PM was developed for a reason. First, the PLS-PM was developed as an alternative to Covariance based Structural Equation Modeling (CBSEM) when exploratory research is conducted. As far as this method concerned, many researchers are misused or overuse the application of PLS-PM without understanding the basic knowledge in structural equation modeling. Thus, the purpose of this paper is to discuss the five common mistakes (data distributions, sample size limitations, unsatisfactory fitness index, misunderstanding between confirmatory and exploratory research, and poor factor loadings) for using PLS-PM over CB-SEM in management research. We concluded that the researchers should respect these methods and justify their use when conducting the research projects because some of the projects might be better for CB-SEM or PLS-PM.
2
Müller, Tobias, Florian Schuberth, and Jörg Henseler. "PLS path modeling – a confirmatory approach to study tourism technology and tourist behavior." Journal of Hospitality and Tourism Technology 9, no. 3 (2018): 249–66. http://dx.doi.org/10.1108/jhtt-09-2017-0106.
Full textAbstract:
Purpose As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to model artifacts. To deal with both kinds of constructs, this paper aims to exploit partial least squares path modeling (PLS-PM) as a confirmatory approach to estimate models containing common factors and composites. Design/methodology/approach The study at hand presents PLS-PM in its current form, i.e. as a full-fledged approach for confirmatory purposes. By introducing the composite to model artifacts, TTH scholars can use PLS-PM to answer research questions of the type “Is artifact xyz useful?”, contributing to a further understanding of TTH. To demonstrate the composite model, an empirical example is used. Findings PLS-PM is a promising approach when the model contains both common factors and composites. By applying the test for overall model fit, empirical evidence can be obtained for latent variables and artifacts. In doing so, researchers can statistically test whether a developed artifact is useful. Originality/value To the best of the authors’ knowledge, this is the first study to discuss the practical application of composite and common factor models in TTH research. Besides introducing the composite to model artifacts, the study at hand also guides scholars in the assessment of PLS-PM results.
3
Klesel, Michael, Florian Schuberth, Jörg Henseler, and Bjoern Niehaves. "A test for multigroup comparison using partial least squares path modeling." Internet Research 29, no. 3 (2019): 464–77. http://dx.doi.org/10.1108/intr-11-2017-0418.
Full textAbstract:
Purpose People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches. Design/methodology/approach The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches. Findings Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach. Research limitations/implications Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations. Originality/value This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.
4
Klesel, Michael, Florian Schuberth, Björn Niehaves, and Jörg Henseler. "Multigroup Analysis in Information Systems Research using PLS-PM." ACM SIGMIS Database: the DATABASE for Advances in Information Systems 53, no. 3 (2022): 26–48. http://dx.doi.org/10.1145/3551783.3551787.
Full textAbstract:
Heterogeneity is a pertinent issue in Information Systems (IS) research because human behavior often differs across groups. In the partial least squares path modeling (PLS-PM) context, several approaches have been proposed to investigate potential group differences. Despite the availability of numerous approaches, literature that compares their efficacy is sparse. Consequently, IS researchers lack guidance on which approach is best suited to detect group differences. We address this issue by presenting the results of an extensive Monte Carlo simulation study that juxtaposes the various approaches' behavior under numerous conditions. In doing so, we first provide an overview on existing approaches proposed for multigroup analysis (MGA) in the PLS-PM context. Moreover, we derive important implications for applied research: Firstly, we show that the omnibus test of group differences (OTG) and approaches based on the comparison of confidence intervals are not recommendable for MGA. Secondly, we provide detailed information as to which approaches are suitable for comparing one specific path coefficient and which are recommended if the complete structural model is compared across groups. Finally, we show that approaches which are designed to compare a single parameter require an adjustment for multiple comparisons when used to compare more than two groups.
5
Matskul, Valerii, Anatoliy Kovalyov, Valentyn Chernyshev, and Diana Okara. "Stable development of travel business in the Odessa region: Estimate using multivariate statistical analysis." SHS Web of Conferences 91 (2021): 01035. http://dx.doi.org/10.1051/shsconf/20219101035.
Full textAbstract:
The article examines the level of sustainable development of the travel business in the Odessa region of Ukraine. This level is evaluated as a latent indicator, which is characterized by a certain set of signs-symptoms. The methodology used for modeling is Partial Least Squares-Path Modelling (or PLS-PM) and the method Time-Wise Multi-Way Principal Component Analysis. This approach allowed us to identify and evaluate latent and explicit factors affecting the sustainable development of travel business in the Odessa region.
6
Nuzila Ismatilah and Abdul Kudus. "Faktor-Faktor yang Memengaruhi Kepuasan Konsumen Pengguna Jasa Transportasi Ojek Online dengan Partial Least Square Path Modeling (PLS - PM)." Bandung Conference Series: Statistics 2, no. 2 (2022): 332–42. http://dx.doi.org/10.29313/bcss.v2i2.4316.
Full textAbstract:
Abstract. One of the new approaches introduced by Herman Wold, is Partial Least Square (PLS) which is often referred to as soft modeling. PLS is a powerful analytical method because it is not based on many assumptions. PLS does not require multivariate normal assumptions, can be used at all measurement scales and the sample size does not have to be large. PLS is used to see the influence and magnitude of the influence of the independent variable (X) on the dependent variable (Y). The variables used are latent variables that cannot be measured directly, except using manifest variables or indicators. In the case of customer satisfaction who does not have a measuring instrument, an indicator is used as a measuring tool. The purpose of this study is to apply the Partial Least Square method to consumer satisfaction using Gojek's Online ojek transportation services. The results of this method as a whole have a significant effect, but there is one variable that does not have an effect, namely reliability, and the variable that can have the greatest influence is empathy.
 Abstrak. Salah satu pendekatan baru yang diperkenalkan oleh Herman Wold, adalah Partial Least Square (PLS) yang sering disebut sebagai soft modelling. PLS merupakan metode analisis yang powerfull karena tidak didasarkan pada banyak asumsi. PLS tidak memerlukan asumsi normal multivariat, dapat digunakan di semua skala pengukuran dan ukuran sampel tidak harus besar. PLS digunakan untuk melihat pengaruh dan besarnya pengaruh variabel independen (X) terhadap variabel dependen (Y). Variabel yang digunakan merupakan variabel laten yang tidak dapat diukur secara langsung, kecuali menggunakan variabel manifes atau indikator. Dalam hal kepuasan konsumen yang tidak memiliki alat ukur, maka digunakanlah indikator sebagai alat ukurnya. Tujuan dari penelitian ini adalah mengaplikasikan metode Partial Least Square pada kepuasan konsumen pengguna jasa transportasi ojek Online milik Gojek.Penelitian ini menghasilkan keberpengaruhan dan besarnya pengaruh dari variabel tangibles, reliability, responsiveness, assurance dan empathy terhadap kepuasan konsumen pengguna ojek Online milik Gojek. Hasil dari metode ini secara keseluruhan memberikan pengaruh yang signifikan, tetapi ada satu variabel yang tidak memberikan pengaruh yaitu reliability, serta variabel yang dapat memberikan pengaruh paling besar adalah empathy.
7
Sánchez-García, Jacqueline Y., Ana Gabriela Ramírez-Gutiérrez, Juan E. Núñez-Ríos, Pedro Pablo Cardoso-Castro, and Omar G. Rojas. "Systems Thinking Approach to Sustainable Performance in RAMSAR Sites." Sustainability 11, no. 22 (2019): 6469. http://dx.doi.org/10.3390/su11226469.
Full textAbstract:
This article explores and validates the integrated use of the viable system model (VSM) and the partial least squares path modeling (PLS-PM) approach to assess the sustainable management of RAMSAR sites carrying out economic activities. This work adopts a systems-thinking approach integrating systemic methodologies in three phases: (1) the VSM was first used to develop a conceptual model of the organisational problem; (2) PLS-PM was used to propose a construct to outline a solution, as well as to statistically validate the relationships proposed in the conceptual model; finally, (3) through the VSM, the relationships between actors were rethought in order to promote sustainable performance. The results obtained suggest that the joint use of VSM and PLS-PM is an effective approach that aids in the identification of relational and structural pathologies affecting the observed RAMSAR systems. It also proved useful to suggest that relationships can lead to the sustainable performance of the sites under study. It should be noted that the framework of systemic tools is constrained in its application to the organisational domain: assessing two RAMSAR areas in Mexico. Methodologically, this is the first application of the integrated use of VSM and PLS-PM to analyse the management and viability/sustainability of RAMSAR areas from an organisational perspective, opening a new avenue for the analysis and optimisation of management of such areas. This study provides tools to support actors and academics related to RAMSAR sites and opens up a discussion on how to rethink the organisational interactions in order to improve RAMSAR sites’ adaptive capabilities.
8
Salam, Rudi, I. Made Sumertajaya, Hari Wijayanto, Anang Kurnia, and Timbang Sirait. "Higher Order Partial Least Squares Path Modeling Using Binary Data: An Application on Multidimensional Poverty and Social Protection in East Java Province." Asian Journal of Mathematics and Computer Research 30, no. 4 (2023): 118–37. http://dx.doi.org/10.56557/ajomcor/2023/v30i48458.
Full textAbstract:
The standard partial least squares path modeling (PLS-PM) estimation process assumes the observed data as continuous variables. With slight modifications, this estimation algorithm can be used for data on a binary scale and even for more complex models such as higher order constructs. This study aims to determine by simulation and application of real data the performance of the higher-order construct modeling approach, which of the repeated indicator and two-stage approaches provides better results. From simulation study it was found that the repeated indicator approach with binary data (BinPLS) was better than the two-stage approach. Empirical results also show that the BinPLS measurement model with the repeated indicator approach is better than standard PLS. Evaluation of the structural model also shows that BinPLS with a repeated indicator approach is the best because it produces path coefficients and the power to explain multidimensional poverty and social protection models that are better than BinPLS with a two-stage approach and standard PLS.
9
Zulkifli, Raudhah, Nazim Aimran, Sayang Mohd Deni, and Fatin Najihah Badarisam. "A comparative study on the performance of maximum likelihood, generalized least square, scale-free least square, partial least square and consistent partial least square estimators in structural equation modeling." International Journal of Data and Network Science 6, no. 2 (2022): 391–400. http://dx.doi.org/10.5267/j.ijdns.2021.12.015.
Full textAbstract:
Structural equation modeling offers various estimation methods for estimating parameters. The most used method in covariance-based structural equation modeling (CB-SEM) is the maximum likelihood (ML) estimator. The ML estimator is typically used when fitting models with normally distributed data. The growth of partial least squares path modeling (PLS-PM), including consistent partial least squares (PLSc), has also been noticed by researchers in the SEM fields. The PLSc has elevated interest in the scholastic setting in measuring the performance of various estimation methods in structural equation modeling. The choice of estimation methods has substantial impact in yielding parameter estimates. There could be a trade-off among the estimation methods’ ability to deal with different types of data based on the model tested. Accordingly, this study aims to compare the performance of ML, generalized least squares (GLS), and scale-free least squares (SFLS) for CB-SEM as well as partial least squares (PLS) and consistent partial least squares (PLSc). Multivariate normal data were generated using Monte Carlo simulation with pre-determined population parameters and sample sizes using R Programming packages. To produce the estimated values, data analysis was performed using AMOS and SmartPLS for CB-SEM and PLS-SEM, respectively. The findings illustrate notable similarities between CB-SEM (ML) and PLS-SEM results when the true indicator loading is certainly high.
10
Lantong, Fabian Umay, Muhammad Rezky Friesta Payu, and Siti Nurmardia Abdussamad. "Pemodelan PLS-PM Pada Penanganan Perilaku Temper Tantrum Anak Autisme di Gorontalo." Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika 13, no. 2 (2025): 107–20. https://doi.org/10.25139/smj.v13i2.9979.
Full textAbstract:
Abstract The number of people with autism in Indonesia is estimated to continue to increase, with 500 new children diagnosed with autism each year. Children with autism are they who have difficulty in communicating, making it difficult to adapt to the environment or unable to interact with their surroundings. Difficulties in communicating and expressing emotions can frustrate children with autism, triggering temper tantrums. Temper tantrums are emotional outbursts shown through physical actions such as hitting or slamming objects, as well as verbally such as shouting or crying. Although various strategies have been developed to deal with temper tantrums, there are still limitations in understanding the specific roles of reinforcement, punishment, and emotional intelligence in influencing this behavior. Therefore, this study aims to determine the Partial Least Square-Path Modeling (PLS-PM) model to examine the influence of reinforcement, punishment, and emotional intelligence on temper tantrum behavior in children with autism in SLB N Gorontalo City. The number of samples used was 31 using saturated sampling technique. The results obtained from this study are reinforcement has a significant effect on emotional intelligence and temper tantrum behavior, while punishment also affects temper tantrum. With an absolute contribution value of 22.85%, it indicates that reinforcement has the greatest contribution to temper tantrum behavior. Keywords: autism; plspm; temper tantrum behavior. Abstrak Penyandang autisme di Indonesia diperkirakan terus meningkat, sebanyak 500 anak baru yang terdiagnosis autisme setiap tahunnya. Anak dengan autisme adalah mereka yang mengalami kesulitan dalam berkomunikasi, sehingga sulit beradaptasi dengan lingkungan atau tidak dapat berinteraksi dengan sekitarnya. Kesulitan berkomunikasi dan mengekspresikan emosi dapat membuat anak autisme frustrasi, sehingga memicu temper tantrum. Temper tantrum adalah ledakan emosi yang ditunjukkan melalui tindakan fisik seperti memukul atau membanting benda, serta secara verbal seperti berteriak atau menangis. Meskipun berbagai strategi telah dikembangkan untuk menangani temper tantrum, masih terdapat keterbatasan dalam memahami peran spesifik penguatan (reinforcement), hukuman (punishment), dan kecerdasan emosional dalam mempengaruhi perilaku ini. Oleh karena itu, penelitian ini bertujuan untuk menentukan model Partial Least Square-Path Modeling (PLS-PM) guna mengkaji pengaruh penguatan (reinforcement), hukuman (punishment), dan kecerdasan emosional terhadap perilaku temper tantrum pada anak autisme di SLB N Kota Gorontalo. Jumlah sampel yang digunakan sebanyak 31 dengan menggunakan teknik pengambilan sampel yaitu sampling jenuh. Hasil yang didapatkan dari penelitian ini adalah penguatan (reinforcement) berpengaruh signifikan terhadap kecerdasan emosional dan perilaku temper tantrum, sementara hukuman (punishment) juga berpengaruh terhadap temper tantrum. Dengan nilai kontribusi mutlak sebesar 22,85% menandakan bahwa penguatan (reinforcement) memiliki kontribusi terbesar terhadap perilaku temper tantrum. Kata Kunci: autisme; perilaku temper tantrum; plspm.
Dissertations / Theses on the topic "PLS–PM modeling"
1
Masson, Marine. "Contribution à la modélisation des préférences des consommateurs en fonction de dimensions sensorielles et subjectives par les modèles d'équations structurelles.Application aux préférences des sièges conducteurs de véhicules." Thesis, Paris, AgroParisTech, 2014. http://www.theses.fr/2014AGPT0015.
Full textAbstract:
En Analyse Sensorielle, les préférences des consommateurs sont généralement modélisées en fonction de données sensorielles par les méthodes de cartographie des préférences. L'objectif de cette thèse est de modéliser les préférences des consommateurs en intégrant, en plus des données sensorielles, de nouvelles variables relatives à leur perception des produits. Nous appellerons ces variables les dimensions subjectives. Elles recouvrent des dimensions pragmatiques liées à l'utilisation du produit et des dimensions plus symboliques telles que l'esthétisme, la modernité, l'originalité…Les problématiques relatives aux dimensions subjectives ont d'abord été étudiées lors d'une étude exploratoire sur des tasses à café. L'ensemble du travail a ensuite été réalisé sur 11 sièges de voitures. Dans un premier temps, des entretiens qualitatifs ont été réalisés auprès de 16 consommateurs d'une part et de 2 designers d'autre part. Ces entretiens ont permis d'identifier les dimensions subjectives caractéristiques des sièges. Une évaluation quantitative des dimensions subjectives et des préférences a ensuite été réalisée par 110 consommateurs. Enfin, les sièges ont été caractérisés sensoriellement par des experts. Les préférences des consommateurs ont été modélisées en fonction des données sensorielles et des dimensions subjectives par des modèles d'équations structurelles à variables latentes, plus précisément par Partial Least Square Path Modeling. Quatre modèles, fondés sur les groupes de préférences, ont été mis en place. Selon le groupe étudié, la contribution des deux jeux de données diffère et quatre profils de clients sont identifiés. D'un point de vue méthodologique, ce travail fournit des éléments de réponse sur l'intérêt des dimensions subjectives pour la modélisation des préférences. L'ensemble de la démarche est en cours d'application sur un produit alimentaire : le chocolat<br>In Sensory Science, preference mapping is used to explain consumers' preferences with sensory data. This PhD aims to integrate not only sensory data but also new variables that are related to consumers' perception of the product in the modelling of consumers' preferences. These variables are labelled as subjective dimensions. They address the pragmatic dimensions that cover the context of use of the products and more symbolic dimensions, such as aesthetics, modernity, originality…An exploratory study based on coffee cups was a first mean to approach the issues related to subjective dimensions. Then, all the work was done on a study of 11 car seats. The first step consisted in qualitative interviews of 16 consumers and of 2 designers. These interviews allowed identifying the subjective dimensions that characterize car seats. 110 consumers then performed a quantitative evaluation of their preferences and subjective dimensions. Finally, the seats were characterized by experts with sensory descriptors. The consumers' preferences were modelled according to both sensory data and subjective dimensions, using structural equations: the Partial Least Square Path Modeling. Four models based on preferences clustering were established. The contribution of two kinds of data differed according to the considered cluster, which led to the identification of four customer profiles. From a methodological point of view, this work provides first elements about the benefit of subjective dimensions in preference modelling. The methodology is being implemented on a food product: chocolate
2
Lopes, Tiago Guia Ribeiro. "Alternative smoothing strategies in smooth partial least squares path modelling." Master's thesis, 2020. http://hdl.handle.net/10362/99737.
Full textAbstract:
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research e CRM<br>The assessment of nonlinear relationships in the context of Partial Least Squares Path Modelling
(PLS-PM) has received a growing interest in recent years. One important contribution to this
subject has been the work of Henseler, Fassot, Dijkstra and Wilson (2012) on the analysis of four
different approaches to quadratic effects. The Smooth Partial Least Squares (PLSs) estimation
technique studied in this work removes any assumptions on the structure of the nonlinear
relationships between latent variables, by applying smoothing spline techniques to the structural
model. Performance results of the PLSs show that it is a powerful tool in the context of predictive
research, for instance to support the definition of targeted policies. Building from the hybrid
approach to the PLS algorithm introduced by Wold (1982), we compare the performance of
alternative spline designs, including natural cubic splines, P-Splines and Thin Plate Regression
Splines (TPRS). For this purpose, Monte-Carlo simulations are carried with a conceptual model
drawn from a comprehensive set of nonlinear relationships, in different sample sizes. All model
configurations are compared using Root Mean Squared Error (RMSE) and absolute bias results.
The benchmarking exercise shows that, in most contexts, P-Splines perform slightly better than
TPRS and natural cubic splines.
Book chapters on the topic "PLS–PM modeling"
1
Davino, Cristina, Pasquale Dolce, and Stefania Taralli. "Quantile Composite-Based Model: A Recent Advance in PLS-PM." In Partial Least Squares Path Modeling. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3_5.
Full text
2
Cataldo, Rosanna, Laura Antonucci, Corrado Crocetta, Maria Gabriella Grassia, and Marina Marino. "A bibliometric study of global research activity in relation to the use of partial least squares for policy evaluation." In Proceedings e report. Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.11.
Full textAbstract:
Structural equation modeling (SEM), especially partial least squares path modeling (PLS-PM) has become a mainstream method in many fields of research. In the last years it has been increasingly disseminated in a variety of disciplines. The researchers have been promoting this new statistical methods for the evaluation of policies. Generally, policy evaluation applies evaluation principles and methods to examine the content, implementation or impact of a policy. To better understand and characterize this trend, a bibliometric study of international papers on this subject has been developed in order to describe the use of SEM and PLS-PM approaches in the policy evaluation in the almost last 20 years. A total of 450 articles from 2000 to 2020 have been selected and analyzed in order to discover the research trends in this field and the main dimensions and words related to the terms “decision making” and “SEM-PLS” approach, that are most commonly employed in the scientific literature. The research has been conducted in theWeb of Science from ISI Web of Knowledge database and Scopus database, with the aim of identifying the major themes, authors, areas, types of the sources, titles, years of publication and countries of these publications, as well as the main themes related to the two topic analyzed
3
Cossu, Jean-Valère, Eric Sanjuan, Juan-Manuel Torres-Moreno, and Marc El-Bèze. "Automatic Classification and PLS-PM Modeling for Profiling Reputation of Corporate Entities on Twitter." In Natural Language Processing and Information Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19581-0_25.
Full text
4
Jayabal, Yogalakshmi, and Chandrashekar Ramanathan. "Clustering Students Based on Student’s Performance - A Partial Least Squares Path Modeling (PLS-PM) Study." In Machine Learning and Data Mining in Pattern Recognition. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08979-9_29.
Full textConference papers on the topic "PLS–PM modeling"
1
Ahmed, Shakeel, Bahram Bahram, Sameer Razzaq, Dilan Dost, and Mehtab Ali. "Developing a PLS-SEM Model to Identify Risk Management Strategies in Construction Contracts: A Case Study in Public Sector Construction of Pakistan." In 14th International Civil Engineering Conference. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-mcn3wd.
Full textAbstract:
Political unpredictability, environmental hazards, technological constraints, economic volatility, and regulatory barriers are a few difficulties facing Pakistan's public sector construction industry. These elements, together with inadequate infrastructure, have made it extremely difficult to guarantee the success of projects. The complex nature of hazards in this industry is frequently overlooked by existing models and tactics, despite the crucial role that efficient risk management plays in reducing these difficulties. Traditional methods do not capture The complexity involved well, increasing the likelihood of project failure. A structural equation modelling technique that enables the estimate of intricate cause-and-effect linkages in route models with latent variables is partial least squares path modelling, also known as partial least squares structural equation modelling (PLS-PM, PLS-SEM). Data from an 82-person questionnaire survey with G Power taking effect size (0.3), alpha error (0.05), and beta error (0.88) were analyzed using PLS-SEM. The participants included customers, contractors, and consultants involved in public sector building projects in Pakistan. The findings indicated that the model's goodness of fit index is 0.405. Since the coefficient of determination test (R2) of the produced model yielded an analysis result of 0.713, indicating a considerable explanation of the link between the causes of risks and their impacts on project success, the developed model was considered to fit. Project management, feasibility study design, and resource material availability are the internal risk categories most affected. Security, economic, and political factors are the primary components of foreign risk. Based on expert and statistical validation testing, the developed risk factor model successfully explained how risk variables affect construction project success.
2
Siletti, Elena, and Francesca De Battisti. "High order PLS path modeling to evaluate well-being merging traditional and big data: A longitudinal study." In CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics. Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/carma2020.2020.11599.
Full textAbstract:
We propose using high order partial least squares path modeling (PLS-PM) todefine a synthetic Italian well-being index merging traditional data,represented by the Quality of Life index proposed by “Il Sole 24 Ore”, andinformation provided by big data, represented by a Subjective Well-beingIndex (SWBI) performed extracting moods by Twitter. High order constructs,which allow to define a more abstract higher-level dimension and its moreconcrete lower-order sub-dimensions, have gained wide attention inapplications of PLS-PM, and many contributions in literature proposed theiruse to build composite indicators. The aim of the paper is to underline somecritical issues in the use of these models and to suggest the implementation ofa new spurious repeated indicator approach. Furthermore, following somerecommendations proposed on the use of PLS-PM in longitudinal studies, wecompare the situation in 2016 and 2017.
3
Sharma, Pratyush Nidhi, Marko Sarstedt, Galit Shmueli, and Kevin H. Kim. "Predictive model selection in partial least squares path modeling (PLS-PM)." In 2nd International Symposium on Partial Least Squares Path Modeling - The Conference for PLS Users. University of Twente, 2015. http://dx.doi.org/10.3990/2.336.
Full text
4
Sizov, Gennadi Y., Dan M. Ionel, and Nabeel A. O. Demerdash. "A review of efficient FE modeling techniques with applications to PM AC machines." In 2011 IEEE Power & Energy Society General Meeting. IEEE, 2011. http://dx.doi.org/10.1109/pes.2011.6039886.
Full text