Toward open science in PLS-SEM: Assessing the state of the art and future perspectives

Adler, Susanne Jana; Sharma, Pratyush Nidhi; Radomir, Lăcrămioara

doi:10.1016/j.jbusres.2023.114291

Cited by 10 publications

(2 citation statements)

References 92 publications

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“…Finally, we strongly recommend researchers follow open science practices to improve research transparency. In line with this, Adler et al (2023) suggested a PLS-SEM-specific template for preregistration that researchers can apply to promote transparency in their analyses. Doing so will ensure increased confidence in their findings.…”

Section: Industrial Management Andmentioning

confidence: 93%

Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox

Cepeda,

Roldán,

Sabol

et al. 2024

IMDS

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Purpose Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.Design/methodology/approach Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.Findings PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.Research limitations/implications Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.Practical implications Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.Originality/value Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.

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Section: Industrial Management Andmentioning

confidence: 93%

Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox

Cepeda,

Roldán,

Sabol

et al. 2024

IMDS

View full text Add to dashboard Cite

show abstract

“…(2) Partial least squares structural equation modeling Partial least squares structural equation modeling (PLS-SEM) is predominantly employed to examine causal links among latent variables [44]. In theoretical models, we can measure the causal relationships between potential variables using the corresponding observed variables.…”

Section: Methods (1) Pearson Correlation Analysismentioning

confidence: 99%

Decoupling Vegetation Dynamics and Climate Change Impacts on Runoff and Sediment in Loess Gully Areas

Zhu,

Song,

Meng

et al. 2024

Agronomy

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While climate change and vegetation dynamics have a strong relationship, few studies have specifically measured the effects of these factors on runoff and sediment development in the gully zone of the Loess Plateau. This study investigates the monthly impacts of climatic change and vegetation dynamics on water flow and sediment movement in the gully zone of the Loess Plateau between 2000 and 2016. In this study, the standard gully watershed of the Loess Plateau is investigated using partial least squares structural equation modeling (PLS-SEM). The state of vegetation in the watershed is characterized by utilizing the vegetation index obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS), along with monthly hydro-meteorological and vegetation data. The collective impacts of vegetation dynamics, climate change, and runoff contribute to 74.3% of the monthly fluctuations in sediment levels. The data indicate that 31.6% of the monthly runoff variability can be ascribed to the combined influence of climate change and vegetation dynamics. Climate change significantly influences flow and sediment via direct and indirect mechanisms, primarily by altering the growth and development of vegetation, which subsequently impacts both runoff and sediment. The impact of vegetation on sediment (−0.246) is more pronounced compared to its impact on runoff (−0.239). Furthermore, the impact of vegetation on sediment (−0.038) was significantly less significant compared to the impact on runoff (−0.208). Hence, the vegetation in the watershed primarily mitigates sediment deposition and suspended sediment transit in the water body by regulating runoff, thereby reducing the sediment load. This study examines the intricate correlation between climate change and vegetation dynamics on water flow and sediment deposition in the gully region of the Loess Plateau. It can serve as a helpful resource for managing water resources, allocating agricultural water, and planning soil conservation in the region.

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Research on the Purchase Intention Analysis Algorithm of Virtual Goods Based on Neural Network and SEM Model

Cao

2024

Smart Innovation, Systems and Technologies

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Toward open science in PLS-SEM: Assessing the state of the art and future perspectives

Cited by 10 publications

References 92 publications

Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox

Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox

Decoupling Vegetation Dynamics and Climate Change Impacts on Runoff and Sediment in Loess Gully Areas

Research on the Purchase Intention Analysis Algorithm of Virtual Goods Based on Neural Network and SEM Model

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