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1 – 10 of 988Mikko Rönkkö, Nick Lee, Joerg Evermann, Cameron McIntosh and John Antonakis
This study aims to provide a response to the commentary by Yuan on the paper “Marketing or Methodology” in this issue of EJM.
Abstract
Purpose
This study aims to provide a response to the commentary by Yuan on the paper “Marketing or Methodology” in this issue of EJM.
Design/methodology/approach
Conceptual argument and statistical discussion.
Findings
The authors find that some of Yuan’s arguments are incorrect, or unclear. Further, rather than contradicting the authors’ conclusions, the material provided by Yuan in his commentary actually provides additional reasons to avoid partial least squares (PLS) in marketing research. As such, Yuan’s commentary is best understood as additional evidence speaking against the use of PLS in real-world research.
Research limitations/implications
This rejoinder, coupled with Yuan’s comment, continues to support the strong implication that researchers should avoid using PLS in marketing and related research.
Practical implications
Marketing researchers should avoid using PLS in their work.
Originality/value
This rejoinder supports the earlier conclusions of “Marketing or Methodology,” with additional argumentation and evidence.
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Mikko Rönkkö, Nick Lee, Joerg Evermann, Cameron McIntosh and John Antonakis
Over the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems…
Abstract
Purpose
Over the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems with the technique but have had little impact on its use in marketing research practice. This study aims to present some of these criticisms in a reader-friendly way for non-methodologists.
Design/methodology/approach
Key critiques of PLS are summarized and demonstrated using existing data sets in easily replicated ways. Recommendations are made for assessing whether PLS is a useful method for a given research problem.
Findings
PLS is fundamentally just a way of constructing scale scores for regression. PLS provides no clear benefits for marketing researchers and has disadvantages that are features of the original design and cannot be solved within the PLS framework itself. Unweighted sums of item scores provide a more robust way of creating scale scores.
Research limitations/implications
The findings strongly suggest that researchers abandon the use of PLS in typical marketing studies.
Practical implications
This paper provides concrete examples and techniques to practicing marketing and social science researchers regarding how to incorporate composites into their work, and how to make decisions regarding such.
Originality/value
This work presents a novel perspective on PLS critiques by showing how researchers can use their own data to assess whether PLS (or another composite method) can provide any advantage over simple sum scores. A composite equivalence index is introduced for this purpose.
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Francesca Magno, Fabio Cassia and Christian M. Ringle
Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also…
Abstract
Purpose
Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.
Design/methodology/approach
Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.
Findings
The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.
Research limitations/implications
This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.
Practical implications
The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.
Originality/value
This is the first article to systematically review the use of PLS-SEM in the quality management discipline.
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Jörg Henseler and Florian Schuberth
In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s…
Abstract
Purpose
In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations for researchers using structural equation models.
Design/methodology/approach
This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.
Findings
There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.
Research limitations/implications
Researchers should be more conscious, open and respectful regarding different research paradigms.
Practical implications
Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.
Originality/value
This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.
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Florian Schuberth, Manuel E. Rademaker and Jörg Henseler
This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is…
Abstract
Purpose
This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessment that have been raised in the literature on PLS-PM.
Design/methodology/approach
This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.
Findings
This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.
Research limitations/implications
Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.
Practical implications
To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.
Originality/value
This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.
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Peni Nugraheni and Istiqomah Nur Alimin
This study aims to examine the factors that influence profit–loss sharing (PLS) financing in Indonesian Islamic banks from the perspective of Islamic banks’ employees. Islamic…
Abstract
Purpose
This study aims to examine the factors that influence profit–loss sharing (PLS) financing in Indonesian Islamic banks from the perspective of Islamic banks’ employees. Islamic banks have important role in influencing the amount of PLS financing distribution through their screening process.
Design/methodology/approach
This study uses questionnaires in collecting data that are distributed to the employees who process or handle PLS financing in Islamic banks in Yogyakarta, Indonesia. The independent variables are risk, financing screening process, analysis of financial statement and competency of the employees of Islamic banks. The data are processed using multiple regression.
Findings
This study finds that risk, the quality of financing screening process and the analysis of financial statement have positive influence on the PLS financing, whereas competency of employees of Islamic banks does not influence PLS financing.
Practical implications
The results of this study are expected to give contribution to increase the role of Islamic banks in encouraging PLS financing. The adequate screening, controlling and monitoring system in Islamic banks should be strengthened to encourage the quality of financing distributed.
Originality/value
Primary data are used in this study to know the perspective of Islamic bank employees in the financing division on the PLS financing. This study attempts to identify the perspective of employees who have direct relationship with the decision of financing in Islamic banks.
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Jörg Henseler, Geoffrey Hubona and Pauline Ash Ray
Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to…
Abstract
Purpose
Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.
Design/methodology/approach
This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.
Findings
PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.
Originality/value
This paper provides updated guidelines of how to use PLS and how to report and interpret its results.
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Nicole Franziska Richter, Rudolf R. Sinkovics, Christian M. Ringle and Christopher Schlägel
Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM…
Abstract
Purpose
Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM (CB-SEM) approach is dominant, the authors argue that the field’s dynamic nature and the sometimes early stage of theory development more often require a partial least squares SEM (PLS-SEM) approach. The purpose of this paper is to critically review the application of SEM techniques in the field.
Design/methodology/approach
The authors searched six journals with an international business (and marketing) focus (Management International Review, Journal of International Business Studies, Journal of International Management, International Marketing Review, Journal of World Business, International Business Review) from 1990 to 2013. The authors reviewed all articles that apply SEM, analyzed their research objectives and methodology choices, and assessed whether the PLS-SEM papers followed the best practices outlined in the past.
Findings
Of the articles, 379 utilized CB-SEM and 45 PLS-SEM. The reasons for using PLS-SEM referred largely to sampling and data measurement issues and did not sufficiently build on the procedure’s benefits that stem from its design for predictive and exploratory purposes. Thus, the procedure’s key benefits, which might be fruitful for the theorizing process, are not being fully exploited. Furthermore, authors need to better follow best practices to truly advance theory building.
Research limitations/implications
The authors examined a subset of journals in the field and did not include general management journals that publish international business and marketing-related studies. Fur-thermore, the authors found only limited use of PLS-SEM in the journals the authors considered relevant to the study.
Originality/value
The study contributes to the literature by providing researchers seeking to adopt SEM as an analytical method with practical guidelines for making better choices concerning an appropriate SEM approach. Furthermore, based on a systematic review of current practices in the international business and marketing literature, the authors identify critical challenges in the selection and use of SEM procedures and offer concrete recommendations for better practice.
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Khemaies Bougatef, Mohamed Sahbi Nakhli and Othman Mnari
The purpose of this paper is to investigate the relationship between Islamic banking and industrial production by decomposing Islamic financing (IF) into profit and loss sharing…
Abstract
Purpose
The purpose of this paper is to investigate the relationship between Islamic banking and industrial production by decomposing Islamic financing (IF) into profit and loss sharing (PLS) and non-profit and loss sharing (non-PLS) modes of financing.
Design/methodology/approach
This paper applies the autoregressive distributed lag (ARDL) approach and Toda and Yamamoto causality test on the monthly data set for Malaysia from 2010M1 to 2018M6.
Findings
The results reveal that IF plays an important role in boosting industrial production in the short run, as well as in the long run. Moreover, this positive effect mainly comes from non-PLS financing. In contrast, no significant relationship was found between PLS financing and industrial development neither in the short run nor in the long run.
Practical implications
The results have several policy implications. The existence of a time lag between the pooling of funds through PLS contracts and their channeling to industrial activities imply that Malaysian Islamic banks should maintain a long-term relationship with investment account holders. In addition, Islamic banks are called to increase the portion of PLS financing. The positive relationship between the industrial production index and IF (through non-PLS techniques) in the short and the long runs implies that policymakers in Malaysia should multiply their efforts to further expand the Islamic banking industry.
Originality/value
The originality of this study lies in decomposing Islamic banks’ financing into PLS financing (muḍārabah and mushārakah) and non-PLS financing to assess the contribution of each mode of financing in industrial development.
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Tobias Müller, Florian Schuberth and Jörg Henseler
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…
Abstract
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.
研究目的
因为旅游酒店科技(TTH)根据游客需求而定制科技产品, TTH必须在结构方程模型(SEM)下结合游客行为和设计等变量。一般行为变量在模型中是常见因子, 本研究将这些变量编入TTH结构成为模块。本研究采用PLS-PM方法来预估含有隐性变量和模块的模型。.
研究设计/方法/途径
本研究设计PLS-PM模式, 即确定性全变量方法。TTH学者们通过引进结构形成模型模块, 使用PLS-PM研究方法, 以回答研究问题“模块xyz有用吗?”, 因此对TTH进一步理解。为了展示复合模型, 本论文采用实际验证。.
研究结果
PLS-PM在面对模块内存在常见因子和复合模块的结构时是有力方法。实际验证结果通过整体最佳模型参数, 得到隐性变量和模块。为此, 研究者们能够在统计方法上测量是否开发的模型模块是否有用。.
研究原创性/研究价值
据作者所知, 本论文是首个研究在TTH领域上应用模块和常见因子模型。本研究引进显性变量在模型模块中, 以指导学者评估PLS-PM结果报告。.
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