Search results

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.

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.

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.

Researchers should be more conscious, open and respectful regarding different research paradigms.

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.

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.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The findings strongly suggest that researchers abandon the use of PLS in typical marketing studies.

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.

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.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

This study aims to examine the role of the dimensions of entrepreneurial orientation (EO) under turbulent market conditions and reveal the role of an entrepreneur's perception of a crisis in shaping the impact of EO on firm performance.

This study uses partial least squares structural equation modeling (PLS-SEM), multiple linear regression (MLR) and fuzzy-set qualitative comparative analysis (fsQCA). The study sample was comprised of 117 one- and two-star hotels that were operating in Poland.

The results showed that proactiveness and risk-taking significantly affected firm performance. Furthermore, the results revealed that an entrepreneur's perception of a crisis moderated the impact of risk-taking and proactiveness on firm performance. In particular, the findings suggested that, in firms where the crisis strongly influenced their operations, performance was affected by proactiveness, while in those firms where the crisis influenced their operations to a low or moderate degree, performance was affected by risk-taking. Furthermore, fsQCA unveiled the role of innovativeness, which (along with risk-taking) is a sufficient condition that leads to firm performance.

Two characteristics make this study original: first, it investigates EO under turbulent market conditions, and second, it analyzes the role of an entrepreneur's perception of crisis consequences for business operations. The study contributes to the literature on entrepreneurship and crisis management with findings on the different roles of EO dimensions under crisis conditions and an observation about the moderating role of an entrepreneur's perception of the impact of a crisis on operational management and how this perception differentiates the impact of risk-taking and proactiveness on firm performance.

Virtual goods consumption has risen dramatically in recent years. Recognizing the benefits of virtual goods in generating revenue for online game companies, marketers strive to understand the motives behind virtual goods purchases. We investigated the direct and indirect effects of functional, emotional, and social values through player satisfaction on purchase intention toward virtual goods among online players.

In total, we surveyed 332 online game players utilizing a structured questionnaire. We employed a multi-analytic approach combining partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to examine the proposed relationships.

The findings show that all dimensions of value and player satisfaction significantly affect the intention to acquire virtual goods. However, social value does not exert a significant effect on player satisfaction. Moreover, we confirmed that player satisfaction mediates the relationships between functional value, emotional value, and purchase intention. Furthermore, NCA results indicated that all predictors in the model are necessary conditions of purchase intention for virtual goods.

These findings contribute to an enhanced understanding of purchase intentions among online game players from a symmetric (PLS-SEM) and asymmetric (NCA) perspective by proposing a multi-analytic approach.

This study, grounded in the SOR theory, aims to enrich the understanding of customer citizenship behaviour in omnichannel fashion retail by examining how different customer experiences enhance customer engagement and how that engagement leads to customer citizenship behaviour. The influence of return policies on the relationship between customer engagement and customer citizenship behaviour was also examined.

Partial least squares structural equation modelling (PLS-SEM) is used to examine the framework of the proposed study with data collected through a survey (n = 251) to examine the opinions of the respondents about the variables mentioned. The authors also assessed the proposed framework using predictive power assessment using PLS predict.

The study results reveal that customers’ experiences of integration and flexibility in omnichannel retail are positively associated with their engagement. However, customer experiences of connectivity, consistency and personalization do not appear to affect customer engagement significantly in omnichannel retail. The return policy positively moderates the relationship between customer engagement and customer citizenship behaviour in the omnichannel fashion retail context. Predictive power assessment shows that the proposed model has high prediction accuracy.

This study contributes to the marketing literature by investigating different dimensions of consumer experience collectively and its impact on customer engagement and citizenship behaviour. Furthermore, the study contributes to omnichannel retail in fashion industry by testing the return policy as a moderator variable on the relationship between customer engagement and citizenship behaviour.

Este estudio, basado en la teoría SOR, enriquece la comprensión del comportamiento cívico del cliente en el comercio minorista de moda omnicanal examinando cómo las diferentes experiencias del cliente mejoran el compromiso de éste y cómo dicho compromiso conduce al comportamiento cívico del cliente. También se examina la influencia de las políticas de devolución en la relación entre el compromiso del cliente y el comportamiento ciudadano del cliente.

Se utilizó la modelización PLS-SEM para examinar el marco del estudio propuesto con datos recogidos mediante una encuesta (n = 251) para examinar las opiniones de los encuestados sobre las variables mencionadas. Los autores también evaluaron el marco propuesto mediante una evaluación del poder predictivo utilizando la predicción PLS.

Los resultados revelan que las experiencias de integración y flexibilidad de los clientes en el comercio minorista omnicanal se asocian positivamente con su compromiso. Sin embargo, las experiencias de los clientes de conectividad, coherencia y personalización no parecen afectar significativamente al compromiso del cliente en el comercio minorista omnicanal. La política de devoluciones modera positivamente la relación entre el compromiso del cliente y el comportamiento ciudadano en el contexto del comercio minorista de moda omnicanal. La evaluación del poder predictivo mostró que el modelo propuesto tenía una alta precisión de predicción.

El estudio contribuye a la literatura de marketing investigando colectivamente diferentes dimensiones de la experiencia del consumidor y su impacto en el compromiso del cliente y el comportamiento ciudadano. Además, este estudio contribuye a la venta minorista omnicanal en la industria de la moda al probar la política de devoluciones como variable moderadora de la relación entre el compromiso del cliente y el comportamiento ciudadano.

本研究以 SOR 理论为基础, 通过研究不同的顾客体验如何提高顾客参与度, 以及顾客参与度如何推动顾客公民行为, 丰富了对全渠道时尚零售中顾客公民行为的理解。研究还探讨了退货政策对顾客参与和顾客公民行为之间关系的影响。

本文采用 PLS-SEM 模型来检验拟议的研究框架, 并通过调查（n = 251）收集数据, 以检验受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

通过调查（n = 251）收集的数据, 使用 PLS-SEM 模型来研究拟议的研究框架, 以考察受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

研究结果表明, 顾客在全渠道零售中对整合性和灵活性的体验与他们的参与度呈正相关。然而, 顾客在连通性、一致性和个性化方面的体验似乎并未对顾客参与全渠道零售产生显著影响。退货政策对全渠道时尚零售中顾客参与和公民行为之间的关系起到了积极的调节作用。 预测能力评估表明, 所提出的模型具有较高的预测准确性。

本研究通过对消费者体验的不同维度及其对顾客参与和公民行为的影响进行综合研究, 为营销文献做出了贡献。此外, 本研究通过检验退货政策作为顾客参与和公民行为之间关系的调节变量, 为时尚行业的全渠道零售做出了贡献。