Rejoinder: fractures in the edifice of PLS

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 comm…

Cautionary Note on the Two-Step Transformation to Normality

ABSTRACT Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normally distributed data, which are commonly found in AIS research. We argue that, rather than transforming the data toward normality, researchers should first seek to analyze and understand the sources of non-normality. Using simulated datasets, we demonstrate three sources of non-normality and their consequences for regression estimation. We then demonstrate that the two-step transformation cannot solve any of these problems and that each source of non-normality can be handled with alternative, existing techniques. We further present two empirical examples to demonstrate these issues wit…

On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Entities such as individuals, teams, or organizations can vary systematically from one another. Researchers typically model such data using multilevel models, assuming that the random effects are uncorrelated with the regressors. Violating this testable assumption, which is often ignored, creates an endogeneity problem thus preventing causal interpretations. Focusing on two-level models, we explain how researchers can avoid this problem by including cluster means of the Level 1 explanatory variables as controls; we explain this point conceptually and with a large-scale simulation. We further show why the common practice of centering the predictor variables is mostly unnecessary. Moreover, …

Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research : A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller stan…

Supplemental Material, Online_supplement_4_-_Tutorial_on_calculations - An Updated Guideline for Assessing Discriminant Validity

Supplemental Material, Online_supplement_4_-_Tutorial_on_calculations for An Updated Guideline for Assessing Discriminant Validity by Mikko Rönkkö and Eunseong Cho in Organizational Research Methods

Interpersonal work resources and school personnel well-being before and after lockdown during the first phase of the COVID-19 pandemic in Finland

This two-wave mixed-methods study used the job demands and resources model to examine the effects of the COVID-19 pandemic on school personnel's work well-being (including burnout, work engagement, and sense of belonging) in spring 2020 in Finland in particular with respect to collegial relationships (respectful engagement) and leadership support. A pre-lockdown survey was administered prior to the pandemic (in January–February, n = 437) and a post-lockdown survey was administered after the two-month lockdown (at the end of May, n = 270). At post-lockdown, the school personnel reported, on average, more exhaustion, less work engagement (measured as enthusiasm and energy at work), and a decr…

Supplemental Material, Coloring_and_code_issues_appen - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, Coloring_and_code_issues_appen for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

Jyväskylästä kirjoitettiin: Käyn läpi Extra-Vipusessa ristiriitaisiksi luokitettuja yhteisjulkaisuja. Julkaisu " Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects" on meillä laitettu A2 ja teillä A1. Meillä varmaan päädytty tuohon A2:een kun tiivistelmässä sanotaan "Building on a systematic review of six leading management journals..". Mutta mitä mieltä olette, kumpi olisi parempi? Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressing the topic, either directly or indirectly, have been published in the rec…

Polynomial Regression and Measurement Error

Many of the phenomena of interest in information systems (IS) research are nonlinear, and it has consequently been recognized that by applying linear statistical models (e.g., linear regression), we may ignore important aspects of these phenomena. To address this issue, IS researchers are increasingly applying nonlinear models to their datasets. One popular analytical technique for the modeling and analysis of nonlinear relationships is polynomial regression, which in its simplest form fits a "U-shaped" curve to the data. However, the use of polynomial regression can be problematic when the independent variables are contaminated with measurement error, and the implications of error can be m…

Sustainable antibullying program implementation : School profiles and predictors

We examined the sustainability of the KiVa antibullying program in Finland from its nationwide roll‐out in 2009 to 2016. Using latent class analyses, we identified four different patterns of implementation. The persistent schools (43%) maintained a high likelihood of participation throughout the study period. The awakened (14%) had a decreasing trend during the first years, but then increased the likelihood of program participation. The tail‐offs (20%) decreased in the likelihood of participating after the third year, and the drop‐offs (23%) already after the first year. The findings suggest that many schools need support during the initial years to launch and maintain the implementation of…

The Choice of Control Variables : How Causal Graphs Can Inform the Decision

Control variables have a central role when empirical data are used to support causal claims in management research. The current literature has been intransparent in so far as to how control variables should be chosen, how many control variables should be chosen and whether a potential control variable should be included. Causal diagrams provide a transparent framework on how to select control variables for causal identification. This article delineates how causal graphs can inform researchers in leadership and management in finding the correct set of control variables and possible solutions in the case that causal identification is not possible or when causal identification requires unobser…

A cautionary note on the finite sample behavior of maximal reliability.

Several calls have been made for replacing coefficient α with more contemporary model-based reliability coefficients in psychological research. Under the assumption of unidimensional measurement scales and independent measurement errors, two leading alternatives are composite reliability and maximal reliability. Of these two, the maximal reliability statistic, or equivalently Hancock's H, has received a significant amount of attention in recent years. The difference between composite reliability and maximal reliability is that the former is a reliability index for a scale mean (or unweighted sum), whereas the latter estimates the reliability of a scale score where indicators are weighted di…

Innovation as a driver of internationalization in the software industry

Innovation and internationalization are two important factors for growth. This study analyzes whether innovativeness has an effect on the internationalization of software firms, and if so, how strong this effect is. Innovation and internationalization have rarely been studied together, with research tending to focus more on the relationship between innovations and growth. However, internationalization is a key prerequisite for growth for companies operating in small domestic markets. This paper analyzes the innovativeness and internationalization of firms, using data from the Software Industry Survey conducted in Finland. Since the speed of firm growth and internationalization are dependent…

Supplemental Material, sj-docx-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, sj-docx-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Supplemental Material, Coding_book - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, Coding_book for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Supplemental Material, Online_supplement_5_-_Deriving_a_cutoff_based_on_simulation_results - An Updated Guideline for Assessing Discriminant Validity

Supplemental Material, Online_supplement_5_-_Deriving_a_cutoff_based_on_simulation_results for An Updated Guideline for Assessing Discriminant Validity by Mikko Rönkkö and Eunseong Cho in Organizational Research Methods

An Updated Guideline for Assessing Discriminant Validity

Discriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review te…

Marketing or methodology? : Exposing the fallacies of PLS with simple demonstrations

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. PL…

Supplemental Material, sj-pdf-1-orm-10.1177_1094428121991907 - Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

Supplemental Material, sj-pdf-1-orm-10.1177_1094428121991907 for Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects by Mikko Rönkkö, Eero Aalto, Henni Tenhunen and Miguel I. Aguirre-Urreta in Organizational Research Methods

Structural Parameters under Partial Least Squares and Covariance-Based Structural Equation Modeling : A Comment on Yuan and Deng (2021)

In their article, Yuan and Deng argue that a structural parameter under partial least squares structural equation modeling (PLS-SEM) is zero if and only if the same structural parameter is zero under covariance-based structural equation modeling (CB-SEM). Yuan and Deng then conclude that statistical tests on individual structural parameters assessing the null hypothesis of no effect can achieve the same purpose in CB-SEM and PLS-SEM. Our response to their article highlights that the relationship they find between PLS-SEM and CB-SEM structural parameters is not universally valid, and that consequently, tests on individual parameters in CB-SEM and PLS-SEM generally do not fulfill the same pur…

Supplemental Material, Online_supplement_2_-_Full_simulation_code - An Updated Guideline for Assessing Discriminant Validity

Supplemental Material, Online_supplement_2_-_Full_simulation_code for An Updated Guideline for Assessing Discriminant Validity by Mikko Rönkkö and Eunseong Cho in Organizational Research Methods

Current Software-as-a-Service Business Models: Evidence from Finland

This paper characterizes the business models of Software-as-a-Service (SaaS) firms based on their value proposition, customer segments, revenue streams, and customer relationship, and analyzes interconnections of these business model elements. The target set of 163 Finnish SaaS and ASP firms was first compared to other software firms and then clustered into four clusters based on indicator data of their business model elements. The comparison reveals that the SaaS and ASP firms have smaller customer and transaction sizes than software firms in general. The resulting classification reveals two different configurations, a pure-play SaaS model and an enterprise SaaS model, and the typical fact…

Contrasting Internationalization Paths of Product- and Service-oriented Software Firms

The internationalization of software firms has been widely researched topic over the last two decades. However, the most of the studies have treated software firms as a homogeneous group, ignoring the fact that software firms actually differ greatly in terms of having either a product or a service orientation. Based on earlier literature, we hypothesized that software product firms would show a tendency to internationalize earlier and at a smaller size than software service firms, and that product firms would show a greater tendency to target countries that are both geographically and culturally distant. In fact, we found no support for most of our hypotheses, with relatively strong and sta…

Cautionary note on the two-step transformation to normality

Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normally distributed data, which are commonly found in AIS research. We argue that, rather than transforming the data toward normality, researchers should first seek to analyze and understand the sources of non-normality. Using simulated datasets, we demonstrate three sources of non-normality and their consequences for regression estimation. We then demonstrate that the two-step transformation cannot solve any of these problems and that each source of non-normality can be handled with alternative, existing techniques. We further present two empirical examples to demonstrate these issues with real da…

Growth intention and variance of firm growth rates

Principal Topic Why some companies grow, and others do not? Answering this question has been one of the main tasks for entrepreneurship researchers (Audretsch et al., 2014; Gilbert et al., 2006; McKelvie & Wiklund, 2010). Differences in managerial motivation is one explanation for varying growth rates in entrepreneurial firms: variation among human motivation and abilities to act has been claimed to have important effects on all phases of the entrepreneurial process (Tominc & Rebernik, 2007), and this relates to the actual firm growth (Delmar & Wiklund, 2008). On a more general level, motivation and the effort that an entrepreneur intends to make have been referred to as growth intentions (…

Impact of accounting process characteristics on accounting outsourcing - Comparison of users and non-users of cloud-based accounting information systems

Article In Press The article of record as published may be found at https://doi.org/10.1016/j.accinf.2019.06.002 Prior literature informs us that a company's decision to outsource a business process depends on process characteristics such as how frequently the process is performed or how specific the assets required by the process are. In this article, we compare the effects of accounting process characteristics on outsourcing decisions across users of traditional and cloud-based accounting information systems (AIS). By focusing on outsourcing of accounting processes among small and medium sized enterprises, we investigate the effect of five business process characteristics (frequency, huma…

Omission of Causal Indicators: Consequences and Implications for Measurement – A Rejoinder

Supplemental Material, Online_supplement_1_-_Chi2(1)_scaling_example - An Updated Guideline for Assessing Discriminant Validity

Supplemental Material, Online_supplement_1_-_Chi2(1)_scaling_example for An Updated Guideline for Assessing Discriminant Validity by Mikko Rönkkö and Eunseong Cho in Organizational Research Methods

Supplemental Material, Online_supplement_3_-_Full_simulation_results - An Updated Guideline for Assessing Discriminant Validity

Supplemental Material, Online_supplement_3_-_Full_simulation_results for An Updated Guideline for Assessing Discriminant Validity by Mikko Rönkkö and Eunseong Cho in Organizational Research Methods

Supplemental Material, sj-rar-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, sj-rar-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Supplemental Material, Coded_data_in_Excel_compressed_to_put_on_line - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, Coded_data_in_Excel_compressed_to_put_on_line for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Supplemental Material, sj-r-1-orm-10.1177_1094428121991907 - Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

Supplemental Material, sj-r-1-orm-10.1177_1094428121991907 for Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects by Mikko Rönkkö, Eero Aalto, Henni Tenhunen and Miguel I. Aguirre-Urreta in Organizational Research Methods

Supplemental Material, sj-do-1-orm-10.1177_1094428121991907 - Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

Supplemental Material, sj-do-1-orm-10.1177_1094428121991907 for Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects by Mikko Rönkkö, Eero Aalto, Henni Tenhunen and Miguel I. Aguirre-Urreta in Organizational Research Methods

Supplemental Material, sj-xlsx-1-orm-10.1177_1094428121991907 - Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

Supplemental Material, sj-xlsx-1-orm-10.1177_1094428121991907 for Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects by Mikko Rönkkö, Eero Aalto, Henni Tenhunen and Miguel I. Aguirre-Urreta in Organizational Research Methods

Supplemental Material, sj-dta-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, sj-dta-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods

Supplemental Material, Coded_data_in_Stata_to_put_on_line - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations

Supplemental Material, Coded_data_in_Stata_to_put_on_line for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods