Predictive Validation of Interaction Terms in PLS-SEM

The use of interaction terms in partial least squares structural equation modeling (PLS-SEM) risks overfitting models to small samples and producing poor out-of-sample generalizability. But the added complexity of interactions in PLS-SEM is not captured by in-sample fit metrics, and we propose that interaction terms in PLS-SEM should be assessed by out-of-sample methods and metrics. However, out-of-sample predictive methods like PLSpredict do not yet account for interaction terms. We start by providing a formal procedure for generating out-of-sample predictions from such models. We then empirically demonstrate that interactions produce far higher Type I error than that expected by researchers, and that out-of-sample predictive metrics indeed offer more accurate assessment of the validity of interaction terms for PLS-SEM. We also show that two-stage estimation of interactions is superior to other popular methods of operationalizing interactions in PLS-SEM, when the generalizability of interactions is of concern

Implementing Open Innovation in Research and Technology Organisations: Approaches and Impact

This article seeks to answer the question of how value proposition is created using a human-centred approach in the context of deservitization, in general, and service dilution, in particular. The article aims to describe the Research and development organisations (RTOs) are at the heart of innovation systems. They help to connect innovation system actors to foster industrial innovation. Due to this intermediary role, they act as paradigmatic open innovation (OI) actors. In this context, RTOs need to balance their knowledge stocks and flows, while assuring their own innovation capabilities and positively impacting the innovation system they influence. Thus, RTOs need to develop collaboration approaches that support their own performance while increasing their capabilities and not threatening their competitive advantages derived from their knowledge stock. In this study we extend the OI research to research organisations analysing their OI approach and the impact on its own performance, developing a new framework for OI study in RTOs using a partial least squares structural equation modelling (PLS-SEM) approach. The research, based on a sample of Spanish RTOs, arises two substantive conclusions. First, an increased number of collaboration partners (collaboration breadth) and the use of a variety of OI practices have a strong impact on RTOs’ overall performance (scientific, transference, and economic results). Second, RTOs need to foster their aperture and promote an active management to benefit from collaborating partners, whereas managers should pay special attention to questions related to the protection and management of intellectual property when promoting the use of different OI practices. Both results also emphasise the importance of managing firms’ knowledge flows in the implementation of OI in RTOs

P-IRLS-PM : a new approach to non-linear formative consctructs

Dissertation presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Information Analysis and ManagementThe traditional approach to PLS-PM estimated the scores of the formative latent variables as exact linear combinations of their associated manifest variables, not allowing for modelling other relationships besides the linear ones. The present study intends to overcome this limitation, introducing the P-IRLS-PM. The P-IRLS-PM is a new approach to the variance based structural equations models, which intends to widen the spectra of how the formative latent scores are represented by its associated manifest variables. Throughout this work the core concepts of the algorithm P-IRLS-PM will be introduced, followed by a Monte Carlo experiment comparing the new approach with the traditional PLS-PM

Heterogeneity, Diversity, and Complementarity in Alliance Portfolios

The divergence that a firm manages to achieve because of its partners is a fundamental question in an alliance portfolio configuration. Diversity can refer not only to the differences between the focal firm and its partners or between the partners themselves but also to the differences arising from various resource endowments in the alliance portfolio. Understanding the significance of these different sources, how they interrelate, and how they affect the firm performance is an unresolved question as unclear definitions and opposing arguments are proposed. This paper expounds the concepts of partner heterogeneity, alliance portfolio diversity, and network resource complementarity to gain a deeper comprehension of the alliance portfolio configuration and how it affects performance. Our analysis of airline alliances at a global level reveals the central role of resource complementarity in the focal firm performance.Ministerio de Economía y Competitividad ECO2013-45329-RMinisterio de Educacion, Cultura y Deporte FPU13/0435

Estimating Moterating effects in PLS-SEM andPLSc-SEM: interaction term gerneration*data treatment

When estimating moderating effects in partial least squares structural equation modeling (PLS-SEM), researchers can choose from a variety of approaches to model the influence of a moderator on a relationship between two constructs by generating different interaction terms. While prior research has evaluated the efficacy of these approaches in the context of PLS-SEM, the impact of different data treatment options on their performance in the context of standard PLS-SEM and consistent PLS-SEM (PLSc-SEM) is as yet unexplored. Our simulation study addresses these limitations and explores if the choice of approach and data treatment option has a pronounced impact on the methods’ parameter recovery. An empirical application substantiates these findings. Based on our results, we offer recommendations for researchers wishing to estimate moderating effects by means of PLS-SEM and PLSc-SEM

Predictive Validity and Formative Measurement in Structural Equation Modeling: Embracing Practical Relevance

Composite-based methods like partial least squares (PLS) path modeling have an advantage over factor-based methods (like CB-SEM) because they yield determinate predictions, while factor-based methods’ prediction is constrained in this regard by factor indeterminacy. To maximize practical relevance, research findings should extend beyond the study’s own data. We explain how PLS practices, deriving, at least in part, from attempts to mimic factor-based methods, have hamstrung the potential of PLS. In particular, PLS research has focused on parameter recovery and overlooked predictive validity. We demonstrate some implications of considering predictive abilities as a complement to parameter recovery of PLS by reconsidering the institutionalized practice of mapping formative measurement to Mode B estimation of outer relations. Extensive simulations confirm that Mode A estimation performs better when sample size is moderate and indicators are collinear while Mode B estimation performs better when sample size is very large or true predictability (R²) is high

Corporate Reputation on Performance of Banking Industries in Nigeria: Using PLS-SEM Tool of Analysis

This analysis examines the influence of corporate reputation on performance of banking industries in Kano state North-West of Nigeria. A survey with 384 qualified observations from financial institutions’ customers in Kano was conducted. Partial Least Squares (PLS-SEM) was used as an alternative to covariance-based SEM, which provides researcher with some flexibility in terms of model complexity and relationship specification.. The model shows corporate reputation that is a reflective construct that has a significant direct effect on performance. The results, besides indicating the suitability of the PLS in statistical analysis, has also contributed to a better understanding of Banking customer in Kano which hitherto has not been tested. Findings are useful for policy makers, management of banking industries and practitioners to enhance corporate reputation, Implications for research and practice and future recommendations are discussed. Keywords: Corporate Reputation, Performance, Banking Industries, PLS-SEM, Nigeria

On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012)

Rigdon's (2012) thoughtful article argues that PLS-SEM should free itself from CB-SEM. It should renounce all mechanisms, frameworks, and jargon associated with factor models entirely. In this comment, we shed further light on two subject areas on which Rigdon (2012) touches in his discussion of CB-SEM and PLS-SEM. Rigdon (2012) highlights ways to make better use of PLS-SEM's predictive capabilities, for example, by reverting to set correlations. We discuss this issue in more detail, highlighting the need to examine the predictive capabilities of models when developing and testing theories, and broach the issue of confirmatory versus exploratory modeling. As a result of our discussion, we call for the continuous improvement of the PLS-SEM method to uncover its capabilities for theory testing while retaining its predictive characte