ICIS 2023: Why I love India so much!

In a few hours I’ll be returning to the Great State of Texas from India, where I’ve been attending the ICIS 2023 Conference. I had the opportunity to meet with WarpPLS users, which I always enjoy very much, and with methodological researchers doing PLS-related work.

Talking about people doing PLS-related work, it was a special treat to be able to meet and talk with Nicholas Danks. The man is a true scholar and a genius. I hope to collaborate with him in the future, and (perhaps, if I am lucky) get some of that talent through osmosis.

Another highlight was talking again with the incomparable Dr. Boo. I was busy distracting her with nonsense when her name was mentioned at the awards ceremony. For those of you who don’t know, she is one of the forerunners of the field of Information Systems, a field that she begun influencing at the young age of 13 (according to my calculations).

This was my first time in India. I loved it so much! This was such a nice experience in no small measure due to Glory George, who was kind enough to show me some of Hyderabad. The people of India are so smart and hard working. Take for example the person on the photo below; he solved a 100-year-old numeric computing problem while riding on the back of a bike in heavy traffic!

Okay, just my imagination. But he was indeed doing what seemed to be some coding, using his friend’s constantly moving upper back as a table. By the way, if you think that traffic in India is chaotic, think again. Those who pay close attention will notice that there is method to what looks like disorderly flow. More than method actually, it is a form of art. Just don’t try driving if you are a beginner; it will be like challenging Ma Long to a “ping pong” match.

Should you want to see and hear the person who is writing this, in keeping with media naturalness theory, check this video. More views and likes will help make my dear friends Steve Harmon and Rolando Santos happy about their masterful video creation and editing work.

Best regards to all!

WarpPLS: A bit of history

The YouTube video linked below (scroll down to the end of the news article) provides a bit of history in connection with the development of WarpPLS. A big thank you to Rolando Santos for his professional video creation work!

https://www.tamiu.edu/newsinfo/2023/10/topworldresearcher10262023.shtml

Best regards to all!

Using logistic regression in PLS-SEM: Dichotomous endogenous variables

The article below discusses how one can use logistic regression with the probit approach, to avoid the problems associated with having dichotomous endogenous variables, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2023). Using logistic regression in PLS-SEM: Dichotomous endogenous variables. Data Analysis Perspectives Journal, 4(4), 1-6.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

A dichotomous endogenous variable would be impossible to occur at the population level, which an empirical sample is assumed to represent, because the structural error term associated with the endogenous variable is expected to be a random variable with many distinct values. Consequently, the endogenous variable is also expected to have many distinct values. This paper discusses how to address this problem, using logistic regression with the probit approach, in the context of structural equation modeling via partial least squares (PLS-SEM). Our discussion is based on an illustrative model analyzed with the software WarpPLS.

Best regards to all!

Contributing to the success of PLS in SEM: An action research perspective

The article below discusses how I employed an action research approach, by working closely with WarpPLS users, to contribute to the success of PLS in SEM. A big thank you to WarpPLS users!

Kock, N. (2023). Contributing to the success of PLS in SEM: An action research perspective. Communications of the Association for Information Systems, 52(1), 730-734.

Link to full-text file for this article:

Contributing to the success of PLS in SEM: An action research perspective

Abstract:

I share with Evermann and Rönkkö (2022) the belief that classic composite-based partial least squares path modeling (PLS-PM) presents shortcomings when used to conduct structural equation modeling (SEM) analyses. The shortcomings can be traced back to one fundamental problem, which is that latent variables (LVs) are approximated in PLS-PM as exact linear combinations of their corresponding indicators. In SEM, each LV is in fact a factor; i.e., a linear combination of the indicators and a measurement residual. My approach to addressing the shortcomings of PLS-PM is rather unique among researchers concerned with quantitative methods. I have employed an action research approach, helping investigators employ SEM in their empirical studies. This has led to my development of a widely used software tool for SEM analyses. I illustrate my action research orientation by discussing three recent methodological developments with which I have been closely involved.

Best regards to all!

Assessing multiple reciprocal relationships in PLS-SEM

The article below discusses how one can assess multiple reciprocal relationships, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2023). Assessing multiple reciprocal relationships in PLS-SEM. Data Analysis Perspectives Journal, 4(3), 1-8.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Two latent variables may influence each other in both directions, in what characterizes a reciprocal relationship. This paper discusses how one can assess multiple reciprocal relationships in the context of structural equation modeling via partial least squares (PLS-SEM). We discuss the assessment of multiple reciprocal relationships, through an illustrative model analyzed with the software WarpPLS.

Best regards to all!

On the validity assessment of formative measurement models in PLS-SEM

The article below discusses how one can conduct a validity assessment of formative measurement models, in the context of structural equation modeling via partial least squares (PLS-SEM).

Amora, J. T. (2023). On the validity assessment of formative measurement models in PLS-SEM. Data Analysis Perspectives Journal, 4(2), 1-7.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Structural equation modeling via partial least squares (PLS-SEM) is the preferred approach when a research model includes formative measurement models. In this paper, the validity assessment of first-order and higher-order measurement models is illustrated using real data employing the WarpPLS, a prominent software tool for PLS-SEM.

Best regards to all!

Assessing univariate and multivariate normality in PLS-SEM

The article below discusses how one can assess univariate and multivariate normality, in the context of structural equation modeling via partial least squares (PLS-SEM).

Ma, K. Q., & Zhang, W. (2023). Assessing univariate and multivariate normality in PLS-SEM. Data Analysis Perspectives Journal, 4(1), 1-7.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Partial least squares structural equation modeling (PLS-SEM) has gained popularity among researchers in part due to its relaxed requirement for multivariate normality. One important step in performing structural equation modeling (SEM) is to test the normality assumption. In this paper, we illustrate how to assess univariate and multivariate normality in PLS-SEM using WarpPLS.

Best regards to all!

Conditional probabilistic analyses with WarpPLS

If an analysis suggests that two variables are causally linked, yielding a path coefficient of 0.25 for example, this essentially means in probabilistic terms that an increase in the predictor variable leads to an increase in the conditional probability that the criterion variable will be above a certain value. Yet, conditional probabilities cannot be directly estimated based on path coefficients; and those probabilities may be of interest to both researchers and practitioners.

By using the “Explore conditional probabilistic queries” menu option, WarpPLS users can estimate conditional probabilities via queries including combinations of latent variables, unstandardized indicators, standardized indicators, relational operators (e.g., > and <=), and logical operators (e.g., & and |). The article below provides an illustration of the use of this software feature in the context of a study of technology, innovation, and SMEs' export intensity.

Haddoud, M. Y., Kock, N., Onjewu, A. K. E., Jafari-Sadeghi, V., & Jones, P. (forthcoming). Technology, innovation and SMEs' export intensity: Evidence from Morocco. Technological Forecasting and Social Change. (Online availability details: Volume 191, June 2023.)

Link to full-text access from the publisher:

https://www.sciencedirect.com/science/article/abs/pii/S0040162523001609

Abstract:

This study seeks to understand the scarcely examined relationships between SMEs' foreign technology licensing, R&D expenditure, innovation and export intensity. Espousing an integrated open innovation and self-selection paradigm, observations of 446 Moroccan SMEs are analysed through structural equation modelling. The definitive path analysis showed that foreign technology licensing and R&D expenditure distinctively affect innovation and, in turn, innovation increases export intensity. In further insights, to illustrate how the distribution of these inputs enhances internationalisation, a probabilistic analysis shows that foreign technology licensing, R&D expenditure and innovation will incrementally stimulate export intensity by >71 %. The permutations of these variables in the fresh setting of Morocco summon scholars' empirical attention at the same time as policymakers' consideration.

(Many thanks to my co-authors, particularly Dr. Mohamed Haddoud, and to the review panel, for all of their work!)

Best regards to all!