Ned Kock

Principles of canonical action research

Abstract.  Despite the growing prominence of canonical action research (CAR) in the information systems discipline, a paucity of methodological guidance continues to hamper those conducting and evaluating such studies. This article elicits a set of five principles and associated criteria to help assure both the rigor and the relevance of CAR in information systems. The first principle relates to the development of an agreement that facilitates collaboration between the action researcher and the client. The second principle is based upon a cyclical process model for action research that consists of five stages: diagnosis, planning, intervention, evaluation and reflection. Additional principles highlight the critical roles of theory, change through action, and the specification of learning in terms of implications for both research and practice. The five principles are illustrated through the analysis of one recently published CAR study.

Media richness or media naturalness? The evolution of our biological communication apparatus and its influence on our behavior toward E-communication tools

E-communication in businesses has been the target of intense research. The theoretical hypotheses that have informed the media richness hypothesis have been influential in some circles and have also been strongly attacked by social theorists. It is argued in this paper that this theoretical polarization involving advocates of the media richness hypothesis and social theorists is due to two problems. The first is that there is a wealth of empirical evidence that provides direct support for the notion that human beings prefer the face-to-face medium for a variety of business tasks that involve communication, which seems to provide support for the media richness hypothesis. The second problem is that the media richness hypothesis is built on a vacuum, as no underlying explanation was ever presented by media richness theorists for our predisposition toward rich (or face-to-face) media. The main goal of this paper is to offer a solution to these problems by providing an alternative to the media richness hypothesis, referred to here as media naturalness hypothesis, developed based on Darwins theory of evolution. The media naturalness hypothesis argues that, other things being equal, a decrease in the degree of naturalness of a communication medium (or its degree of similarity to the face-to-face medium) leads to the following effects in connection with a communication interaction: (a) increased cognitive effort, (b) increased communication ambiguity, and (c) decreased physiological arousal. Like the media richness hypothesis, the media naturalness hypothesis has important implications for the selection, use, and deployment of e-communication tools in organizations. However, unlike the media richness hypothesis, the media naturalness hypothesis is compatible with social theories of behavior toward e-communication tools. Among other things, this paper shows that the media naturalness hypothesis (unlike its media richness counterpart) is compatible with the notion that, regardless of the obstacles posed by low naturalness media, individuals using those media to perform collaborative tasks may achieve the same or better task-related outcomes than individuals using media with higher degrees of naturalness.

Expanding the Boundaries of E-Collaboration

This article provides an introduction to the special issue on Expanding the Boundaries of E-Collaboration. It presents an operational definition of the term e-collaboration, and a historical review of the development of e-collaboration tools and related academic research. That is followed by an introductory development of the notion of e-collaboration boundaries. The article concludes with a summarized discussion of the articles published in the special issue.

Advanced Mediating Effects Tests, Multi-Group Analyses, and Measurement Model Assessments in PLS-Based SEM

Use of the partial least squares PLS method has been on the rise among e-collaboration researchers. It has also seen increasing use in a wide variety of fields of research. This includes most business-related disciplines, as well as the social and health sciences. The use of the PLS method has been primarily in the context of PLS-based structural equation modeling SEM. This article discusses a variety of advanced PLS-based SEM uses of critical coefficients such as standard errors, effect sizes, loadings, cross-loadings and weights. Among these uses are advanced mediating effects tests, comprehensive multi-group analyses, and measurement model assessments.

Using WarpPLS in E-collaboration Studies: An Overview of Five Main Analysis Steps

Most relationships between variables describing natural and behavioral phenomena are nonlinear, with U-curve and S-curve relationships being particularly common. Yet, structural equation modeling software tools do not estimate coefficients of association taking nonlinear relationships between latent variables into consideration. This can lead to misleading results, particularly in multivariate and complex phenomena like those related to e-collaboration. One notable exception is WarpPLS available from: warppls.com, a new structural equation modeling software currently available in its first release. The discussion presented in this paper contributes to the literature on e-collaboration research methods by providing a description of the main features of WarpPLS in the context of an e-collaboration study. The focus of this discussion is on the softwares features and their use and not on e-collaboration study itself. Particular emphasis is placed on the five steps through which a structural equation modeling analysis is conducted through WarpPLS.

Communication flow orientation in business process modeling and its effect on redesign success: Results from a field study

Business process redesign has been intensely studied, particularly since the mid 1990s. One aspect that received little attention, however, is the relationship between business process modeling choices and redesign success. This research gap is addressed through a multi-methods study of 18 business process redesign projects conducted in 18 different organizations. A structural equation model is developed and tested based on data collected from those projects; the results are then triangulated with qualitative data. The structural equation model depicts relationships between the following broad perceptual constructs: communication flow orientation of a business process model, quality of a business process model, and business process redesign success. The communication flow orientation of a business process model is defined as the extent to which a model explicitly shows how communication interactions take place in a process. A models perceived quality is defined as the degree to which the model presents the following perceptual sub-constructs: ease of generation, ease of understanding, completeness, and accuracy. The results of the study suggest that the degree of communication flow orientation of a business process model is significantly related to the models perceived quality. Perceived model quality, in turn, is significantly related to perceived business process redesign success. Interestingly, a business process models perceived completeness does not seem to be influenced by a models communication flow orientation. The structural equation model accounted for 56% of the explained variance in the business process redesign success construct. The main implication of this study is that a focus on communication flows in business processes is an important ingredient in successful business process redesign projects.

Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach

The author discusses common method bias in the context of structural equation modeling employing the partial least squares method PLS-SEM. Two datasets were created through a Monte Carlo simulation to illustrate the discussion: one contaminated by common method bias, and the other not contaminated. A practical approach is presented for the identification of common method bias based on variance inflation factors generated via a full collinearity test. The authors discussion builds on an illustrative model in the field of e-collaboration, with outputs generated by the software WarpPLS. They demonstrate that the full collinearity test is successful in the identification of common method bias with a model that nevertheless passes standard convergent and discriminant validity assessment criteria based on a confirmation factor analysis.

Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results

This is a follow-up on a previous article Kock, 2010b discussing the five main steps through which a nonlinear structural equation modeling analysis could be conducted with the software WarpPLS warppls.com. Both this and the previous article use data from the same e-collaboration study as a basis for the discussion of important WarpPLS features. The focus of this article is on specific features related to saving and analyzing grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving the various minor and major results of the analysis. Even though its focus is on an e-collaboration study, this article contributes to the broad literature on multivariate analysis methods, in addition to the more specific research literature on e-collaboration. The vast majority of relationships between variables, in investigations of both natural and behavioral phenomena, are nonlinear; usually taking the form of U and S curves. Structural equation modeling software tools, whether variance-or covariance-based, typically do not estimate coefficients of association based on nonlinear analysis algorithms. WarpPLS is an exception in this respect. Without taking nonlinearity into consideration, the results can be misleading; especially in complex and multi-factorial situations such as those stemming from e-collaboration in virtual teams.

Using WarpPLS in e-Collaboration Studies: Mediating Effects, Control and Second Order Variables, and Algorithm Choices

This is a follow-up on two previous articles on WarpPLS and e-collaboration. The first discussed the five main steps through which a variance-based nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (Kock, 2010b). The second covered specific features related to grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving various results (Kock, 2011). This and the previous articles use data from the same e-collaboration study as a basis for the discussion of important WarpPLS features. Unlike the previous articles, the focus here is on a brief discussion of more advanced issues, such as: testing the significance of mediating effects, including control variables in an analysis, using second order latent variables, choosing the right warping algorithm, and using bootstrapping and jackknifing in combination.

Information systems theorizing based on evolutionary psychology: an interdisciplinary review and theory integration framework

Evolutionary psychology holds great promise as one of the possible pillars on which information systems theorizing can take place. Arguably, evolutionary psychology can provide the key to many counterintuitive predictions of behavior toward technology, because many of the evolved instincts that influence our behavior are below our level of conscious awareness; often those instincts lead to behavioral responses that are not self-evident. This paper provides a discussion of information systems theorizing based on evolutionary psychology, centered on key human evolution and evolutionary genetics concepts and notions. It is argued here that there is often a need to integrate evolutionary and non-evolutionary theories, and four important preconditions for the successful integration of evolutionary and non-evolutionary theories are discussed. An example of integration of evolutionary and non-evolutionary theories is provided. The example focuses on one evolutionary information systems theory-media naturalness theory-previously developed as an alternative to media richness theory, and one non-evolutionary information systems theory, channel expansion theory.