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People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

This study sought to distinguish characteristics of cognitive processes while using information technology. In particular, it identifies similarities and differences between mind wandering and cognitive absorption in technology-related settings in an effort to develop a deeper understanding of the role that mind wandering plays when using information technology.

Data was gathered using an online survey including responses from 619 English-speaking adults in 2019. We applied a confirmatory factor analysis and used a robust variant of maximum likelihood estimator with robust standard errors and a Satorra–Bentler scaled test statistic. The data analysis procedure was conducted with the R environment using the psych package for descriptive analysis, and lavaan to investigate the factorial structure and the underlying correlations.

We discuss the benefits of carefully differentiating between cognitive processes in Information Systems research and depict avenues how future research can address current shortcomings with a careful investigation of neurophysiological antecedents.

To date, mind wandering has been explored as a single phenomenon, though research in reference disciplines has begun to distinguish varieties and how they distinctly impact behavior. We demonstrate that this distinction is also important for our discipline by showing how two specific types of mind wandering (i.e. deliberate and spontaneous mind wandering) are differently correlated with sub-dimensions of cognitive absorption, a well-studied construct.

The purpose of this paper is to distinguish different types of sustainable digital entrepreneurs (SDEs) and explore their approaches toward enhancing organizational resilience.

Investigation of entrepreneur characteristics using Grounded Theory methodology; 12 semi-structured telephone interviews with (owner-)managers of digital-resilient small and medium-sized enterprises (SMEs) and start-ups in Germany; adaptation of a sustainability-digitalization-matrix for initial clustering; investigation of reoccurring patterns (within and between clusters) through variable-oriented content analysis; application of the capability-based conceptualization of organizational resilience for synthesis and extension.

First, the authors present a new typology of SDEs, including descriptions of the four main types (Process-Oriented System Thinker, Unconventional Strategist, Dynamic Visionary and Success-Oriented Opportunist). Second, the authors propose a conceptual framework with six success factors of organizational resilience. The framework accentuates the influence of SDEs on organizational culture and the macro-environment.

Digital sustainability and resilience are emerging management principles. The insights gained will allow (future) entrepreneurs to perform a self-assessment and replicate approaches toward enhancing SME resilience; for example, governing the co-creation of an organizational culture with a strong integrative view on sustainability and digitalization.

SMEs are characterized by high vulnerability and a reactive response to the disruptions caused by sustainability crises and digitalization. Blending sustainable and digital entrepreneurship at a micro-level, the authors identified the success factors underpinning organizational resilience that are associated with the characteristics of four types of SDEs.

Toxic behavior in multiplayer video games diminishes the potential revenue of gaming companies by spreading a bad mood, negatively affecting game play, and subsequently leading to the churn of players. However, research investigating why toxic behavior occurs is still scarce. To address this issue, this study disjunctively tests three different theoretical approaches (social cognitive theory, theory of planned behavior, and online disinhibition effect) to explain toxic behavior and propose a unified theory of toxic behavior.

In total, 320 respondents participated in a questionnaire study. This study analyzes the data with covariance-based statistics (i.e. regression analysis and structural equation modelling), and the approach is twofold. First, the hypotheses of three theories are disjunctively tested. Second, a unified theory of toxic behavior is proposed.

The results of this study indicate that online disinhibition best explains toxic behavior, whereby toxic behavior victimization, attitude, and behavioral control also play an important role.

The findings of this study offer an opportunity to better understand a contemporary and especially meaningful form of negative behavior online.

To maintain revenue and popularity, the computer game industry can use the findings of this study to prevent and better address toxic behavior and its negative consequences.

Toxic behavior among video game players is a relatively new and unexplored phenomenon; therefore, this study makes a valuable contribution to the research field by testing the explanatory power of three theoretical approaches and proposing a unified theory of toxic behavior.