Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Originality/value 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.

Mind wandering is an important brain activity that fosters creativity and productivity. Research suggests that individuals spend up to 50% of their waking time thinking about things that are unrelated to the present situation or task. Previous literature has acknowledged the importance of mind wandering in technology-related contexts by investigating its mediating role between task and individual performance. In this study, we go one step further and investigate the direct relationship between technology use and mind wandering. In particular, we investigate if different types of technology use (hedonic use vs. utilitarian use) have an impact on mind wandering. Results from a factorial survey study (n=90) suggest that there is a significant difference between hedonic use and utilitarian use when it comes to mind wandering. Based on these insights, we discuss the role of mind wandering for IS research and potentials for future research.

Toxic behavior (TB)-a form of releasing frustration and anger in a detrimental way-is a common phenomenon in online games. Despite its importance, a validated questionnaire measuring TB is yet missing. In this paper, we apply a comprehensive procedure for scale development by using two difference sources of items. In the first one, the item pool is adapted from an existing scale. In the second one, the act frequency approach is applied to generate a pool of items. We evaluated both scales based on survey data from 380 online gamers. Both instruments are juxtaposed based on their psychometric properties. The results indicate that the adapted scale performs better in the context of our study than the scale generated from the act frequency approach and is, thus, the preferable choice. With a validated measurement scale in place, we discuss how future research can benefit from the TB scale proposed here.

Heterogeneity is a pertinent issue in Information Systems (IS) research because human behavior often differs across groups. In the partial least squares path modeling (PLS-PM) context, several approaches have been proposed to investigate potential group differences. Despite the availability of numerous approaches, literature that compares their efficacy is sparse. Consequently, IS researchers lack guidance on which approach is best suited to detect group differences. We address this issue by presenting the results of an extensive Monte Carlo simulation study that juxtaposes the various approaches' behavior under numerous conditions. In doing so, we first provide an overview on existing approaches proposed for multigroup analysis (MGA) in the PLS-PM context. Moreover, we derive important implications for applied research: Firstly, we show that the omnibus test of group differences (OTG) and approaches based on the comparison of confidence intervals are not recommendable for MGA. Secondly, we provide detailed information as to which approaches are suitable for comparing one specific path coefficient and which are recommended if the complete structural model is compared across groups. Finally, we show that approaches which are designed to compare a single parameter require an adjustment for multiple comparisons when used to compare more than two groups.

Virtual Reality (VR) allows users to experience their environment differently and more immersively than traditional information systems (IS). Therefore, it is important to also study cognitive processes in VR settings. In this proposal, we focus on the concept of mind wandering, which is an emerging concept in IS research that can be studied using neurological measures such as eye tracking. Current literature suggests that mind wandering is a complex concept with different dimensions, namely deliberate and spontaneous mind wandering. While previous literature has provided initial evidence on the feasibility of eye tracking to approximate mind wandering, this study seeks to investigate how well eye tracking performs when it comes to a more nuanced perspective on mind wandering applied in an VR setting.

PurposeThis 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.Design/methodology/approachData 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.FindingsWe 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.Originality/valueTo 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.

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Employees increasingly complete organizational tasks using privately owned consumer technologies such as private devices (e.g., smartphones) or private Internet accounts (e.g., email accounts). Higher satisfaction constitutes a major reason for this bring-your-own behavior (BYOB). However, little research has theoretically explored and empirically tested this assumption. This study sheds light on this phenomenon by analyzing the effect of BYOB on IT satisfaction. Drawing from social cognitive theory, we propose choice self-efficacy as a new construct that intermediates the relationship between BYOB and IT satisfaction. Building on results from survey data (n = 400), we provide new evidence that BYOB has a positive effect on IT satisfaction whereby choice self-efficacy plays a vital element as it mediates this relationship. Since IT satisfaction shapes how people use technology and how they perform with it, we derive important implications for future research on IT consumerization. Furthermore, we provide several conclusions for practitioners and discuss how to enhance IT satisfaction and choice self-efficacy. This paper proceeds as follows: in Section 2, we review existing literature on IT consumerization and IT satisfaction. In Section 3, we present our theoretical development by proposing a research model that addresses the relationship between BYOB and IT satisfaction. We review previous use of self-efficacy in the information systems (IS) literature and conceptualize choice self-efficacy as a new contextualized variable that mediates the relationship between BYOB and IT satisfaction. In Section 44, we describe our research methodology. In Section 5, we present the results of this study and conclude by discussing the study's implications and promising aspects for future research.