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Information technology is associated with psychological and physical risks such as high stress levels and antisocial behavior. The purpose of this paper is to understand why people engage in technology risk behavior, despite the negative consequences that might follow. Focusing on online games, this study identifies factors that affect individuals' intention to play online games and investigate whether the effects of these factors differ across different risk levels.

Experimental design was used as the research methodology. Subjects were randomly assigned to a single treatment with two conditions: high and low risk scenarios. A total of 597 responses were analyzed to test the research hypotheses.

The research findings reveal that subjective norms, curiosity and playfulness have a positive effect on the intention to play online games, while critical mass has no effect on the intention decisions. Further, among the three significant constructs, playfulness turned out to be the only factor that is affected by risk levels.

This study extends prior literature on technology adoption by examining the effect of different risk levels on adoption intention decisions. It further extends prior literature on online games by identifying the factors that drive individuals to play games while accounting for the risks associated with playing these games.

The research study identifies factors that should be taken into consideration when promoting the adoption of technologies, including online games.

This study offers a new understanding of technology adoption decisions that takes into account the different levels of risk associated with technology use. It shows that an individual's curiosity and the pressure emanating from one's social network are powerful behavior drivers that persist regardless of the level of risk. Further, this research study is among the first to apply categorical least squares methodology combined with a procedure for a moderated structural equation model to test a structural equation model with categorical multiplicative terms in LISREL.

Using observational and experimental designs, the purpose of this study was to explore if the power relation between the offender and the victim of incivility and the level of perceived severity of the incivility were associated with bystanders’ intentions to help when witnessing workplace incivility.

In Study 1, 160 participants completed a questionnaire where they described a recent uncivil incident they had witnessed, and completed measures of perceived severity and measures of their behavioural response as bystanders. In Study 2, 183 participants were randomised to read one of two vignettes (a manager being uncivil towards a subordinate or vice versa), and completed measures of perceived severity and of their motivation to intervene. The authors investigated whether the power relation between perpetrator and victim, and the perceived severity of the uncivil exchange, were associated with prosocial bystander behaviours in Study 1 and with motivation to defend the victim of incivility in Study 2.

Higher perpetrator power was significantly associated with the incident being perceived as more severe, and higher perpetrator power was directly related to greater tendency to confront, and lower tendency to avoid, the perpetrator. Perpetrator power was indirectly associated with social support according to the perceived severity. A supervisor acting in an uncivil manner was rated as more severe than a subordinate acting in such a way. Perceived severity mediated the relationship between perpetrator power and the witness’s introjected, identified and intrinsic motivation to intervene.

This study extends previous work by investigating how the perpetrator’s power influences both the bystander’s prosocial behaviour and their motivation to defend the victim. Furthermore, previous research has not considered how perceptions of severity might mediate the relationship between power, behaviour and motivation.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.

The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

This chapter explores a relatively underresearched assumption in the diversity literature, namely, that more variety in demographic characteristics, educational or functional backgrounds, or hierarchical status in the workforce represents a wider repertoire of perspectives, approaches, and ways of thinking. Using data from members of innovation teams across 27 organizations in 11 industries (for which variation in thinking should be highly valued), we explore at the individual level whether people with different demographic and informational backgrounds evidence differences in ways of thinking which we define in terms of cognitive styles, learning styles, cultural orientations, and communication preferences. We find large differences in ways of thinking due to culture and communication preferences but modest and limited differences in ways of thinking by level and type of education, occupational function, and hierarchical status. We find few differences by gender. The findings raise questions about the frequently repeated claims that categorical and informational diversity among organizational members reflects differences in ways of thinking.

Continues a series on topics in research methodology, statistics and data analysis techniques for the library and information sciences. Discusses the chi‐square test for relationship between two categorical variables.

Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.

This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.

PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.

This paper provides updated guidelines of how to use PLS and how to report and interpret its results.