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This paper tests the feasibility and empirical implications of a spatial econometric model with a full set of interaction effects and weight matrix defined as an equally weighted group interaction matrix applied to research productivity of individuals. We also elaborate two extensions of this model, namely with group fixed effects and with heteroskedasticity. In our setting, the model with a full set of interaction effects is overparameterised: only the SDM and SDEM specifications produce acceptable results. They imply comparable spillover effects, but by applying a Bayesian approach taken from LeSage (2014), we are able to show that the SDEM specification is more appropriate and thus that colleague interaction effects work through observed and unobserved exogenous characteristics common to researchers within a group.

The purpose of this paper is to examine the effects of interaction techniques (e.g. swiping and tapping) and the range of thumb movement on interactivity, engagement, attitude, and behavioral intention in single-handed interaction with smartphones.

A 2×2 between-participant experiment (technological features: swiping and tapping×range of thumb movement: wide and narrow) was conducted to study the effects of interaction techniques and thumb movement ranges.

The results showed that the range of thumb movement had significant effects on perceived interactivity, engagement, attitude, and behavioral intention, whereas no effects were observed for interaction techniques. A narrow range of thumb movement had more influence on the interactivity outcomes in comparison to a wide range of thumb movement.

While the subject of actual and perceived interactivity has been discussed, the issue has not been applied to smartphone. Based on the research results, the mobile industry may come up with a design strategy that balances feature- and perception-based interactivity.

This study adopted the perspective of the hybrid definition of interactivity, which includes both actual and perceived interactivity. Interactivity effect outcomes mediated by perceived interactivity.

This study examines the use of linear regressions that include interaction terms, finding frequent interpretation errors in published accounting research. We provide insights on how to estimate, interpret, and present interactive regression models, and explain seldom-used but easily-implemented methods to report conditional marginal effects. We also examine the use of interaction terms in tax and financial reporting trade-off studies, evaluating the conceptual fit between a regression model with interactions and alternative definitions of trade-off. Although we advocate the use of interactive models, noise levels common in accounting research greatly reduce the ability to detect interaction effects.

This chapter reviews the methods available to hospitality and tourism researchers to perform moderation analysis with continuous variables in partial least squares structural equation modeling (PLS-SEM), with the objective of enhancing understanding and encouraging the use of these techniques in future papers. The product term method is presented first, followed by an empirical example/application in the context of hospitality and tourism. Two extensions, namely the two-stage approach that can help cope with formative and higher-order constructs, and the orthogonalizing approach that can help generate more accurate results and overcome multicollinearity among tourism variables in the presence of a continuous moderator variable, are then presented and discussed. The chapter concludes by presenting guidelines and recommendations for improving the use of interaction effects in analyses of tourism variables, as well as highlighting ongoing developments in both the product term method and PLS-SEM software.

The purpose of this paper is to test empirically whether there exist spillover externalities in job satisfaction, i.e., to test whether individual-level job satisfaction is affected by the aggregate job satisfaction level in a certain labor market environment.

The authors use a linear-in-means model of social interactions in the empirical analysis. The authors develop an original strategy, motivated by the hierarchical models of social processes, to identify the parameters of interest. BHPS and WERS datasets are used to perform the estimations both at the establishment and local labor market levels.

The authors find that one standard deviation increase in aggregate job satisfaction leads to a 0.42 standard deviation increase in individual-level job satisfaction at the workplace level and a 0.15 standard deviation increase in individual-level job satisfaction at the local labor market level. In other words, the authors report that statistically significant job satisfaction spillovers exist both at the establishment level and local labor market level; and, the former being approximately three times larger than the latter.

First, this is the first paper in the literature estimating spillover effects in job satisfaction. Second, the authors show that the degree of these spillover externalities may change at different aggregation levels. Finally, motivated by the hierarchical models of social processes, the author develop an original econometric identification strategy.

The purpose of this paper is to provide an illustrated step-by-step guideline of the partial least squares factorial structural equation modeling (PLS FAC-SEM) approach. This approach allows researchers to assess whether and how model relationships vary as a function of an underlying factorial design, both in terms of the design factors in isolation (i.e. main effects) as well as their joint impact (i.e. interaction effects).

After an introduction of its building blocks as well as a comparison with related methods (i.e. n-way analysis of variance (ANOVA) and multi-group analysis (MGA)), a step-by-step guideline of the PLS FAC-SEM approach is presented. Each of the steps involved in the PLS FAC-SEM approach is illustrated using data from a customer value study.

On a methodological level, the key result of this research is the presentation of a generally applicable step-by-step guideline of the PLS FAC-SEM approach. On a context-specific level, the findings demonstrate how the predictive ability of several key customer value measurement methods depends on the type of offering (feel-think), the level of customer involvement (low-high), and their interaction (feel-think offerings×low-high involvement).

This is a first attempt to apply the factorial structural equation models (FAC-SEM) approach in a PLS-SEM context. Consistent with the general differences between PLS-SEM and covariance-based structural equation modeling (CB-SEM), the FAC-SEM approach, which was originally developed for CB-SEM, therefore becomes available for a larger amount of and different types of research situations.

As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle.

A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results.

The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic.

This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

The aim of this study is to investigate the effects of different virtual product experiences (VPEs, interpersonal and machine) on sense of virtual community (SOVC) for consumers. Furthermore, parasocial interaction (PSI) and the sequence of VPEs likely moderate the relationship between different combinations of VPEs and SOVC.

The study employed a factorial online experimental design: 8 (combinations of VPEs, between subjects) x 2 (sequences of VPEs, between subjects). Participants were randomly assigned to the 16 groups.

The results show that with a high degree of PSI, the “escapism + social” VPEs group has the greatest beneficial effects on SOVC, whereas with a low degree of PSI, the “aesthetics + information” VPEs group has the greatest beneficial effects on SOVC. Besides, in VPES sequence 1 (interpersonal → machine), the “escapism + social” VPEs group has a greater effect on SOVC, whereas in sequence 2 (machine → interpersonal), there was no statistically significant difference for VPEs combinations relative to SOVC.

This study determines that consumers with different degrees of PSI differ from one another regarding their interactions with web sites and communities. Therefore, the characteristics of PSI provide manufacturers with various marketing strategies for interaction. The combinations and sequences of interpersonal and machine VPEs in this study can provide manufacturers with suggestions for appropriate online shopping web site design.

Although the importance of these virtual experiences is continuously increasing, there is still a lack of studies that empirically analyze from the combinations of machine interaction and interpersonal interaction of VPEs of the effects on consumer behavior.

Interactive or moderation effects are normally examined using hierarchical regression analysis and the product‐term. The purpose of this paper is to test an alternative perspective of interaction, which is based on how leaders combine different leadership behaviors (i.e. task‐oriented and socio‐emotional leadership).

Data from 191 full‐time, white‐collar employees were obtained using a cross‐sectional design and a self‐administered questionnaire. Task‐oriented leadership (i.e. pressure) and socio‐emotional leadership (i.e. support) were measured using items from Misumi. Two measures were used for follower satisfaction with the leader: the satisfaction component of the job descriptive index and a single‐item measure. Satisfaction with how the leader combines leadership behaviors was measured using a single‐item measure.

The findings show that follower satisfaction with the way the leader combines task‐oriented and socio‐emotional leadership augments the effects of these two types of leadership on follower satisfaction with the leader. Non‐significant interactions were found between pressure and support using the product‐term method for examining interactions.

The paper examined only satisfaction with the leader. The sample is relatively small, consisted entirely of white‐collar employees, and the response rate is unknown. All the data were obtained from participants and hence mono‐source effects are possible.

The findings draw attention to the need to approach interactive effects more carefully and demonstrate the importance of combinative aspects of leadership style.

The paper provides an alternative view of interaction effects.

With a start in the observation that there is a large variation in how companies interact with each other, the paper aims to anlayse the economic consequences of this variation. As the more extensive interaction is costly, the variation also indicates a variation in the economic dimension.

This is a conceptual paper.

Three different economic streams can be identified. Firstly, the interaction costs can be reduced by taking advantage of time and scope. Interaction over time give opportunity to use some of the costs as investments through creation of relationships. By using the same counterpart for several products, scope can be used to reduce interaction costs. Secondly, developed business relationships can be used to create relation revenues. The counterparts can use each other for developing better solutions and for development of knowledge. Finally, the actors can also get positive network effects. One example is the joint development with third parties such as sub-suppliers or customer’s customer.

The discussion ends in two major implications. One is the central role of managers and the other the crucial role of economic deals. Managers are crucial both to identify relevant cost and revenue items as well as to exploit them. Deals are important as it is only with direct counterparts where there are monetary streams. In all other relationships, there is only indirect consequences.

It is obvious that the type of cost and revenue streams identified above will require new and different economic tools. A base for this is given here.