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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.

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.

Our econometric research allows for a possible response of a person's hours worked to hours typically worked by members of a multidimensional labor market reference group that considers demographics and geographic location. Instrumental variables estimates of the canonical labor supply model expanded to permit social interactions pass a battery of specification checks and indicate positive and economically important spillovers for adult men. Ignoring or incorrectly considering social interactions in male labor supply can misestimate the response to tax reform by as much as 60%.

The present research builds on three complementary theories to explore how social influence processes in interaction bring about opinion and sentiment change: expectation states theory, affect control theory, and social influence network theory.

An experimental study is used to test intersections between the theories and assess how performance expectations, affective impressions of group members, and emergent perceptions of their influence work together to generate opinion and sentiment change.

Respondent opinions shifted in the direction of group leaders’ opinions, regardless of behavioral interchange patterns. Opinion change was greater when a third group member shared the leader’s opinion. Change in affective impressions was shaped by the group leader’s opinion, the assertiveness of their behavior, and the support of a third group member. The perceived influence composition of the group predicted opinion and sentiment change, above and beyond the effects of conditional manipulations. Features of the group interaction led to inferences about status characteristics that reinforced the influence order of the group.

The chapter tests hypotheses from earlier work and explores status signals not yet tested as predictors of opinion change – behavioral interchange patterns and the degree of support for one’s ideas. In addition, it examines inferences about status characteristics following the group discussion, and influence effects on the prevailing definition of the situation.

This chapter contributes to recent integrative work that explores the relationship between performance expectations, affective impressions, and social influence. Synergistic processes forwarded by earlier research are tested, along with several newly proposed linkages.

Purpose: This study examines the relationship between gender, nationality, care responsibilities for children, and the psychological work climate of researchers.

Basic Design: Based on a dataset of approximately 2,900 cases, the main effects of gender and nationality, their interaction effect and the interaction effects of gender with care responsibilities for minor children, and with hierarchical position are considered in relation to work climate. Dummy regressions and t-tests were performed to estimate and compare the means and regression parameters of the perceived group climate and the view of leaders as evaluated by researchers. The dataset used was taken from a full survey of employees of the Max Planck Society, which is one of Germany’s largest research organizations with over 80 facilities and institutes in various disciplines and a focus on basic research.

Results: Gender differences concerning the evaluation of the work climate are particularly pronounced among doctoral candidates and researchers who have a non-EU nationality. Gender gaps increasingly level out with each successive career step. Additionally, a main effect of gender and a weak interaction of gender and care responsibility for minor children was supported by the data. A main effect of nationality on work climate ratings was found but could not be meaningfully interpreted.

Interpretation and Relevance: The interaction effect between gender and the position of a researcher can be interpreted as being a product of the filtering mechanism of the research system. With this interpretation, the results of the study can plausibly be explained in the light of previous research that concludes that female researchers face higher career hurdles than male researchers.

This chapter analyzes the indirect effects of environmental management system (EMS) implementation and its certification and relates these to international governance in the context of new public environmental management. Building on a comprehensive quantitative dataset, it assesses the effects of ISO 14001 and EMAS (Eco-Management and Auditing Scheme) certification as well as temporal experience with EMS implementation on organizational activities outside the scope of EMS, while taking into account embeddedness and interaction effects. The analysis reveals heterogeneous effects, with limited evidence of embeddedness and interaction effects. As well, no influences of national business systems can be identified. Implications for the role of national governments in implementing sustainability strategies, even beyond environmental management, and aspects of standard flexibility in the process of governing firms to implementing such strategies in an international context are discussed.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

Interactivity is a dimension that describes a certain condition in business networks – a propensity to use interaction in business as a major means in development processes. Expectations formed as a collective attitude and knowledge about existing economic conditions and the importance of joint solutions formed through interactions to handle them are an expression of interactivity in the network. This collective condition is important because there are some obstacles confronting the development of substantive interaction. Businesses engage in interaction only when they acknowledge and accept that mutuality is something positive and a necessary condition to achieve some positive outcomes that cannot be achieved in isolation, and that interdependencies can be used in a constructive way. Finally, there must be managers prepared to use resources to build up relationships and to develop joint solutions that will pay in the long run. All relationships require investments. These attitude and knowledge factors, which are aspects of interactivity, are a condition for handling resources and activities to create efficiency and innovativeness.

As an extension to Assael’s (2011) review on media synergy, this chapter examines the latest evolvement of media synergy research in the past 10 years by integrating studies from a wide range of leading journals.

We searched a total of 17 major journals in advertising, communication, and marketing from 2005 to 2014 and identified a total of 42 articles on media synergy. These studies were reviewed to assess the current status of media synergy research.

Studies of inter-media interaction at the individual level provide mixed support for a media synergistic effect, and the occurrence of this effect demands certain boundary conditions. Research on multi-media engagement has been gaining momentum in the past few years and is a promising subject in media synergy research.

We envision two growing approaches in future media synergy research: the neuroscientific approach and the data mining approach.

This chapter posits that media synergy research has evolved in the most recent years to a new phase, which is multi-media engagement. Hence, this chapter extends Assael’s work in terms of explicating media synergy in the context of social media engagement and identifying research gaps in current literature.

This chapter addresses social embeddedness effects on ex ante management of economic transactions. We focus on dyadic embeddedness, that is the history of prior transactions between business partners and the anticipation of future transactions. Ex ante management through, for example, contractual arrangements is costly but mitigates risks associated with the transaction, such as risks from strategic and opportunistic behavior. Dyadic embeddedness can reduce such risks and, hence, the need for ex ante management by, for instance, making reciprocity and conditional cooperation feasible. The chapter presents a novel theoretical model generating dyadic embeddedness effects, together with effects of transaction characteristics and management costs. We stress the interaction of the history of prior transactions and expectations of future business. Hypotheses are tested using new and primary data from an extensive survey of more than 900 purchases of information technology (IT) products (hard- and software) by almost 800 small- and medium-sized enterprises (SMEs). Results support, in particular, the hypotheses on effects of dyadic embeddedness.