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This study provides a comprehensive framework of adaptation in triadic business relationship settings in the service sector. The framework is based on the industrial network approach (see, e.g., Axelsson & Easton, 1992; Håkansson & Snehota, 1995a). The study describes how adaptations initiate, how they progress, and what the outcomes of these adaptations are. Furthermore, the framework takes into account how adaptations spread in triadic relationship settings. The empirical context is corporate travel management, which is a chain of activities where an industrial enterprise, and its preferred travel agency and service supplier partners combine their resources. The scientific philosophy, on which the knowledge creation is based, is realist ontology. Epistemologically, the study relies on constructionist processes and interpretation. Case studies with in-depth interviews are the main source of data.

Conceptualizing trust alone or as the starting point for understanding both trust and distrust is insufficient. Therefore, this chapter focuses on the construction of phenotypic trustscapes and distrustscapes that permit an abstract exploration of the concepts of trust and distrust using societal and dyadic relationships and perceptions of the individual as the units of analysis. For theoretical understanding of trust and distrust, it uses social and evolutionary biologic multi-level theory. This chapter builds on the existing trust literature in three ways: (1) by triangulating on trust and distrust through the use of a number of research methodologies; (2) by placing trust and distrust in value orientation theory and models; and (3) by extricating trust and distrust from reciprocity constructs, and placing them into separate phenotypes: trustscapes and distrustscapes. These efforts show that both trust and distrust are naturally occurring phenomena, with one or the other predominant in specific contexts. The chapter includes scenarios in Japan, Bulgaria, and Indonesia to demonstrate how micro- and macro-level examples of trustscapes and distrustscapes function.

For many of the current leadership theories, models, and approaches, the answer to the question posed in the title, “Is leadership more than ‘I like my boss’?,” is “no,” as there appears to be a hierarchy of leadership concepts with Liking of the leader as the primary dimension or general factor foundation. There are then secondary dimensions or specific sub-factors of liking of Relationship Leadership and Task Leadership; and subsequently, tertiary dimensions or actual sub-sub-factors that comprise the numerous leadership views as well as their operationalizations (e.g., via surveys). There are, however, some leadership views that go beyond simply liking of the leader and liking of relationship leadership and task leadership. For these, which involve explicit levels of analysis formulations, often beyond the leader, or are multi-level in nature, the answer to the title question is “yes.” We clarify and discuss these various “no” and “yes” leadership views and implications of our work for future research and personnel and human resources management practice.

Dyadic multi-dimensionality informs the variation that exists within and between network ties and suggests that ties are not all the same and not all equally strategic. This chapter presents a model of dyadic evolution grounded in dyadic multi-dimensionality and framed within actor-level, dyadic-level, endogenous, and exogenous contexts. These contexts generate both strategic catalysts that motivate network action and bounded agency that may constrain such network action. Assuming the need to navigate within bounded agency, the model highlights three strategic processes that demonstrate how dyadic multi-dimensionality underlies the evolution of strategic network ties.

The social relations model (SRM; Kenny, 1994) explicitly proposes that leadership simultaneously operates at three levels of analysis: group, dyad, and individual (perceiver and target). With this model, researchers can empirically determine the amount of variance at each level as well as those factors that explain variance at these different levels. This chapter shows how the SRM can be used to address many theoretically important questions in the study of leadership and can be used to advance both the theory of and research in leadership. First, based on analysis of leadership ratings from seven studies, we find that there is substantial agreement (i.e., target variance) about who in the group is the leader and little or no reciprocity in the perceptions of leadership. We then consider correlations of leadership perceptions. In one analysis, we examine the correlations between task-oriented and socioemotional leadership. In another analysis, we examine the effect of gender and gender composition on the perception of leadership. We also explore how self-ratings of leadership differ from member perceptions of leadership. Finally, we discuss how the model can be estimated using conventional software.

Drawing from theories of structural power and relational competence, this paper proposes an innovative theoretical model able to predict relationship outcomes during adolescence by mapping the partners’ resources and patterns of exchange in four contexts (family, work/school, leisure time, and survival) as power bases in the relationship. Adolescent dating is an important juncture in the developmental pathway to adult partnership, both in terms of relational satisfaction and relationship violence. Power processes can capture the dynamics of both healthy and unhealthy relationships, regardless of gender, contingent to the power advantage (or disadvantage) within the relationship and can produce predictable consequences for partner’s behavior. Knowing which partner holds what kind and amount of power and in which decision-making areas may be used to predict the actions of either partner and ultimately identify the trajectories of their relationships.

This commentary on Kenny and Livi (2009) expands on aspects of leadership categorization theory that are consistent with the application of the social relations model (SRM). It critically considers limits to the generalization of the variance components analysis results described in Kenny and Livi's first example, and briefly summarizes results of an additional study that supports their findings. Finally, this commentary suggests interpretational issues of interest to researchers who wish to continue to apply the SRM to multi-level issues in the study of leadership.

Purpose – This chapter (a) summarizes leader–member exchange (LMX) measurement practices since the influential reviews by Schriesheim, Castro, and Cogliser (1999) and Gerstner and Day (1997), (b) clarifies the status of LMX as a broad construct from a hierarchical factor model, (c) conducts multitrait-multimethod (MTMM) analyses on leader and follower reports of multidimensional LMX, and (d) investigates discriminant validity between Member LMX and satisfaction with supervisor.

Methodology/Approach – We used (a) a literature search of LMX measurement practices, (b) a combination of meta-analysis and factor analysis to specify the broad LMX construct underlying Liden and Maslyn's (1998) (LMX-MDM) multidimensional instrument, (c) MTMM analyses of leader and member ratings of the LMX-MDM, and (d) a combination of meta-analysis and multiple regression to assess incremental validity of Member LMX beyond satisfaction with supervisor.

Findings – Since 1999, 85% of LMX studies now use one of two dominant LMX scales (LMX-7, Scandura, & Graen, 1984; LMX-MDM, Liden & Maslyn, 1998). These two measures are correlated (rcorrected=.9), suggesting the LMX-7 and the LMX-MDM are alternate forms of the same instrument. 94% of studies that used these two measures treat LMX as a single, broad construct rather than as a multidimensional set of constructs. MTMM analyses suggest Leader LMX and Member LMX are two, separate-but-related constructs (i.e., confirming two source factors and no lower-order trait factors). Last, Member LMX meta-analytically correlates with satisfaction with supervisor at rcorrected=.8. There is some incremental validity of LMX, but the pattern is inconsistent across samples.

Social Implications – We point out that LMX researchers have now moved toward standard measurement of LMX – as a broad, higher-order factor that varies between leader and follower. By doing so, we reveal that the stage is set for cumulative and replicable research on leadership as a dyadic, follower-specific phenomenon.

Originality/Value of Paper – Our chapter is the first to reveal consensus in LMX measurement across studies; to summarize the standard treatment of LMX as a single, broad factor; and to apply MTMM analyses to demonstrate separate Leader LMX and Member LMX source factors.

This study aims to understand the role of technology in relationship maintenance among romantic partners.

It takes a qualitative, inductive approach and collected data from in-depth interviews with 20 individuals who are married or in cohabiting relationships.

This study supports the extension of relationship maintenance typology derived from face-to-face relationship studies to technology-mediated communication, but highlights how technology use transforms the implementation of maintenance behaviors. Technology helps couples coordinate tasks and keep in touch with friends and families. Although technology-mediated communication cannot replace face-to-face interactions in relationship talk and sharing in-depth feelings, it plays an important role in redefining the ways in which couples interact positively, maintain mutual understanding, and secure the future of the relationship. Moreover, this study identifies a new maintenance behavior, communication coordination. These maintenance behaviors reflect a tension between maintaining connectivity and managing the boundary between work and home and between the public and private spheres.

This study builds on previous work on technology use and relationship maintenance, but takes a different qualitative, inductive approach to address the limitations in the survey research dominant in the literature. It helps us understand the advantages and challenges in maintaining relationships in the digital age and also explores the factors that influence the patterns of technology use in relationship maintenance.