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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.

Many data situations require the consideration of network effects among the cross-sectional units of observation. In this chapter, the authors present a generalized panel model which accounts for two features: (i) network effects present through weighted dependent variables as regressors, exogenous variables, as well as the error components, and (ii) higher-order network effects due to ex ante unknown network decay functions or the presence of multiplex (multi-layer) networks among all of those. The authors outline the model, the basic assumptions, and present simulation results.

Of all the various interventions into the market economy, which have been invented and implemented by man and state, those that historically have caused the gravest consequences in the advanced industrialized economies surely are the inflationist policies, which lead inexorably to the business cycle in all of its various aspects and manifestations. In this paper, we shall attempt to trace through a number of socio-economic consequences and implications of the business cycle. We are convinced that ultimately the business cycle has political implications, which are just as far reaching and grave as its numerous economic consequences.

This chapter proposes an approach toward the estimation of cross-sectional sample selection models, where the shocks on the units of observation feature some interdependence through spatial or network autocorrelation. In particular, this chapter improves on prior Bayesian work on this subject by proposing a modified approach toward sampling the multivariate-truncated, cross-sectionally dependent latent variable of the selection equation. This chapter outlines the model and implementation approach and provides simulation results documenting the better performance of the proposed approach relative to existing ones.

This chapter takes its point of departure in the vision of educating public leaders and managers with the ability to create public value in a networked governance structure. The purpose of the chapter is to revise this vision by unpacking the notion of public value in contemporary governance and discuss the implications for public leadership and for public leadership and management programs.

The chapter explores the notion of public value as a conceptual framework for emergent forms of networked governance. Drawing on insights from sociology of law and governmentality studies, a set of key tensions inherent in the public value discourse are identified as the diagnostic impetus to consider the somewhat excessive leadership figure put forward in the literature. The chapter shows that the discourse of networked governance and public value thinking is rather contested and imply a certain kind of hybridisation of public administration and public purpose into opposite identity spheres. Instead of forming a ‘whole system’ as suggested in the literature, the hybridisation implicates an ongoing suspension that allows the governance structure to become tense and unresolved. The hybridisation forms new dilemmatic spaces in contemporary governance, it is argued.

The author suggests that public leadership should be considered as hybrid practices, formed around an ongoing search of ‘publics’ and images of ‘wholeness’ by way of oscillating between varying values and identities. This form of hybrid leadership calls for new explorative learning formats in public leadership programs, it is argued.

The chapter undertakes a careful critical reading and conceptual examination of the current paradigm of public value management. By drawing on sociology of law and Foucault’s genealogy of rationalities of government the examination brings new insight into the doubled identities and dilemmatic spaces of contemporary governance and elaborates the concept of public leadership theorized as distributed and hybrid practices.

We investigate how Salesforce’s key people used analogies and metaphors during the deployment of their (then) radical business model innovation. Our analysis shows how Salesforce’s entrepreneurial team skillfully used a mix of analogies and metaphors to communicate its innovations and differentiate the company from its competitors. We also show how business model innovators can weave together analogies and metaphors to create distinct meta-narratives that elicited strong emotions and helped construct a memorable organizational identity that galvanized stakeholders around the firm’s ecosystem appeal. We conclude by discussing the implications of our findings for business model and cognition research.

Relational thinking and spatial analyses have become highly relevant for higher education research. However, choices of research methods and specifically of statistical procedures do not often correspond to the epistemological underpinnings implied by relational perspectives. Against this background, this chapter illustrates the uses and challenges of geometric data analysis (GDA) for studying the complexities and dynamics of current spaces of higher education. GDA can be described as a set of statistical techniques that allow the identification, assessment and visualisation of complex relations in social science data. Using an investigation into the social topologies of first-year students as an example, we discuss the mathematical foundations, the step-by-step procedures of data analysis, the interpretation of results and strategies for integrating GDA into multimethod research designs. In sum, we argue that GDA does not only entail a comprehensive set of statistical instruments that permit visual analysis of relational structures, but also enables the systematic integration of qualitative and quantitative methods, hence supporting the development of innovative and coherent research designs and analytical strategies.