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The authors argue that organization design needs to play a more active role in the explanation of differential performance and outline a set of ideas for achieving this both in theoretical and empirical research. Firms are heterogeneous in terms of (1) how well they do things, capturing persistent productivity differences, and (2) how they do things – and both reflect firms’ organization design choices. Both types of heterogeneity can be persistent, and are interdependent, although they have typically been studied separately. The authors propose a simple formal framework – the “aggregation function framework” – that aligns organization design thinking with the emphasis on performance heterogeneity among firms that is characteristic of the strategy field. This framework allows for a more precise identification of how exactly organization design may contribute to persistent performance differences, and therefore what exactly are the assumptions that strategy and organization design scholars need to be attentive to.

The paper analyses the effects of individual and household characteristics on current poverty status, while controlling for initial conditions, past poverty status and unobserved heterogeneity in 14 European countries for the period 1994–2001, using the European Community Household Panel. The distinction between true state dependence and individual heterogeneity has important policy implications, since if the former is the main cause of poverty it may be crucial to break the ‘vicious circle’ of poverty using income-supporting social policies, whereas if it is the latter anti-poverty policies should focus primarily on education, training, development of personal skills and other labour market oriented policies. The empirical results are similar in qualitative terms but rather different in quantitative terms across the EU countries covered in the paper. State dependence remains significant in all model specifications, even after controlling for unobserved heterogeneity or when removing possible endogeneity bias. Higher poverty rates and higher poverty persistence are associated with particular welfare state regimes, although the link is substantially weakened when other explanatory variables are included in the analysis.

This chapter reconstructs the roots of configurational analysis in organization theory and organizational economics, focusing on the elements of configurational thinking that are particularly relevant to organizational design; and outlining some future prospects for a configurational theory of organization design. We detect the presence of configurational ideas in many organization theories and organizational economics approaches. We argue that this, seldom acknowledged, continuity extends and enriches the implications of configurational analysis for organization design. In addition, we define and identify ‘structural heterogeneity’ as an organizational property that can be distinctively studied by configurational analysis, distinguishing between internal heterogeneity – diversity of organizational attributes within one configuration – and external heterogeneity – diversity of organizational configurations under the same environmental conditions. Some of the insights that can be gained through a configurational analysis of structural heterogeneity are illustrated through a fs/QCA study of a multi-industry sample of firms.

We examine the roles of sample initial conditions and unobserved individual effects in consistent estimation of the dynamic binary response panel data model. Different specifications of the model are estimated using female welfare and labor force participation data from the Survey of Income and Program Participation. These include alternative random effects (RE) models, in which the conditional distributions of both the unobserved heterogeneity and the initial conditions are specified, and fixed effects (FE) conditional logit models that make no assumptions on either distribution. There are several findings. First, the hypothesis that the sample initial conditions are exogenous is rejected by both samples. Misspecification of the initial conditions results in drastically overstated estimates of the state dependence and understated estimates of the short- and long-run effects of children on labor force participation. The FE conditional logit estimates are similar to the estimates from the RE model that is flexible with respect to both the initial conditions and the correlation between the unobserved heterogeneity and the covariates. For female labor force participation, there is evidence that fertility choices are correlated with both unobserved heterogeneity and pre-sample participation histories.

Purpose – Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence for observed and unobserved heterogeneity within data underlying the American customer satisfaction index (ACSI) model. Examining data for two specific industries (utilities and hotels) reveals only modest differences. However, we suppose that unobserved heterogeneity critically affects the results. These insights provide the basis for shaping further differentiated ACSI model analyses and more precise interpretations.

Methodology/approach – This study applies the partial least squares (PLS) path modeling method and uses empirical data to estimate and compare the ACSI model results on the aggregate and industry-specific data levels. In addition, the finite mixture PLS path modeling (FIMIX-PLS) method is employed to further examine across industry similarities and within industry differences.

Findings – This research uncovers unobserved heterogeneity that guides forming three segments of customers within each industry. The major segment in each industry represents customers that are fairly loyal (i.e., neither disloyal nor extremely loyal) while the other two smaller segments are not as similar across the two industries. Our study identifies substantial differences across these segments within each industry. An importance-performance map analysis illustrates these differences and provides the basis for managerial implications.

Originality/value of the chapter – The unobserved heterogeneity revealed within industries in a given country (i.e., the United States of America) underlines the need to be open to differences within populations, beyond the observed heterogeneity across distinct groups or cultures, and the need to reconsider reporting requirements in academic research.

This chapter estimates a dynamic reduced-form model of intra-firm promotions using an employer–employee panel of over 300 of the largest corporations in the United States in the period from 1981 to 1988. The estimation conditions on unobserved individual heterogeneity and allows for both an endogenous initial condition and sample attrition linked to individual heterogeneity in demonstrating the relative importance of variables that influence promotion. The role of the executive’s functional area in promotion is considered along with the existence and source of promotion fast tracks. We find that while the principal determinant of promotions is unobserved individual heterogeneity, functional area has a high explanatory power, resulting in promotion probabilities that differ by functional area for executives at the same reporting level and firm. No evidence is found that an executive’s recent speed of advancement in pay grade has a positive causal impact on in-sample promotions after conditioning on the executive’s career speed of advancement, except for the lowest level executives the data. Fast tracks appear to largely result from heterogeneity in persistent individual characteristics, not from an inherent benefit in recent advancement itself.

The presence of respondents with apparently extreme sensitivities in choice data may have an important influence on model results, yet their role is rarely assessed or even explored. Irrespective of whether such outliers are due to genuine preference expressions, their presence suggests that specifications relying on preference heterogeneity may be more appropriate. In this paper, we compare the potential of discrete and continuous mixture distributions in identifying and accommodating extreme coefficient values. To test our methodology, we use five stated preference datasets (four simulated and one real). The real data were collected to estimate the existence value of rare and endangered fish species in Ireland.

We formulate static and dynamic empirical models of promotion where the current promotion probability depends on the hierarchical level in the firm, individual human capital, unobserved individual specific attributes, time-varying firm-specific variables, as well as endogenous past promotion histories (in the dynamic version). Within the static versions, we investigate the relative influence of the key determinants of promotions and how these influences vary by hierarchical levels. In the dynamic version of the model, we examine the causal effect of past speed of promotion on promotion outcomes. The model is fit on an eight-year panel of 30,000 American executives employed in more than 300 different firms. The stochastic process generating promotions may be viewed as a series of promotion probabilities which become smaller as an individual moves up in the hierarchy and which are primarily explained by unobserved heterogeneity and promotion opportunities. Firm variables and observed human capital variables (age, tenure, and education) play a surprisingly small role. We also find that, conditional on unobservables, the promotion probability is only enhanced by the speed of promotion achieved in the past (a structural fast track effect) for a subset of the population and is negative for the majority. In general, the magnitude of the individual-specific effect of past speed of promotion is inversely related to schooling, tenure, and hierarchical level.