The Virtual Design Team (VDT) extends and operationalizes Galbraith's (1973) information-processing view of organizations. VDT simulates the micro-level information processing, communication, and coordination behavior of participants in a project organization and predicts several measures of participant and project-level performance. VDT-1 (Cohen 1991) and VDT-2 (Christiansen 1993) modeled project organizations containing actors with perfectly congruent goals engaged in complex but routine engineering design work within static organization structures. VDT-3 extends the VDT-2 work process representation to include measures of activity flexibility, complexity, uncertainty, and interdependence strength. It explicitly models the effects of goal incongruency between agents on their information processing and communication behavior while executing more flexible tasks. These extensions allow VDT to model more flexible organizations executing less routine work processes. VDT thus bridges rigorously between cognitive and social psychological micro-organization theory and sociological and economic macro-organization theory for project teams. VDT-3 has been used to model and simulate the design of two major subsystems of a complex satellite launch vehicle. This case study provides initial evidence that the micro-contingency theory embodied in VDT-3 can be used to predict organizational breakdowns, and to evaluate alternative organizational changes to mitigate identified risks. VDT thus supports true “organizational engineering” for project teams.

Four antecedents, it is argued, are necessary precursors for a firm to capture rents from innovation. The antecedents are causal understanding; innovation team proficiency; emergence and mobilization of new competences; and creation of competitive advantages, each of which are conceptually distinct and precisely defined in the paper. These constructs are linked together in a stage model and subsequently operationalized and tested using LISREL. Substantial support is found for the central thesis, that achieving each of the four antecedent processes increases the predicted rents from an innovation project.

This paper considers minimizing the makespan in the 3-machine assembly-type flowshop scheduling problem. After problem formulation, we present a proof to show that the general version of this problem is strongly NP-complete. We then discuss a few polynomially solvable cases of the problem and present the solution algorithms. Next, a branch and bound solution scheme is suggested. Finally, three heuristics to find approximate solutions to the general problem are proposed and their error bounds are analyzed.

A model is developed which allocates an available budget to research alternatives subject to budgetary constraints on both organizational and technical entities. The solution algorithm is based on the out-of-kilter minimum cost network flow algorithm and is programmed for use in a time-share, conversational mode. Although the model does not describe the decision processes observed empirically, its output is sufficiently similar to actual allocations that it can be viewed as predictive. Strengths and weaknesses of the model are detailed based on questionnaire and interview data provided by the potential users of the system. The decision information system is used to illustrate that experimentation concerned with better understanding of the adoption process can be used to facilitate model design and application.

New start-up companies, which are considered to be a vital ingredient in a successful economy, have a different objective than established companies: They want to maximise their chance of long-term survival. We examine the implications for their operating decisions of this different criterion by considering an abstraction of the inventory problem faced by a start-up manufacturing company. The problem is modelled under two criteria as a Markov decision process; the characteristics of the optimal policies under the two criteria are compared. It is shown that although the start-up company should be more conservative in its component purchasing strategy than if it were a well-established company, it should not be too conservative. Nor is its strategy monotone in the amount of capital it has available. The models are extended to allow for interest on investment and inflation.

We study employee mental health to assess the long-term nonmonetary consequences of mergers. Using employer-employee level data linked to individual health records, we document that the incidences of stress, anxiety, depression, and psychiatric medication usage increase following mergers. These effects are prevalent among employees from both targets and acquirers, in weak and in growing profitable firms. Employees who experience negative career developments within the merging firms, ‘blue-collar’ workers, and employees with lower skills are most affected. Mergers that generate more mental illness among employees perform worse after the transaction. A variety of tests address endogeneity concerns.

This paper robustly connects observed portfolio choices to correlations of individual income shocks with an aggregate shock (or, equivalently, with stock market returns). The share of nonparticipating individuals displaying a positive correlation, and therefore a negative hedging demand for stocks, is above 79% in both our samples. Furthermore, correlations predict nonparticipation to the equity market, also out-of-sample and for the same individual over time. These results support the traditional hedging motive explanation for nonparticipation. Such new insight owes to the income shocks comovements across individuals, which we model and exploit to identify correlations.

An understanding of differences in nonmonetary work conditions is fundamental for a complete characterization of individuals’ well-being at work. Thus, to fully characterize gender inequalities in the labor market, scholars have begun to explore gender differences in nonmonetary work conditions. We examine one such condition—meaningful work—using nationally representative survey data linked with worker and employer administrative data. We document a large and expanding gender gap in meaningful work, wherein women experience their jobs as more meaningful than men do. We then explore patterns underlying this difference. We find little correlation between women’s higher experience of meaningful work and either labor market decisions related to first parenthood or women’s underrepresentation in leadership jobs. Instead, the gender gap appears to be highly correlated with the sorting of more women into occupations with a high level of beneficence: the sense of having a prosocial impact. Though both women and men experience such jobs as more meaningful, women do so by a larger margin. Next, we consider the relationship between the gender difference in meaningful work and the gender wage gap, contributing to the discussion on compensating differentials in work amenities. We find that, whereas the gender gap in meaningful work closes a substantial part of the wage gap in lower paid jobs, it does little to close the gap in higher paid jobs in which the gender wage gap is largest.

We study a large-scale (n = 50,000) natural field experiment implemented by the U.S. Social Security Administration aimed at increasing the timely and accurate self-reporting of wages by Supplemental Security Income (SSI) recipients. A letter reminding SSI recipients of their wage reporting responsibilities significantly increased both the likelihood of reporting any earnings and the total earnings reported. However, the specific letter content—providing social information or highlighting the salience of penalties—had no systematic effect. We develop a conservative estimate that the letters generated roughly $5.91 in savings per dollar spent, highlighting the value of such a nudge in this important context.