Explaining Anomalous High Performance in a Health Care Supply Chain*

An implicit assumption in distributing and coordinating work among independent organizations in a supply chain is that a focal organization can use financial or contractual mechanisms to enforce compliance among the other organizations in meeting desired performance objectives. Absent contractual agreement or financial gain, there is little incentive for independent organizations to coordinate their process improvement activities. In this study, we examine a health care supply chain in which the work is distributed among independent organizations. We use a detailed case study and an abductive reasoning approach to understand how and why the independent organizations choose to coordinate and collaborate in their work. Our study makes two contributions to the literature. First, we use well‐established lean principles to explain how independent organizations achieve superior performance despite highly uncertain and variable customer demand—a context considerably different from the origins of lean principles. Second, we forward relational coordination theory to explain why the organizations in this decentralized supply chain coordinate their work. Relational coordination includes the use of shared goals, shared knowledge, and mutual respect for one another's work as primary mechanisms to explain process improvement in the absence of any contractual incentives. Our study constitutes a first step in generating theory for work design and its improvement in decentralized supply chains.     

Enterprise risk management for automation in correctional facilities with pandemic and other stressors

Real-time tracking of tool and equipment inventories is a critical function of many organizations and sectors. For prisons and correctional facilities, tracking and monitoring of assets such as cookware, hardware, keys, janitorial equipment, vocational/technical specialty tools, etc., is essential for safety, security, trust, efficiency, education, etc. The performance of automated systems for this purpose can be diminished by a variety of emergent and future sociotechnical factors alone and in combination. This article introduces a methodology for contractor evaluation and selection in acquisition of innovative asset management systems, with an emphasis on evolving system requirements under uncertainty. The methodology features a scenario-based preferences analysis of emergent and future conditions that are disruptive to the performance of the asset-control system. The conditions are across technologies, operating environments, regulations, workforce behaviors, offender behaviors, prices and markets, organizations, cyber threats, etc. The methodology addresses the influence and interaction of the conditions to disrupt system priorities. Examples include: (i) infectious disease disrupting priorities among requirements and (ii)  radio-frequency identification (RFID) and wireless-technology innovations disrupting priorities among stakeholders. The combinations of conditions that most and least matter for the system acquisition are characterized. The methodology constitutes a risk register for monitoring sources of risk to project performance, schedule, and cost throughout the system lifecycle. The results will be of interest to both practitioners and scholars engaged in systems acquisition as the pandemic interacts with other factors to affect risk, uncertainty, and resilience of organizational missions and operations.     

Toward Disaster‐Resilient Cities: Characterizing Resilience of Infrastructure Systems with Expert Judgments

Resilient infrastructure systems are essential for cities to withstand and rapidly recover from natural and human‐induced disasters, yet electric power, transportation, and other infrastructures are highly vulnerable and interdependent. New approaches for characterizing the resilience of sets of infrastructure systems are urgently needed, at community and regional scales. This article develops a practical approach for analysts to characterize a community's infrastructure vulnerability and resilience in disasters. It addresses key challenges of incomplete incentives, partial information, and few opportunities for learning. The approach is demonstrated for Metro Vancouver, Canada, in the context of earthquake and flood risk. The methodological approach is practical and focuses on potential disruptions to infrastructure services. In spirit, it resembles probability elicitation with multiple experts; however, it elicits disruption and recovery over time, rather than uncertainties regarding system function at a given point in time. It develops information on regional infrastructure risk and engages infrastructure organizations in the process. Information sharing, iteration, and learning among the participants provide the basis for more informed estimates of infrastructure system robustness and recovery that incorporate the potential for interdependent failures after an extreme event. Results demonstrate the vital importance of cross‐sectoral communication to develop shared understanding of regional infrastructure disruption in disasters. For Vancouver, specific results indicate that in a hypothetical M7.3 earthquake, virtually all infrastructures would suffer severe disruption of service in the immediate aftermath, with many experiencing moderate disruption two weeks afterward. Electric power, land transportation, and telecommunications are identified as core infrastructure sectors.     

Evidence for Learning to Learn Behavior in Normal Form Games

Evidence presented in Salmon (2001; Econometrica 69(6) 1597) indicates that typical tests to identify learning behavior in experiments involving normal form games possess little power to reject incorrect models. This paper begins by presenting results from an experiment designed to gather alternative data to overcome this problem. The results from these experiments indicate support for a learning-to-learn or rule learning hypothesis in which subjects change their decision rule over time. These results are then used to construct an adaptive learning model which is intended to mimic more accurately the behavior observed. The final section of the paper presents results from a simple simulation based analysis comparing the performance of this adaptive learning model with that of several standard decision rules in reproducing the choice patterns observed in the experiment.JEL Classification: C92, C72     

On Weighing Gains and Investments at the Margin of Risk Regulation

Analysts have long noted an apparent discrepancy in the level of investment seemingly necessary to meet "acceptable" levels of public safety. At the margin of risk regulation, i.e., where safety determination is judged acceptable, the traditional cost-benefit calculus appears to contribute obvious rationale to the final political decision. Efforts are now being made to introduce a measure of consistency into the application of risk-cost benefit analysis to radiological protection. This paper reviews these efforts from a UK perspective. It also looks at how the issue was treated in a public setting through the Sizewell B Public Inquiry.     

Fertility timing,wages, and human capital

Women who have first births relatively late in life earn higher wages. This papers offers an explanation of this fact based on a simple life-cycle model of human capital investment and timing of first birth. The model yields conditions (that are plausibly satisfied) under which late childbearers will tend to invest more heavily in human capital than early childbearers. The empirical analysis finds results consistent with the higher wages of late childbearers arising primarily through greater measurable human capital investment.Helpful comments were provided by Claudia Goldin, Paul Taubman, by seminar participants at Baruch College, CUNY Graduate Center, Queens College, Rutgers University, and the University of Pennsylvania, and anonymous referees. An earlier version of this paper was presented at the March 1989 annual meetings of the Population Association of America.     

Archetype Change in Professional Organizations: Survey Evidence from Large Law Firms

This paper examines the proposition that the traditional archetype of the professional partnership is said to have changed into a more 'business-like' entity, the managed professional business. It broadens the restricted case sample base on which much of the evidence has been adduced, by developing a survey questionnaire through which 197 large British law firms were sampled. Change, consistent with the notion of a more commercially oriented and consciously managed organization, is concentrated in the market-facing area of the firm but coexists with areas of continuity in the governance of the firm and its strategic management. The findings reveal a more managerial form of organization in which the core elements of the traditional form of professional organization have not been transformed. These results contest the assertion of either transformational or sedimented change found in other, case-based research and suggest that archetype change needs theoretically to be distinguished from the general phenomenon of greater managerialism within the professional service firm.     

Toward Computerizing a Causal Modeling Approach to Strategic Problem Framing*

This paper proposes an object-oriented approach to the development of interactive software for the purpose of managerial problem solving. A prototype is being developed using CSM causal mapping to represent each manager's perceptions of the relationships between key variables of a firm's strategic situation. This paper suggests the design of GDSS that would enable a group of managers to discuss, learn from each other, and possibly develop consensus about decisions or their causes. Issues involving future development are discussed.