Does IO Economics Really Make the Case for Investments in IT: A Rejoinder

The preceding critique [1] of the paper “The Information Problems in Organizations: A Research Model for the Value of Information and Information Systems” [3], reaches general conclusions with respect to the original paper and the applicability of economics to MIS research. These conclusions are based on arguments developed at a different level of analysis than that used in the original paper, and without considering the goals and intent of the original paper. The differences between the critique and the original paper are highlighted.     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.     

Ambulance allocation for maximal survival with heterogeneous outcome measures

This paper proposes new models for locating emergency medical services (EMS) by incorporating survival functions for capturing multiple-classes of heterogeneous patients. The Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP) aims to maximize the overall expected survival probability of multiple-classes of patients, whereby different classes could be defined according to agreed patient categories based on response time targets, or by capturing differing medical conditions each with a corresponding survival function. Furthermore, we propose and demonstrate an approximation approach to solving the extended stochastic version of MESLMHP, which utilizes queuing theory to permit the modeling of congestion and utilization at each ambulance station, and does not require assumptions to be made on the utilization of ambulances. Both models are demonstrated using data from the ambulance service in Wales. We show that our multiple outcome measures and survival-maximizing approach, rather than one based on average response time targets alone or a single patient class provides more effective EMS ambulance allocations.     

Leadership and emotion management for complex tasks: Different emotions,different strategies

Emotions in the workplace influence a number of critical cognitive tasks including information processing and decision-making. Moreover, the effect of emotion on these operations is often emotion-specific. Given these unique effects, leaders may need to learn how to manage subordinates' discrete emotions, and not just general affect. This laboratory experiment examined the effects of leaders suggesting different regulation strategies after subordinates experienced anger or pessimism. Effects of these emotions under different leader-facilitated regulation strategies were evaluated with respect to planning, a critical organizational task, and perceptions of leader effectiveness. Results demonstrated that the type of leader-facilitated regulation strategy moderates the relationships of anger and pessimism to planning. The findings imply that leaders should understand the differential effects of discrete emotions, and be prepared to help subordinates manage emotions accordingly.     

Supply Chain Inventory Replenishment: The Debiasing Effect of Declarative Knowledge

Previous experimental research demonstrates that inefficient replenishment decision making in the supply chain can be caused by specific judgment and decision biases. Based on the literature we use controlled experiments involving both student subjects and supply chain managers to test debiasing interventions that provide declarative knowledge, which is theorized to enhance the acquisition of procedural knowledge. We first investigate the effects of three debiasing components in a single‐echelon setting: knowledge of bullwhip, inventory position (IP), and use of a target order‐up‐to quantity. Experiment 1 (N = 1,608 decisions by 67 student subjects) using a 2 × 2 × 2 factorial design for the three components finds that the conceptual understanding of IP is salient for efficient replenishment decisions. We next examine the effects of the components in a simulated, multi‐echelon, serial supply chain, which introduces the additional complexity of coordination risk. Experiment 2 (N = 3,072 decisions by 128 student subjects) using a 2 × 2 × 2 factorial design finds that although subjects benefit from training components, there is evidence of cognitive overload with an increased quantity of information. Finally we test whether these debiasing components may be an effective training program for practicing supply chain managers who can be expected to have higher levels of procedural knowledge through experience gained in the field. Experiment 3 (N = 864 decisions by 36 supply chain managers) using a 2 × 1 design investigates the effects of an instructional training intervention which includes all three debiasing components and finds the intervention to reduce costs by 14%. We provide avenues for future research and successful practice.     

The max quasi-independent set problem

In this paper, we deal with the problem of finding quasi-independent sets in graphs. This problem is formally defined in three versions, which are shown to be polynomially equivalent. The one that looks most general, namely, f-max quasi-independent set, consists of, given a graph and a non-decreasing function f, finding a maximum size subset Q of the vertices of the graph, such that the number of edges in the induced subgraph is less than or equal to f(|Q|). For this problem, we show an exact solution method that runs within time O^*(2^{\fracd-27/23d+1n})O^{*}(2^{\frac{d-27/23}{d+1}n}) on graphs of average degree bounded by d. For the most specifically defined γ-max quasi-independent set and k-max quasi-independent set problems, several results on complexity and approximation are shown, and greedy algorithms are proposed, analyzed and tested.     

Private equity regulation: a comparative analysis

This article examines the existing contractual arrangements and industry standards in private equity. It shows that investors are, in principle, capable of structuring their particular investments according to their own preferences, there are a range of governance problems and risks that could be potentially hazardous for some classes of investors. We examine the circumstances where existing industry codes and legal tools can be used to address the problems that arise in relation to private equity and buyout activity.     

A multicriteria decision analysis model for faculty evaluation

In the context of increasing demands for social and financial accountability of universities, the required implementation of transparent faculty evaluation systems constitutes a challenge and an opportunity for universities strategically aligning the activity of academic staff with the university goals. However, despite growing interest in the performance appraisal of faculty, only a few reported studies propose models that cover the full range of academic activities and the models in use are typically based on ad hoc scoring systems that lack theoretical soundness. This article approaches faculty evaluation from an innovative comprehensive perspective. Based on the concepts and methods of multiple criteria value measurement, it proposes a new faculty evaluation model that addresses the whole range of academic activities and can be applied within and across distinct scientific areas, while respecting their specificities. Constructed through a socio-technical process, the model was designed for and adopted by the Instituto Superior Técnico, the engineering school of the Technical University of Lisbon. The model has a two-level hierarchical additive structure, with top-level evaluation areas specified by second-level evaluation criteria. A bottom non-additive third level accounts for the quantitative and qualitative dimensions of academic activity related to each evaluation criterion. The model allows (a) the comparison of the performance of academic staff with performance targets reflecting the strategic policy concerns of university management; (b) the definition of the multicriteria value profile of each faculty member at the top level of the evaluation areas; (c) the computation of an overall value score for each faculty member, through an optimisation procedure that makes use of a flexible system of weights and (d) the assignment of faculty members to rating categories.     

The quality and use of regulatory analysis in 2008

This article assesses the quality and apparent use of regulatory analysis for economically significant regulations proposed by federal agencies in 2008. A nine-member research team used a six-point (0-5) scale to evaluate regulatory analyses according to criteria drawn from Executive Order 12866 and Office of Management and Budget Circular A-4. Principal findings include: (1) the average quality of regulatory analysis, though not high, is somewhat better than previous regulatory scorecards have shown; (2) quality varies widely; (3) biggest strengths are accessibility and clarity; (4) biggest weaknesses are analysis of the systemic problem and retrospective analysis; (5) budget or "transfer" regulations usually receive low-quality analysis; (6) a minority of the regulations contain evidence that the agency used the analysis in significant decisions; (7) quality of analysis is positively correlated with the apparent use of the analysis in regulatory decisions; and (8) greater diffusion of best practices could significantly improve the overall quality of regulatory analysis.