Improving Voting Systems through Service‐Operations Management

We apply service‐operations‐management concepts to improve the efficiency and equity of voting systems. Recent elections in the United States and elsewhere have been plagued by long lines, excessive waiting times, and perceptions of unfairness. We build models for the waiting lines at voting precincts using both traditional steady‐state queueing methods and simulation models. We develop solution methods to allocate voting machines optimally to precincts. Our objective functions consider both the efficiency and the equity of the voting system. We compare our allocation algorithm to several competing methods, including those used in practice. We examine several different strategies for improving voting operations on both the demand and the capacity side of voting systems, and we present a complete case study of applying our method to data from the 2008 election for Franklin County, Ohio. We conclude that our method is superior to existing polices in terms of efficiency and equity and that it is robust in terms of uncertainties regarding turnout rates on Election Day. We also suggest several operational improvements to the voting process drawn from the service‐operations literature.     

Cost of Equity in Homeland Security Resource Allocation in the Face of a Strategic Attacker

Hundreds of billions of dollars have been spent in homeland security since September 11, 2001. Many mathematical models have been developed to study strategic interactions between governments (defenders) and terrorists (attackers). However, few studies have considered the tradeoff between equity and efficiency in homeland security resource allocation. In this article, we fill this gap by developing a novel model in which a government allocates defensive resources among multiple potential targets, while reserving a portion of defensive resources (represented by the equity coefficient) for equal distribution (according to geographical areas, population, density, etc.). Such a way to model equity is one of many alternatives, but was directly inspired by homeland security resource allocation practice. The government is faced with a strategic terrorist (adaptive adversary) whose attack probabilities are endogenously determined in the model. We study the effect of the equity coefficient on the optimal defensive resource allocations and the corresponding expected loss. We find that the cost of equity (in terms of increased expected loss) increases convexly in the equity coefficient. Furthermore, such cost is lower when: (a) government uses per‐valuation equity; (b) the cost‐effectiveness coefficient of defense increases; and (c) the total defense budget increases. Our model, results, and insights could be used to assist policy making.     

Local Resources and Procurement Practices in Humanitarian Supply Chains: An Empirical Examination of Large‐Scale House Reconstruction Projects

Different procurement decisions taken by relief organizations can result in considerably different implications in regards to transport, storage, and distribution of humanitarian aid and ultimately can influence the performance of the humanitarian supply chain and the delivery of the humanitarian aid. In this article, we look into what resources are needed and how these resources evolve in the delivery of humanitarian aid. Drawing on the resource‐based view of the firm, we develop a framework to categorize the impact of local resources on the configuration of humanitarian supply chains. In contrast to other papers, the importance of localizing the configuration of the humanitarian supply chain is not only conceptually recognized, but empirical investigations are also provided. In terms of methodology, this article is based on the analysis of secondary data from two housing reconstruction projects. Findings indicate that the use of local resources in humanitarian aid has positive effects on programs’ overall supply chain performance and these effects are not only related to the macroeconomic perspective, but benefits expand to improvements related to the use of knowledge. At the same time, it was found that local sourcing often comes with a number of problems. For example, in one of the cases, significant problems existed, which were related to the scarcity of local supplies. Both housing reconstruction projects have indicated the continuous need for changes throughout the programs as a dynamic supply chain configuration is important for the long‐term sustainability of reconstruction aid.     

Financial Health Economics

We provide a theoretical and empirical analysis of the link between financial and real health care markets. This link is important as financial returns drive investment in medical research and development (R&D), which, in turn, affects real spending growth. We document a “medical innovation premium” of 4–6% annually for equity returns of firms in the health care sector. We interpret this premium as compensating investors for government‐induced profit risk, and we provide supportive evidence for this hypothesis through company filings and abnormal return patterns surrounding threats of government intervention. We quantify the implications of the premium for the growth in real health care spending by calibrating our model to match historical trends, predicting the share of gross domestic product (GDP) devoted to health care to be 32% in the long run. Policies that had removed government risk would have led to more than a doubling of medical R&D and would have increased the current share of health care spending by more than 3% of GDP.     

Buttressing Supply Chains against Floods in Asia for Humanitarian Relief and Economic Recovery

Floods are the most frequent category of disasters worldwide. Among all geographic regions, Asia has suffered the most. While there are several ongoing humanitarian efforts and initiatives, we believe there is a new opportunity to coordinate “last mile” humanitarian efforts in the event of a flood using micro‐retailers. Because micro‐retailers are the “last mile” nodes in traditional retail supply chains in many Asian countries, we propose the use of social enterprise to buttress these supply chains for distribution of essential goods by coordinating with micro‐retailers before and after floods. We also present a stylized model to quantify the benefits of doing so.     

Designing Efficient Infrastructural Investment and Asset Transfer Mechanisms in Humanitarian Supply Chains

We analyze the efficacy of different asset transfer mechanisms and provide policy recommendations for the design of humanitarian supply chains. As a part of their preparedness effort, humanitarian organizations often make decisions on resource investments ex ante because doing so allows for rapid response if an adverse event occurs. However, programs typically operate under funding constraints and donor earmarks with autonomous decision‐making authority resting with the local entities, which makes the design of efficient humanitarian supply chains a challenging problem. We formulate this problem in an agency setting with two independent aid programs, where different asset transfer mechanisms are considered and where investments in resources are of two types: primary resources that are needed for providing the aid and infrastructural investments that improve the operation of the aid program in using the primary resources. The primary resources are acquired from earmarked donations. We show that allowing aid programs the flexibility of transferring primary resources improves the efficiency of the system by yielding greater social welfare than when this flexibility does not exist. More importantly, we show that a central entity that can acquire primary resources from one program and sell them to the other program can further improve system efficiency by providing a mechanism that facilitates the transfer of primary resources and eliminates losses from gaming. This outcome is achieved without depriving the individual aid programs of their decision‐making autonomy while maintaining the constraints under which they operate. We find that outcomes with centralized resource transfer but decentralized infrastructural investments by the aid programs are the same as with a completely centralized system (where both resource transfer and infrastructural investments are centralized).     

Assessing Trade‐offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences

Humanitarian aid agencies deliver emergency supplies and services to people affected by disasters. Scholars and practitioners have developed modeling approaches to support aid delivery planning, but they have used objective functions with little validation as to the trade‐offs among the multiple goals of aid delivery. We develop a method to value the performance of aid delivery plans based on expert preferences over five key attributes: the amount of cargo delivered, the prioritization of aid by commodity type, the prioritization of aid by delivery location, the speed of delivery, and the operational cost. Through a conjoint analysis survey, we measure the preferences of 18 experienced humanitarian logisticians. The survey results quantify the importance of each attribute and enable the development of a piecewise linear utility function that can be used as an objective function in optimization models. The results show that the amount of cargo delivered is the most valued objective and cost the least important. In addition, experts prioritize more vulnerable communities and more critical commodities, but not to the exclusion of others. With these insights and the experts’ utility functions, better humanitarian objective functions can be developed to enable better aid delivery in emergency response.     

Impeding the Juggernaut of Innovation Diffusion: A Production‐Constrained Model

Models of innovation diffusion typically depict an inexorable momentum once the process begins to roll. Limited production capacity, however, can place a cap on this process, leading to waiting lines of potential customers, thus diminishing overall service quality and the speed of diffusion. Identifying the minimum production capacity needed for unimpeded and unimpaired diffusion can ensure that there are no customers waiting to adopt the product. We propose a production‐capacity‐constrained diffusion model that considers an exogenous industry production capacity and accounts for word‐of‐mouth effects from adopters as well as waiting customers. We derive analytical expressions for minimum capacity needed under multiple production scenarios. We present a dual‐objective non‐linear least squares procedure with large‐scale grid search for estimating the parameters. We apply our model to several new product innovation data sets, ranging from vacuum cleaners to sports utility vehicles in the United States to iPhones globally. Our estimates show that product shortages exist, ranging from mild to severe, in all of these product markets. We are able to corroborate some of our findings with independent external sources of evidence. We find that information on industry capacity can be recovered with as few as 5 years of sales data. Our model has practical implications for policy makers and can help equity analysts triangulate industry capacity better, particularly when such information is closely held.     

An Equilibrium Model of Health Insurance Provision and Wage Determination

We investigate the effect of employer‐provided health insurance on job mobility rates and economic welfare using a search, matching, and bargaining framework. In our model, health insurance coverage decisions are made in a cooperative manner that recognizes the productivity effects of health insurance as well as its nonpecuniary value to the employee. The resulting equilibrium is one in which not all employment matches are covered by health insurance, wages at jobs providing health insurance are larger (in a stochastic sense) than those at jobs without health insurance, and workers at jobs with health insurance are less likely to leave those jobs, even after conditioning on the wage rate. We estimate the model using the 1996 panel of the Survey of Income and Program Participation, and find that the employer‐provided health insurance system does not lead to any serious inefficiencies in mobility decisions.     

Toward an Effective Design of Behavioral Health Care Delivery: An Empirical Analysis of Care for Depression

A criticism of behavioral health care delivery is that it has largely missed the social determinants of behavioral health disorders and their diagnosis. Toward addressing this criticism, this study evaluates the delivery of behavioral health care as a part of primary care operations. Focusing on the treatment of depression, the study results show that: (i) primary care clinics operating in communities with superior social environment characteristics are associated with improved depression outcomes in the short term, and (ii) psychosocial resources (social and emotional support) and the built environment (man‐made resources and infrastructure to support human activity) of primary care clinics are associated with sustaining the improvement in depression outcome in the long term. Centering our attention on IT‐enabled, evidence‐based, and affordable primary care as mechanisms that can enable the integration of behavioral and medical care delivery, the results suggest that IT‐enabled and evidence‐based primary care are associated with improvements in depression outcomes. We also find that the effect of improving the affordability of behavioral health care delivery depends on the community's socioeconomic status. Primary care clinics in socioeconomically disadvantaged communities practicing cost‐containment are associated with improvements in depression outcomes, and, therefore, can contribute toward reducing disparities in behavioral health care delivery. Counter to our original expectations, we find that the effect of evidence‐based care on improvements on depression outcomes increases as the availability of medically trained behavioral health care specialists practicing in a community increases lending support to concerns that primary care clinics in resource‐rich communities obtain greater benefit from quality improvement interventions.     

COMPETITIVE MARKETS WITH ENDOGENOUS HEALTH RISKS

We study an economy where agents' productivity and labor endowment depend on their health status, and indivisible occupational choices affect individual health distributions. We show that Pareto efficiency requires cross‐transfers across occupations. Moreover, workers with relatively less safe jobs must get positive transfers whenever labor supply is not very reactive to wages, a condition in line with the findings of a large empirical literature. In these instances, compensating wage differentials equalizing the utilities of ex‐ante identical workers in different jobs undermine ex‐ante efficiency. Moreover, competitive equilibria where only assets with deterministic payoffs are traded are not first‐best. Finally, we show that simple transfer schemes, implemented through linear subsidies to health insurance, enhance efficiency.     

Improving Humanitarian Operations through Technology‐Enabled Collaboration

Humanitarian supply chains involve many different entities, such as government, military, private, and non‐governmental organizations and individuals. Well‐coordinated interactions between entities can lead to synergies and improved humanitarian outcomes. Information technology (IT) tools can help facilitate collaboration, but cost and other barriers have limited their use. We document the use of an IT tool to improve last‐mile supply distribution and data management in one of many camps for internally displaced persons after the January 2010 earthquake in Haiti, and we describe other current uses of technology in camp management. Motivated by these examples and the interest among humanitarian organizations in expanding the use of such tools to facilitate coordination, we introduce a cooperative game theory model and explore insights about the conditions under which multi‐agency coordination is feasible and desirable. We also outline an agenda for future research in the area of technology‐enabled collaboration in the humanitarian sector.     

Ambiguity,Learning, and Asset Returns

We propose a novel generalized recursive smooth ambiguity model which permits a three‐way separation among risk aversion, ambiguity aversion, and intertemporal substitution. We apply this utility model to a consumption‐based asset‐pricing model in which consumption and dividends follow hidden Markov regime‐switching processes. Our calibrated model can match the mean equity premium, the mean risk‐free rate, and the volatility of the equity premium observed in the data. In addition, our model can generate a variety of dynamic asset‐pricing phenomena, including the procyclical variation of price–dividend ratios, the countercyclical variation of equity premia and equity volatility, the leverage effect, and the mean reversion of excess returns. The key intuition is that an ambiguity‐averse agent behaves pessimistically by attaching more weight to the pricing kernel in bad times when his continuation values are low.     

Inter‐Organizational Fit,Relationship Management Capability,and Collaborative Performance within a Humanitarian Setting

Donors and governments are increasingly calling for more collaborative relationships between humanitarian organizations (HOs), to improve the efficiency and effectiveness of humanitarian operations by exchanging information, knowledge, and resources. This study examines the relative efficacy of partners' characteristics (i.e., compatibility and resource complementarity) and partners' relationship management capability on collaborative relationships, incorporating mutual trust and reciprocal commitment as two mediator constructs. We use Partial Least Squares to examine the proposed hypotheses using a sample of 191 respondents. Data are collected through a web‐survey of international humanitarian non‐governmental organizations (NGOs) in countries across Africa, Asia, and South America. The results reveal that (i) resource complementarity and relationship management capability are significant factors influencing collaborative performance through their effects on partners' mutual trust and reciprocal commitment, and that (ii) partners' compatibility (i.e., missions, values, and operational methods) does not significantly drive success or failure of collaboration between international NGOs. These results suggest that given the present diversity of HOs' characteristics, the success of collaboration is associated with the partners' level of understanding of each other's objectives, operations, and values, and to the extent to which organizations efficiently communicate and coordinate their joint activities. The managerial implications of the findings are also discussed.     

Preventing and Diagnosing Colorectal Cancer with a Limited Colonoscopy Resource

This paper explores how the capacity of colonoscopy services should be allocated for screening and diagnosis of colorectal cancer to improve health outcomes. Both of these services are important since screening prevents cancer by removing polyps, while diagnosis is required to start treatment for cancer. This paper first presents a basic compartmental model to illustrate the trade‐off between these two analytically. Further, a more realistic population dynamics model with resource constraints is introduced for colorectal cancer screening and analyzed numerically. The best resource allocation decisions are investigated with the objectives of minimizing mortality or incidence rates. We provide a sensitivity analysis with respect to policy and disease‐related parameters. We conclude that to minimize mortality, the capacity should be rationed to ensure that the wait for diagnosis is at reasonable levels. When the relevant performance measure is the incidence rate, screening is allocated more capacity compared to the case with mortality rate measure. We also show that benefits from increasing compliance to screening programs can only be realized if there is sufficient service capacity.     

Information Diffusion among Agents: Implications for Humanitarian Operations

The basis for this article is an information‐processing view of the UN's cluster approach. We use agent‐based modeling and simulations to show that clusters, if properly utilized, encourage better information flow and thus facilitate effective response to disasters. The article intends to turn the attention of the humanitarian community to the importance of sharing information and the role of cluster leads in facilitating humanitarian aid. Our results indicate that if cluster leads act as information hubs, information reaches its target faster, enabling a prompt humanitarian response. In addition, we show that information quality is critical for effective resource utilization—if cluster leads filter information, it moves faster. We also found evidence that the willingness to exchange information plays a larger role in transmitting information than that of an information hub, particularly during later stages of response operations.     

GIFT EXCHANGE AND WORKERS' FAIRNESS CONCERNS: WHEN EQUALITY IS UNFAIR5

We study how different payment modes influence the effectiveness of gift exchange as a contract enforcement device. In particular, we analyze how horizontal fairness concerns affect performance and efficiency in an environment characterized by contractual incompleteness. In our experiment, one principal is matched with two agents. The principal pays equal wages in one treatment and can set individual wages in the other. We find that the use of equal wages elicits substantially lower efforts. This is not caused by monetary incentives per se because under both wage schemes it is profit‐maximizing for agents to exert high efforts. The treatment difference instead seems to be driven by the fact that the norm of equity is violated far more frequently in the equal wage treatment. After having suffered from violations of the equity principle, agents withdraw effort. These findings hold even after controlling for the role of intentions, as we show in a third treatment. Our results suggest that adherence to the norm of equity is a necessary prerequisite for successful establishment of gift‐exchange relations. (JEL: J33, D63, M52, C92, J41)     

考虑异质性行为的灾后应急物资动态调度优化

在以人道主义为本的应急救援活动中，不可忽视被救灾民和施救决策者们异质性行为的影响。一方面，将各灾民因救援物资需求未被及时满足而呈现的差异化心理痛苦度量成经济损失，并纳入应急救援调度的社会成本这一决策目标中；另一方面，在灾后物资调度决策中，关注具有异质性偏好的各应急决策者所展现出的不同救援态度。结合面向联合机会约束规划的动态供需平衡限制，最终构建一个考虑灾民和决策者们异质性行为的多阶段灾后救援物资分配和应急路径优化模型。采用2008年汶川地震为案例背景，应用遗传算法对模型求解和参数分析，将仿真结果与不考虑异质性行为的传统救援调度方案进行比较，得出一些结论为构建高效的应急救援体系提供有益参考。     

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two‐stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user‐defined level to achieve the equity‐efficiency tradeoff in the decision‐making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk‐return tradeoff, equity‐reconstruction expenditures tradeoff, and variation of per‐capita expected earthquake loss in different income classes are also presented.     

Cross‐Training with Imperfect Training Schemes

Cross‐training workers is one of the most efficient ways of achieving flexibility in manufacturing and service systems for increasing responsiveness to demand variability. However, it is generally the case that cross‐trained employees are not as productive on a specific task as employees who were originally trained for that task. Also, the productivity of the cross‐trained workers depends on when they are cross‐trained. In this work, we consider a two‐stage model to analyze the effects of variations in productivity levels on cross‐training policies. We define a new metric called achievable capacity and show that it plays a key role in determining the structure of the problem. If cross‐training can be done in a consistent manner, the achievable capacity is not affected when the training is done, which implies that the cross‐training decisions are independent of the opportunity cost of lost demand and are based on a trade‐off between cross‐training costs at different times. When the productivities of workers trained at different times differ, there is a three‐way trade‐off between cross‐training costs at different times and the opportunity cost of lost demand due to lost achievable capacity. We analyze the effects of variability and show that if the productivity levels of workers trained at different times are consistent, the decision maker is inclined to defer the cross‐training decisions as the variability of demand or productivity levels increases. However, when the productivities of workers trained at different times differ, an increase in the variability may make investing more in cross‐training earlier more preferable.