计量经济分析 = Econometric analysis

What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

: Projected growth in spending on the federal government's big health and retirement programs -Medicare, Medicaid, and Social Security dominates the long-run budget outlook. If current policies continue, that spending is likely to grow significantly faster than the economy as a whole over the next few decades. By 2040, the Congressional Budget Office (CBO) projects those outlays will rise to about 17 percent of gross domestic product (GDP)-more than double their current share. The expected surge in health and retirement spending stems from three fundamental factors. First, the large baby-boom generation will begin to reach retirement age within the next decade or so and become eligible to receive benefits from Social Security and Medicare. Second, people are likely to live longer than they did in the past and spend more time in retirement. Third, advances in medical technology will probably keep pushing up the cost of providing health care. The demographic changes projected over the coming decades will significantly increase the number of retirees per worker in the labor force and affect both sides of the federal government's budgetary ledger. In 1960, 5.1 workers supported each beneficiary in the Social Security program; today, the ratio is about 3.4 to 1, and in 2040, it is projected to fall to just 2.1 workers per beneficiary. As a result, the growth of federal outlays for Social Security and Medicare will climb rapidly, whereas the growth of revenues from payroll taxes (which largely finance those programs now) will slow.

The Long-Term Budget Outlook

In this day, in the age of big data, consumers leave an easily traceable digital footprint whenever they visit a website online. Firms are interested in capturing the digital footprints of their consumers to understand and predict consumer behavior. This study deals with how big data analytics has been used in the domains of information systems, operations management, and healthcare . We also discuss the future potential of big data applications in these domains (especially in the areas of cloud computing, Internet of Things and smart city, predictive manufacturing and 3‐D printing, and smart healthcare) and the associated challenges. In this study, we present a framework for applications of big data in these domains with the goal of providing some interesting directions for future research.

Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap

This chapter contains sections titled: 2.1 Introduction, 2.2 Agent Communications, 2.3 Agent Interaction Protocols, 2.4 Societies of Agents, 2.5 Conclusions, 2.6 Exercises, 2.7 References

Multiagent Systems and Societies of Agents

Health Information Exchanges HIE are becoming integral parts of the national healthcare reform efforts, chiefly because of their potential impact on cost reduction and quality enhancement in healthcare services. However, the potential of an HIE platform can only be realized when its multiple constituent users actively participate in using its variety of services. In this research, we model HIE systems as multisided platforms that incorporate self-service technologies whose value to the users depends on both user-specific and network-specific factors. We develop a model of adoption, use, and involvement of clinical practices in the coproduction of the HIE services. This model is grounded in social network theory, service operations theory, and institutional isomorphism theory. A longitudinal study of actual adoption and use behaviors of 2,054 physicians within 430 community medical practices in Western New York over a three-year period has been carried out to evaluate the proposed model. This study has been supported by HEALTHeLINK, the Regional Health Information Organization of Western New York, which has an extensive database comprising over half a million transactions on patient records by the HIE users. We extracted panel data on adoption, use, and service coproduction behaviors from this database and carried out a detailed analysis using metrics derived from the foundational theories. Positioning practices within two distinct but interrelated networks of patients and practitioners, we show that adoption, use, and service coproduction behaviors are influenced by the topographies of the two networks, isomorphic effects of large practices on the smaller ones, and practice labor inputs in HIE use. Our findings provide a comprehensive view of the drivers of HIE adoption and use at the level of medical practices. These results have implications for marketing and revenue management of HIE platforms, as well as public health and national/regional healthcare policy making.

Health Information Exchange as a Multisided Platform: Adoption, Usage, and Practice Involvement in Service Co-Production

The importance of the Healthcare Information Exchange (HIE) in increasing healthcare quality and reducing risks and costs has led to greater interest in identifying factors that enhance adoption and meaningful use of HIE by healthcare providers. In this research we study the interlinked network effects between two different groups of physicians -- primary care physicians and specialists -- as significant factors in increasing the growth of each group in an exchange. An analytical model of interlinked and intragroup influences on adoption is developed using the Bass diffusion model as a basis. Adoption data on 1,060 different primary and secondary care physicians over 32 consecutive months was used to test the model. The results indicate not only the presence of interlinked effects, but also that their influence is stronger than that of the intragroup. Further, the influence of primary care physicians on specialists is stronger than that of specialists on primary care physicians. We also provide statistical evidence that the new model performs better than the conventional Bass model, and the assumptions of diffusion symmetry in the market are statistically valid. Together, the findings provide important guidelines on triggers that enhance the overall growth of HIE and potential marketing strategies for HIE services.

Network Effects in Health Information Exchange Growth

With the rapid growth of rich-media content over the Internet, content and service providers (SP) are increasingly facing the problem of managing their service resources cost-effectively while ensuring a high quality of service (QoS) delivery at the same time. In this research we conceptualize and model an Internet-based storage provisioning network for rich-media content delivery. This is modeled as a capacity provision network (CPN) where participants possess service infrastructures and leverage their topographies to effectively serve specific customer segments. A CPN is a network of SPs coordinated through an allocation hub. We first develop the notion of discounted QoS capabilities of storage resources. We then investigate the stability of the discount factors over time and the network topography using a test-bed on the Internet through a longitudinal empirical study. Finally, we develop a market maker mechanism for optimal multilateral allocation and surplus sharing in a network. The proposed CPN is closely tied to two fundamental properties of Internet service technology: positive network externality among cooperating SPs and the property of effective multiplication of capacity allocation among several distributed service sites. We show that there exist significant incentives for SPs to engage in cooperative allocation and surplus sharing. We further demonstrate that intermediation can enhance the allocation effectiveness and that the opportunity to allocation and surplus sharing can play an important role in infrastructure planning. In conclusion, this study demonstrates the practical business viability of a cooperative CPN market.

Capacity Provision Networks: Foundations of Markets for Sharable Resources in Distributed Computational Economies

Availability, as a part of Service Level Agreement (SLA), is a critically important issue in cloud services, as an application may not be able to run after certain server or network failures. Cloud service providers seek to not only fulfill the SLA, but also simultaneously minimize their operating costs, which are dominated by the energy consumption. In order to minimize the impact of a server/switch failure inside the datacenter on a single application, one would like to spread out the Virtual Machines (VM) for the application across different racks. However, in doing so, the power consumption may increase significantly. In this paper, we develop a variance-based metric to measure the risk of violating the availability requirement. We then propose two heuristic algorithms to place VMs in online and offline manners, respectively. These algorithms aim to strike a balance between minimizing the risk of violating the availability requirement and minimizing the energy, in order to reduce the overall cost.

Availability-aware energy-efficient virtual machine placement

The Internet infrastructure is increasingly utilized for the provision and delivery of a variety of services. The rapid growth and substantial demand fluctuations of the supported services are placing strain on the service providers to effectively manage their infrastructure resources. Capacity Provision Network (CPN) is a market-driven mechanism that enables the service providers to efficiently allocate, share and trade service capabilities. Central to the operation of CPN is the notion of discounted capacities which capture the underlying topology of the Internet. It serves as a practical instrument for service providers to evaluate the utility of capacity services available at remote sites vis-a-vis the capacities available locally and from the content providers. We conducted an Internet based longitudinal field experiment to empirically assess and validate the critical properties of discount factors. Our analysis reveals that discount factors exhibit markedly lower volatility than network delays, and are more stable over seasonal and temporal trend patterns. The results related to size effects suggest that sharing and trade agreements with larger content can be particularly effective. Our finding on the existence of the concavity property points to the ability of intermediation services to enhance the overall gains from resource sharing arrangements.

Anna Ye Du

Papers

Health Information Exchange as a Multisided Platform: Adoption, Usage, and Practice Involvement in Service Co-Production

Network Effects in Health Information Exchange Growth

Capacity Provision Networks: Foundations of Markets for Sharable Resources in Distributed Computational Economies

Availability-aware energy-efficient virtual machine placement

Topographically discounted Internet infrastructure resources: a panel study and econometric analysis