Mean shift and influence measures in linear measurement error models with stochastic linear restrictions

We present influence diagnostics for linear measurement error models with stochastic linear restrictions using the corrected likelihood of Nakamura in 1990. The case deletion and mean shift outlier models are developed to identify outlying and influential observations. We derive a corrected score test statistic for outlier detection based on mean shift outlier models. The analogs of Cook's distance and likelihood distance are proposed to determine influential observations based on case deletion models. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics and a simulation study has been used to evaluate the performance of the proposed estimators based on the mean squares error criterion and the score test statistic. Finally, a numerical example is given to illustrate the theoretical results.     

贵州社会管理创新:经验、问题与出路

近年来,贵州社会管理创新取得了一些成效,其主要经验是强化中国共产党在社会管理创新中的领导地位,发挥政府在社会管理创新中的主导作用,创新内容要关注民生。尽管如此,贵州社会管理创新还存在社会矛盾化解机制不健全、基层政府社会管理力量薄弱、社会组织培育机制不健全等问题,应通过完善源头治理机制、改革基层社会管理体制、优化社会组织培育机制等途径来解决。     

The recruitment and selection of hospital medical consultants

Abstract

The literature on selection has been dominated in recent decades by the ‘prediction’ paradigm. Such an approach requires a substantial number of positions to be filled in order to compute validity coefficients. There are other approaches, using a different paradigm, when concentrated on adjusting the organization and the employee. Here careful analysis of job demands is essential. This article describes such an analysis, taking the medical consultant as an example. The method can be used in an iterative way. It is useful when one has to work with small numbers of positions.     

图书馆的知识管理与可持续发展策略

新世纪图书馆具有与过去迥然不同的特征,在知识经济的背景下,图书馆要拓展发展空间,实现可持续发展,就必须与时俱进,积极实施知识管理,不断提高知识创新和知识服务能力。本文从管理观念创新、管理模式创新、管理体制创新、管理内容创新四个方面论述了知识经济时代图书馆管理创新的重要性。并阐述了图书馆可持续发展的重要性及实现图书馆可持续发展的具体措施。     

An Examination of How Supervisors Influence Their Subordinates to Engage in Environmental Behaviors

Employee engagement in environmental behaviors is an important topic in operations management. Drawing upon stakeholder, commitment, and organizational support theories, this study creates and tests an empirical model of how store managers (i.e., supervisors) influence their direct reports (i.e., subordinates) to become engaged in environmental behaviors. Based on a dataset derived from supervisors and their subordinates who are employed at the same grocery store location across a large retail grocery chain, we test our study's nomological model and find support for the linkages proposed. Key research and managerial implications are discussed.     

Keep Your Friends Close? Supply Chain Design and Disruption Risk

In this article, we evaluate the relationship between supply chain design decisions and supply chain disruption risk. We explore two supply chain design strategies: (i) the dispersion of supply chain partners to reduce supply chain disruption risk versus (ii) the co‐location of supply chain partners to reduce supply chain disruption risk. In addition, we assess supply chain disruption risk from three perspectives: the inbound material flow from the supplier (supply side), the internal production processes (internal), and the outbound material flow to the customer (customer side) as a disruption can occur at any of these locations. We measure disruption risk in terms of stoppages in flows, reductions in flow, close calls (disruptions that were prevented at the last minute), disruption duration (time until normal operation flow was restored), and the spread of disruptions all the way through the supply chain. We use seemingly unrelated regression (SUR) to analyze our data, finding that lead times, especially supply side lead times, are significantly associated with higher levels of supply chain disruption risk. We find co‐location with suppliers appears to have beneficial effects to the reduction of disruption duration, and, overall supply side factors have a higher impact when it comes to supply chain disruption risk than comparable customer side factors.     

A Business Model Innovation Typology

An effective business model is the core enabler of any company's performance. Business model innovation is not only becoming more and more important due to increasing and globalizing competition, but also an enormous challenge, both theoretically and practically. Although many managers are eager to consider more disruptive changes to their business model, they often do not know how to articulate their existing or desired business model and, even less so, understand the possibilities for innovating it. One of the steps toward developing more theoretical insight and practical guidelines is the identification of types and the development of a typology of business model innovations. Ten retrospective case studies of business model innovations undertaken by two industrial companies provide the empirical basis for this article. We analyzed the characteristics of these innovations as well as their success rates. The findings suggest that there are indeed various business model innovation types, each with its own characteristics and challenges.     

Optimal Digital Rights Management with Uncertain Piracy

Many firms that sell digital copies of copyrighted materials online face a common dilemma: the use of digital rights management (DRM) to impede pirates can impose restrictions on legitimate use. We introduce a two‐period model in which the use of DRM in the first period affects the probability that a consumer finds a pirated copy in the second period; the threat of legal action reduces consumers’ consumption of pirated copies; and firms choose whether to sell, and at what prices, either strongly or weakly DRM‐protected products, or both. Furthermore, we incorporate the role of uncertainty concerning future levels of piracy. Using a two‐period model with uncertainty, we investigate a firm's optimal DRM strategies and present the optimal pricing strategy as well as product launch strategy under different market conditions. We find that one important characteristic of the optimal strategy is that it is optimal to maintain the same product line configuration strategy for both periods. We also characterize the conditions under which each strategy is optimal.     

A COMPARISON OF SEQUENCING RULES FOR A TWO-STATE HYBRID FLOW SHOP

A common manufacturing environment in many industries (such as the glass, steel, paper, costume jewelry, and textile industries) is a hybrid flow shop. This system has continuous-process machinery in the fist state of manufacturing and repetitive-batch equipment in the second. Little research has investigated this type system. Scheduling managers of hybrid flow shops tend either to use existing job-shop rules or to devise their own rules. These approaches often are less than adequate for efficient scheduling. In this paper we extend the rule presented by Narasimhan and Panwalker [4] to include a general class of hybrid flow shops. This extenstion, called the generalized cumulative minimum-deviation (GCMD) rule, is compared under various operation conditions to three other sequencing rules: shortest processing time, longest processing time, and minimum deviation. The operating conditions are determined by the number of machines at both stages. The results of 7200 simulation runs demonstrate that the GCMD rule is better than the other rules in minimizing each of five chosen criteria. Thus, the GCMD rule can help managers to schedule hybrid flow shops efficiently to achieve various corporate objectives.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.