Stochastic dominance for ranking ventures: Comments and extensions

This paper suggests some extensions to Tilley and Eilon's paper on ranking ventures. Tilley and Eilon consider concave utility functions consisting of two linear segments and this allows all rectangular distributions to be ordered. Such utility functions have a wide scope and allow other distributions to be ordered.     

Successful joint ventures in Science Parks

Technology-based firms are looking for ways of minimizing the increasing risks and costs of developing new products and processes. Acquisition of new technology through a collaborative development is one way which is finding favour. Universities, their associated Science Parks and spinout companies offer opportunities for such partnerships which are growing in importance. The services available by this route to large companies are attracting a substantial international clientele.     

Bottleneck identification and ranking model for mine operations

Abstract

Mining has a long history of production and operations management. Considering the increasing complexity of reserves, declining metal grades, and worldwide price volatilities, mines have to operate more efficiently than ever. In recent years, companies have been adopting innovative solutions and technologies to reduce costs and remain competitive in the global market. Specifically, management of bottlenecks has been in the focus of the manufacturing industry for decades now. The mining industry has made significant advancements in process improvement tools using equipment, human, and asset tracking capabilities. However, to date, there is no holistic approach or system to identify and manage the bottleneck in the entire value chain of mining. This research proposes a new method to identify and rank the bottlenecks in a mine value chain. The method is applied in a coal mine and the results are presented in the case study.     

A data envelopment analysis approach for ranking journals

We create a data envelopment analysis (DEA) model to rank business journals, using data from the Thomson Reuters Journal Citation Reports^® (JCR). As opposed to previous models that ranked journals in only one field and mostly relied on survey data, this model is used to rank 358 business journals from five different JCR categories according to such citation-based factors as the number of articles, the number of citations, impact factor, five-year impact factor, immediacy index, eigenfactor score, and article influence score. We compute relative efficiencies of the journals and thereby create plausible journal rankings that largely, but not completely, corroborate three widely used business publication journal ranking lists. In addition, we show how the different characteristics of the JCR data impact the DEA ranking model. Finally, we identify journals that are not on the business publication lists but consistently perform very well relative to those benchmark journals, and should possibly be included in the business publication ranking lists. We also identify journals whose inclusion in widely used business publication rankings cannot be justified by our methodology.     

Testing for Stochastic Monotonicity

We propose a test of the hypothesis of stochastic monotonicity. This hypothesis is of interest in many applications in economics. Our test is based on the supremum of a rescaled U‐statistic. We show that its asymptotic distribution is Gumbel. The proof is difficult because the approximating Gaussian stochastic process contains both a stationary and a nonstationary part, and so we have to extend existing results that only apply to either one or the other case. We also propose a refinement to the asymptotic approximation that we show works much better in finite samples. We apply our test to the study of intergenerational income mobility.     

中国新兴企业自主创新陷阱突破路径分析

中国新兴企业自身的特点和所处的转型经济的特殊环境,使得自主创新很容易掉入两种陷阱——失败陷阱和成功陷阱.组织学习理论认为这两种陷阱的根源在于割裂了探索式与利用式学习的互补关系.本文以系统动力学为基础,提出突破这两种陷阱的路径:一是通过知识存量、企业特定的不确定性和绩效差距动态结合探索式与利用式学习;二是系统地考虑中国新兴企业两种重要的资源—社会资本和公司企业家精神—对探索式与利用式学习的动态关系产生的影响.并且以两家典型新兴企业新产品开发项目为背景,利用Vensim_PLE Plus软件进行模拟分析,揭示了这条突破路径随时间发展而变化的轨迹,具有重要的理论和实践指导意义.     

Consistent Tests for Stochastic Dominance

Methods are proposed for testing stochastic dominance of any pre–specified order, with primary interest in the distributions of income. We consider consistent tests, that are similar to Kolmogorov–Smirnov tests, of the complete set of restrictions that relate to the various forms of stochastic dominance. For such tests, in the case of tests for stochastic dominance beyond first order, we propose and justify a variety of approaches to inference based on simulation and the bootstrap. We compare these approaches to one another and to alternative approaches based on multiple comparisons in the context of a Monte Carlo experiment and an empirical example.     

Power imbalance and value creation in joint ventures

Joint ventures (JVs) often do not create expected value due to power imbalance between partners. Despite the fact that JV partners are embedded in relational constraints, prior research has largely relied on economic reasoning by focusing on equity ownership difference between JV partners as the main source of power imbalance. We extend prior research to also consider important relational factors represented by repeated ties between partners and network openness, as well as institutional status difference and network status difference as two additional dimensions of power imbalance. Our findings indicate that ownership power imbalance by itself does not have a significant effect on value creation. However, value creation is facilitated when there is ownership power imbalance between partners with more repeated ties. In contrast, value creation may be hindered when JV partners with unequal ownership are embedded in more open interfirm alliance networks. Furthermore, value creation is facilitated if JV partners that have unequal ownership also have network status power imbalance in the same direction.     

Exploiting value system multiplicity and preference voting for robust ranking

Under a data envelopment analysis (DEA) framework, full ranking of a group of decision making units (DMUs) can be carried out through an adequate amalgamation of the cross-efficiency (CE henceforth) scores produced for each DMU. In this paper, we propose a ranking procedure that is based on amalgamating the weight profiles selected over the cross-evaluation rather than related CE scores. The new approach builds, for each DMU, a collective weight profile (CWP henceforth) by exploiting the preference voting system embedded within the matrix of weights, which views the assessing DMUs as voters and the input/output factors as candidates. The occurrence of zero votes is discussed as a special case and a two-level aggregation procedure is developed. The CWPs that are produced extend the concept of collective appreciation to the input/output factors of each DMU so that group dynamics is truly reflected, mainly in decision making circumstances where factor prioritization is necessary for making choices or allocating resources. The robustness of the proposed ranking approach is evaluated with three examples drawn from the literature.     

Strategic management: New ventures and small business

This paper examines the factors influencing the formulation and implementation of strategy in new and small firms. Small businesses vary substantially in their resource positions, the goals of their founders and their potential. They also vary in stage of development: thus strategic management is examined separately in the start-up stage, the early-growth stage, and the later-growth stage. Intracorporate entrepreneurship in established firms is also considered. Despite this diversity, small firms create an environment for strategic management in which both the opportunities and constraints are different from those in large organizations.     

An effective total ranking model for a ranked voting system

In this paper an effective model to rank candidates in a preferential election is proposed. It is an extension and simplified form of a recently proposed model for ranking efficient candidates. The model consists of fewer constraints and can be used for ranking inefficient as well as efficient candidates. Some techniques are introduced to decrease the complexity of the proposed model by obtaining some of the results by inspection.     

股票组织的套期保值策略研究

本文从两个角度研究了股票组合的套期保值问题,提出了两种股票组合的套期保值方案,并对这两种方案进行了分析和比较研究。     

From gain-sharing to gain-generation: The quest for distributive justice in international joint ventures

This research investigates how distributive justice (DJ) affects cooperation-related outcomes in international joint ventures (IJVs) through several routes that intersect with reciprocal commitment, organizational attachment and contractual specification. Grounded in the convergent insights of IJV theory and justice theory, this study argues that DJ improves IJV performance through enhanced mutual commitment and interparty attachment, as well as through DJ's complementary role with IJV contract. The findings extend previous research by demonstrating that (1) DJ is an important variable affecting IJV stability via the mediation of interorganizational attachment and (2) DJ and IJV contract function as complements rather than substitutes in governing cooperation and improving IJV profitability and stability.     

Probabilistic dominance criteria for comparing uncertain alternatives: A tutorial

This paper is a tutorial which demonstrates the current state-of-the-art methods for incorporating risk into project selection decision making. The projects under consideration might be R&D, IT, or other capital expenditure programs. We will show six decision making methods: 1. mean-variance (MV), 2. mean-semivariance, 3. mean-critical probability, 4. stochastic dominance, 5. almost stochastic dominance (ASD), and 6. mean-Gini. We will also describe the assumptions about the risk attitudes of the decision maker which are associated with each of the techniques. While all these methods have been previously applied elsewhere, this is the first paper which shows all of their applications in the project selection context, together with their interrelationships, strengths and weaknesses. We have applied all six techniques to the same group of five hypothetical projects and evaluated the resulting nondominated sets. Among the methods reviewed here, stochastic dominance is recommended because it requires the least restrictive assumptions. ASD and mean-Gini are recommended when stochastic dominance is not practical or when it does not yield definitive choices. MV, mean-semivariance, and mean-critical probability are shown to be flawed.     

Revised antitrust guidelines. Forming physician network joint ventures

What do physician executives need to know about antitrust guidelines? This article presents an overview of the revised "Statements of Antitrust Enforcement Policy in the Health Care Area," released in late 1996. Antitrust concepts and implicated federal statutes are described, and implications for forming physician network joint ventures are explored. Requirements of the revised standards used by the agencies to determine a permissible integration are addressed, as well as the factors considered in antitrust scrutiny of physician ventures.     

A multi-criteria ranking algorithm (MCRA) for determining breast cancer therapy

Breast cancer is the leading cause of cancer deaths among women. The selection of an effective, patient-specific treatment plan for breast cancer has been a challenge for physicians because the decision process involves a vast number of treatment alternatives as well as treatment decision criteria, such as the stage of the cancer (e.g., in situ, invasive, metastasis), tumor characteristics, biomarker-related risks, and patient-related risks. Furthermore, every patient's case is unique, requiring a patient-specific treatment plan, while there is no standard procedure even for a particular stage of the breast cancer. In this paper, we first determine a comprehensive set of criteria for selecting the best breast cancer therapy by interviewing medical oncologists and reviewing the literature. We then present two analytical hierarchy process (AHP) models for quantifying the weights of criteria for breast cancer treatment in two sequential steps: primary and secondary treatment therapy. Using the weights of criteria from the AHP model, we propose a new multi-criteria ranking algorithm (MCRA), which evaluates a large variety of patient scenarios and provides the best patient-tailored breast cancer treatment alternatives based on the input of nine medical oncologists. We then validate the predictions of the multi-criteria ranking algorithm by comparing treatment ranks of the algorithm with ranks of five different oncologists, and show that algorithm rankings match or are statistically significantly correlated with the overall expert ranking in most cases. Our multi-criteria ranking algorithm could be used as an accessible decision-support tool to aid oncologists and educate patients for determining appropriate and effective treatment alternatives for breast cancer. Our approach is also general in the sense that it could be adapted to solve other complex decision-making problems in medicine, healthcare, as well as other service and manufacturing industries.     

Accuracy of Simulations for Stochastic Dynamic Models

This paper is concerned with accuracy properties of simulations of approximate solutions for stochastic dynamic models. Our analysis rests upon a continuity property of invariant distributions and a generalized law of large numbers. We then show that the statistics generated by any sufficiently good numerical approximation are arbitrarily close to the set of expected values of the model's invariant distributions. Also, under a contractivity condition on the dynamics, we establish error bounds. These results are of further interest for the comparative study of stationary solutions and the estimation of structural dynamic models.