Do mergers improve hospital productivity?

This paper complements the existing literature on hospital mergers by using data envelopment analysis (DEA) to generate both efficiency and productivity measures to ascertain whether hospital mergers, at least in the short run, result in performance gains. Using data over the period 1996–1998, we apply DEA, both pre-merger and post-merger, to set of hospitals that merged in 1997 as well as to a matching control group of non-merging hospitals over the same timeframe. A comparison of DEA efficiency scores and the Malmquist index values across the case and control hospitals allow us to assess whether any increase in productivity is the result of a merger rather than simply and randomly adding two hospitals' inputs and outputs together.     

Analyzing linear mergers

Mergers are functions that transform k (possibly dependent) random sources (distributions) into a single random source, in a way that ensures that if one of the input sources has min‐entropy rate δ then the output has min‐entropy rate close to δ. Mergers have proven to be a very useful tool in explicit constructions of extractors and condensers, and are also interesting objects in their own right. In this work we give a refined analysis of the merger constructed by [Raz, STOC'05] (based on [Lu, Reingold, Vadhan, and Wigderson, STOC'03 pp. 602–611, 2003]). Our analysis uses min‐entropy instead of Shannon's entropy to derive tighter results than the ones obtained in [Raz STOC'05]. We show that for every constant r and k it is possible to construct a merger that takes as input k strings of length n bits each, and outputs a string of length n/r bits, such that if one of the input sources has min‐entropy b, the output will be close to having min‐entropy b/(r + 1). This merger uses a constant number of additional uniform bits. One advantage of our analysis is that b (the min‐entropy of the “good” source) can be as small as a constant (this constant depends on r and k), while in the analysis given in [Raz STOC'05], b is required to be linear in n. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2008     

Formulation and analysis of horizontal mergers among oligopolistic firms with insights into the merger paradox: a supply chain network perspective

In this paper, we consider oligopolistic firms with supply chain networks who are involved in the production, storage, and distribution of a homogeneous product to demand markets and explore what has become known in the literature as the “merger paradox.” We present the oligopolistic supply chain network equilibrium model associated with the competing firms before the horizontal mergers and also develop the supply chain network optimization model post the complete merger. In addition, we develop the model in which only a subset of the firms in the industry merge. The governing concept of the competing firms is that of Cournot–Nash equilibrium. We utilize finite-dimensional variational inequality theory for the formulation, analysis, and solution of both the pre and the post-merger supply chain network problems. We provide numerical examples for which we compute the total costs, the total revenues, as well as the profits obtained for the firms pre and post the mergers for a variety of distinct oligopoly problems. The generality of the network models and the flexibility of the computational approach, which yields closed form expressions for the product flows at each iteration, allows us to obtain deeper insights into the merger paradox.     

A stochastic service network model with application to hospital facilities

This paper presents a methodology for estimating expected utilization and service level for a class of capacity constrained service network facilities operating in a stochastic environment. A semi-Markov process describes the flows of customers (patients) through a network of service units. We model the case where one of the units has finite capacity and no queues are allowed to form. We show that the expected level of utilization and service can be computed from a simple linear relationship based on (a) the equilibrium arrival rates at each unit which are associated with the case of infinite capacity, (b) mean holding times for each unit, and (c) the probability that the finite capacity unit is at full capacity. We use Erlang's loss formula to calculate the probability of full capacity, show this calculation to be exact for two cases, and recommend its use as an approximation in the general case. We test the accuracy of the approximation on a set of published data. In the discussion, we present a technique for analyzing collected patient flow data using the results of this methodology.     

Superior mesh quality with automatic node mergers

Automatic surface :meshers have been designed with the intent to eliminate the manual effort involved in creating a finite element model. Naturally, the quality of the mesh must be such that the solver will yield accurate results. For geometries having boundaries with short edges relative to the rest of the geometry, the existing meshers yield poor-quality meshes. Hence, the stress analyst must manually attain reasonable mesh quality. This manual effort is very tedious and time consuming. Mesh quality improvement techniques such as smoothing, fail to improve the mesh quality. In this work, a new technique is introduced, which improves the initial boundary node loop quality, and in turn yields high-quality meshes. Examples show marked improvement in quality, and the meshes are comprised of fewer elements.     

Earnouts in mergers and acquisitions: A game-theoretic option pricing approach

This paper presents a valuation approach for merger and acquisition (M&A) deals employing contingent earnouts. It is argued that these transactions have option-like features, and the paper uses a game-theoretic option approach to model the value of such claims. More specifically, the paper examines the impact of uncertainty on the optimal timing of M&A using earnouts, and it also investigates the impact of uncertainty on the terms of the earnout. Optimal earnout and initial payment combinations are endogenously derived from the model, and testable hypotheses are developed. The theoretical contribution of this paper is a dynamic decision-making model of the invest-to-learn option generated upon investment in an acquisition. The paper also offers practical implications for the design of acquisitions employing earnouts.     

Industry structural inefficiency and potential gains from mergers and break-ups: A comprehensive approach

An efficiency indicator of industry configuration (allowing for entry/exit of firms) is presented which accounts for four sources components: (1) size inefficiencies arising from firms which can be conveniently split into smaller units; (2) efficiency gains realized through merger of firms; (3) re-allocation of inputs and outputs among firms; (4) technical inefficiencies. The indicator and its components are computed using linear and mixed-integer programming (data envelopment analysis models). A method to monitor the evolution of these components in time is introduced. Data on hospitals in Australia show that technical inefficiency of hospitals accounts for less than 15% of total industry inefficiency, with 40% attributable to size inefficiencies and the rest to potential mergers and re-allocation effects.     

Hybrid biobjective evolutionary algorithms for the design of a hospital waste management network

Colombian environmental authorities are exploring new alternatives for improving the disposal of hospital waste generated in the Department of Boyacá (Colombia). To design this hospital waste management network we propose a biobjective obnoxious facility location problem (BOOFLP) that deals with the existing tradeoff between a low-cost operating network and the negative effect on the population living near the waste management facilities. To solve the BOOFLP we propose a hybrid approach that combines a multiobjective evolutionary algorithm (NSGA II) with a mixed-integer program. The algorithms are compared against the Noninferior Set Estimation (NISE) method and tested on data from Boyacá’s hospital waste management network and publicly available instances.     

Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model

This paper develops a novel two-stage cost efficiency model to estimate and decompose the potential gains from Mergers and Acquisitions (M&As). In this model, a hypothetical DMU is defined as a combination of two or more candidate DMUs. The hypothetical DMU would surpass the traditional Production Possibility Set (PPS). In order to solve the problem, a Merger Production Possibility Set (PPS_M) is constructed. The model minimizes the total cost of the hypothetical DMU while maintaining its outputs at the current level, and estimates the overall merger efficiency by comparing its minimal total cost with its actual cost. Moreover, the overall merger efficiency could be decomposed into technical efficiency, harmony efficiency, and scale efficiency. We show that the model can be extended to a two-stage structure and these efficiencies can be decomposed to both sub-systems. To show the usefulness of the proposed approach, we applied it to a real dataset of top 20 most competitive Chinese City Commercial Banks (CCBs). We concluded that (1) there exist considerably potential gains for the proposed merged banks. (2) It is also shown that the main impact on potential merger gains are from technical and harmony efficiency. (3) As an interesting result we found that the scale effect works against the merger, indicating that it is not favorable for a full-scale merger.     

Estimation of potential gains from mergers in multiple periods: a comparison of stochastic frontier analysis and Data Envelopment Analysis

A new dynamic Data Envelopment Analysis (DEA) approach is created to provide valuable managerial insights when assessing the merger performance. This new approach allows us to dynamically evaluate the pre-merger firms and the post-merger firm in a multi-period situation. A case study of bank branch merger is conducted to illustrate and validate the proposed approach. Both stochastic frontier analysis and data envelopment analysis are used and compared leading to highly correlated results. The computation show that merger results in an overall efficiency achievement in a banking industry.     

Multiterminal network flows and applications

The paper discusses the ways to use the condensation technique of Gomory/Hu in the case of non-symmetric networks. Sufficient conditions to get the value of a maximal flow as row resp. column sum of the capacity matrix are derived. Procedures to determine the cut with minimal capacity are developed and applications of the minimal cut technique to problems of optimal sequencing are given.

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Zusammenfassung Das Papier diskutiert die Möglichkeiten, die Kondensationstechnik von Gomory/Hu auf den Fall unsymmetrischer Netzwerke zu übertragen. Es werden hinreichende Bedingungen dafür abgeleitet, daß der Wert eines maximalen Flusses mit der Zeilenbzw. Spaltensumme der Kapazitätsmatrix übereinstimmt. Es werden Verfahren entwickelt, den Schnitt minimaler Kapazität zu bestimmen. Anwendungen der minimalen Schnitt-Technik auf Probleme der optimalen Reihenfolge werden vorgestellt.

     

不完全信息下考虑效率和规模的多时点并购决策

针对企业并购过程中存在不完全信息和多时点信息的问题,提出了一种考虑效率和规模的企业并购决策方法. 通过证据推理集结并购双方的不完全的、多时点的评价信息,利用\,DEA\,方法判断合并企业规模是否过大,并筛选出可行并购方案,再根据合并企业竞争型并购交叉效率高低决策最佳并购目标. 最后算例分析说明了方法的有效性和实用性.     

General network design: A unified view of combined location and network design problems

This paper presents a unified framework for the general network design problem which encompasses several classical problems involving combined location and network design decisions. In some of these problems the service demand relates users and facilities, whereas in other cases the service demand relates pairs of users between them, and facilities are used to consolidate and re-route flows between users. Problems of this type arise in the design of transportation and telecommunication systems and include well-known problems such as location-network design problems, hub location problems, extensive facility location problems, tree-star location problems and cycle-star location problems, among others. Relevant modeling aspects, alternative formulations and possible algorithmic strategies are presented and analyzed.     

A unified network performance measure with importance identification and the ranking of network components

In this paper, we propose the first network performance measure that can be used to assess the efficiency of a network in the case of either fixed or elastic demands. Such a measure is needed for many different applications since only when the performance of a network can be quantifiably measured can the network be appropriately managed. Moreover, as we demonstrate, the proposed performance measure, which captures flow information and behavior, allows one to determine the criticality of various nodes (as well as links) through the identification of their importance and ranking. We present specific networks for which the performance/efficiency is computed along with the importance rankings of the nodes and links. The new measure can be applied to transportation networks, supply chains, financial networks, electric power generation and distribution networks as well as to the Internet and can be used to assess the vulnerability of a network to disruptions.     

Classes of network connectivity and dynamics

Many kinds of complex systems exhibit characteristic patterns of temporal correlations that emerge as the result of functional interactions within a structured network. One such complex system is the brain, composed of numerous neuronal units linked by synaptic connections. The activity of these neuronal units gives rise to dynamic states that are characterized by specific patterns of neuronal activation and co‐activation. These patterns, called functional connectivity, are possible neural correlates of perceptual and cognitive processes. Which functional connectivity patterns arise depends on the anatomical structure of the underlying network, which in turn is modified by a broad range of activity‐dependent processes. Given this intricate relationship between structure and function, the question of how patterns of anatomical connectivity constrain or determine dynamical patterns is of considerable theoretical importance. The present study develops computational tools to analyze networks in terms of their structure and dynamics. We identify different classes of network, including networks that are characterized by high complexity. These highly complex networks have distinct structural characteristics such as clustered connectivity and short wiring length similar to those of large‐scale networks of the cerebral cortex. © 2002 Wiley Periodicals, Inc.     

Entropy maximisation and queueing network models

Over recent years it has become increasingly evident that classical queueing theory cannot easily handle complex queueing systems and networks with many interacting elements. As a consequence, alternative ideas and tools, analogous to those applied in the field of Statistical Mechanics, have been proposed in the literature. In this context, the principles of Maximum Entropy (ME) and Minimum Relative Entropy (MRE), a generalisation, provide consistent methods of inference for characterising the form of an unknown but true probability distribution, based on information expressed in terms of known to exist true expected values or when, in addition, there exists a prior estimate of the unknown distribution. This paper traces the progress achieved so far towards the creation of ME and MRE product-form approximations and related algorithms for the performance analysis of general Queueing Network Models (QNMs) and indicates potential research extensions in the area.Earlier research on entropy maximisation and QNMs was sponsored by the UK Science and Engineering Research Council (SERC) with grant GR/D/12422, while recent and current work is supported by SERC grants GR/F/29271 and GR/H/18609. Research on Complex I/O subsystems was funded by Metron Technology Ltd., UK, under grant JJCA415.     

Congestion network problems and related games

This paper analyzes network problems with congestion effects from a cooperative game theoretic perspective. It is shown that for network problems with convex congestion costs, the corresponding games have a non-empty core. If congestion costs are concave, then the corresponding game has not necessarily core elements, but it is derived that, contrary to the convex congestion situation, there always exist optimal tree networks. Extensions of these results to a class of relaxed network problems and associated games are derived.     

Robust discrete optimization and network flows

We propose an approach to address data uncertainty for discrete optimization and network flow problems that allows controlling the degree of conservatism of the solution, and is computationally tractable both practically and theoretically. In particular, when both the cost coefficients and the data in the constraints of an integer programming problem are subject to uncertainty, we propose a robust integer programming problem of moderately larger size that allows controlling the degree of conservatism of the solution in terms of probabilistic bounds on constraint violation. When only the cost coefficients are subject to uncertainty and the problem is a 0–1 discrete optimization problem on n variables, then we solve the robust counterpart by solving at most n+1 instances of the original problem. Thus, the robust counterpart of a polynomially solvable 0–1 discrete optimization problem remains polynomially solvable. In particular, robust matching, spanning tree, shortest path, matroid intersection, etc. are polynomially solvable. We also show that the robust counterpart of an NP-hard -approximable 0–1 discrete optimization problem, remains -approximable. Finally, we propose an algorithm for robust network flows that solves the robust counterpart by solving a polynomial number of nominal minimum cost flow problems in a modified network. The research of the author was partially supported by the Singapore-MIT alliance.The research of the author is supported by a graduate scholarship from the National University of Singapore.Mathematics Subject Classification (2000): 90C10, 90C15