Stochastic efficiency analysis with a reliability consideration

Stochastic Data Envelopment Analysis (DEA) models have been introduced in the literature to assess the performance of operating entities with random input and output data. A stochastic DEA model with a reliability constraint is proposed in this study that maximizes the lower bound of an entity׳s efficiency score with some pre-selected probability. We define the concept of stochastic efficiency and develop a solution procedure. The economic interpretations of the stochastic efficiency index are presented when the inputs and outputs of each entity follow a multivariate joint normal distribution.     

Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment

This article presents the development of a conceptual framework which aims to assess Decision Making Units (DMUs) from multiple perspectives. The proposed conceptual framework combines the Balanced Scorecard (BSC) method with the non-parametric technique known as Data Envelopment Analysis (DEA) by using various interconnected models which try to encapsulate four perspectives of performance (financial, customers, internal processes, learning and growth).The practical relevance of the conceptual model has been tested by using it to assess the performance of DMUs in a multinational company which operates in two business areas. Various models were developed with the collaboration of the directors of the company in order to conceive an appropriate and consensual framework, which may provide useful information for the company. The application of the conceptual framework provides structured information regarding the performance of each DMU (from multiple perspectives) and ways to improve it. By integrating the BSC and the DEA approaches this research helps to identify where there is room for improving organisational performance and points out opportunities for reciprocal learning between DMUs. In doing so, this article provides a set of recommendations relating to the successful application of DEA and its integration with the BSC, in order to promote a continuous learning process and to bring about improvements in performance.     

A network DEA approach for series multi-stage processes

We present in this paper a general network DEA approach to deal with efficiency assessments in multi-stage processes. Our approach complies with the composition paradigm, where the efficiencies of the stages are estimated first and the overall efficiency of the system is obtained ex post. We use multi-objective programming as modeling framework. This provides us the means to assess unique and unbiased efficiency scores and, if required, to drive the efficiency assessments effectively in line with specific priorities given to the stages. A direct comparison with the multiplicative decomposition approach on data drawn from the literature brings into light the advantages of our method and some critical points that one should be concerned about when using the multiplicative efficiency decomposition.     

Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling

National policy initiatives require the expenditure of large amounts of resources over several years. It is common for these initiatives to generate large amounts of data that are needed in order to assess their success. Educational policies are an obvious example. Here we concentrate on Mexico׳s “Educational Modernisation Programme” and try to see how this plan has affected efficiency in teaching and research at Mexico׳s universities. We use a combined approach that includes traditional ratios together with Data Envelopment Analysis models. This mixture allows us to assess changes in efficiency at each individual university and explore if these changes are related to teaching, to research, or to both. Using official statistics for 55 universities over a six year period (2007–2012), we have generated 12 ratios and estimated 21 DEA models under different definitions of efficiency. In order to make the results of the analysis accessible to the non-specialist we use models that visualise the main characteristics of the data, in particular scaling models of multivariate statistical analysis. Scaling models highlight the important aspects of the information contained in the data. Because the data is three-way (variables, universities, and years) we have chosen the Individual Differences Scaling model of Carroll and Chang. We complete the paper with a discussion of efficiency evolution in three universities.     

科技类评审中项目选择的两阶段综合集成方法

科技类评审中,如何合理地选择出若干优秀项目加以资助或激励至关重要。本文研究了科技类评审中的项目选择问题,指出在目前通行的两阶段评议法中存在通讯评议阶段的决策信息不能有效传递到会议评议阶段的情况,应采用适当的方法将两个阶段专家给出的评价信息进行综合处理,以得到更为合理的项目评审结果,进而给出了两阶段综合集成的框架与具体方法。算例表明,可以更充分的利用两阶段的专家评价信息,得到满意的选择结果。     

Software firm evolution and innovation–orientation

The software industry is experiencing dramatic growth worldwide. This paper offers a theoretical framework to examine the growth and evolution of software firms from an innovation–orientation perspective. While it is apparent that the attitudes and perceptions of a firm’s key stakeholders towards innovative product development hold valuable insights on its future growth and evolution, such a perspective has received limited theoretical attention in studies on firm evolution. In this paper, we define a software firm growth stage model that reflects the changes in a firm’s process and product portfolios. We offer a set of research propositions that link the innovation-related attitudes and perceptions of a firm’s internal stakeholders to firm evolution. The research model has several important implications for both research and practice and can be extended to other high technology contexts.     

资源约束型两阶段生产系统的DEA效率评价模型

经典的数据包络分析(DEA)模型将决策单元看作"黑箱",忽视决策单元的内部过程,必然会高估决策单元的效率。本文研究了一种资源约束型两阶段生产系统的DEA效率评价方法,针对此类生产过程的内部过程,研究其内部运行机制对整体效率的影响。本文提出的模型实质上是一类特殊的网络DEA模型,其评价原理有别于已有的研究成果,但更有助于管理者确定生产过程的非有效来源及其效率改进方向。实例证实本文方法的合理性。     

Towards an integrative framework of performance in product development projects

This paper aims to identify the factors that are associated with high performance in product development projects. The study takes a multidisciplinary approach in order to first explore key characteristics of product development processes. A synthesis of literatures from the fields of organization theory, strategic management, innovation management, project management, and group effectiveness provides the necessary theoretical foundations for analyzing the complex organizational processes that are involved in a typical product development project. The theoretical development that follows leads to the formulation of a series of propositions regarding relationships between product development performance dimensions and a variety of factors. An integrative framework that summarizes the proposed relationships is then developed. The paper concludes with a discussion that focuses on key elements of product-development strategies and management processes and how these can be controlled in order to enhance product development performance.     

Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into ‘performers’ and ‘underperformers’. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity’s performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model’s use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.     

STOCHASTIC COST-VOLUME-PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

In this paper we incorporate a linear demand function to model the price-volume causal relationship into stochastic cost-volume-profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.     

The Effects of Information Overload on Software Project Risk Assessment*

Managers are responsible for providing effective information technology governance of the software development process. Ineffective governance leads to serious resource misallocations and negative consequences concerning Sarbanes‐Oxley compliance. In order for managers to make informed decisions about software development projects, they often need more information than is available through normal information channels, that is, they need an in‐depth review of the at‐risk project. Such in‐depth reviews, however, are costly. Hence, accurate identification of at‐risk projects for in‐depth review is critical to management's ability to govern. This research considers how two factors, information load and time pressure, affect the quality of the project‐selection process. We examine quality by observing the decision strategies involved and then relating these strategies to subsequent decision making. An experiment was conducted with experienced information systems auditors using a combination of policy‐capturing and computerized process‐tracing techniques. The participants in our study cope with information overload by accelerating their decision‐making process and adopting noncompensatory decision processes. Contrary to prior research, our process‐tracing analysis suggests that participants rarely filter information, thus implying that decision makers are unable to process all the information. Coping by resorting to noncompensatory strategies did not decrease decision quality unless combined with accelerated information processing. Participants also increase their weight on the software project risk factors that they repeatedly access and that they view for longer periods of time. The theoretical contributions and practical implications regarding what actions managers can take to reduce the negative impact of information overload are discussed.     

The Development Manager's Advisory System: A Knowledge-Based DSS Tool for Project Assessment*

This research investigates whether the knowledge-based decision support system (KBDSS) paradigm provides the necessary supporting structure and developmental framework for product development evaluation. To address the research questions posed in this study, it is necessary to develop and implement KBDSS's at specific decision points along the product development cycle. This paper describes the design, development, and implementation of a KBDSS to support a product development manager's decision concerning full-scale development of a new product. From the systems design perspective, this paper addresses the integration and innovative use of a variety of techniques for knowledge acquisition, modeling, and processing. The approach utilized obtains the benefits of normative modeling as well as the flexibility and developmental advantages of knowledge-based systems. Since its implementation, the system has been successfully used by a development manager to support his recommendation for an ongoing project. His complete satisfaction with this system served as the impetus for the design and development of a multi-expert system which was implemented at the strategic level.     

Aligning Needs and Capacities to Boost Government Competitiveness

National competitiveness indices are often theoretical underdeveloped, limiting their engagement with academic literature. Because many are based on neoliberal ideology, a new approach is needed to incorporate governance and administration theory, and to enhance relevance to developing countries. This article introduces government competitiveness, a concept that recognizes overlooked factors like the role of social organizations, the use of diverse policy inputs and policy development processes, and the imperative to address human needs at all development stages. The conceptual foundation draws from systems theory, needs theory, and intervention stages theory to inform a comprehensive framework that bridges development scholarship and practice.

     

Auditors' Assessment of Management's Disposition: An Attributional Analysis*

Auditors' assessment of management's dispositions presumably affects their subsequent judgments. However, little is known about the process by which auditors infer characteristics of management. This paper proposes the theory of correspondent inferences [25] as a framework for examining auditors' assessment of management's dispositions; the model is tested in a laboratory experiment using experienced audit managers. The results are consistent with the proposed theoretical framework. Implications for future research are discussed.     

基于广义模糊数的软件成本加权CBR估算研究

在软件项目开发过程中,准确估算出软件成本在提高软件质量和保障软件成功开发方面起到重要支撑作用。针对软件项目历史数据库中部分属性在项目开发初期难以给予精确数值(仅仅能给出模糊数),而已有软件成本估算模型不能很好地处理模糊信息的问题,本文在基于案例推理模型(CBR)基础上集成广义模糊数,提出了基于广义模糊数的CBR模型。使用基于广义模糊数的相似度度量方法代替传统CBR模型中采用的欧式距离等相似度度量方法,采用模糊C均值聚类(FCM)方法将已有软件项目历史数据库中的精确数值进行模糊化处理,以匹配新项目中的模糊数。进一步采用粒子群算法(PSO)来优化属性的权重,构建基于广义模糊数的加权CBR模型。最终在实验中采用Desharnais数据来检验构建模型的有效性。实证结果表明,在与常用的欧式距离CBR模型相比,构建的基于广义模糊数的加权CBR模型能有效提高估算精度,采用PSO优化属性权重能提高模型的估算精度。     

Task partitioning in new product development teams: A knowledge and learning perspective

R&D alliances and outsourcing elements of the new product development process are now commonplace practices among many firms. However, little previous work has examined how these organizational choices influence project knowledge and learning. Based on a comparison of three new product development projects in the software industry, this paper examines how task partitioning in the project influences learning and knowledge development within the firm. The paper suggests that internal development projects encourage synthetic learning and development of architectural and tacit knowledge; in contrast, outsourcing and joint ventures encourage analytic learning and development of component and explicit knowledge.     

Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis

We propose a new approach to estimate technical coefficients from a set of Decision Making Units (DMUs) under the assumption that their production plans are set by process engineers through Linear Programming (LP) techniques. The idea behind this approach is that most manufacturing and agricultural firms routinely resort to LP-based modeling in their decision making processes in order to plan output production and, therefore, this particularity should be taken into account when estimating their technical efficiency. A usual model of LP for these sectors is the so-called product-mix problem, which we relate to a standard Data Envelopment Analysis (DEA) model in terms of the Directional Distance Function. In this paper, we finally show how to estimate the technical coefficients of a sample of Andalusian farms in Spain and how this information can be seen as a complement to the usual by-products associated with estimating technical efficiency by DEA.     

A learning ladder toward efficiency: Proposing network-based stepwise benchmark selection

Starting from the knowledge-based view of efficiency improvement, we propose a network-based approach to find the optimal stepwise benchmarking paths toward the efficiency frontier. The approach treats the Data Envelopment Analysis system as a network of teaching and learning firms and calculates the overall shortest paths taking into account both input endowment similarity and the efficiency gap covered in each step. In addition, based on network centrality concepts, the method discriminates between efficient and intermediate units, and highlights possible outliers or specialized units. As a real-world example, the method is applied to a network of Canadian bank branches and practical implications are discussed.     

R&D网络的自组织演化模型及其仿真研究

从复杂适应系统理论出发,将R&D网络的演化视为复杂系统的自组织过程进行研究。从宏观阶段划分、微观企业行为规则和网络特征统计量3个维度构建R&D网络自组织演化的分析框架,基于复杂网络理论建立R&D网络自组织演化的理论模型,运用数值仿真方法揭示其演化规律以及知识溢出效率对网络特征统计量的影响。研究结果表明,R&D网络的自组织演化过程最终可达到稳定状态,企业具有择优连接的意识,使网络呈现出无标度和集聚特征,知识溢出效率对网络规模、网络利用效率具有显著影响,这为政府正确制定宏观政策提供了理论依据。利用诺基亚的R&D网络对上述理论模型进行验证,模型与实际网络基本吻合,在一定程度上说明模型的正确性。