DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991–2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.     

Operational Productivity,Corporate Social Performance,Financial Performance,and Risk in Manufacturing Firms

We examine the relationship between Operational Productivity (OP), Corporate Social Performance (CSP), Financial Performance (FP), and risk. Our sample frame comprises 476 firms in nine US manufacturing industries during the period 1999–2009. We employ DEA‐based measures for OP and CSP, two operationalizations for FP to reflect current profitability and market value, and two operationalizations for risk to reflect bankruptcy risk and stock price volatility. We confirm that OP is essential for good financial performance and reduced risk (as expected), but the main effects of CSP are mixed. Importantly, we find that OP moderates the CSP–FP and CSP–risk relationships. Specifically, if OP is poor, CSP is of limited benefit to FP or risk. However, at or above a threshold level of OP, firms can use CSP to build upon it to yield further improvements in FP and reductions in risk. We discuss the implications of our findings for theory and practice.     

Supplier Rationalization: A Sourcing Decision Model

We draw on extant literature on strategic sourcing and supply base rationalization to anchor our argument that measuring supplier performance diversity is germane to executing an effective supply base rationalization strategy. We explicate how a novel approach to data envelopment analysis (DEA) efficiency assessment can be utilized to measure this performance diversity. More specifically, our methods are anchored in cross efficiency analysis in DEA that allows for evaluating the efficiency of a supplier with respect to the optimal weights (strengths) of its peers. This methodology is applied to an actual supplier dataset of a large multinational telecommunications company in categorizing their supply base into groups for effective supplier rationalization. We conclude that measuring and analyzing the performance diversity within the framework of DEA provides a mechanism for firms to better balance a rationalized and diversified supply base with unique skills.     

Responses of institutional investors corporate to social performance measures

This study represents a first attempt to empirically examine the impact of data relating to corporate social performance (CSP) on institutional ownership. Findings, though not statistically significant, are consistent with the hypothesis that institutional investors increase ownership when CSP data are positive and, minimally, do not decrease investment. Additionally, although fewer institutions invest in the on-average smaller and more highly-leveraged firms in the socially responsible group, institutions invest in about the same percent of overall equity, suggesting that they may be making some sort of risk trade-off.     

Measuring strategic decision making efficiency in different country contexts: A comparison of British and Turkish firms

This paper compares the relative efficiency of the strategic decision making (SDM) processes of British and Turkish firms. The technique of data envelopment analysis (DEA) is used to measure the relative efficiency of these firms. The evidence obtained by the DEA analysis reveals that the Turkish firms tend to be superior to the British firms in terms of their SDM efficiency. There is a significant difference in scale returns with respect to the country of origin of the firms. The analysis of the improvement potential of inputs indicates that Turkish firms place more emphasis on managing environmental turbulence to enhance their SDM efficiency, while British firms tend to overly focus on the design of an appropriate organizational structure. However, no significant difference was noted between the two groups of firms with regard to the level of resources and effort exerted on formal strategic planning practices. The analysis of output deficits reveals that there is a significant difference between British and Turkish firms in the sources of inefficiency.     

MEASUREMENT OF MULTIPLE SITES IN SERVICE FIRMS WITH DATA ENVELOPMENT ANALYSIS

Data envelopment analysis (dea) has become an increasingly popular method to measure performance for service firms with multiple sites. DEA is superior to many traditional methods for firms that have multiple goals. The promise of DEA is that the complex, multi-objective problem of performance measurement can be reduced to a single number. Unfortunately, the practice of DEA often belies the promise. Misconceptions concerning the purpose and implementation of DEA can cause DEA applications to be less than successful. Here, the technique is explained, and a guide to the implementation of DEA is proposed, utilizing DEA studies of retail bank branches.     

Using Malmquist Indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes–Oxley Act

There have been many criticisms of the Sarbanes–Oxley (SOX) Act passed in July of 2002 to correct business accountability and performance practices. The act has a major emphasis on accounting and its practices. This paper attempts a response to these criticisms by investigating changes in productive efficiency for 62 of the largest US public accounting firms between the periods (2000–2001) and (2003–2004)—the periods before and after enactment of SOX in July of 2002. DEA is used to calculate Malmquist indexes of productivity and efficiency changes. This index is used because it can distinguish between changes in technical efficiency, which limit the possibilities, and changes in the performance efficiencies for each firm. Contrary to many of the criticisms, results indicate that accounting firms have exhibited significant post SOX growth in productive efficiency which is better than pre-SOX performances.     

The impact of corporate sustainability performance on information asymmetry: the role of institutional differences

This paper empirically investigates whether corporate sustainability performance (CSP) affects information asymmetry (IA) for European firms listed in the STOXX Europe 600 from 2002 to 2013. We find a significantly negative effect of CSP on IA. By exploiting institutional differences between the European countries, we determine that the negative effect of CSP on IA is more pronounced in liberal market economies compared to coordinated market economies, thus pointing to a substitutive effect of CSP and economic coordination. Further, the impact is greater in countries with stricter disclosure requirements. In such countries, there is generally a greater appetite for company-specific information. However, disclosure requirements fulfil this need only partially because they concentrate on the corporate governance dimension of corporate sustainability. Hence, information on the social pillar especially matters to investors in a complementary manner and drives the overall effect. Our study contributes to the literature on the positive capital market effects of CSP by showing the proposed effect in European capital markets and the institutional determinants of its strength.     

Revisiting the Corporate Social and Financial Performance Link: A Contingency Approach

This study draws on and extends contingency theory, in relation to stakeholder theory to understand the corporate social performance (CSP) and financial performance (CFP) link, by evaluating under what circumstances CSP influences CFP. Contingencies include stakeholder configurations/salience and crisis conditions. Using differentiated measures of CSP, this study examined financial effects of various specific stakeholder facing activities pre‐ and post‐crisis in the food/beverage and pharmaceutical industries, and in firms selling search versus experience goods. The results indicate that pre‐crisis CSP is related to post‐crisis financial effects, but the relationships are dependent on the interactions among the contingencies studied, so investments in certain social areas improve CFP, whereas others may hurt it. This confirms that a finer grained approach should be taken to the examination of CSP and CFP. On a practical basis, it shows that deep stakeholder knowledge and attention to complementary factors to CSP, such as advertising, must be understood, so CSP activities are of benefit to the firm.     

Governance Structures,Multidimensional Efficiency and Firm Profitability

Using a panel data set of 361 German corporations for the period 1991–1996 we test the hypothesis that firms with more efficient governance structures have higher profitability. To determine efficiency we compare firms with respect to ownership concentration, the identity of owners, capital structure, investment and firm growth by a multi-input/multi-output Data Envelopment Analysis (DEA). This non-parametric linear programming technique considers both multiple in- and out- puts. Based on the concept of pareto efficiency, it computes an efficiency score where the associated weights of the inputs and outputs are determined endogenously. The DEA efficiency scores are then used as explanatory variables in panel data regressions of profitability. Our main finding is that the efficiency scores indeed contribute significantly to explaining profitability differences between firms, even after controlling for industry effects and unobserved systematic firm effects.     

矩阵型网络DEA模型及其实证检验

针对传统DEA模型无法有效的评价矩阵型网络系统的效率,本文构建了矩阵型网络决策单元的生产可能集,建立了矩阵型网络DEA模型。在此基础上证明了决策单元在矩阵型网络DEA模型下为弱DEA有效的充分必要条件为其每个子系统均为弱DEA有效。最后,选用美国的十个电力公司作为决策单元对模型进行实证检验,得出结论:矩阵型网络DEA模型弥补了传统DEA模型无法反映内部有效性从而可能得到错误结果的缺陷,并能精确地计算出各个子过程的效率,辨识出具体需要改进的子过程。同时新模型为评价复杂系统的效率提供了新的思路。     

Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization

The performance of a decision making unit (DMU) can be evaluated in either a cross-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. In order to eliminate the inconsistency caused by using different frontier facets to calculate efficiency, common-weights DEA models have been developed, under which a group of DMUs can be ranked for a specific period. This study proposes a common-weights DEA model for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity changes of all DMUs have a common basis for comparison. The common-weights global MPI not only has sound properties, but also produces reliable results. The case of Taiwan forests after reorganization shows that the MPIs calculated from the conventional DEA model produce misleading results. The common-weights global MPI approach, on the other hand, correctly identifies districts with unsatisfactory performance before the reorganization and those with unsatisfactory productivity improvement after the reorganization.     

Estimation of portfolio efficiency via DEA

Traditional DEA models and nonlinear (diversification) DEA models are often used in performance evaluation of portfolios. However, the diversification models are usually very complicated to compute except the very basic models. And the classic DEA models still need to be further justified and tested, since it is not clear whether they are over-linearised according to the diversification models. The existing studies on performance evaluation via the classic DEA models generally focus on the selection of inputs and outputs. In this work, we investigate theoretical foundation of DEA models for portfolios from a perspective of sampling portfolio. We show the classic DEA provides an effective and practical way to approximate the portfolio efficiency (PE). We further verify this approach through different portfolio models with various frictions and bounds on the market. Through the comprehensive simulations carried out in this study, we show that with adequate data sets, the classic DEA models can effectively sample portfolios to take into account sufficient diversification, and thus can be used as an effective tool in computing the PE for their performance assessments. This study can be viewed as a justification of the classic DEA performance assessments and the way to introduce other efficiency notions (like allocation efficiency, scale efficiency, etc) into assessment of portfolios.     

企业风险管理与经营效率:来自中国保险业的经验证据

本文从风险管理的视角对企业效率评估的数据包络分析技术进行了改进,探讨了风险管理与经营效率的内在关联,并以中国保险业为例,对1999年以来企业真实的经营效率水平进行了评估。结果表明:企业内部的风险管理能力对其经营效率水平的提升具有明显的影响,而且这种影响力正在逐渐加强。不考虑企业内部的风险管理水平将直接导致其经营效率的测算结果出现低估,2002年以后这种低估的程度越发明显,这可归因于同期保险企业开始逐渐重视提高自身的风险管理能力。以上结论也为企业如何在管控风险的同时提升经营效率水平提供了有价值的指导。     

企业信息披露中的模仿行为研究——基于制度理论的分析

本文在制度理论的分析框架下,研究合法性压力和不确定性条件下企业信息披露中的模仿行为及由此导致的制度同形现象.本文以2006-2010年我国重污染行业上市公司年报中的环境信息披露为研究对象,发现企业环境信息披露存在同形性和模仿行为,且属于模仿其它企业平均水平的频率模仿,而不是模仿领先者.本文将已有的信息披露研究从经济学分析的视角向经济社会学进行拓展,丰富了对信息披露过程中决策者认知过程和制度化过程的认识,同时也透过信息披露中的模仿行为从更加微观的层面为制度化过程中的趋同现象提供了新的证据.     

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.     

Managing stakeholder pressures: Toward a typology of corporate social performance profiles

Why do some firms ignore some stakeholders while courting others? We propose two key drivers of firms' social postures and derive from this analysis a novel typology of corporate social performance (CSP) profiles. Although we expect that other drivers exist, we argue that a useful starting point for understanding any given CSP profile is to consider the pressure exerted on an organization by its stakeholders in conjunction with its level of resource endowment. Our preliminary typology identifies six distinct CSP profiles that reflect different opportunities and risks for stakeholder management: the CSP Vanguard, Opportunist, Generalist, Minimalist, Specialist, and Laggard. All else equal, the first two CSP profiles imply more nonmarket opportunities than risk, whereas we expect Laggards and Specialists to face greater risk in their responses to social and environmental issues. According to our framework, Generalists and Minimalists probably operate between these two extremes of business risk. Our conceptual analysis seeks to advance research and practice for more strategic stakeholder management.     

Data envelopment analysis 1978–2010: A citation-based literature survey

This study surveys the data envelopment analysis (DEA) literature by applying a citation-based approach. The main goals are to find a set of papers playing the central role in DEA development and to discover the latest active DEA subareas. A directional network is constructed based on citation relationships among academic papers. After assigning an importance index to each link in the citation network, main DEA development paths emerge. We examine various types of main paths, including local main path, global main path, and multiple main paths. The analysis result suggests, as expected, that Charnes et al. (1978) [Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research 1978; 2(6): 429–444] is the most influential DEA paper. The five most active DEA subareas in recent years are identified; among them the “two-stage contextual factor evaluation framework” is relatively more active. Aside from the main path analysis, we summarize basic statistics on DEA journals and researchers. A growth curve analysis hints that the DEA literature’s size will eventually grow to at least double the size of the existing literature.     

DEA target setting approach within the cross efficiency framework

Target setting is an important reason that data envelopment analysis (DEA) is widely applied to analyze efficiency. However, the efficiency overestimation of traditional DEA may affect the rationality of target setting, and even may make this method invalid in target setting. This paper innovatively proposes the definition of cross efficient, and develops two new target setting approaches for individual decision-making unit (DMU) and global optimization to improve the cross efficiency of DMUs in different decision-making situations. Then the influence of decision maker's preference on the improvement direction is discussed, and then these approaches are further extended. This paper solves the limitations of traditional DEA in target setting, and provides different directions to improve cross efficiency for meeting decision makers’ needs. Finally, two examples are provided to illustrate the effectiveness of these approaches.