On constructing a composite indicator with multiplicative aggregation and the avoidance of zero weights in DEA

Peer reviewe

Conceptual issues in constructing composite indices

This paper presents an analysis of the conceptual issues associated with the construction of composite indices. Composite indices, which are constructed by averaging a number of indicators or sub-indices, are multidimensional, in that they represent aggregate measures of a combination of factors. They are often used to simplify complex measurement constructs, and often have a strong political appeal due to the fact that they simplify complex matters into a single number. However, composite indices are often criticized due to their subjectivity. Indeed the methodology used to construct an index generates considerable debate on various aspects, such as the weighting method used, possible correlation among the different sub-indices, missing variables, standardisation procedures and others. This paper will attempt to propose some desirable criteria for the construction of composite indices, including simplicity, ease of comprehension, and coverage issues and transparency. It will also discuss a number of methodological considerations including weighting. An analysis and evaluation of the different methods used by a selection of renowned composite indices, including the University of Malta’s resilience index, and the effects of certain assumptions on results will also be carried out.peer-reviewe

An evaluation of cross-efficiency methods: With an application to warehouse performance

Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a selection of methods popular in the literature. These methods are applied to performance measurement of European warehouses. We develop a cross-efficiency method based on a rank-order DEA model to accommodate the ordinal nature of some key variables characterizing warehouse performance. This is one of the first comparisons of methods on a real-life dataset and the first time that a model allowing for qualitative variables is included in such a comparison. Our results show that the choice of model matters, as one obtains statistically different rankings from each one of them. This holds in particular for the multiplicative and game-theoretic methods whose results diverge from the classic method. From a managerial perspective, focused on the applicability of the methods, we evaluate them through a multidimensional metric which considers their capability to rank DMUs, their ease of implementation, and their robustness to sensitivity analyses. We conclude that standard weight-restriction methods, as initiated by Sexton et al. [48], perform as well as recently introduced, more sophisticated alternativesSpanish Ministry of Science and Innovation (Ministerio de Ciencia e Innovación), the State Research Agency (Agencia Estatal de Investigación) and the European Regional Development Fund (Fondo Europeo de Desarrollo Regional) under grants EIN2020-11226

An Evaluation of Cross-Efficiency Methods, Applied to Measuring Warehouse Performance

In this paper method and practice of cross-efficiency calculation is discussed. The main methods proposed in the literature are tested not on a set of artificial data but on a realistic sample of input-output data of European ware- houses. The empirical results show the limited role which increasing automation investment and larger warehouse size have in increasing productive performance. The reason is the existence of decreasing returns to scale in the industry, resulting in sub-optimal scales and inefficiencies, regardless of the operational performance of the facilities. From the methodological perspective, and based on a multidimensional metric which considers the capability of the various methods to rank warehouses, their ease of implementation, and their robustness to sensitivity analyses, we conclude to the superiority of the classic Sexton et al. (1986) method over recently proposed, more sophisticated methods

Tools for Composite Indicators Building

Our society is changing so fast we need to know as soon as possible when things go wrong (Euroabstracts, 2003). This is where composite indicators enter into the discussion. A composite indicator is an aggregated index comprising individual indicators and weights that commonly represent the relative importance of each indicator. However, the construction of a composite indicator is not straightforward and the methodological challenges raise a series of technical issues that, if not addressed adequately, can lead to composite indicators being misinterpreted or manipulated. Therefore, careful attention needs to be given to their construction and subsequent use. This document reviews the steps involved in a composite indicator’s construction process and discusses the common pitfalls to be avoided. We stress the need for multivariate analysis prior to the aggregation of the individual indicators. We deal with the problem of missing data and with the techniques used to bring into a common unit the indicators that are of very different nature. We explore different methodologies for weighting and aggregating indicators into a composite and test the robustness of the composite using uncertainty and sensitivity analysis. Finally we show how the same information that is communicated by the composite indicator can be presented in very different ways and how this can influence the policy message.JRC.G.9-Econometrics and statistical support to antifrau

Development of a holistic index for safer roads

This research aims to develop a road safety assessment index (RSAI) based on the safe system concept. This index can be used to rate and rank countries according to the effectiveness of the national road safety strategic plans; to monitor the progress towards a set target; and to suggest strategic solutions. To develop the RSAI, its thematic indicators are identified to cover safer road infrastructure and mobility, safer vehicles, and safer road-user behaviour. A sub model is developed for each thematic indicator, along with their individual indicators that can give a full reflection. The road assessment programme (RAP) is considered to identify the indicator of safer road infrastructure and mobility. For this, a procedure for extending the RAP methodology is developed and evaluated. The new car assessment programme (NCAP) of rating cars is chosen to identify the safer vehicle indicator. While seven indicators are selected to form the sub model of safer road-user behaviour. The chosen indicators are weighted and aggregated to form the RSAI’s preliminary models. These models are evaluated through comparing with the rate of road fatalities, to decide the final form of the RSAI model. The results show the suitability of the RSAI model in assessing the road safety level, and in achieving its purposes

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Understanding the Organizational Factors that Impact Police-Community Relations

There has been a significant amount of attention refocused on problems surrounding police and communities of color. The most consistent remedy identified has been reforming police departments, which is an organizational-level solution. However, only minimal strides have been made in empirical research to understand the organizational correlates associated with police-community relations. Thus, this research investigated the impact that police departments’ organizational and managerial characteristics have on police-community relations. The key contributions of this research to the literature are three-fold. First, a composite indicator of police-community relations was developed by compiling a large nationwide dataset of local police-departments. This multidimensional indicator includes citizen complaints, police use of force, assaults against police officers, and civilian deaths by police. Second, the role that specific organizational characteristics—community-oriented policing, passive representation, professionalism, and control mechanisms—have on police-community relations was estimated using ordinary least squares regression analyses from over 250 police departments. The findings portrayed that only specific (and very few) organizational and managerial characteristics of police departments impact police-community relations. Specifically, police departments that had formal partnerships with the community, dedicated beat patrol officers, and minority representation were found to have lower levels of use of force. Police departments with higher numbers of officers dedicated to problem-solving activities in the community had lower levels of citizen complaints; in contrast, departments that were more formalized had higher levels of citizen complaints. Lastly, to understand the causal mechanisms undergirding organizational factors and police-community relations, an in-depth case study was conducted in Hartford, Connecticut. The case study included (a) 88 interviews with police officers, public officials, and community leaders, (b) 67.7 hours of participant observations, and (c) a review of secondary sources. A thematic content analysis of the data underscored the importance of police departments cultivating soft skills, investing in human resources, and being intentional about engaging the community. Specifically, police departments can influence police-community relations by impacting the level and quality of service provision and/or officer attitudes and behavior. Taken as a whole, this study adds to the knowledge base of organizational behavior, public management, and policing studies while also providing implications for policy and practice