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

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

The linguistic and cognitive mechanisms underlying language tests in healthy adults : a principal component analysis

Pour un processus d’évaluation linguistique plus précis et rapide, il est important d’identifier les mécanismes cognitifs qui soutiennent des tâches langagières couramment utilisées. Une façon de mieux comprendre ses mécanismes est d’explorer la variance partagée entre les tâches linguistiques en utilisant l’analyse factorielle exploratoire. Peu d’études ont employé cette méthode pour étudier ces mécanismes dans le fonctionnement normal du langage. Par conséquent, notre objectif principal est d’explorer comment un ensemble de tâches linguistiques se regroupent afin d’étudier les mécanismes cognitifs sous-jacents de ses tâches. Nous avons évalué 201 participants en bonne santé âgés entre 18 et 75 ans (moyenne=45,29, écart-type= 15,06) et avec une scolarité entre 5 et 23 ans (moyenne=11,10, écart-type=4,68), parmi ceux-ci, 62,87% étaient des femmes. Nous avons employé deux batteries linguistiques : le Protocole d’examen linguistique de l’aphasie Montréal-Toulouse et Protocole Montréal d’Évaluation de la Communication – version abrégé. Utilisant l’analyse en composantes principales avec une rotation Direct-oblimin, nous avons découvert quatre composantes du langage : la sémantique picturale (tâches de compréhension orale, dénomination orale et dénomination écrite), l'exécutif linguistique (tâches d’évocation lexicale - critères sémantique, orthographique et libre), le transcodage et la sémantique (tâches de lecture, dictée et de jugement sémantique) et la pragmatique (tâches d'interprétation d'actes de parole indirecte et d'interprétation de métaphores). Ces quatre composantes expliquent 59,64 % de la variance totale. Deuxièmement, nous avons vérifié l'association entre ces composantes et deux mesures des fonctions exécutives dans un sous-ensemble de 33 participants. La performance de la flexibilité cognitive a été évaluée en soustrayant le - temps A au temps B du Trail Making Test et celle de la mémoire de travail en prenant le total des réponses correctes au test du n-back. La composante exécutive linguistique était associée à une meilleure flexibilité cognitive (r=-0,355) et la composante transcodage et sémantique à une meilleure performance de mémoire de travail (r=.0,397). Nos résultats confirment l’hétérogénéité des processus sous-jacent aux tâches langagières et leur relation intrinsèque avec d'autres composantes cognitives, tels que les fonctions exécutives.To a more accurate and time-efficient language assessment process, it is important to identify the cognitive mechanisms that sustain commonly used language tasks. One way to do so is to explore the shared variance across language tasks using the technique of principal components analysis. Few studies applied this technique to investigate these mechanisms in normal language functioning. Therefore, our main goal is to explore how a set of language tasks are going to group to investigate the underlying cognitive mechanisms of commonly used tasks. We assessed 201 healthy participants aged between 18 and 75 years old (mean = 45.29, SD = 15.06) and with a formal education between 5 and 23 years (mean = 11.10, SD =4.68), of these 62.87% were female. We used two language batteries: the Montreal-Toulouse language assessment battery and the Montreal Communication Evaluation Battery – brief version. Using a Principal Component Analysis with a Direct-oblimin rotation, we discovered four language components: pictorial semantics (auditory comprehension, naming and writing naming tasks), language-executive (unconstrained, semantic, and phonological verbal fluency tasks), transcoding and semantics (reading, dictation, and semantic judgment tasks), and pragmatics (indirect speech acts interpretation and metaphors interpretation tasks). These four components explained 59.64% of the total variance. Secondarily, we sought to verify the association between these components with two executive measures in a subset of 33 participants. Cognitive flexibility was assessed by the time B-time A score of the Trail Making Test and working memory by the total of correct answers on the n-back test. The language-executive component was associated with a better cognitive flexibility score (r=-.355) and the transcoding and semantics one with a better working memory performance (r=.397). Our findings confirm the heterogeneity process underlying language tasks and their intrinsic relationship to other cognitive components, such as executive functions

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

Essays on Global Financial Inclusion

This thesis consists of three main essays on the global dimension of financial inclusion. These empirical analyses are different, yet related to each other. The main focus of the thesis is on constructing a broader multidimensional measure of financial inclusion as a composite index that can be used to assess the ease of and use of the access to financial markets. Additionally, as one of the main contributions of this study, access to other financial institutions such as microfinance institutions, post offices and cooperatives, has been added to the analysis to explore its impact on poverty and Islamic finance. The International Monetary Fund’s International Financial Statistics and Financial Access Survey databases, the World Bank’s Global Financial Development and Global Findex databases, and the survey data by Beck et al. (2006a) are used to collect the indicators of the indices. Using the broader multidimensional financial inclusion indices as a proxy of financial access, the study aims to assess the impact of financial inclusion on poverty reduction in the third chapter. In the next chapter, using the constructed financial inclusion indices as a proxy of financial exclusion, it aims to explore the impact of Islamic finance on financial exclusion to examine why our constructed financial inclusion indices are better measurements of financial access. Using the constructed indices in two different analyses, this thesis tests the arguments in studies that have made original contributions in the literature, to explore the predictability and comparability of these indices as the proxy of financial inclusion

Essays in microfinance: their capital structure and financial inclusion.

This study examines three central themes within the MF literature, within the context of the current drive and efforts by governments in sub-Saharan Africa (SSA) to improve institutional and governance quality, whilst implementing Microfinance as a blanket development policy tool. First, within an institutional context, we test for the institutional and firm specific determinants of the funding structure of MFIs. Secondly, we examine the impact of funding/capital structure on MFI financial and social performance. Finally, within the context of unfavourable financial exclusion level in SSA, we question just how much important MFIs are in improving the drive towards financial inclusion on the continent (by examining the impact of MFIs on financial inclusion in SSA). In order to achieve the above aims, this research project utilizes a comprehensive panel dataset for 38 countries in SSA, for the period 2004-2016. A database (MIX Market) specially purposed for MFI reporting and data bank was implemented in collecting the data employed for this research. In addition, World Bank data was employed in collecting country specific, and macro-economic data, whilst data from the heritage index, ease of doing business index, and corruption index were employed as explanatory variables. This analysis examines key capital structure variables unique to MFIs namely; Leverage and Deposits. The leverage measure for MFIs captures total borrowing (as well as short and long tenure financing), in addition to donated equity, capturing the donations made to MFIs by donors by way of equity, finally, deposits are MFI clients timed deposits. In order to achieve the aims, we utilize a fixed-effect panel data estimation technique for analysis of the obtained data (which includes 778 MFIs with 3,338 data points), in addition to employing dummy variables to further enhance the analysis. The institutional and firm specific variables include; creditor rights, corruption indicators, governance quality, and MFI characteristics variables such as; size, risk and age. The second analysis utilizes MFI social and financial performance dependent variables, against capital structure variables. Finally, the third empirical analysis employs financial inclusion index, in addition to a broad set of independent variables which capture MFI penetration, technology utilization (mobile subscription), geography (population density), institutional quality (public credit registry, and corruption control), macroeconomic (inflation, gross income), and financial development variables (deposit interest rate, and domestic credit to private sector). The results for the impacts of the institutional determinants of the capital structure of MFIs reveal that (for both leverage the deposit models) institutional measures are important in determining the capital structure of MFIs. In particular, the measure for investor protection is significant in determining the leverage of MFIs. This is a new finding within the Microfinance literature within the context of sub-Saharan Africa. This confirms the importance of a strong institutional environment in attracting funding for the sector. Further confirming this position are the measures of economic freedom, which appear to be significant in determining the donated equity for MFIs. Specifically, financial freedom is positive and significant, whilst the measure of income GNI per capita is relevant in determining the donated equity of MFIs. The second analysis examines the influence of capital structure on a comprehensive set of MFI performance. These include financial performance measure such as; sustainability, return on asset, risk and MFI efficiency. On the other hand, social performance captures the outreach of MFIs (measured by percent of female borrowers). In addition the outreach measure is split into two measures capturing both the breadth (number of active borrowers) and depth (average loan balance per borrower) of MFI outreach. Two Major findings are observed here. Firstly, the measure for financial performance MFI sustainability reveal that short-term leverage is significant in explaining MFI sustainability. On the other hand, the measure for social performance (percent of female borrowers), is negatively influenced by short-term leverage, suggesting MFIs operating principally with short-term leverage are less likely to achieve their social performance (often because of the pressure attached to the utilisation of short-term leverage). However, the measure for long-term leverage significantly influences the measure of social performance. The final analysis utilises a financial inclusion index, with the key regressor variable identified as a measure of MFI activity (MFI penetration rate). Key findings reveal that: MFIs (as measured by their penetration rates) appear to be insignificant in influencing financial inclusion in SSA. More specifically, the relationship appear to be in an inversely related with the measure for financial inclusion. This finding is telling, and a significant new finding within the literature. Perhaps expected, given the operational preferences of MFIs in Africa to focus on urban clients as opposed to rural penetration. Secondly, institutional measures such as; corruption control, appear to be positive in influencing financial inclusion, reiterating the need for good governance and strong institutions. Worthy of note however is the measure for the information environment as measured by public credit registry. For instance, the results of the analysis showed that the existence of a public credit registry plays a significant role in influencing the financial inclusion in SSA. Fortunately, the policy implications are somewhat evident. Creating an enabling environment for funders to come into the sector and feel protected should be apriority. Policies that strengthen financial reporting practices, transparency in government, and embracing the absolute power of the rule of law are important for the continent in the short and longer term. From a macro-environment standpoint improving national income via increased productivity of local institutions, is a positive signal to international funders. Governments in SSA and policy makers, are required to create suitable local capital markets and healthy ways of providing long-term favourable financing to MFIs within the SSA region. It is clear from the various models of analysis that long-term leverage on favourable terms on average is crucial for the long-term sustainability and performance of MFIs within the SSA region. Therefore, Implementing a long-term funding strategy via affordable local currency denominated markets will tremendously improve the sector in SSA, and hence, should be the priority for policy makers.. The rationale being that with long-term funding MFIs are able to operate with more scope to expand operations without the pressure of meeting foreign denominated funding repayment obligations. A key finding for this research is the revelation that MFIs are less impactful in aiding the financial inclusion drive in SSA, as anecdotal evidence would suggest. Conversely, we find that the measure for mobile penetration is highly significant in influencing financial inclusion in SSA. Despite the findings for MFIs, the use of MFIs to achieve this goal could indeed still be attainable, however in their current capacity this is not possible. Therefore, re-tooling MFIs to meet such demands is crucial, and should be of high priority for policy makers and funders of the MFI sector. One of such ways to achieve deeper rural coverage could be an implementation of mobile banking technology in executing financial services. Some of the more important findings indicate that –with some hope- the implementation of financial technology such as mobile money could be of benefit to countries in SSA. Policy makers are therefore better off putting in place sound institutional framework such as strengthening and localising public credit registries. This research analysis indicates that this is significant in aiding/impacting financial inclusion in SSA. Establishment of functional and efficient public credit registries, will greatly improve the processing of financial information and aid information asymmetry. In addition to this MFIs can then be trimmed down in their operative capacities, so as to aid agility in their operations, to better enable them reach the bottom of the pyramid competently