1,720,998 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Mesures d'efficacité et évaluation de regroupement de bureaux distributeurs : une approche non paramétrique
No full textData Envelopment Analysis Models for a Mixture of Non-ratio and Ratio Variables
Get PDFPerformance comparison is a delicate business, even among organizations of the same
kind. The simplest of all is usually the ratio of a single output to a single input. The
problem lies in the fact that one aspect of the business could hardly represent the whole
picture and the landscape the business is operating in. Businesses have complex structures and oer variety of products so it is only fair to take all into consideration to judge their performance against others in an industry. Data Envelopment Analysis (DEA) is one method suitable when there are multiple inputs and outputs to be considered. It is
a non-parametric method conceptualized by Farrell in 1957. However, it was not untill 20 years later, that Charnes, Cooper and Rhodes brought this concept into practice by finding a way to realize this idea and make it work. The breakthrough came from the
fact that under certain assumptions Farrell's idea could be formulated as a linear mathematical program (LP) which could be solved using the simplex and similar methods.
One limitation of the existing DEA models is their inability to work with ratio variables
because the linear combination of DMUs do not generally translate to linear combination
of inputs and outputs in the ratio form. In this work, our contribution to the field includes extending Farrell's idea to include ratio inputs and outputs and operationalizing
four models under variable returns to scale assumption. Three non-oriented models are
formulated and linearized and one non-linear model is solved using a heuristic.Ph.D
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Data Envelopment Analysis Models for a Mixture of Non-ratio and Ratio Variables
No full textPerformance comparison is a delicate business, even among organizations of the same
kind. The simplest of all is usually the ratio of a single output to a single input. The
problem lies in the fact that one aspect of the business could hardly represent the whole
picture and the landscape the business is operating in. Businesses have complex structures and oer variety of products so it is only fair to take all into consideration to judge their performance against others in an industry. Data Envelopment Analysis (DEA) is one method suitable when there are multiple inputs and outputs to be considered. It is
a non-parametric method conceptualized by Farrell in 1957. However, it was not untill 20 years later, that Charnes, Cooper and Rhodes brought this concept into practice by finding a way to realize this idea and make it work. The breakthrough came from the
fact that under certain assumptions Farrell's idea could be formulated as a linear mathematical program (LP) which could be solved using the simplex and similar methods.
One limitation of the existing DEA models is their inability to work with ratio variables
because the linear combination of DMUs do not generally translate to linear combination
of inputs and outputs in the ratio form. In this work, our contribution to the field includes extending Farrell's idea to include ratio inputs and outputs and operationalizing
four models under variable returns to scale assumption. Three non-oriented models are
formulated and linearized and one non-linear model is solved using a heuristic.Ph.D
A Big Data Approach to Accounting Fraud Detection Using Data Envelopment Analysis and One Class Support Vector Machine
Get PDFThis thesis investigates a method to use Data Envelopment Analysis (DEA) in the context of big data to improve data analysis for the volume and velocity aspects of big data. First, DEA is used to identify fraud indicators in a large dataset. One class support vector machine (OC-SVM) is then used to identify outliers in the same dataset to evaluate the performance of the proposed DEA model. A second DEA model is proposed as a variable selection tool to enhance the performance of an OC-SVM model. The results show that although the proposed DEA model on its own is not as effective in detecting anomalies as OC-SVM, there is potential to use DEA as a variable selection tool to enhance the training and prediction process for anomaly detection using OC-SVM. The parameters and methods examined in this thesis are not exhaustive, but it does provide a baseline for future work.M.A.S
Evaluating Pension Funds Considering Unobservable Variables Bridging Pension Funds Mutual Funds through the Development of a New DEA Model
No full textPrivate pension plans provide an important source of retirement income for employees and their families. The effective performance of private pension plans is an important issue to investigate because of the social and economic implications for investors, managers and governments. Typically, financial ratios which have inherent limitations, are used to evaluate pension funds’ performance. The objective of this research is to develop Data Envelopment Analysis (DEA) models which evaluate the private pension funds’ performance and suggest useful measures based on detailed data acquired from the federal regulator OSFI (Office of the Superintendent of Financial Institutions Canada). The research has three sections. The first section evaluates private pension funds’ performance by considering the effect of regulations which are not under the control of fund managers as well as comparing pension funds with mutual funds which have different characteristics. A new DEA model is developed that can evaluate different entities with different cultures from the same industry such as pension funds and mutual funds. The results show that the new DEA model provided a more realistic assessment of pension funds’ performance and comparison between pension funds and mutual funds. In section two, the reason for low minimum efficiency scores in DEA for pension funds is examined. It is found that the presence of very low efficiency scores is not uncommon in this industry. In section three, a new methodology is introduced which evaluates the pension funds’ performance by considering the importance of different variables based on an expert’s judgements as well as borrowing useful information from the mutual funds’ dataset. The results show that the discriminatory power of DEA increases after adding an expert’s opinions as well as mutual funds’ information to the pension funds’ DEA model and three different target levels are defined for inefficient plans. Since private pension funds have unique characteristics compared to other investment funds as well as the significant importance of retirement income to people, the results of this research will be of interest to government, financial and industrial managers.Ph.D
A Comprehensive Study of Bank Branch Growth Potential and Growth Trends through the Development of a Unique DEA Formulation and a New Restricted DEA Model
Get PDFDEA has been widely used in branch performance work to evaluate intermediation, profitability and production efficiency. However, traditional modeling approaches fail to assess growth potential and customer retention; two very significant components of a bank's economic health and market stability. To address this issue, this research integrates Operations Research (OR) techniques with DEA methodologies to develop a new formulation for more accurately modeling branch growth from one time period to another. This model was found to be successful in evaluating a branch's growth potential and with the integration of Malmquist Index techniques, and was able to identify growth trends over an extended period of time. In addition, this study introduces a new restricted DEA model that restricts the Most Productive Possibilities Set (MPPS) to a convex subset of non-negative growth units through the restriction of the non-negative intensity variable found in the dual form of DEA. To verify both models and test the validity of the results, several data sets were used, including one provided by one of the Big Five Canadian Banks and one from a large Turkish bank.Ph.D
A Hybrid Bayesian and Data-envelopment-analysis-based Approach to Measure the Short-term Risk of Initial Public Offerings
Get PDFInitial public offerings (IPOs) are perhaps the most exhilarating events on stock exchanges. Yet, the ‘ambiguity’ of the risk of IPOs overshadows the thrill and deters many investors from possibly considering the IPOs. It is the insufficient accounting and market history at the IPO stage that burdens their proper risk quantification. The main objective pursued by this thesis is to offer a methodology for measuring the short-term risk of IPOs which conforms to the mathematical principles of market risk analysis employed in the case of public companies. Here, short-term risk is defined as the uncertainty associated with the stock price of the IPO of interest (IPOI) 90 days subsequent to the issuing day and is quantified as a value-at-risk (VaR) inferred from the probability density function of price on day 90 (i.e., PDF_90^IPOI). This thesis develops a Bayesian framework where PDF_90^IPOI can be estimated in a recursive and iterative process. In most IPO cases, there exist limited hard data, yet, strong ‘prior’ belief (soft data). The Bayesian setting offers a unique risk quantification approach which befits and serves these two characteristics of IPOs.
To obtain the data required for carrying out the risk analysis, this research relies upon the ‘closest comparable’ of IPOI. The ‘closest comparable’ would be a public firm whose pre-IPO idiosyncratic financial data most resemble those of IPOI. Furthermore, it is expected to have gone public in similar macro-economic and sector conditions. Concisely, the risk quantification process involves two phases: In Phase I, a Data Envelopment Analysis-based multi-dimensional similarity metric is developed to select the closest comparable. Phase I indeed identifies the most suitable source of ‘prior’ knowledge and passes the output to Phase II which encompasses the Bayesian process. Phase II is designed to formulate and refine the ‘prior’ evidence and then employ the achieved ‘posterior’ knowledge towards estimating PDF_90^IPOI. This PDF_90^IPOI subsequently acts as the basis for VaR inferences. In the last stage of the research, the proposed Bayesian VaR methodology is examined (backtested) using the following two tests: test of uniform cumulative probability values and test of VaR break frequency.Ph.D
- …
