Sophisticating business performance management for banks: using data envelopment analysis on business process level

2012 ◽  
Vol 13 (3/4) ◽  
pp. 227 ◽  
Author(s):  
Anne Schaefer ◽  
Andreas Burger ◽  
Jürgen Moormann
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Business Process ◽  
Business Performance ◽  
Data Envelopment ◽  
Business Performance Management ◽  
Using Data ◽  
Process Level

scholarly journals Performances Management When Modelling Internal Structure of a Production Process

2020 ◽  
Vol 15 (7) ◽  
pp. 133
Author(s):  
Claudio Pinto
Keyword(s):  
Data Envelopment Analysis ◽  
Production Process ◽  
Performance Management ◽  
Internal Structure ◽  
Relative Efficiency ◽  
Data Envelopment ◽  
Method Performance ◽  
Decomposition Formula ◽  
New Strategy ◽  
Process Level

Performance management is a central point for both public and private organizations. In the data envelopment analysis (DEA) method, performance management takes the form of measuring relative efficiency. Furthermore, considering each organization and or production process as a black box,  inputs are transformed into outputs. In reality, production organizations or processes are composed of different parts that carry out different related activities. For this reason, modeling the internal structure of a production process like a system of interconnected parts makes it possible to measure its performance at the sub-process level. In this paper, we hypothesized a production process, made up of three interconnected parts. It is a new strategy to acquire relative efficiency consisting of building a block inside the system with at least two sub-processes. This step refers to a basic model of relational Network Data Envelopment Analysis (NDEA). Also, we used the additive decomposition formula to measure the efficiency of the whole process. We highlighted the differences in the measurement, between the direct application of the relational NDEA model and the measurement with the block approach model.We compared the cumulative empirical distribution functions of the efficiency scores of a sub-process with the decomposition formula multiplicative and our  approach. In conclusion, the paper proposes, a new strategy to measure the relative performances of a production process model as a network system of three subprocesses, which combines the NDEA and the DEA. This allows us to reevaluate, the indications of policy at the individual sub-process level (block). Moreover, it is a versatile approach which allows aggregation of the sub-processes in blocks, according to the particular policy requirements, legislative technological constraints, etc.

Evaluating Business Performance Using Data Envelopment Analysis and Grey Relational Analysis

2021 ◽  
pp. 115-148
Author(s):  
Tihana Škrinjarić ◽  
Boško Šego
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Business Performance ◽  
Business Failure ◽  
Special Focus ◽  
Data Envelopment ◽  
Relational Analysis ◽  
Using Data ◽  
Grey Relational ◽  
A Company

Financial ratios are used in a variety of ways today. Empirical research is getting bigger, with a special focus on predicting business failure, the strength of a company, investment decision making, etc. This chapter focuses on two methodologies suitable to deal with many data to evaluate business performance. They are data envelopment analysis and grey relational analysis. The empirical part of the chapter conducts an empirical analysis with the aforementioned two approaches. Firms are ranked based on their performances and detailed interpretations are obtained so that managers within businesses can get useful information on how to utilize such an approach to modelling. This study implicates that using the two mentioned approaches can be useful when making investment decisions based on many data available for the decision maker. This is due to the methodology being suitable to handle big data and correctly quantifying the overall financial performance of a company.

scholarly journals Data Envelopment Analysis for Malaysia Courier Services Performance and Customer Satisfaction

2020 ◽  
Vol 5 (3) ◽  
pp. 25-33
Author(s):  
Teoh Yeon Kin Teoh ◽  
Suzanawati Abu Hasan ◽  
Siti Nur Atikah Zahari
Keyword(s):  
Data Envelopment Analysis ◽  
Customer Satisfaction ◽  
Business Performance ◽  
Efficiency Score ◽  
Analytical Models ◽  
Data Envelopment ◽  
Service Companies ◽  
Courier Service ◽  
Key Issues ◽  
Using Data

One of the key issues of the current courier services in Malaysia is the efficiency of the courier itself. In today's competition, many factors have recognized that influence the efficiency of courier services. Hence, numbers of analytical models and formu las were introduced to measure the efficiency of courier service. This paper presents a practical approach for identifying the level of customers’ satisfaction towards courier service companies using Data Envelopment Analysis and four courier services whic h were Poslaju, City - Link Express , J&T Expres s, and GD Express in Hulu Terengganu were selected. Data Envelopment Analysis is chosen in this study because it can deal with complex connections between several inputs and outputs on performance evaluation iss ues. The input criteria considered in this study are assurance, empathy, reliability, responsiveness, tangibility, and price. Meanwhile, customer satisfaction is chosen as the output criteria. The results showed that Poslaju is ranked as the most efficient company, followed by City - Link Express in second and J&T Express as the third. The least efficiency score obtained makes GD Express as the last ranked courier service among these four courier services. Furthermore, the results are mainly influenced by the input criteria of assurance, empathy, and tangibility. This study helps the customer to select the most efficient courier service that can save their time, money, and energy. Finally, this study also can guide courier services to decide on which criteria are effective to be improved to enhance their business performance.

Performance management of OECD countries on Covid-19 pandemic: a criticism using data envelopment analysis models

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa İsa Doğan ◽  
Volkan Soner Özsoy ◽  
H. Hasan Örkcü
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Oecd Countries ◽  
Data Envelopment ◽  
Discrimination Power ◽  
Content Type ◽  
Rate Of Spread ◽  
Number Of Patients ◽  
The World ◽  
Using Data

Purpose The Covid-19 pandemic spread rapidly around the world and required strict restriction plans and policies. In most countries around the world, the outbreak of the disease has been serious and has greatly affected the health system and the economy. The factors such as the number of patients with chronic diseases, the number of people over 65 years old, hospital facilities, the number of confirmed Covid-19 cases, the recovering Covid-19 cases and the number of deaths affect the rate of spread of Covid-19. This study aims to evaluate the performances of 21 Organisation for Economic Co-operation and Development (OECD) countries against the Covid-19 outbreak using three data envelopment analysis (DEA) models. Design/methodology/approach In this study, the performance of 21 OECD countries to manage the Covid-19 process has been analysed weekly via DEA which is widely used in various practical problems and provides a general framework for efficiency evaluation problems using the inputs and outputs of decision-making units. Findings The analysis showed that 11 countries out of 21 countries were efficient for selected weeks. According to the DEA results from the 20-week review (09 April 2020–20 August 2020), information about the course of the epidemic prevention and the normalization process for any country can be obtained. Originality/value In this study, due to the problem of the discrimination power of DEA, the cross-efficiency model and the super-efficiency model also used. In addition, the output-oriented model was preferred in this study for Covid-19 management efficiency.

Od Business Intelligence do Business Performance Management

2012 ◽  
pp. 39-43
Author(s):  
Janusz Nesterak ◽  
Bernard Ziębicki
Keyword(s):  
Performance Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Performance Management

Zarządzanie przedsiębiorstwem we współczesnych warunkach wymaga stosowania zaawansowanych systemów umożliwiających gromadzenie i przetwarzanie informacji do postaci użytecznej w podejmowaniu decyzji zarządczych. Możliwości takie stwarzają systemy klasy Business Intelligence. Systemy te obecnie są już szeroko stosowane w krajowych przedsiębiorstwach. Ostatnio coraz popularniejsze stają się systemy określane mianem Business Performance Management, które są traktowane jako kolejna generacja Business Intelligence. Istota systemów Business Performance Management dotychczas nie była szeroko prezentowane w literaturze krajowej. Część badaczy zajmujących się tą tematyką traktuje wymienione kategorie systemów jako tożsame. W artykule przedstawiono istotę systemów Business Performance Management oraz omówiono różnice pomiędzy tą kategorią rozwiązań i systemami Business Intelligence. Omówiono także elementy tworzące systemy Business Performance Management. Przedstawiono również metodykę oraz korzyści stosowania Business Performance Management w przedsiębiorstwach. (abstrakt oryginalny)

Data Envelopment Analysis (DEA) in the Psychological Sciences

2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart
Keyword(s):  
Data Envelopment Analysis ◽  
Aggressive Behavior ◽  
Personality Traits ◽  
Educational Administration ◽  
Latent Variable ◽  
Organizational Management ◽  
Data Envelopment ◽  
Targeted Interventions ◽  
Component Skills ◽  
Using Data

Using methods like linear regression or latent variable models, researchers are often interested in maximizing explained variance and identifying the importance of specific variables within their models. These models are useful for understanding general ideas and trends, but often give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method with roots in organizational management that make such insights possible. Unlike models mentioned above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides readers with a brief history and past usages of DEA from organizational management, public health, and educational administration fields, while also describing the underlying math and processes behind said model. This paper then extends the usage of this method into the psychology field using two separate studies. First, using data from the Project KIDS dataset, DEA is demonstrated using a simple view of reading framework identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying and comparing new subsets of readers. Three new subsets of readers were identified using this method, with direct implications leading to more targeted interventions. Second, DEA was used to measure individuals’ efficiency in regulating aggressive behavior given specific personality traits or related skills. This study found that despite comparable levels of component skills and personality traits, significant differences were found in efficiency to regulate aggressive behavior on the basis of gender and feelings of provocation.

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