A novel application of data envelopment analysis and production trade-offs for efficiency evaluation of banking institutions : the case for Pakistan

A growing body of empirical literature has attempted to measure the efficiency of banking sector using Data Envelopment Analysis (DEA) by focusing on different aspects of banking services. However, standard DEA models often fail to sufficiently discriminate between efficiency scores of banks particularly with small sample size. Moreover, sometimes knowledge about different banking operations is available that needs to be incorporated in the evaluation method to assess their impact on the performance of banks. This research deals with the efficiency evaluation of banking sector through DEA based on additional information about multiple banking operations without which efficiency is generally overestimated. The main objective of this thesis is to develop a better informed DEA model that is capable of incorporating additional information about different bank specific characteristics by overcoming the problem of poor discrimination. For this purpose, the current study has proposed a novel methodological integration of DEA with production trade-offs in banking context and named it “DEATOB Framework”. This framework is universal in nature and can be applied to banking sectors of other countries. The study also aims to provide the empirical application of DEATOB Framework for which a sample of 29 commercial banks of Pakistan is selected. The results indicate that this framework evaluates banks on the basis of additional characteristics and provides better discrimination between good and bad performers as compared to the standard DEA model. The final objective is to extend the proposed framework to other banking models. For this purpose, the profitability model is chosen considering the profit maximization goal of banks and a separate PDEATOB Framework is developed. An empirical application of this framework is also provided to demonstrate its workability. This thesis also provides an insight on scale efficiency and relationship of efficiency with the banks size and ownership after application of the proposed frameworks

Design and performance evaluation of failure prediction models

Prediction of corporate bankruptcy (or distress) is one of the major activities in auditing firms’ risks and uncertainties. The design of reliable models to predict distress is crucial for many decision-making processes. Although a variety of models have been designed to predict distress, the relative performance evaluation of competing prediction models remains an exercise that is unidimensional in nature. To be more specific, although some studies use several performance criteria and their measures to assess the relative performance of distress prediction models, the assessment exercise of competing prediction models is restricted to their ranking by a single measure of a single criterion at a time, which leads to reporting conflicting results. The first essay of this research overcomes this methodological issue by proposing an orientation-free super-efficiency Data Envelopment Analysis (DEA) model as a multi-criteria assessment framework. Furthermore, the study performs an exhaustive comparative analysis of the most popular bankruptcy modelling frameworks for UK data. Also, it addresses two important research questions; namely, do some modelling frameworks perform better than others by design? and to what extent the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Further, using different static and dynamic statistical frameworks, this chapter proposes new Failure Prediction Models (FPMs). However, within a super-efficiency DEA framework, the reference benchmark changes from one prediction model evaluation to another one, which in some contexts might be viewed as “unfair” benchmarking. The second essay overcomes this issue by proposing a Slacks-Based Measure Context-Dependent DEA (SBM-CDEA) framework to evaluate the competing Distress Prediction Models (DPMs). Moreover, it performs an exhaustive comparative analysis of the most popular corporate distress prediction frameworks under both a single criterion and multiple criteria using data of UK firms listed on London Stock Exchange (LSE). Further, this chapter proposes new DPMs using different static and dynamic statistical frameworks. Another shortcoming of the existing studies on performance evaluation lies in the use of static frameworks to compare the performance of DPMs. The third essay overcomes this methodological issue by suggesting a dynamic multi-criteria performance assessment framework, namely, Malmquist SBM-DEA, which by design, can monitor the performance of competing prediction models over time. Further, this study proposes new static and dynamic distress prediction models. Also, the study addresses several research questions as follows; what is the effect of information on the performance of DPMs? How the out-of-sample performance of dynamic DPMs compares to the out-of-sample performance of static ones? What is the effect of the length of training sample on the performance of static and dynamic models? Which models perform better in forecasting distress during the years with Higher Distress Rate (HDR)? On feature selection, studies have used different types of information including accounting, market, macroeconomic variables and the management efficiency scores as predictors. The recently applied techniques to take into account the management efficiency of firms are two-stage models. The two-stage DPMs incorporate multiple inputs and outputs to estimate the efficiency measure of a corporation relative to the most efficient ones, in the first stage, and use the efficiency score as a predictor in the second stage. The survey of the literature reveals that most of the existing studies failed to have a comprehensive comparison between two-stage DPMs. Moreover, the choice of inputs and outputs for DEA models that estimate the efficiency measures of a company has been restricted to accounting variables and features of the company. The fourth essay adds to the current literature of two-stage DPMs in several respects. First, the study proposes to consider the decomposition of Slack-Based Measure (SBM) of efficiency into Pure Technical Efficiency (PTE), Scale Efficiency (SE), and Mix Efficiency (ME), to analyse how each of these measures individually contributes to developing distress prediction models. Second, in addition to the conventional approach of using accounting variables as inputs and outputs of DEA models to estimate the measure of management efficiency, this study uses market information variables to calculate the measure of the market efficiency of companies. Third, this research provides a comprehensive analysis of two-stage DPMs through applying different DEA models at the first stage – e.g., input-oriented vs. output oriented, radial vs. non-radial, static vs. dynamic, to compute the measures of management efficiency and market efficiency of companies; and also using dynamic and static classifier frameworks at the second stage to design new distress prediction models

Nonparametric efficiency and productivity change measurement of banks with corporate social responsibilities : the case for Ghana

This thesis has twofold objectives. The first is to develop a framework based on the existing theory and method of Data Envelopment Analysis (DEA) for measuring performance of financial firms that have the dual goals of profit maximisation and Corporate Social Responsibilities (CSRs). The second is to examine the impact of banking regulatory reforms including bank ownership, specialisation, and capitalisation types on the average efficiency and frontier differences of banking subgroups. The objectives are achieved using the standard DEA, the metafrontier analysis and the global frontier differences (GFD). DEA can handle multidimensional inputs and outputs without specifying specific functional forms. CSR is conceptually justified and modelled as an additional output into the banking intermediation approach. Two DEA models, one with CSR and another without CSR are measured and compared. Parametric and nonparametric tests and regressions are utilised to support, empirically, the relevance of CSR in bank performance evaluation. Do foreign banks outperform private-domestic and state banks? Should banks diversify their products or focus in narrow range of products and services? Are listed banks more efficient than non-listed banks? The second part of the thesis contributes to the extant literature by answering these questions using the metafrontier analysis and the GFD to provide new evidence on the effect that the entry of foreign and private-domestic banks, universal banking and listing of banks on the stock market, have on bank performance. Banks are segmented into groups based on their bank-specific attributes and their average efficiencies and bestpractice differences compared. Relevant policy recommendations are drawn from the analysis for both the banking regulator and bank management. The final methodological contribution extends the GFD by defining a further decomposition of the global frontier shift, into components that indicate whether an observation is situated in a more or less favourable location in the production possibility set. Consequently, a four-factor “Newly-decomposed Malmquist productivity change index” is proposed. The index and its decompositions have potentially interesting policy implications, which are illustrated using the empirical data on Ghanaian banks. The index is in the spirit of the standard Malmquist index but the intuition is that some components can be used to draw conclusions about productivity changes for a whole population of firms whilst others determine whether individual firms are in favourable locations and/or moving towards locations that are more favourable over time. More importantly, arguably, a listed, universal or foreign bank can be located in a favourable position and move towards location that is more favourable by virtue of its bank-specific attributes or by contributing more towards CSR. These factors are explored and policy measures prescribed in the final contribution of the thesis

Agricultural Cooperative in the Face of the Challenges of Globalization, Sustainability and Digitalization

The enormous contribution of agricultural cooperative societies to the rural world has not gone unnoticed. This is corroborated by many international entities. The International Cooperative Alliance estimates that 12% of the world's population is linked to one of the 3 million cooperatives that exist worldwide. Therefore, cooperative societies are not a marginal phenomenon. In relation to the role played by agricultural cooperatives in the world, it should be said that the agricultural cooperative is an enterprise unconditionally and stably linked to the rural environment, to the farmer and the stockbreeder. For this reason, it plays a leading role in the local economy and in the fixation of the population to the territory, thus contributing to the balance and management of the territory, which makes them true agents of rural development. On the other hand, cooperative societies have been the guarantors of the structuring of agriculture in rural areas in many countries. These organizations constitute the main structured, organized, professionalized and stable network established throughout the territory, in contact with the rural environment, with the capacity to communicate with and influence farmers and stockbreeders. They directly or indirectly provide much of the employment in the rural world and cooperative societies by nature develop their activity under cooperative principles and values that make them exponents of socially responsible enterprises and, therefore, are the key to sustainable development, as promulgated by the United Nations through the SDGs

Sustainability, Digital Transformation and Fintech: The New Challenges of the Banking Industry

In the current competitive scenario, the banking industry must contend with multiple challenges tied to regulations, legacy systems, disruptive models/technologies, new competitors, and a restive customer base, while simultaneously pursuing new strategies for sustainable growth. Banking institutions that can address these emerging challenges and opportunities to effectively balance long-term goals with short-term performance pressures could be aptly rewarded. This book comprises a selection of papers addressing some of these relevant issues concerning the current challenges and opportunities for international banking institutions. Papers in this collection focus on the digital transformation of the banking industry and its effect on sustainability, the emergence of new competitors such as FinTech companies, the role of mobile banking in the industry, the connections between sustainability and financial performance, and other general sustainability and corporate social responsibility (CSR) topics related to the banking industry. The book is a Special Issue of the MDPI journal Sustainability, which has been sponsored by the Santander Financial Institute (SANFI), a Spanish research and training institution created as a collaboration between Santander Bank and the University of Cantabria. SANFI works to identify, develop, support, and promote knowledge, study, talent, and innovation in the financial sector

Incorporating declared capacity uncertainty in optimizing airport slot allocation

Slot allocation is the mechanism used to allocate capacity at congested airports. A number of models have been introduced in the literature aiming to produce airport schedules that optimize the allocation of slot requests to the available airport capacity. A critical parameter affecting the outcome of the slot allocation process is the airport’s declared capacity. Existing airport slot allocation models treat declared capacity as an exogenously defined deterministic parameter. In this presentation we propose a new robust optimization formulation based on the concept of stability radius. The proposed formulation considers endogenously the airport’s declared capacity and expresses it as a function of its throughput. We present results from the application of the proposed approach to a congested airport and we discuss the trade-off between the declared capacity of the airport and the efficiency of the slot allocation process

INTERNAL AUDIT CHARACTERISTICS AND QUALITY OF ACCOUNTING INFORMATION IN NIGERIA

The basic goal of Accounting is to provide enabling accounting information for reliable decision-making. The quality level of this accounting information comes from the company's governance practices, thereby emphasizing the importance of corporate governance in companies. Recently, following the financial crises resulting in accounting scandals, attention has been moving towards Internal Audit Function as an important factor in the structure of Corporate Governance. This paper therefore examined the extent of the relationship between internal audit function and the quality of accounting information of companies. The study adopted the Survey research design. The research instrument employed was Questionnaire which was administered to internal auditors of the “Big Four”. Linear regression analysis was employed in the analysis of the data collected with the use of Statistical Packages for Social Sciences (SPSS). The results revealed that there is a significant relationship between the internal audit characteristics and the quality of accounting information. It was recommended that in order to provide credibility to the financial statement, there should be a law in place mandating attachment of internal auditors report to the financial statemen

Assessment of Socio-Economic Sustainability and Resilience after COVID-19

The pandemic period has caused severe socio-economic damage, but it is accompanied by environmental deterioration that can also affect economic opportunities and social equity. In the face of this double risk, future generations are ready to be resilient and make their contribution not only on the consumption side, but also through their inclusion in all companies by bringing green and circular principles with them. Policy makers can also favor this choice