http://localhost:8081/jspui/handle/123456789/119 2025-07-01T10:59:18Z http://localhost:8081/jspui/handle/123456789/17375 Title: PERFORMANCE OF PUBLIC SECTOR BANKS: A FUNCTION OF HUMAN RESOURCES DEPLOYMENT ANDEXPENDITURE Authors: Kumar, Suman Abstract: In the growing economics like India, banking sector is reckoned as hub and barometer of the financial system. This sector has been recognized as the major pillar of the Indian economy which plays a predominant role in the sustainable economic development of country. Hence, there is a need to utilize HR expenditure as strategic investment. Thus, balanced HR expenditure and HR deployment at optimum level is vital for overall performance of banking organization. Human Resource Deployment planning is an integral approach for managing such dynamic and fast changing situations. Since man is one of the primary sources of wealth creation, proper deployment of human potential will have an immense pay off for any organization. The effective deployment of the HR of an organization is the main aspect of HR planning. HR deployment under the HR planning is now one of the effective means for accomplishing the business of the organization. The HR utilization refers to phenomenon in which available HR is deployed effectively for the maximum achievement of organizational or national goals and objectives by the individuals or by collective efforts. Human capital can he rcgwded as business need to invest in the asset to ensure its survival and growth. The major employee expenditure comes from direct indirect forms of compensation, usually wages and fringe benefits. The focus on HR expenditure with a rich history of data based research, including staffing, training, workplace health, employee attitudes, and employee turnover, which also represent some of the most important strategic HR function. Efficiency is the central terms used in assessing and measuring the performance of organizations. Performance, in both profit and non-profit organizations, can be defined as an appropriate combination of efficiency and effectiveness. The data is gathered from 26 to 28 'I' PSBs existed in India during the F.Y. 2003-04 to F.Y. 2011-12. The input and output variables of PSBs are available in the form of secondary data. In this study we have selected Data Envelopment Analysis (DEA) for measuring the efficiency of banks because DEA is best suited analysis tool for measuring the banking efficiency all over the world. DEA is a relatively new "data oriented" approach for evaluating the performance of a set of peer entities called Decision Making Units (DMUs) which convert 91 multiple inputs into multiple outputs. DEA, which is a non-parametric, multi-factor, productivity analysis tool, considers multiple input and output measurements in evaluation of relative efficiencies of DMUs suc.h as banks. In this study DEA frontier software is being used, which is the latest software. The DEA frontier used Excel solver and it does not set any limit on the number of DMUs. DEA frontier has been designed to run as many as DEA models as possible to overcome the limitations set by standard Excel solver. DEA frontier has a version "DEA Frontier Open Solver Xlam" that is designed for use with the open source COIN- or CBC optimization engine via open solver. This version of DEA frontier can solve large signed DEA problems. Through the above mentioned software, the efficiency of DMUs can be measured by its different models like multiplier models, envelopment models, returns to scale models, super efficiency models. However in this study only those models are selected for which different DEA analysis literatures on banking are available. The main difficulty in any application of DEA is •1 in the selection of inputs and outputs. The criticality in making selection of these inputs and outputs is quite subjective. The study presents the details of the analyses carried out to examine the rehionslups of the variables represented in the theoretical models. This study has been carried on two models. The first model of this study examines the relation between HR deployment and performance of PSBs with number of employees and fixed assets as the independent variables and investment, loan / advances and non-interest income as dependent variables. The second model of this study examines the relationship between HR expenditure and performance of PSBs with expenditure on wages as independent variables and with deposit and non-interest income as dependent variables. Banking sector occupies a crucial place in undertaking the development efforts and acts as a vehicle for socio-economic transformation as well as catalyst to economic growth. The banks are backbone of any financial system and after independence there has been tremendous change in baking practices. If the assessment of staff deployment is carried out on the basis of activity analysis and productivity criteria, it could be possible to attain higher business volume with minimum staff thus HR expenditure can be substantially reduced and bank profitability improved. Results show these models establish a link between HR expenditure and performance of PBs. The results under the return-to-scale show that maximum PSBs are on DRS. So for bringing them at CRS or optimum level it is necessary to ascertain quality of inputs i.e. proper iv HR deployment. The slack analysis also suggests regarding the improvement in HR deployment and control on expenditure on HR towards attaining the efficiency. The super efficiency model also suggests where the requirements of adjustment of inputs lies like 4 number of employees and expenditure on wages for getting more efficiency. In this way this study not only established empirical relation between HR deployment and HR expenditure with the performance of PSBs but also suggests the diagnosis for improvement and accordingly management of PSBs can take decision. 2013-07-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17374 Title: ORGANIZATIONAL CLIMATE AND ROLE EFFICACY - AS PREDICTORS OF MANAGERIAL EFFECTIVENESS Authors: Kumar, Umesh Abstract: exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed respectively to obtain the factor structure and fitness of the obtained factor pattern on the focused sample. In third phase of analysis, study hypotheses were tested; test of differences such as independent sample t test and one way ANOVA and multiple hierarchical regressions were employed. Mediation and moderated mediation was checked by using bootstrap approach through structural equation modeling (SEM). Conclusively, research fmdings suggest that the constituents of organizational climate and role efficacy can boost managerial effectiveness. Additionally, fmdings exhibited the importance of demographic variables on the casual paths between organizational climate, role efficacy and managerial effectiveness. Conversely, study indicates little evidences that demographic variables cause the occurrence of perceptual difference in study variables (organizational climate, role efficacy and managerial effectiveness). The study has many key implications. Firstly, it established the reliability and validity of instruments for measuring the organizational climate, role efficacy and managerial effectiveness in Indian context. Subsequently, it exhibited the functions of organizational climate and role efficacy on managerial effectiveness through testing a complex mediation and conditional mediation model. Therefore, added in the existing literature. Present work also recommends the relevance of employing SEM in pursuance of complex casual behavior models. Strategies to achieve organizational competitiveness through effectiveness of organizational members could be drawn on these research findings 2013-03-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17356 Title: PERFORMANCE EVALUATION AND FLOW ALLOCATION 04 DECISION MODEL FOR SUSTAINABLE SUPPLY CHAIN Authors: Jakhar, Suresh Kumar Abstract: The thesis proposes a sustainable supply chain performance evaluation, partner selection and flow optimization decision making model. Both qualitative as well as quantitative criteria are considered to gauge the sustainable supply chain performance, having the objectives of economic growth, environmental protection, and societal development. A three echelon supply chain network is considered which includes different suppliers, manufacturers, and distributors. An integrated methodology of structural equation modeling (SEM), fuzzy analytical hierarchy process (FAHP), and fuzzy multi-objective linear programming (FMOLP), has been applied to the proposed model. The methodology is realized in three stages. In the first stage. SEM approach is applied to estimate the weightage of the sustainable supply chain performance evaluation criteria and their sub criteria. In the second stage, FAlIP is applied in finding the relative weightage of available alternatives for partnership at different stages of the supply chain. The relative weights of the alternatives are calculated with respect to the sustainable supply chain performance evaluation criteria and their sub criteria. The weights estimated by SEM approach and FAHP approach are combined together to obtain the overall relative weightings of the supply chain alternatives available at different stages of the chain. Finally, in the third stage FMOLP approach is applied to partner selection and flow allocation to optimize the overall sustainable performance. The proposed model is demonstrated with a sample of Indian apparel industry supply chain network. For sustainable supply chain performance evaluation, 3 criteria and 19 sub criteria are selected based on the analysis of existing literature and subsequently followed by suggestions from the experts in academia as well as practitioners working in the Indian apparel industry supply chain network. The 3 selected criteria are sustainable supplier partnership performance, sustainable production performance, sustainable delivery and logistics performance. A structured questionnaire was designed to obtain the respondents' perception to know how important the above mentioned criteria and their sub criteria are. The questionnaire was administered using a mail survey to 496 organizations having at least 10 years of their operational experience. 278 usable respoiises were received which result in 56% response rate. A second order confirmatory SEM model is formulated to estimate the relative weightage of above mentioned criteria and their sub criteria based on the responses. The results indicate satisfactory reliability, validity, and overall model fit. The reliabilities of the different measures included in the model ranges from 0.95 to 0.98 thus indicating good item reliability. The composite reliabilities for all the constructs are above the threshold value of 0.70 (ranging from0.95 to 0.98), indicating high reliability for all the constructs (Fornell and Larcker, 1981). The average variance extracted values ranged from 0.93 to 0.98, exceeding the 0.50 threshold value and indicates good convergent validity. The overall fit indices for the proposed model with, Chi square/df= 1.62, RMSEA = 0.048, GFI = 0.914, CFl = 0.985, indicates an acceptable fit (Fornell and Larcker, 1981).The results indicate that highest weightage is given to sustainable production performance (0.71) followed by sustainable supplier partnership performance (0.62) and finally, sustainable delivery and logistic performance (0.47) to improve the overall sustainable apparel industry supply chain performance. To demonstrate the FAI-IP approach application, a case study of Indian apparel industry's supply chain network is exercised. In the case study, a set of 3 fabric suppliers, apparel manufacturers, and distributers are considered at each stage respectively. The relative weightages of the suppliers, manufacturers, and distributors are calculated by the FAHP approach with respect to each sustainable supply chain performance evaluation criteria and their sub-criteria. The weights estimated by SEM approach (for sustainable supply chain performance evaluation criteria and their sub-criterion) are combined with the relative weights calculated by the FAI-IP approach (for suppliers, manufacturers and distributors) to obtain the overall relative weights of the suppliers, manufacturers and distributors. These overall weights are used in the FMOLP model formulation for flow allocation decision making. In the FMOLP model formulation, the expected demand at 3 distribution centers, for 3 different time periods are considered. The five objective functions as; (1) Maximizing the Total Value of Sustainable Purchasing Performance, (2) Maximizing the Total Value of Sustainable Production, (3) Maximizing the Total Value of Sustainable Deliver and Logistics Performance, (4) Minimization of Total Cost, (5) Minimization of Total Carbon Emission are considered. By using the Zimmerman's approach, the FMOLP problem is solved. The optimization results indicate that the supply chain partners are selected and flow quantities are allocated to them who perform better on overall sustainable supply chain performance evaluation criteria. The salient characteristics of different analytical tools are combined together to bring out a reliable and effective evaluation process. The evaluation structure proposed in this thesis provides a concise approach to supply chain managers to monitor their supply chain performance with the relative importance of sustainability criteria and their sub criteria in Indian apparel industry supply chain network. Furthermore, this can help them to stimulate continuous improvements. The thesis proposes an idea that, for effective sustainability practices in the apparel industry supply chain, the proposed methodology can be used for partner selection and flow allocation decision making. 2013-03-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17348 Title: EFFICIENCY AND MARKET RETURN OF BANKING SECTOR 4 IN INDIA: AN EMPIRICAL EVALUATION Authors: Sharma, Dipasha Abstract: Aftermath of deregulation, globalisation of economies, entry of foreign and private banks, the strong presence of capital market and global financial instability have created opportunities as well as many challenges in front of Indian banking sector to sustain its performance and profitability with the efficient flow of funds from borrowers to savers. Therefore, these regulatory, macro-economic and bank-specific factors may have a significant contribution to the overall performance of Indian banking sector which can be measured in terms of efficiency, productivity 10 and return/ value to investors. The motivation of this study is to perform a robust performance evaluation of Indian banking sector using frontier analysis techniques and investigate a statistically significant association between efficiency/ productivity and market performance aspect of Indian banks. Thus, this study aims to address following research questions in light of regulatory changes, financial crisis and the impact of market forces in Indian banking sector, namely: I. Whether the regulatory variables and micro-economic variables (including deregulation. policy changes, ownership. origin and bank-specific variables) influence the performance of the Indian banking sector measured in terms of efficiency and productivity? AM Whether the performance of the Indian banking sector measured in terms of efficiency and productivity iflfluenced by the uncontrollable macro-economic conditions (Financial disruption, change in Gross Domestic product (GDP), and inflation)? Have market performance of Indian banks statistically affected by their operational efficiency and productivity and if so then how much variation in market performance are explained by the operational performance? Can market performance and operational performance of Indian banks be linked together to develop a new measure of performance? This study adopts a stepwise analysis approach to achieve its ultimate objective. development of a new measure of efficiency linking both the operational efficiency and market performance of Indian banks. V variables which includes bank-specific variables (bank size, bank's expense-preference behaviour, bank's diversification strategy, non-performing assets, capital adequacy, profitability), macro-economic conditions (GDP growth, inflation rate and dummy variab!e to capture global financial crisis) and regulatory variab!es(ownership structure, origin of banks, age, listing on stock exchange, dummies for foreign origin specifications) using Tobit regression and Panel regression models respective!y. Resu!ts ofTobit pooled and Panel data regression exhibit bank size, bank's diversiFication strategy, bank's expense-preference behaviour, capital adequacy and profitabi!ity in the bank-specific variables as major determinants of efficiency of the Indian banking sector. Among the macro-economic indicators. GDP growth and inflation are found to be the significant drivers of efficiency of banks whereas age and listing on a stock exchange as qualitative variables have a significant relationship with the efficiency !evel of banks. Results of panel data regression models advocate that the productivity growth of banks driven by rnain!y bank's expense-preference behaviour, non-performing assets, GDP growth and inflation with the dummy representatives of financia! crisis, listing on the stock exchange and ownership structure. As the second stage, resu!ts exhibit positive and statistica!!y significant association between the listing on stock exchanges and efficiency! productivity !eve!. This study deve!ops statistical models between efficiency/ productivity measures and market performance indicators (arinual stock market return as market performance indicator and Market Va!ue Added & Economic Value Added as shareho!der va!ue indicators). To assess the statistica!ly significant association beteen market performance indicators and efficiency/ productivity indicators, a number of panel data regression models were deve!oped in the third stage of the study. The results of panel data regression models exhibit that the banks' operation endow with significant information towards annual market return and market value added. As the study found a significant association between efficiency measures and market performance indicators and considering this, the study further develops a new measure of efficiency termed as 'Market Return Efficiency'- maximisation of stock market return using a given level of inputs and outputs using Stochastic Frontier Analysis (SFA). 2013-05-01T00:00:00Z