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Title: Integrating data envelopment analysis and balanced scorecard for improving organizations' performance assessment
Author: Ellelly, Nouran Nabil A. M.
ISNI:       0000 0004 7966 9144
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 2019
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In today's business environment, organizations aim to improve their performance to compete efficiently in a highly competitive global market. Thus, the concept of performance measurement has received significant attention from both academics and practitioners. It has been recognized that performance measurement should take into consideration all aspects of the organization and reflect the organization's multidimensional nature, including both financial and non-financial factors. Consequently, the Balanced Scorecard (BSC) has been developed to address such a need. Applying the BSC is changing the way top managers administer their organizations and would require them to devote adequate attention to both financial and non-financial aspects, both internally and externally. Although the BSC has been applied in various areas, there are some pitfalls associated with using it as a tool for evaluating organization performance. The criticisms include first, the fact that BSC lacks a formal implementation methodology; second, adopting a broad set of interrelated indicators may lead to information overload and cause complicated optimization problems; third, BSC does not possess the ability to specify a common scale of measurement; fourth, it does not have a standardized baseline or benchmark required to distinguish between different organization' performance; and fifth, BSC does not include a mathematical model or a weighting scheme. Recent studies suggest that these limitations can be reduced by combining BSC with other techniques such as Data Envelopment Analysis (DEA), as these two techniques complement each other. The purpose of this thesis is to develop an improved performance assessment framework by combining BSC and DEA approaches to assess organizations' performance and then applying this model to assess these organizations' efficiency levels. The targeted population is all organizations traded on the London Stock Exchange and included in the FTSE All-Share Index, and secondary data are obtained from the financial statements published in the "DataStream" database. The final data set used for the current study consists of 307 organizations covering a period of five years, from 2012 to 2016. The study also adds to the extant literature by conducting cross-industry level analysis using the combined DEA-BSC model. Hence, it provides managers in different industries with insight to evaluate organizations' efficiency level to improve their competitive plans and long-term objectives. The findings of the study suggest that for the seven different industries included in the analysis, the financial perspective of BSC has the greatest effect on the efficiency levels of the xv organizations. Additionally, the findings provide an overview of the stability status of each industry by examining the efficiency scores for each industry over the five-year period. The findings provide a broader time horizon and take into account changes that happened in organisations' performance outcomes over time. Furthermore, the results of the analysis categorize organizations in terms of the level of efficiency, identify the possible reasons for such inefficiencies in performance, and provide guidance on potential improvements.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available