ABSTRACTThe current era is the wonderful age of information and knowledge; the age of incredible acceleration of technology and creativity. In recent years, a wave of implementation and operation of office automation systems has swept the country and many organizations have shown a desire to use these systems. The main objective of this study is to investigate the impact of office automation systems on enhancing employee performance at Semnan Province Department of Tax Administration, Iran. This research is a descriptive-survey research in terms of method and, in terms of objective, can be classified as an applied research. The statistical population of this study is all employees of the General Department of Taxation of Semnan Province with a degree equivalent to and above high school diploma to 317 people. The statistical sampling method of this research, according to its subject and nature, is stratified sampling with appropriate allocation for employees and educational classes. The Cochran formula yielded an estimate of the sample population equal to 174 participants. Data are analyzed using the SPSS software. Diagrams have drawn by the EXCEL software and structured equations have calculated by the AMOS software. All research hypotheses are verified and the results show that the office automation system is effective in improving employee performance. Manuscript profile

This paper builds upon the foundation laid by Shetty's research, aiming to enhance our understanding of decision-making unit (DMU) efficiency. In doing so, we introduce a novel approach that offers a more comprehensive method for ranking DMUs. By aggregating this information, we establish a benchmark against which the efficiency of individual DMUs can be assessed. This approach not only simplifies the evaluation process but also provides a more holistic perspective, enabling researchers to discern patterns and trends across the entire dataset. The method proposed in the aforementioned paper proved to be efficacious particularly in scenarios where the number of efficient DMUs was limited, enabling the model to accurately rank them. Therefore, as the number of efficient DMUs escalates, the effectiveness of the proposed methodology in accurately ranking them may diminish. Efficient Decision Making Units (DMUs) construct the defining hyperplane; therefore, the exclusion of these contributing efficient DMUs in an attempt to derive their ranking, amidst an increase in their numbers, will impede the acquisition of efficiency scores for virtual DMUs. Hence, achieving a comprehensive ranking of all DMUs is unattainable unless those positioned precisely on the defining hyperplane are included. In this complementary method, we delineate an anti-ideal virtual DMU encompassing all DMUs situated on the corresponding defining hyperplane, which may be oriented in various directions. Then, we use this method for ranking efficient DMUs. As the proposed method aligns with the aforementioned study, it incorporates all the advantages, including simplicity and stability, and notably eliminates the identified flaw.

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