A STUDY ON ORGANISATIONAL POLITICS IN HIGHER EDUCATIONAL INSTITUTIONS AT TIRUCHIRAPPALLI DISTRICT (POWERS, BEHAVIOR AND PERFORMANCE OF THE EMPLOYEES)

K. Maithily; Dr. R. Sheeba

A STUDY ON ORGANISATIONAL POLITICS IN HIGHER EDUCATIONAL INSTITUTIONS AT TIRUCHIRAPPALLI DISTRICT (POWERS, BEHAVIOR AND PERFORMANCE OF THE EMPLOYEES)

Authors

K. Maithily

Research Scholar, Department of Commerce, Bishop Heber College (Autonomous), Tiruchirappalli, Tamil Nadu, India

Dr. R. Sheeba

Assistant Professor, Department of Commerce, Bishop Heber College (Autonomous), India.

Keywords:

Job Involvement, Job Turnover Intension', Organizational Politics, Perception Of Organizational Politics, Quality Of Education, Teaching Facilities.

Synopsis

Purpose: Politics, institutional performance, administrative authority, and SDG4 are all examined and analyzed in this study. Specifically, by illuminating the interplay between the way future generations are taught and their perceptions of the power dynamics inside organizations. The researcher had constructed a model to facilitate the dissemination of information on the study field. This model provides a framework for thinking about how employees' impressions of organizational politics affect their actions and productivity on the job. Insight into the means through which individuals or groups might exert influence in order to attain their aims. It's important to assess the benefits and drawbacks of working in a politically charged environment for the sake of all employees.
The moderating model was analyzed using data from two hundred college staffs in Trichy. The information was gathered from both primary and secondary resources.
Finding: The researchers determined that a lack of office politics correlates with a reduced likelihood of employee turnover. Workers now pay little attention to office politics. Despite seldom encountering politics, employees work with a great deal of involvement. The company has to keep an eye on the workers to ensure their needs are met in a politically charged workplace. What are the approaches to assess politics may be explored further by incorporating other dimensions in the variables. Methods for Dealing with Politics? Future studies might potentially focus on other industries.
Practical implication: The organization has to keep an eye on the workers to ensure their needs are met in a politically charged workplace.

References

[1] https://www.google.com/search?q=definition+of+politics+in+organization+by+authors.

[2] https://www.civilserviceindia.com/subject/Management/notes/the-individual-processes-power-and-politics.html.

[3] Ahmed, S., Farooqi, M. T. K., & Iqbal, A. (2020). Influence of Organizational Politics on University Teachers’ Performance. Global Social Sciences Review, V(II), 341–355. https://doi.org/10.31703/gssr.2020(v-ii).33.

[4] Arshad, M., Masood, M., & Amin, G. (2013). Effects of Performance Appraisal Politics on Job Satisfaction, Turnover Intention and Loyalty to Supervisor. International Review of Management and Business Research, 2(3), 653–673. http://www.irmbrjournal.com/papers/1379412617.pdf.

[5] Bhattarai, G. (2021). Perception of organizational politics and employee performance: Antidotal role of impression management. Problems and Perspectives in Management, 19(1), 103–115. https://doi.org/10.21511/ppm.19(1).2021.09

[6] Bodla, M. A., & Danish, R. Q. (2008). The Perceptions of Organisational Politics and Work Performance: Exploring the Differences in Public and Private Sector. The International Journal of Knowledge, Culture, and Change Management: Annual Review, 8(4), 123–132. https://doi.org/10.18848/1447-9524/cgp/v08i04/50562

[7] Cohen,A. & Vigoda,E. (1999).Politics and the workplace: An empirical examination of the relationship between political behavior and work out comes, Public Productivity& ManagementReview,22(3),389-406.129MAHMOODAHMADBODLA,RIZWAN QAISERDANISH

[8] Delle, E. (2013). The Influence of Perception of Organizational Politcs on Employee Job Involvement and Turnover Intentions: Empirical Evidence from Ghanaian Organizations. European Journal of Bussiness and Managment, 5(9), 151–161.

[9] Iqbal Khan, Tariq, Rudsada Kaewsaeng-on, Mubashar Hassan Zia, Sheraz Ahmed, and Abdul Zahid Khan. 2020. “Perceived Organizational Politics and Age, Interactive Effects on Job Outcomes.” SAGE Open 10 (3). https://doi.org/10.1177/2158244020936989.

[10] RAJKUMAR, R., & SUDHA, G. (2013). FIBROMYALGIA–AN OUTCOME OF WORK LIFE IMBALANCE.

[11] Senthilkumar, K., & Rajkumar, R. (2019). A study on women entrepreneurship in Tanjore region. International Conference on Management Research, 2(2), 9-13.

[12] Senthilkumar, K., & Rajkumar, R. (2018). Analysis of consumer behaviour towards various cement brands grades with special reference to Thanjavur district. International Conference on Management Research, 1(1), 4-8.

[13] Sudha, G., & Rajkumar, R. (2014). Influence of gender on better balance. Journal of Business Studies, 1(SPL), 47-54. University of Jaffna.

[14] Sudha, G., & Rajkumar, R. (2012). Work life balance for working women - Is it so tough. Sankhya - International Journal of Management and Technology, 3(2), 100-103. SIMS Publication.

[15] Senthilkumar, K., K. Iyyappan, and S. Subramaniam. "Customer awareness on electronic banking in Thanjavur town—An empirical study." 2012-International Conference on Management Issues in Emerging Economies (ICMIEE). IEEE, 2012.

[16] Senthilkumar, K. (2014). Medical tourism: Changing scenario in health care sector. Holy Grace Management Review, 6(1), 118-122.

[17] Senthilkumar, K. (2014). Analysis of consumer behavior towards various cement brands & grades with special reference to Thanjavur district. Emerging Paradigms in Management Research, 3(2), 4-9.

[18] Senthilkumar, K. (2012). A comparative study on innovation management of health care services in rural India with other developing countries of Asia. In Conference Proceedings of Strategic Trends on Innovations & Creativity in Management Practices, 2(1), 31.

[19] Senthilkumar, K. (2012). Challenges and opportunities with special reference to Indian cement industry. Sankhya International Journal of Management and Technology, 3(1), 252-255.

[20] Senthilkumar, K. (2011). Evolution and evaluation of Indian cement industry. International Journal of Applied Management Research (IJAMR), 3(1), 779-784. IJAMR.

[21] Kasthuri, S., and A. Nisha Jebaseeli. "An artificial bee colony and pigeon inspired optimization hybrid feature selection algorithm for twitter sentiment analysis." Journal of Computational and Theoretical Nanoscience 17.12 (2020): 5378-5385.

[22] Kasthuri, S., and A. Nisha Jebaseeli. "Study on social network analysis in data mining." International Journal of Analytical and Experimental Modal Analysis (IJAEMA),(UGC CARE-A Journal), Impact Factor 6.3 11.VIII (2019): 111-116.

[23] Kasthuri, S., and A. Nisha Jebaseeli. "Review analysis of Twitter sentimental data." Bioscience Biotechnology Research Communications (BBRC),(UGC CARE Journal-Web of Science), Special Issue 13.6 (2020): 209-214.

[24] Kasthuri, S., and A. Nisha Jebaseeli. "Social network analysis in data processing." Adalya Journal,(UGC CARE-B Journal–Web of Science), Impact Factor 5 (2020): 260-263

[25] Kasthuri, S., and A. Jebaseeli Nisha. "Review on social network analysis in data mining." Infokara Res 8.12 (2019): 1168-1172.

[26] Ambika, G., and D. P. Srivaramangai. "A study on security in the Internet of Things." Int. J. Sci. Res. Comput. Sci. Eng. Inform. Technol 5.2 (2017): 12-21.

[27] Ambika, G., and P. Srivaramangai. "Encrypted Query Data Processing in Internet Of Things (IoTs): CryptDB and Trusted DB." (2018).

[28] Ambika, G. "Advanced Human Activity Recognition: Leveraging Adaptive Neural Networks and Diverse Machine Learning Algorithms on IoT Data." Fuzzy Systems and Soft Computing, vol. 19, no. 02(V), 2024, pp. 11–17.

[29] G. Ambika, “IoTCryptDB: Encrypted query data processing in Internet of Things,” International Journal of Scientific Research in Computer Science Applications and Management Studies, vol. 7, no. 4, p. 18, Jul. 2018.

[30] Ambika, G. "Processing Over Encrypted Query Data in Internet of Things (IoTs): CryptDBs, MONOMI and SDB." International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, Issue-8, 2018, p. 8.

[31] Shanti, M. A., and K. Saravanan. "Knowledge data map—A framework for the field of data mining and knowledge discovery." International Journal of Computer Engineering & Technology 8.5 (2017): 67-77.

[32] Shanti, M. A., and K. Saravanan. "An Effect of Data Mining Techniques in Public Healthcare-A Case Study." International Journal of Civil Engineering and Technology 9.9 (2018): 115-122.

[33] Shanti, M. A. "A Study to Analyse the Quality of Work Life with Special Reference to Private Sector Bank Employees in Kumbakonam Town of Thanjavur District." Our Heritage, vol. 68, 2020.

[34] Shanti, M. A. "Earthquake Prediction Using SVM Based Time Predictable Technique." International Journal of Computer Sciences and Engineering (IJCSE), vol. 7, no. 4, 2019, pp. 2347–2693.

[35] Shanti, M. A., and K. Saravanan. "Wartortle—A Data Mining and Knowledge Discovery Suite for Data Analysis and Reporting." International Journal of Applied Engineering Research, vol. 13, no. 10, 2018, pp. 7835–7841.

[36] Amalarethinam, George. "DI, Vaaheedha Kfatheen. S,“Max-min Average Algorithm for Scheduling Tasks in Grid Computing Systems”." International Journal of Computer Science and Information Technologies 3.2 (2012): 3659-3663.

[37] Amalarethinam, G. D. I., and V. S. Kfatheen. "Max-Min average algorithm for scheduling tasks in grid computing systems." International Journal of Computer Science and Information Technologies 3.2 (2014): 3659-62.

[38] Sumathy, P., and Ahilan Chandrasekaran. "An Optimized Image Pre-Processing Technique for Face Emotion Recognition System." Annals of the Romanian Society for Cell Biology 25.6 (2021): 6247-6261.

[39] Agilan, C. "A Comprehensive Survey on Emotion Recognition Techniques Using Image Processing." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96569-96579. Indian Journal of Natural Sciences.

[40] Agilan, C. "Enhancing Human Emotion Detection through Optimization-Driven CNN Models." Indian Journal of Natural Sciences, vol. 16, no. 90, 2025, pp. 96422-96433. Indian Journal of Natural Sciences.

[41] Agilan, C. "Energy Efficient Clustering and Dynamic Slot Allocation for Wireless Sensor Networks." IEEE Explore, vol. 1109, ACOIT62457, 2024, https://ieeexplore.ieee.org/xpl/conhome/10939027/proceeding.

[42] Agilan, C. "Optimization-Based Clustering Feature Extraction Approach for Human Emotion Recognition." The Scientific Temper, vol. 15, no. spl.04, 2024, pp. 24-31. Web of Science.