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Santhoshkumar, R.
- The Impact on Talent Management in B-School Institutions with Reference to Bangalore City-A Study
Authors
1 Dept. of Management Studies, Adhiyamaan College of Engineering, Hosur, Krishnagiri, MS University, Tirunelveli, Tamil Nadu, IN
2 Department of Business Administration, Thiyagarajar College of Arts and Science, Madurai, Tamil Nadu, IN
Source
Review of Professional Management- A Journal of New Delhi Institute of Management, Vol 9, No 2 (2011), Pagination: 105-109Abstract
This research paper examines the applicability of Talent Management in B-schools in Bangalore city. The paper, at the start, defines critical concepts of talent management at all levels of B-school managements. The primary data have been collected from 100 different levels of faculty in B-schools and then hypotheses are tested on the basis of the measure of applicability of talent management.
The analysis draws following conclusions. The faculty feels that Talent Management creates the competitive Advantage for the B-schools and they believe that their B-schools recruitment policy is leveraged towards recruiting top talent. Finally, the study offers some suggestions to B-schools for effective talent Management as well as for better selection process for recruitment of highly skilled faculty.
Keywords
Talent Management, Retain, Skilled, Faculty.- Renewable Energy Source in Home
Authors
1 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, IN
2 Arunkumar is with the Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, IN
3 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering, IN
Source
Fuzzy Systems, Vol 9, No 6 (2017), Pagination: 122-126Abstract
A smart community is a distributed system consisting of a set of smart homes which utilize the smart home scheduling technique to enable customers to automatically schedule their energy loads targeting various purposes such as electricity bill reduction. Smart home scheduling is usually implemented in a decentralized fashion inside a smart community, where customers compete for the community level renewable energy due to their relatively low prices. Typically there exists an aggregator as a community wide electricity policy maker aiming to minimize the total electricity bill among all customers. This paper develops a new renewable energy aware pricing scheme to achieve this target. We establish the proof that under certain assumptions the optimal solution of decentralized smart home scheduling is equivalent to that of the centralized method, reaching the theoretical lower bound of the community wide total electricity bill. In addition, an advanced cross entropy optimization technique is proposed to compute such a pricing scheme, which is also integrated with smart home scheduling. The simulation results demonstrate that our pricing scheme facilitates the significant reduction of both the community wide electricity bill and individual electricity bills compared to the state-of-the-art smart home scheduling technique. In particular, the community wide electricity bill can be reduced to only 0.06% above the theoretic lower bound.