Purpose Companies are looking for certain employability attributes and personality traits while recruiting and selecting suitable candidates for their organizations and there is a mismatch in what the higher educational institutes are grooming the graduates. There is therefore a need for proactive management of career development of students. The paper aims to discuss these issues. Design/methodology/approach This research involved an exploratory study on a database of 445 students enrolled and passed out from the five batches of two years business management course from 2012 to 2016 in a business school in India, to identify the parameters which led to generating good placement package for them. The impact of independent variables of live industry projects, communication skills, academic performance, classroom attendance and co-curricular activities on the placement package was studied using stepwise regression analysis. Findings The study revealed that industry projects, co-curricular activities, communication skills and academic performance were the key enablers which helped the students become industry ready and employable. Research limitations/implications This research involved the study of effect of only four independent variables- academic performance, communication skills, participation in live industry projects and co-curricular activities on the placement package received by the students. There is a scope of extending this study by considering the effect of other variables such as educational background (graduation stream, performance in that stream, scores attained in competitive exams, etc.), family background (family income, occupation of parents and their qualification, family size, etc.), geographical background (rural, urban or semi-urban) and work experience on the final placement package received by the student. Practical implications Employability depends on a multitude of factors which can be broadly put under three categories of knowledge, skills and attitude (Khare, 2014). Universities need to work right from the first year toward developing a wider range of employability skills rather than focusing only on developing generic competencies in the students. The results of regression analysis indicate that the impact of different predictors for a good placement package vary in strength and a student needs to focus on balancing all of them in order to get a good placement. Educational institutes can replicate this study to identify the overall employability of their students. Originality/value With the increase in demand from industry for work ready graduates, there is a huge pressure on educational institutes to prepare their students for the corporate world. Such studies would help the institutes in focusing on various parameters which would ultimately assist students pursuing courses in post graduate level like business management or other master courses in getting good placements.

The liberalising of Business Education in 1990 by the Indian Government has resulted in a large number of management schools offering management courses at graduate and post graduate levels. In the last five years, the number of B-school seats has grown three times. Excluding the few top B-schools like IIMs, most of the B-schools in the country are churning “unemployable” graduates. The paper uses convenience sampling to collect data from students and faculty members of different B-schools in order to find out their usage of digital technologies like Whatsapp for teaching and learning. It also explains the use of digital technology in curriculum designing. This further helps them in placing students in good profiles and better packages as they are able to share more practical real time insights with them.

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Cloud computing provide many services on demand to their end users, and customer can borrow those resources from CSP on only pay-per-use basis. There are many issues arises day by day in cloud computing environment. Job scheduling is one of the major issues. In scheduling we are focusing on to execute maximum no. of user's jobs by utilizing minimum no. of resources which is available in cloud computing. Also scheduling of user's jobs defines how to allocate an appropriate resource to these request come from end users to finish task in minimum time. In this research paper, we are introducing cloud computing, job scheduling and Artificial Neural Network (ANN) based task allocation model has been proposed to increase the performance of the cloud computing system and also find the optimal system cost.