4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence
http://hdl.handle.net/11718/14018
ICADABAI-20152024-03-29T04:40:35ZTransforming Big Data Into Actionable Insights
http://hdl.handle.net/11718/14092
Transforming Big Data Into Actionable Insights
Chauhan, Rohit
In order for big data to be refined and made actionable, it will require the pressure of advanced analytics and then marketing adoption of the learnings found within the unrefined “big” source. This paper will show that four emerging data trends will enable the necessary evolution from big data to advanced customer segment analytics. This new approach will be enhanced by transactional data and secured by new technology and compliance regulations. Data must transform the customer experience, create operational efficiency and define new business models.
Four emerging trends will drive the growth of big data and its transition to advanced analytics: mobile, social, cloud-based data and the Internet of Things. Companies must apply the right analytics pressure to create diamonds of data rather than unrefined blocks. In order to make data actionable it will need to be secured, subjected to proper compliance and enhance the consumer experience. Data and technology are allowing us to answer very difficult questions that have not yet been asked e.g., purchase sequence.
The complete data set that emerges from the four sources mentioned as well as Internet traffic analytics has come very close to producing a 360 degree picture of the customer. In order to see that picture with clarity, transactional data is critical. Transactional data will produce new levels of actionable customer segments that define the future of advanced analytics. Prescriptive analytics represent the nirvana state for the discipline. Companies should strive to approach that ideal rather than become consumed with admiring their past descriptive analytics successes. Integrating analytics at key points of intersection in real-time will allows maximization of the benefits of insights to the bottom line.
2015-01-01T00:00:00ZReal Estate Investment Selection and Empirical Analysis of Property Prices: Study of Select Residential Projects for Gurgaon, India
http://hdl.handle.net/11718/14090
Real Estate Investment Selection and Empirical Analysis of Property Prices: Study of Select Residential Projects for Gurgaon, India
Sehgal, Sanjay; Upreti, Mridul; Pandey, Piyush; Bhatia, Aakriti
The paper studies the residential micromarket of the Gurgaon region of the Delhi NCR, India to identify key determinants of real estate investment selection and perform empirical analysis of property prices. Primary survey suggested that developer’s goodwill is the most important factor for investors incase of under construction residential properties (forward projects). Other factors include location, amenities, project density and construction quality. These factors enjoy almost equal importance for selecting completed (spot projects). The factor information can be used to construct property quality rating classes. High risk adjusted returns were provided by high quality spot projects and low quality forward projects. Long run equilibrium relationship was observed between spot and forward prices with the former playing the lead role. GDP and non food bank credit are the macroeconomic variables that can predict property prices. Highest pre-tax Internal Rate of Return was observed for forward projects in first quarter holding itself while for spot projects it was around 8th quarter. The research has implication for property developers, real estate investors and market regulators. The study contributed to real estate investment literature for emerging markets.
2015-01-01T00:00:00ZEstimating Export Demand: An Empirical Analysis
http://hdl.handle.net/11718/14089
Estimating Export Demand: An Empirical Analysis
Chowdhury, Joy; Mahawar, Aman; Laha, Arnab Kumar
Export of a country plays major role since it affects many economic indicators/parameters/variables like current account deficit, foreign exchange reserves etc. Generally all the economies try to boost up the export sector and formulate strategy for the higher growth in export. Thus it is very important to investigate the determinants of the export demand for an economy. In this paper we have tried to find out the determinants of bilateral export which will be helpful for the policy makers in formulating policy. We have considered 15 countries which mean
105 country pairs. We have estimated the bilateral export demand function by using gravity model. We found that distance between two countries, product of GDP between two countries, openness, and real effective exchange rate are significantly affecting the bilateral export. We also found that exports are higher for countries sharing the common border. Moreover, common language has also positive impact on the bilateral export.
2015-01-01T00:00:00ZOccupational Stress among custodians of civic law: An exploratory study
http://hdl.handle.net/11718/14088
Occupational Stress among custodians of civic law: An exploratory study
Majumdar, Malini N.; Dutta, Avijan; Sengupta, Kalyan
Purpose of the study: The purpose of this paper is to identify the factors responsible for creating occupational stress among West Bengal Police Officials.
Design/methodology/approach – The authors employ an existing standardized scale on Occupational Stressors with some modifications resulting from pilot survey as well as in depth and focus group interviews. The researchers draw on a data set of 310 structured questionnaires covering four hierarchies from Sub Inspectors to ADC/ ASP and above from 5 districts and one commisionerate under West Bengal Police jurisdiction to understand their perceptions about the stressors that police officials often encounter while discharging their duties.
Findings: A confirmatory factor analysis (CFA) has confirmed the five constructs in the data set namely Organizational Stressors (OS), Hierarchical Stressors (HS), Situational Stressors (SS) and Environmental Stressors (ES) and Personal Stressors (PS). CFA suggested a good model fit with GFI>0.9, NFI>0.9, IFI>0.9 and CFI>0. Goodness of fit is initially analyzed through Chi-square value of our proposed model (2.81, df 73, p=.000).
Research Implications: Police are supposed to maintain law and order of the society. On many occasions owing to some internal and external influence they are unable to deal with the situation those results into helplessness at their professional as well as personal life. The paper reveals the major occupational stressors and suggests various measures to deal with these effectively and reduce the negative impact of them.
2015-01-01T00:00:00Z