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Kapur, Sandeep
- Comparison of Full Profile Approach and Self-Explicated Approach of Conjoint Analysis
Abstract Views :394 |
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Authors
Affiliations
1 Department of Business Management Punjab Agriculture University Ludhiana, IN
2 Standard Chartered Bank Ludhiana, IN
1 Department of Business Management Punjab Agriculture University Ludhiana, IN
2 Standard Chartered Bank Ludhiana, IN
Source
Journal of Management Research, Vol 8, No 1 (2008), Pagination: 45-56Abstract
This study empirically compares the full profile and self-explicated approach of conjoint analysis. Both the approaches were tested on the same set of respondents. Empirical evidence revealed that the effect of task presentation on importance ratings obtained through both the techniques were not the same rank correlation though positive, was not significant. Thus, there is no difference between attribute importance ranking by both the groups. However, differences in the overall rankings under full profile approach and self-explicated approach existed. Further, there is no difference between the part-worth values obtained through full profile and self-explicated approaches. In case of comparison of partworths, in seven attribute levels, the chi-square test was significant and in case of other seven attribute levels it was not found to be significant. As a result, we cannot conclude that these two techniques are similar or different, because as per this study, there is partial relation between the results.Keywords
Toothpaste, Colgate, Close-up, Pepsodent, Conjoint Analysis, Full Profile Approach and Selfexplicated ApproachReferences
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- Resource Utilization in Cloud Computing using Hybrid Algorithm
Abstract Views :189 |
PDF Views:0
Authors
Affiliations
1 Guru Kashi University, Sardulgarh Road, Talwandi Sabo - 151302, Punjab, IN
1 Guru Kashi University, Sardulgarh Road, Talwandi Sabo - 151302, Punjab, IN
Source
Indian Journal of Science and Technology, Vol 9, No 43 (2016), Pagination:Abstract
Objectives: The proposed algorithm represents a multivariate selection and security mechanism for the data which has to be kept at the cloud server. The paper also focuses on the prioritization of the data so that for a given span of time data with high priority is processed first. Methods/Statistical Analysis: The paper has presented a unique way to select encryption algorithm so that miss-utilization is prevented. The paper has included lattice based encryption NTRU (N-th degree Truncated Polynomial Ring Unit) and key based encryption for the security of data. Findings: The unused data bits have been optimized using GA (Genetic Algorithm) and the results have been calculated in terms of total number of completed jobs with priority and the CPU Utilization made against the Jobs. Application/Improvements: Resources which will be utilized at the cloud server would cost the user with some amount but there is optimization of resources in terms of CPU utilization and job completion.Keywords
Cloud Computing, Genetic Algorithm, NTRU Algorithm, Resource Utilization, Security.- Evaluation of Bearish Option Payoffs in USD-INR Market
Abstract Views :319 |
PDF Views:0
Authors
Affiliations
1 School of Business Studies, Punjab Agricultural University, Ludhiana, Punjab, IN
1 School of Business Studies, Punjab Agricultural University, Ludhiana, Punjab, IN