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A Digital Approach:A Trend Analysis in Data Collection and Challenges in Ito Industry


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1 Jain University, India
 

Research outcome and its quality are based on various parameters. Data is one of the important deciding factors for the quality of the research. Data collection is an important stage in every research; it could be primary or secondary data collection. So, it is critical for the researcher to have different tools, techniques, approaches and strategies in order to succeed in the process of data collection as per the research plan. This paper aims to explain the various approaches, techniques, challenges and few notable factors during our data collection process in our formal research titled as "An analysis and effective implementation of matrix organization in IT Outsourcing industry". Obviously, the challenges are part of the research however it is important for the researcher to understand the complexity, focus on people, changing the strategy to contact respondents, find the alternate solution and move forward with the research project. All these continuous and focused efforts result in getting a good response from the people which plays a vital role in the research. Also, in this paper, we will discuss few patterns which we have observed during data collection process and which are related to people, society, psychological and organizational behavior.

Keywords

Respondents, Strategy, Approach, Organization, Observations, Matrix Organization, Data Collection.
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  • William Martorelli and Wolfgang Benkel, The Forrester Wave: Global Infrastructure Outsourcing, Q1 2015, January 13, 2015, retrieved from https://www.forrester.com/William-Martorelli?objectid=BIO801
  • http://www.goglobalworx.com/solutions/survey-data-collection/
  • L.Sudershan Reddy & Kannamani.R. (2015). “The challenges of matrix organization system in IT outsourcing industry”. International journal of information technology & computer sciences perspectives Volume 4, Number 2, April to June 2015.
  • L.Sudershan Reddy & Kannamani.R. (2016), “A Pilot Study– An analysis and Effective Implementation of Matrix Organization in IT Outsourcing Industry”. Asia Pacific Journal of Research, Vol: I. Issue XXXVIII, April 2016.
  • https://en.wikipedia.org/wiki/Data_collection
  • C R Kothari (1997). “Research Methodology – Methods & Technique”. New Age International Publishers
  • R Pannerselvam (2008). “Research Methodology”, PHI Learning Pvt. Ltd. 6th Printing

Abstract Views: 284

PDF Views: 122




  • A Digital Approach:A Trend Analysis in Data Collection and Challenges in Ito Industry

Abstract Views: 284  |  PDF Views: 122

Authors

L. Sudarshan Reddy
Jain University, India
R. Kannamani
Jain University, India

Abstract


Research outcome and its quality are based on various parameters. Data is one of the important deciding factors for the quality of the research. Data collection is an important stage in every research; it could be primary or secondary data collection. So, it is critical for the researcher to have different tools, techniques, approaches and strategies in order to succeed in the process of data collection as per the research plan. This paper aims to explain the various approaches, techniques, challenges and few notable factors during our data collection process in our formal research titled as "An analysis and effective implementation of matrix organization in IT Outsourcing industry". Obviously, the challenges are part of the research however it is important for the researcher to understand the complexity, focus on people, changing the strategy to contact respondents, find the alternate solution and move forward with the research project. All these continuous and focused efforts result in getting a good response from the people which plays a vital role in the research. Also, in this paper, we will discuss few patterns which we have observed during data collection process and which are related to people, society, psychological and organizational behavior.

Keywords


Respondents, Strategy, Approach, Organization, Observations, Matrix Organization, Data Collection.

References