Methods and Challenges in Data Collection
1. FOREWARD
Authors as Adams, Khan, Hafiz and Raeside (1), suggest some method for data collection, basing on the situation, warning from possible threats to the validity and reliability of data collected.
Whatever the method of data collection chosen (observations, experimentation, survey, interviews, diary method, case study, data storage, triangulation), there are several hypothesis that need to be considered since the beginning (1); the challenges born from the nature of the research and level of detail the researcher want to reach, then by time and budget available, so careful consideration and planning of data collection is required.
There are some common principles, for examples try to eliminate as much as possible human errors, analyze all useful data instead of the only one which seems to fit in the theory, run multiple tests to check eventual errors.
Collecting data is crucial in many different field of business interest, e.g. from concurrency evaluation to create a model for the estimation of pipe price, before to meet the supplier for the final negotiation.
For example, first strategy adopted from bid and proposal department, for the evaluation of piping price impact, is to evaluate raw material steel price and add a certain percentage which consider total cost of ownership. Second strategy can consider different elements which compose final price, starting from source of data instead of estimate a percentage only.
This is one of the key elements: Bebell, O’Dwyer, Russel and Hoffmann (2) studied the importance of technology in the last past years to help researcher to evaluate and confute data availability and validity, for example triangulating the same data. In any case, quantitative methods doesn’t contextualizes in the situation, considering for example the market situation, the human ability to concretize business relationship, …
2. CHALLENGES
3.1 Source of data
World is full of data and opinion, the advent of technology and
Authors as Adams, Khan, Hafiz and Raeside (1), suggest some method for data collection, basing on the situation, warning from possible threats to the validity and reliability of data collected.
Whatever the method of data collection chosen (observations, experimentation, survey, interviews, diary method, case study, data storage, triangulation), there are several hypothesis that need to be considered since the beginning (1); the challenges born from the nature of the research and level of detail the researcher want to reach, then by time and budget available, so careful consideration and planning of data collection is required.
There are some common principles, for examples try to eliminate as much as possible human errors, analyze all useful data instead of the only one which seems to fit in the theory, run multiple tests to check eventual errors.
Collecting data is crucial in many different field of business interest, e.g. from concurrency evaluation to create a model for the estimation of pipe price, before to meet the supplier for the final negotiation.
For example, first strategy adopted from bid and proposal department, for the evaluation of piping price impact, is to evaluate raw material steel price and add a certain percentage which consider total cost of ownership. Second strategy can consider different elements which compose final price, starting from source of data instead of estimate a percentage only.
This is one of the key elements: Bebell, O’Dwyer, Russel and Hoffmann (2) studied the importance of technology in the last past years to help researcher to evaluate and confute data availability and validity, for example triangulating the same data. In any case, quantitative methods doesn’t contextualizes in the situation, considering for example the market situation, the human ability to concretize business relationship, …
2. CHALLENGES
3.1 Source of data
World is full of data and opinion, the advent of technology and
References: 1) Adams, John; Khan, Hafiz T A; Raeside, Robert (2007) “Research Methods for Graduate Business and Social Science Students. Sage India” 2) Damian Bebell, Laura M. O’Dwyer, Michael Russell, Tom Hoffmann - 2010 Concerns, Considerations, and New Ideas for Data Collection and Research in Educational Technology Studies 3) Richard W. Swartz and Charles Hancock – 2002 Data collection through web-based Technology 4) Reetta Raitoharju1, Eeva Heiro2, Ranjan Kini3, and Martin D’Cruz - 2009 Challenges of multicultural data collection and analysis: experiences from the health information system research