Book contents
- Frontmatter
- Contents
- List of figures and tables
- 1 Introduction
- PART 1 BASIC CONCEPTS
- PART 2 WHAT DO WE KNOW OF INFORMATION BEHAVIOUR?
- PART 3 DISCOVERING AND USING KNOWLEDGE OF INFORMATION BEHAVIOUR
- 8 Research approaches
- 9 Research methodologies in action
- 10 Using knowledge of information behaviour to design information systems
- 11 Conclusion
- Appendix: Defining ‘information’ and ‘information behaviour’
- Index
9 - Research methodologies in action
from PART 3 - DISCOVERING AND USING KNOWLEDGE OF INFORMATION BEHAVIOUR
Published online by Cambridge University Press: 09 June 2018
- Frontmatter
- Contents
- List of figures and tables
- 1 Introduction
- PART 1 BASIC CONCEPTS
- PART 2 WHAT DO WE KNOW OF INFORMATION BEHAVIOUR?
- PART 3 DISCOVERING AND USING KNOWLEDGE OF INFORMATION BEHAVIOUR
- 8 Research approaches
- 9 Research methodologies in action
- 10 Using knowledge of information behaviour to design information systems
- 11 Conclusion
- Appendix: Defining ‘information’ and ‘information behaviour’
- Index
Summary
Introduction
The purpose of this chapter is not to list and discuss the range of methodologies and associated methods available, but rather to present three case studies which illustrate fundamental dimensions of difference in approach, giving a flavour of what they can offer and what might be their limitations. The first is a hypothesis-testing approach in which numerical data is quantitatively analysed in order deductively to test a predefined hypothesis. The second entails a qualitative analysis of textual data in order inductively to explore a phenomenon in a more open-ended way.
Hypothesis testing: a deductive quantitative study
Anand and Gomez-Mejia (2014) report a study that sought to test a number of specific hypotheses that had been developed based on a review of relevant theory and previous research. The study focused on the information-seeking behaviour of the members of top management teams in a selection of small American entrepreneurial firms. In particular, they sought to investigate the effects of types of reward structure on the seeking of information from outside ‘affiliate’ organizations (customers and vendors). The researchers hypothesized that:
• The higher the proportion of income that is made up of cash incentive payments (relative to base pay) the more top managers will engage in information seeking from external affiliate sources. This effect will be more pronounced in higher-technology-intensive firms.
• Base rates of pay will have a moderating effect. This moderating effect will be stronger in the case of higher-technology-intensive firms.
• Information seeking from external affiliate sources will decrease when cash incentives are linked to aggregate performance.
The reasoning behind these hypotheses was built on risk-bearing theory, and was as follows:
• The larger the proportion of cash incentives relative to base pay, the greater the risk for executives in that they are more dependent on immediate and short-term performance for their payment. They are therefore more likely to ‘play it safe’ and focus on ‘harvest’ strategies which emphasize maximizing income from existing popular products (as opposed to engaging in more fundamental or revolutionary but risky developments).
• Information from affiliate sources is most likely to be helpful in supporting harvest strategies and maximizing short-term performance rather than leading to more fundamental longer-term changes.
- Type
- Chapter
- Information
- Introduction to Information Behaviour , pp. 195 - 216Publisher: FacetPrint publication year: 2015