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Understanding Secondary Data in Management Research: A Comprehensive Guide

This resource provides an insightful overview of secondary data in research, detailing its types, benefits, and techniques for effective literature reviews. It highlights the savings in time and cost, enhances data accuracy, and aids in hypothesis development. The guide emphasizes the importance of evaluating secondary data for accuracy, credibility, and bias. Additionally, practical examples illustrate how to apply these concepts in real-world scenarios, such as opening a new coffee shop by analyzing relevant secondary data sources. Ideal for students and professionals alike.

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Understanding Secondary Data in Management Research: A Comprehensive Guide

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  1. Research in Management Class 2 – Secondary Data Dr. Michele Parent Based on slides by Dr John Nadeau Week of January 17, 2010

  2. Chapter 3 Objectives • Know the types of secondary data available • Appreciate the benefits of secondary data • Know how to write a literature review • Understand model conceptualization and hypothesis formulation

  3. Types of Secondary Data • Secondary data – information not gathered for an immediate research study, but rather for some other purpose. • Internal secondary data • External secondary data

  4. Benefits for Using Secondary Data • Saves time and money • Secondary data will become more accurate • Data may not be available otherwise • Useful in eliminating information gaps • Assists in developing hypotheses and in problem definition • Aids in the evaluation of primary data

  5. Literature Reviews • Collection of materials on a topic • Summary and synthesis of sources • Purpose – guide the reader through the topic, identify areas of controversy, and formulate questions for further research • Objectives • Provide background • Clarify thinking • Reveal whether information already exists • Define important constructs • Suggest methodological approaches

  6. Evaluating Secondary Data • Purpose • Accuracy • Consistency • Credibility • Methodology • Bias

  7. Internal Sources • Traditional • Sales invoices • Accounts receivable reports • Quarterly sales reports • Sales activity reports • Other sources

  8. External Sources • Popular Sources • Scholarly Sources • Government • North American Industry Classification System (NAICS) • Guidebooks/Directories • Commercial/Syndicated (e.g. Consumer Panels)

  9. Syndicated - Consumer Panels • Benefits • Lower cost than primary data collection methods • Rapid availability and timeliness • Accurate reporting • High level of specificity • Weakness • Sampling error • Turnover • Response bias

  10. Discussion Question You are planning to open a coffee shop in one of two areas in your community. What secondary data would you be interested in and where would you locate it?

  11. Developing a Conceptual Model

  12. Example: A Model of Profitability in Professional Sport (NHL) Source: Nadeau and O’Reilly (2006) “Developing a Profitability Model for Professional Sport Leagues: The Case of the National Hockey League” , International Journal of Sport Finance, 1, 46-62.

  13. Hypotheses • A hypothesis is an empirically testable though yet unproven statement developed in order to explain phenomena • Types of hypotheses include • Null or Alternate • Nondirectional • Inverse (negative) directional • Direct (positive) directional

  14. Exercise Team: Members & Topics Secondary Data Hunt

  15. Next Class • Hand in Group memo or set meeting for Individual Research Proposal • Exploratory and Observational Research • Read Chapter 4

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