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7-1
Chapter 7
Secondary Data
Searches
7-2
Learning Objectives
Understand the . . .
• purpose and process of exploratory
research
• two types and three levels of
management decision-related secondary
sources
• five types of external information and the
factors for evaluating the value of a source
and its content
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Learning Objectives
Understand . . .
• the process for conducting a literature
search
• data mining and how internal data mining
techniques differ from literature searches.
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Exploratory Phase
Search Strategy
Discovery/ Analysis
Secondary Sources
Expert
Interview
Search
Strategy
Individual
Depth Interviews
Group
Discussions
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Exhibit 7-1 Integration of
Secondary Data into the
Research Process
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Objectives of Secondary
Searches
• Expand understanding of management
dilemma
• Gather background information
• Identify information that should be
gathered
• Identify sources for and actual questions
that might be used
• Identify sources for and actual sample
frames that might be used
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Conducting a
Literature Search
Define management dilemma
Consult books for relevant terms
Use terms to search
Locate/review secondary sources
Evaluate value of each source
and content
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• Whiteboard technology makes the discussion of
symptoms relevant to the managementresearch question hierarchy easier
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Levels of Information
Primary
Sources:
Memos
Letters
Interviews
Speeches
Laws
Internal records
Secondary
Sources:
Encyclopedias
Textbooks
Handbooks
Magazines
Newspapers
Newscasts
Tertiary
Sources:
Indexes
Bibliographies
Internet
search engines
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Exhibit 7-2 Integrating
Secondary Data
7-11
The
U.S. Government
is the
world’s largest
source of data
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Information Sources
Indexes/
Bibliographies
Directories
Dictionaries
Types
Handbooks
Encyclopedias
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Evaluating Information
Sources
Purpose
Format
Scope
Evaluation
Factors
Audience
Authority
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Exhibit 7-4 Review of
Advanced Search Options
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Exhibit 7-5 Advanced
Searching Process
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Exhibit 7-9 The Evolution of
Data Mining
Evolutionary Step
Investigative Question
Enabling Technologies
Characteristics
Data collection (1960s)
“What was my average
total revenue over the last
five years?”
Computers, tapes, disks
Retrospective, static data
delivery
Data access (1980s)
“What were unit sales in
California last
December?”
Relational databases
(RDBMS), structured
query language (SQL),
ODBC
Retrospective, dynamic
data delivery at record
level
Data navigation (1990s)
“What were unit sales in
California last December?
Drill down to
Sacramento.”
Online analytic
processing (OLAP),
multidimensional
databases, data
warehouses
Retrospective, dynamic
data delivery at multiple
levels
Data mining (2000)
“What’s likely to happen
to Sacramento unit sales
next month? Why?”
Advanced algorithms,
multiprocessor
computers, massive
databases
Prospective, proactive
information delivery
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Exhibit 7-10
Data Mining in Business
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Exhibit 7-12
Data-Mining Process
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Key Terms
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Bibliography
Bibliographic Database
Data Mart
Data Mining
Data Visualization
Data Warehouse
Dictionary
Directory
Encyclopedia
Exploratory research
Handbook
Individual depth interview
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Index
Literature search
Portal
Primary sources
Search query
Secondary sources
Source evaluation
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Purpose
Scope
Authority
Audience
Format
• Tertiary sources