rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Large databases for strategy research
  name:
    name part: Erickson, G. Scott
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Rothberg, Helen N.
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: enk
    date issued: 2019
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: This case illustrates how to identify and apply existing data sets as an alternative to conducting time-consuming primary research. In particular, with the advent of big data and the explosion in the availability of useful data, more and more existing data will make itself available to researchers, particularly in the business disciplines. The case covers the application of readily available financial data to research on the intangible assets (knowledge assets) of organizations. A well-known metric, the Tobin's q, is evaluated, including different forms and applications, providing insight into decisions to be made about how existing data best fit a particular research study. Extensions are provided, illustrating how data can be enhanced over time and in different applications. In this case, competitive intelligence activity is combined with the knowledge development (Tobin's q) data as is information on big data capabilities. Guidance is provided on data combination, the added potential from such combinations, and the limitations. As in all research, one of the key points is to understand the origins of the data, the meaning, and how best to apply them.
  target audience: specialized
  note: G. Scott Erickson, Helen N. Rothberg.
  note: Includes bibliographical references and index.
  subject:
    topic: Business
    topic: Data processing
  subject:
    topic: Research
    topic: Methodology
  subject:
    topic: Gestion
    topic: Informatique
  subject:
    topic: Recherche
    topic: Méthodologie
  subject:
    topic: Business
    topic: Data processing
  subject:
    topic: Research
    topic: Methodology
  classification: HF5548.2 .E75 2019
  classification: 658.054
  related item:
    title info:
      title: SAGE Research Methods
      part name: Cases
  identifier: 9781526477026
  identifier: 1526477025
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 190103
    record change date: 20240923170422.7
    record identifier: in00005495378
    language of cataloging:
      language term: eng