Finding natural groups in data: an application to strategic group research

Graham Leask, Rakesh Bissoondeeal, Jane Binner

Research output: Working paper

Abstract

The best way of finding “natural groups” in management research remains subject to debate and within the literature there is no accepted consensus. The principle motivation behind this study is to explore the effect of choices of method upon strategic group research, an area that has suffered enduring criticism, as we believe that these method choices are still not fully exploited. Our study is novel in the use of a variety of more robust clustering and validation techniques, rarely used in management research, some borrowed from the natural sciences, which may provide a useful and more robust base for this type of research. Our results confirm that methods do exist to address the concerns over strategic group research and adoption of our chosen methods will improve the quality of management research.
Original languageEnglish
Place of PublicationBirmingham (UK)
PublisherAston University
VolumeRP0714
ISBN (Print)978-1-85449-704-8
Publication statusPublished - Apr 2007

Publication series

NameAston Business School research papers
PublisherAston University
No.RP0714

Fingerprint

Strategic groups
Management research
Criticism
Clustering

Bibliographical note

RP0714

Keywords

  • classification
  • numerical taxonomy
  • pharmaceutical industry
  • strategic groups
  • cluster analysis
  • principal components

Cite this

Leask, G., Bissoondeeal, R., & Binner, J. (2007). Finding natural groups in data: an application to strategic group research. (Aston Business School research papers; No. RP0714). Birmingham (UK): Aston University.
Leask, Graham ; Bissoondeeal, Rakesh ; Binner, Jane. / Finding natural groups in data : an application to strategic group research. Birmingham (UK) : Aston University, 2007. (Aston Business School research papers; RP0714).
@techreport{611279ef69c5485cad7f3e97337f1159,
title = "Finding natural groups in data: an application to strategic group research",
abstract = "The best way of finding “natural groups” in management research remains subject to debate and within the literature there is no accepted consensus. The principle motivation behind this study is to explore the effect of choices of method upon strategic group research, an area that has suffered enduring criticism, as we believe that these method choices are still not fully exploited. Our study is novel in the use of a variety of more robust clustering and validation techniques, rarely used in management research, some borrowed from the natural sciences, which may provide a useful and more robust base for this type of research. Our results confirm that methods do exist to address the concerns over strategic group research and adoption of our chosen methods will improve the quality of management research.",
keywords = "classification, numerical taxonomy, pharmaceutical industry, strategic groups, cluster analysis, principal components",
author = "Graham Leask and Rakesh Bissoondeeal and Jane Binner",
note = "RP0714",
year = "2007",
month = "4",
language = "English",
isbn = "978-1-85449-704-8",
volume = "RP0714",
series = "Aston Business School research papers",
publisher = "Aston University",
number = "RP0714",
type = "WorkingPaper",
institution = "Aston University",

}

Leask, G, Bissoondeeal, R & Binner, J 2007 'Finding natural groups in data: an application to strategic group research' Aston Business School research papers, no. RP0714, Aston University, Birmingham (UK).

Finding natural groups in data : an application to strategic group research. / Leask, Graham; Bissoondeeal, Rakesh; Binner, Jane.

Birmingham (UK) : Aston University, 2007. (Aston Business School research papers; No. RP0714).

Research output: Working paper

TY - UNPB

T1 - Finding natural groups in data

T2 - an application to strategic group research

AU - Leask, Graham

AU - Bissoondeeal, Rakesh

AU - Binner, Jane

N1 - RP0714

PY - 2007/4

Y1 - 2007/4

N2 - The best way of finding “natural groups” in management research remains subject to debate and within the literature there is no accepted consensus. The principle motivation behind this study is to explore the effect of choices of method upon strategic group research, an area that has suffered enduring criticism, as we believe that these method choices are still not fully exploited. Our study is novel in the use of a variety of more robust clustering and validation techniques, rarely used in management research, some borrowed from the natural sciences, which may provide a useful and more robust base for this type of research. Our results confirm that methods do exist to address the concerns over strategic group research and adoption of our chosen methods will improve the quality of management research.

AB - The best way of finding “natural groups” in management research remains subject to debate and within the literature there is no accepted consensus. The principle motivation behind this study is to explore the effect of choices of method upon strategic group research, an area that has suffered enduring criticism, as we believe that these method choices are still not fully exploited. Our study is novel in the use of a variety of more robust clustering and validation techniques, rarely used in management research, some borrowed from the natural sciences, which may provide a useful and more robust base for this type of research. Our results confirm that methods do exist to address the concerns over strategic group research and adoption of our chosen methods will improve the quality of management research.

KW - classification

KW - numerical taxonomy

KW - pharmaceutical industry

KW - strategic groups

KW - cluster analysis

KW - principal components

M3 - Working paper

SN - 978-1-85449-704-8

VL - RP0714

T3 - Aston Business School research papers

BT - Finding natural groups in data

PB - Aston University

CY - Birmingham (UK)

ER -

Leask G, Bissoondeeal R, Binner J. Finding natural groups in data: an application to strategic group research. Birmingham (UK): Aston University. 2007 Apr. (Aston Business School research papers; RP0714).