Handbook of Management Scales

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The Handbook of Management Scales is a collection of previously used multi-item scales to measure constructs in empirical management research literature.

Critical Introduction[edit]

The Handbook of Management Scales was first edited by A. Wieland in 2010 and has since grown. It contains a collection of measurement scales, which are the basis for empirical research. Unfortunately, management researchers often neglect the importance of good scales. This leads to models with a high goodness-of-fit but with poor reliabiliy and validity. Construct definition and content validity are probably the most important and most neglected criteria to ensure that a scale really measures what it is intended to measure. Expert judges can help to improve content validity by capturing all important aspects that together encircle a construct.

The deletion of scale items (often called “scale purification”) may improve Cronbach's alpha or the statistical performance indicators of a model. However, important aspects to be measured may then disappear and this can bias the scale into a new direction. Content validity may then be destroyed and must therefore carefully be observed all along the scale purification process. Judges could also be asked to label a new construct giving them the items retained after scale purification to compare the judgement to the intended construct. Content validity may also be improved by adding missing aspects to an existing scale or by merging two existing scales.

Reflective scales often prevail in management research. But researchers should know when to use reflective and when to use formative scales. Too often do researchers specify a model with a reflective scale that is actually formative. Likert scales and semantic differential scales are probably the most common scales in management research. However, researchers often fail to weigh the pros and cons of such scales. Researchers should take more time to think about the appropriate measurement. The Handbook of Management Scales helps to find previously used scales, but will not release the researcher from carefully testing the scales in terms of reliability and validity before using them.

You are invited to contribute by adding new multi-item metrics (edit this page) to this Scales Handbook. Scales from high-ranked journals are preferred that are developed in a systematic scale development process and that are tested to measure a construct in terms of specification (reflective vs. formative), dimensionality, reliability, and validity (including content, convergent, discriminant, and nomological validity). For each scale at least its objective items, source, and, if available, reliability (e.g. Cronbach's alpha, item reliability, composite reliability, average variance extracted) are listed.

Unidimensional constructs[edit]

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Multidimensional constructs[edit]

The list in the previous section contains scales to measure constructs that were often conceptualized as dimensions of multidimensional constructs (mostly second-order constructs). The following list contains the name of multidimensional constructs and the names of their dimensions.

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Example[edit]

The following scale example can be used, if you want to add a new scale (click edit this page to add a new one).

Journals[edit]

Rankings are recommended to assess the quality of a journal. The better the quality of a journal the more likely is a good quality of a scale published in it. Widely accepted rankings are the German VHB-JOURQUAL and the British ABS Academic Journal Quality Guide. In this handbook scales are used from various high-ranked management journals, e.g.

  • Academy of Management Journal
  • Decision Sciences
  • Information Systems Research
  • International Journal of Logistics Management
  • International Journal of Operations & Production Management
  • International Journal of Physical Distribution & Logistics Management
  • Journal of Business Logistics
  • Journal of Management
  • Journal of Marketing
  • Journal of Operations Management
  • Journal of Supply Chain Management
  • Management Science
  • Organizational Research Methods
  • Production and Operations Management

Recommended literature[edit]

  • MacKenzie et al. (2011): Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques. MIS Quarterly, Vol. 35, No. 2, pp. 293-334.

Related Handbooks[edit]

External links[edit]