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Published on 01 January 2001 |

Version 1st Edition

Decision Making Styles in Financial Behaviour : Towards a Method for Measurement and Application, 2000-2001

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Nicholson, N.;Soane, E.;Willman, P.;Fenton-O'Creevy, M.

Description

The research sought to fill a gap in knowledge and practice about individual differences in how professionals in the financial services industry make decisions. The practical importance of the investigation relates to potentially important effects on both person-job fit and performance. Identifying orientations that relate differentially to decision environments in finance, e.g. functional roles and types of markets, could help guide key placement decisions and developmental discussions at the workplace. The facets of decision style focused upon in this research came from two sources: suggestions arising from the Principal Investigators' previous research and an extensive literature review. The literature reveals a number of different aspects of decision making. Of these, five related closely to the distinctions observed in the previous research and seemed likely to be more generally pertinent to the finance environment: achievement, emotional involvement, risk preferences, structure (vs. autonomy) and spontaneity (vs. deliberation).<br> The research had three objectives. First, to develop an effective measure of several aspects of decision making that were likely to impact upon person-job fit and the performance of individuals in the financial environment (the Decision Making Styles Questionnaire, DMSQ). Second, to develop such a measure would contribute to understanding in decision theory. Third, the application of a measure of decision styles could provide valuable data relevant to individual and organisational performance. The prior research found that in the field the selection, placement and advancement of people in finance decision-making tends to be unsystematic without any attention to non-technical criteria such as psychological profile. In the finance industry, the cumulative effect of even a small mismatch between an individual and their job requirements could lead to preventable losses. Hence a measure that provided individual profiles that could be matched to job characteristics would be likely to prove useful in many organisations.

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Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

31%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

UK Data Service

Assigned Domain

Subfield

Management Science and Operations Research

Field

Decision Sciences

Domain

Social Sciences

Confidence Score

49%

Source

Scholar Data Model

Normalization Factors

FT

38.47

CTw

1.00

MTw

1.00