An empirical study of the career anchors that govern career decisions

Abstract

Purpose – The purpose of this paper is to examine two of Feldman and Bolino's proposals: career anchor plurality and career anchor relationships. Design/methodology/approach – A novel method for examining the relationships between career anchors called “indices of mutual presence” is developed for this study to generate meaningful results from ordinal and ipsative career anchor data. Findings – Evidence for some individuals having multiple career anchors was found. Complementary and exclusivity career anchor relationships are identified and a model for representing them is presented. The importance and possible benefit of understanding both an individual's preferred and “unpreferred” anchors is discussed. The non-reflexive nature of career anchors is explored and the idea of “mutually” exclusive career anchors is rejected. Weaknesses in the octagon shaped career anchor relationships diagram presented by Feldman and Bolino are discussed. Research limitations/implications – Despite the benefits associated with forced-choice assessments, some have expressed concern because of the nature of this type of evaluation. Each time an item is preferred, another item must be “unpreferred.” Thus, for one item to have a high preference count, some other item must necessarily have lower preference counts. The resulting data is ordinal rather than interval or ratio. It contains information regarding order of preference, but provides little insight into magnitude of preference. This makes it difficult to identify and examine how much more or less one individual prefers an item when compared to another individual. Originality/value – The second property of forced-choice data that raises concern is its ipsative nature. As respondents are constrained to unprefer an item each time the prefer one, the total preference counts remain the same for every individual. As a result, the preference scores for every individual will always sum to the same value. When data has this property, it is called ipsative. Ipsative data is not free to vary, and thus statistical methods which analyze variance may yield spurious results. Thus, traditional factorial statistical methods cannot be appropriately used with ipsative data (Baron, 1996; Bartram, 1996; Closs, 1996). It is commonly believed that researchers trade ease of use and accuracy for fewer available statistical tools when using forced-choice methods. However, this paper attempts to use “indices of mutual presence” developed for this study (described below) that do not rely on variance to generate meaningful results from ipsative career anchor data.