Date Published: June 20, 2018
Publisher: Public Library of Science
Author(s): Hendrik Slabbinck, Arjen van Witteloostuijn, Julie Hermans, Johanna Vanderstraeten, Marcus Dejardin, Jacqueline Brassey, Dendi Ramdani, Alexander N. Sokolov.
Many Management (sub-)disciplines, from Organizational Behavior and Marketing to Accounting and Strategy, are interested in antecedents and consequences of individual attitudes and traits. A key aspect of personality profiles are explicit and implicit motives. Yet, Management scholars mainly focus on explicit motives, with limited attention to implicit motives. We argue that this state of affairs probably came into being because current Management researchers mainly rely on implicit motive measures that are either difficult to apply or to develop, hampering researchers from applying implicit motive measures. To overcome the downsides of available instruments, we develop a Brief Implicit Association Test (BIAT) as an efficient, reliable and valid measure of implicit motives, particularly the needs for achievement, affiliation and power. To explore our BIAT’s predictive validity, we apply this measure to a specific research domain within Management: Entrepreneurship. We examine implicit motives’ association with entrepreneurial self-efficacy, business founding, and financial profitability. Our results show that the introduction of implicit motives can unlock stranded discussions in this research domain. Overall, we argue that implicit motives can help to push the boundaries of the study of deep-level attributes in a wide range of organizational and managerial settings.
Identifying and quantifying the motives of decision-makers is a key aspect in many disciplines of Management research, varying from work floor employees in Organizational Behavior to upper echelon managers in Strategy [1–4]. Although Organizational Behavior researchers have acknowledged that motives may also have an unconscious, implicit aspect [2,3,5,6], many if not most researchers in Management research only assess explicit motives while their implicit counterparts remain largely untapped. This implies a missed opportunity because an impressive body of research in Psychology and a slow but steadily growing stream of research in Management clearly show that these implicit motives influence many business, economic, political and societal phenomena independent and different from (or in interaction with) motivational dispositions that people attribute explicitly to themselves at a conscious level [7–11]. A plausible reason for this lack of Management research into implicit motives is that measurement instruments that are relatively easy to develop and/or administer were missing until recently.
Our results show that the BIAT is a good measure for the assessment of implicit motives, and that this is the case both from a psychometric as well as a practical viewpoint. In line with implicit motives theory [31,73], the data from our study provide initial evidence that the BIAT predicts the kind of behavioral patterns that are assumed to be determined by implicit motives (i.e., spontaneous behavior and long-term behavioral trends). Confirming the divergent validity of the BIAT, only explicit motives are related to responses in specific situations that require conscious thought and deliberation (i.e., entrepreneurial self-efficacy). In addition, the found relationships between explicit motive scores and the measures of entrepreneurial self-efficacy may be partially explained by socially desirable responding or common-method variance [102,113].
Of course, as any study, our work has limitations that point to promising future research avenues. First, although the present study provides initial support for the validity of the BIAT as a measure of implicit motives, generating convincing results in an entrepreneurship context, more work is required before the BIAT can be established as a valid alternative to the in-depth story-writing alternatives that are based upon detailed and fine-grained content-coding procedures. Specifically, more replications are needed, preferably with a variety of different outcome variables, in diverse research domains, including Management research, and with different types of participants. In this context, the BIAT instrument introduced above provides, we believe, a very promising tool that can be further developed and perfected in future work.
In conclusion, the BIAT is an easy-to-use and valid measure of implicit motives that has the potential to boost the introduction of implicit constructs in Management research. Given what we know from the psychology of motives, many subtle effects of motives on attitudes, behaviors and outcomes go unnoticed when Management researchers focus on their explicit manifestations only. After all, implicit motives orient different types of attitudes, behaviors and outcomes than explicit motives do. For example, as we revealed in our substantive example, implicit motives may affect entrepreneurial outcomes where their explicit counterparts do not, and vice versa. Of course, the validity of a measure cannot be established in one study , but rather requires looking at various sorts of validity over a series of studies. Hence, we hope this paper encourages Management scholars to apply the BIAT to achieve a superior understanding of the effects of (explicit and implicit) motives on a wide range of attitudes, behaviors and outcomes in many different managerial and organizational settings and contexts.