Modeling desired behaviors: do leaders need new technology?

Abstract

Purpose -Leaders model behaviors they want followers to emulate, and they use various technologies to enhance their message, but which tools are most effective? Using two studies, this paper sets out to compare the effectiveness of newer and older computer technologies used by leaders for describing and demonstrating desired behaviors. Design/methodology/approach -The first study, an interdisciplinary experimental design, involved 110 students across two college campuses and data were analyzed using a 2 (modeling and no modeling) £ 2 (older and newer technology) between-subjects ANOVA. The second study further explored modeling with both technologies on one campus, and data were analyzed with independent samples t-tests. Findings -Newer technology was more effective than older technology in increasing desired behaviors but only when coupled with modeling of those behaviors by the leader. However, after the novelty of the new technology had worn off, no significant difference in production of desired behaviors was observed. Practical implications -Justifying the expense of purchasing new technology to replace functional older equipment is an important consideration for businesses and universities. Organizational leaders need factual, unbiased data to guide their decisions about allocating limited financial resources. Originality/value -The studies were designed to provide decision-makers with some much-needed empirical data.

Building psychological contract: the role of leader member exchanges

“…Convergent validity was established and measured by examining fit indices. The normed fit index (NFI) (W 0.95) indicates acceptable convergent validity while the AVE (W 0.5) indicates acceptable discriminant validity (Brown and White, 2009). The findings confirmed the validity of the final models with excellent model fit statistics for this construct measure as reported in Table I.…”

“…This evidence through LMX suggests that leaders can influence their subordinates' attitudes and behaviours (Likert, 1967). For example, leaders influence subordinates via communication of organizational ideals and values, and through influencing followers' sense making (Brown and White, 2009). In addition, leaders can utilize their formal (legitimate authority) and informal power (expertise, knowledge of the job) (McGregor, 1960;Raven and French, 1958) to influence perceptions of fulfilled employeeemployer unwritten obligations and expectations.…”

Leader-member exchanges and psychological contract: testing for interaction effects

“…The results from CFA for the measurement model conform to acceptable guidelines (Table I) (Schermeller-Engel et al, 2003). The NFI (W0.95) indicates acceptable convergent validity while the Average Variances Extracted (AVE W0.5) indicates acceptable discriminant validity (Brown and White, 2009) (Table I). For discriminant validity, the results indicate that the constructs' AVEs were greater than the CFA-squared latent correlations (Table II), thus indicating the measurement scales' ability to discriminate between measures that are supposed to be distinct (Farrell, 2010).…”

Norm-based leadership and the challenge of democratically elected authoritarians

“…Formal, hierarchical leaders have a unique role, based on a combination of institutional power and the capacity to exercise symbolic influence through their own behavioral modeling (Johnson, 1990; Klapp, 1965). 7 “By serving as exemplars who model desired behaviors,” note Brown and White (2009), “leaders aim to increase the levels of those behaviors among their followers” (p. 126). The status of leaders—their hierarchical position, their power and prestige, and so on—invites emulation (Brown and White, 2009; Trice and Beyer, 1991).…”

“…7 “By serving as exemplars who model desired behaviors,” note Brown and White (2009), “leaders aim to increase the levels of those behaviors among their followers” (p. 126). The status of leaders—their hierarchical position, their power and prestige, and so on—invites emulation (Brown and White, 2009; Trice and Beyer, 1991). Evidence of that emulation effect can be found in the rise of hate crimes following Trump’s election (Edwards and Rushin, 2018).…”