Impact of rater personality on transformational and transactional leadership ratings

This study addresses the role of rater personality in ratings of transformational and transactional leadership. In a naturalistic field study, we found that rater personality (i.e., agreeableness, openness, extraversion, and conscientiousness) was positively associated with ratings of transformational leadership, but significant rater personality effects were not found in an experimental study where leadership behavior was invariant. These results suggest that disagreements among raters about leaders' behaviors are not due solely to random error and may instead reflect true differences either in (a) the behaviors leaders exhibit toward individual followers or (b) personality-related differences between followers in attention to and recall of leadership behaviors. We also found that personality (of subordinates and peers) was not randomly distributed across leaders, though clustering effects were generally small. Practically, our results suggest that (a) individual reports of leadership may be better at predicting leadership outcomes than aggregated group reports – especially those related to individual attitudes and behaviors – though they are rarely used in the literature; (b) aggregation is complicated because rater personality is associated with leadership ratings and is not randomly distributed across leaders; and (c) corrections for measurement error based on inter-rater agreement may not be appropriate due to non-random unique rater variance.     

At the crux of dyadic leadership: Self–other agreement of leaders and direct reports — Analyzing 360-degree feedback

The purpose of this research is to investigate the use of dyads instead of whole rating groups for analyzing 360° feedback. A Center for Creative Leadership sample of direct subordinates was matched with their focal leaders (J = 4810 dyads). Two CCL Benchmark scales (Building & Mending Relationships and Problems with Interpersonal Relationships) were used to determine if this dyadic pairing produced high self–other agreement (SOA). Using Within and Between Analysis (WABA), results suggest the viability of detecting unitary, whole dyadic effects only under specific boundary conditions. Other conditions produced highly dispersed dyadic results. Thus, dyadic convergence is not a universal phenomenon in these data. Tying the dyadic results back to the original rater group's consistency as reported in Markham, Smith et al. (2014), those rater groups with high internal agreement form clearer dyadic pairings when compared to rater groups that were moderate or low in agreement. Implications and future directions are discussed.     

The role of inferential accuracy in performance rating

The presence of shared implicit theories of performance is used in explaining the failure of behavioral anchors to improve performance ratings. It is proposed that efforts to improve rating accuracy also will be hampered by a preoccupation with observation. Instead, attention needs to be focused on the inferential accuracy of the rater and the cognitive processes and implicit theories upon which raters rely.     

Innovation behavior in the hotel industry

We develop and test a model of innovation behavior in the hotel industry. The model relates four types of innovation—i.e., management, external communication, service scope and back-office—to the key determinants: service provider characteristics, customer competences and the market drivers. Using statistical probit models and cross-sectional survey data from a stratified sample of hotels in the Balearic Islands (N=331) we were able to verify the model including innovation types determinants and the innovation impact on hotels performance. Main findings verify the model indicating the effects of these determinants on innovation and the positive impact of the innovation on the hotels performance. Hence, innovation decisions determinants are: the additional services on offer, that bookings are made through tour operators, that hotels are part of a hotel chain and that the owners of the hotel run the business.     

Reconsidering the accuracy of follower leadership ratings

Accurate behavioral measurement is essential to developing a science of leadership, yet accurate measurement has remained elusive. The use of follower reports of leader behavior creates challenges given that a large body of basic and applied research suggests that behavioral ratings reflect not only recall of actual behaviors, but also inferences based on semantic memory, which may vary among individuals. In this paper, we examine several explanations for rater effects that are associated with follower individual differences, contextual factors, and even research methods, such as the type of measure used, that may bias ratings of leader behavior. We also develop a conceptual model to illustrate these processes. Finally, we offer potential solutions to increase accuracy in follower reports of leader behavior.     

Technology Acceptance Model 3 and a Research Agenda on Interventions

Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre‐ and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.     

Behaviorally anchored rating scales: some theoretical issues.

A number of theoretical problems exist which underline the development and implementation of behaviorally anchored rating scales in particular and all performance evaluation procedures in general. Several specific areas need additional study. It is concluded that future research should concentrate on the process of performance evaluation in the framework of a cognitive, information-processing model of the rater.     

An Application of Expectancy Theory to Explain a Manager's Intention to Use a Decision Support System

A continuing gap exists between the capabilities of sophisticated computer-based information systems and the extent to which these systems are used by individuals. Studies which have examined the relationship between system utilization and various user, system, implementation, and organizational variables have provided few consistent findings. A new approach to this topic is suggested by a recent study by Davis, Bagozzi, and Warshaw [11], which indicates that individuals' intentions to use a system determine subsequent use. A large body of psychology-based research also supports this relationship between behavioral intentions and subsequent behavior. This study employs expectancy theory, which has often been used to examine behavioral intentions, to explain managers' intentions to use a decision support system (DSS). The results imply that the variables of the expectancy force model are determinants of a manager's behavioral intentions to use a DSS, and the variables of the expectancy valence model are determinants of the attractiveness of using a DSS to a manager.     

Examination of Structured Interview Ratings Across Time: The Effects of Applicant Race, Rater Race, and Panel Composition

This study examined the relationship between race and interview ratings in a structured selection panel interview. Data from 1,334 police officer applicants who were interviewed by three-person panels were examined to explore how applicant race, rater race, and panel racial composition related to interview ratings and change from initial to final ratings. Results revealed the largest effect was for panel racial composition, such that predominately White panels provided significantly more favorable ratings to applicants of all races compared to panels composed of predominately Black raters. However, a significant three-way interaction between rater race, applicant race, and panel composition was also found. Specifically, Black raters evaluated Black applicants more favorably than White applicants only when they were on a predominately Black panel. These results may help explain past inconsistencies in the literature regarding the effects of rater race and applicant race on ratings.     

Exploring team mental model dynamics during strategic change implementation in professional service organizations. A sensemaking perspective

The purpose of this paper is to provide a deeper process understanding of team mental model dynamics in a context of strategic change implementation. To do so, we adopt a change recipient sensemaking perspective with the objective to identify salient determinants of team mental model dynamics. We aim to contribute to the managerial and organizational cognition literature by identifying critical micro-foundations that shape team cognition and interpretation processes during strategic change implementation. This adds to the field’s understanding of the under-researched collective dimension of strategic processes in general and strategic change implementation more specifically. Through an explorative case study conducted at a professional service organization, we identified five determinants of team mental model dynamics: coherence between ostensive and performative aspects of organizational routines, equivocality of expectations, dominance of organizational discourse, shifts in organizational identification and cross-understanding between departmental thought worlds. Case findings reveal that implementation processes of strategic change become intricate and difficult if change recipient sensemaking is not effectively acted upon. The five determinants identified require adequate managerial attention in order to avoid slipping into organizational inertia. As a consequence, professional workers are unable to ‘drop their tools’ and fail to integrate the strategic change effort in updated team mental models.     

基于扎根理论的强制性公民行为影响因素研究

探索强制性公民行为的影响因素,对于拓展相关理论和指导管理实践都十分有益。以扎根理论为主导工具进行研究,对强制性公民行为影响因素的概念模型进行了探索性研究,并得出了强制性公民行为影响因素的三大类属:个体因素、客体因素以及环境因素。研究结果还表明,个体因素在客体因素或环境因素对强制性公民行为的影响路径中起中介或调节作用;客体因素和环境因素对强制性公民行为的交互效应存在。     

Evidence on the Superiority of Analysts Quarterly Earnings Forecasts for Small Capitalization Firms*

Financial analysts provide information to support investment analysis and decisions for an ever increasing number of firms. As part of their services they also produce earnings forecasts for covered firms. While there has been much research investigating the determinants of financial analyst earnings forecast superiority for large, widely-followed firms, little research has focused on smaller firms. Until recently, these smaller firms have been largely ignored. This study focuses exclusively on small firms and provides evidence of differing behavior for such firms compared to results previously reported for large firms. Errors in quarterly earnings per share forecasts of small firms obtained from a univariate time-series model are also examined. Regression results indicate that time-series model parameters possess information content with respect to forecast accuracy for analyst-covered firms only. These results are obtained after controlling for firm size, model adequacy, and industry, quarter, and year effects. This suggests that analysts are more likely to cover small firms for which they are able to decipher information correlated with that impounded in the “shocks” in the quarterly earnings time series as captured by the time-series model parameters.     

Explaining Labour Turnover: Empirical Evidence from UK Establishments

Abstract. This paper investigates the determinants of labour turnover using establishment‐level survey data for the UK. The main contribution of our paper is that it estimates the impact of wages, unionization, training and other aspects of working conditions on labour turnover. Our main findings are: (i) turnover is inversely related to the relative wage; (ii) unionism reduces turnover: this is due mainly to the ability of unions to improve conditions of work rather than the voice‐exit model of Freeman; (iii) there is a complex relationship between turnover and training; and (iv) turnover is lower in the ‘high‐tech’ sector.     

Labour Market Structures,Labour Market Policy and Wage Formation in the OECD

This paper investigates why the incentive to moderate wages in an environment of rising unemployment differs so strongly among the OECD countries. In the first part we develop an insider-outsider bargaining model in which the wage results from a confrontation of the insiders' wage claims and the employer's wage offer. The second part of the paper empirically tests the model's predictions for the determinants of wage flexibility. The degree of centralization of wage bargaining, the extent of active labour market policy and the characteristics of the unemployment benefit system are shown to be relevant determinants.     

Revisiting the determinants of local government performance

Managing financial resources efficiently is a requirement for all levels of government. However, measuring the performance of governments or other public authorities is usually highly complex. The results of this type of assessment are likely to be biased or perverse. This study attempts to identify non-discretionary or exogenous variables that are associated with better/worse economic performance of local governments (the determinants of efficiency). Based on past research, the paper starts by providing a classification for the different types of determinants of local government performance. Afterwards, using data from all Portuguese municipalities, the relationship between a large number of factors and the efficiency scores is assessed. To accomplish this, several Tobit, OLS and double-bootstrap models were implemented. The efficiency scores are computed through non-parametric frontier methodologies. The results indicate that analysts must be prudent while interpreting the economic results achieved by each municipality. To be impartial and robust any performance evaluation model should (at least) consider the effects of the determinants of cost efficiency identified in this paper.     

Bayesian Network for Risk of Diarrhea Associated with the Use of Recycled Water

Estimating potential health risks associated with recycled (reused) water is highly complex given the multiple factors affecting water quality. We take a conceptual model, which represents the factors and pathways by which recycled water may pose a risk of contracting gastroenteritis, convert the conceptual model to a Bayesian net, and quantify the model using one expert's opinion. This allows us to make various predictions as to the risks posed under various scenarios. Bayesian nets provide an additional way of modeling the determinants of recycled water quality and elucidating their relative influence on a given disease outcome. The important contribution to Bayesian net methodology is that all model predictions, whether risk or relative risk estimates, are expressed as credible intervals.     

13 When Group Identities Matter

Abstract

Performance appraisals are a critical part of organizational life, and bias in appraisals is consistently mentioned as a barrier to advancement for diverse workers. This chapter reviews the literature on rater bias in performance appraisals, defined as effects on performance ratings due to ratee category membership. We focus on the major theoretical frameworks (e.g., stereotype fit and relational demography) used in the study of bias, organizing the research findings by the four most commonly studied demographic categories: gender, race, age, and disability. The review allows better understanding of the gaps in our knowledge and identifies needed future research directions in this literature stream. We conclude the chapter with several concerns including a lack of empirical research testing propositions concerning the effect of organizational variables on bias.     

Age and Gender Differences in Perceived Accident Likelihood and Driver Competences

Road traffic accident involvement rates show clear age and gender differences which may in part be accounted for by differences in risk perception and perceptions of driving competence. The present study extends and replicates that of Matthews and Moran (1986). Young (18–30 years) and older (45–60 years) male and female drivers responded to a questionnaire on perceived accident risk and driving competence (judgment and skill) with respect to themselves and four target groups, and also rated a series of videotaped driving sequences with respect to likelihood of accident occurrence and perceived driving competence. Results showed that effects of rater characteristics were generally confined to the questionnaire. Younger males were perceived as most likely to experience an accident and were judged to be lower than other groups in driving competence. Younger groups showed little bias against older groups and vice versa , but gender-related bias was apparent. The findings of Matthews and Moran were generally confirmed. The results are discussed with reference to four main issues: (1) demographic bias effects—which are generally weak; (2) stereotyping on the basis of gender and/or age of driver; (3) group-specific bias; (4) self-appraisal bias.     

Women’s Employment Status and Hours Employed in Urban Brazil: Does Husbands’ Presence Matter?

The determinants of hours worked for employed women in developing countries is a little‐studied topic. We compare the determinants of employment with the determinants of hours worked for prime‐aged urban Brazilian women with and without husbands present. Given employment status, we find systematic differences for women in couple‐headed and female‐headed households. For the former, the same variables that affect employment do a good job of explaining hours worked. In contrast, our model generally fails to capture determinants of variation in hours worked for women who are sole heads of households. Sample selectivity functions in opposite directions for the two groups.