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The social relations model (SRM; Kenny, 1994) explicitly proposes that leadership simultaneously operates at three levels of analysis: group, dyad, and individual (perceiver and target). With this model, researchers can empirically determine the amount of variance at each level as well as those factors that explain variance at these different levels. This chapter shows how the SRM can be used to address many theoretically important questions in the study of leadership and can be used to advance both the theory of and research in leadership. First, based on analysis of leadership ratings from seven studies, we find that there is substantial agreement (i.e., target variance) about who in the group is the leader and little or no reciprocity in the perceptions of leadership. We then consider correlations of leadership perceptions. In one analysis, we examine the correlations between task-oriented and socioemotional leadership. In another analysis, we examine the effect of gender and gender composition on the perception of leadership. We also explore how self-ratings of leadership differ from member perceptions of leadership. Finally, we discuss how the model can be estimated using conventional software.

Peer evaluations of performance increasingly are being used to make organizational decisions and to provide individuals with performance related feedback. Using Kenny’s social relations model (SRM), data from 14 teams of undergraduate students who completed performance ratings of themselves and other team members were analyzed. Results indicated a significant target variance effect for the majority of performance dimensions and a significant perceiver variance effect for all performance dimensions. Results further indicated that, in general, how individuals see themselves is not congruent with how others see them, how individuals see themselves is congruent with how they see others, how individuals are seen on a particular dimension is related to how they are seen on other performance dimensions, and, how a person is seen by others does not relate to how that individual sees others. Implications, limitations, and suggestions for future research using the SRM are discussed.

Average quadratic quality loss function (QQLF) measures quality of a given process using mean shift from its target value and variance. While it has a target parameter for the mean, it lacks a target for the variance revisable for counting any progress of the process across different quality levels, above/below the standard level; thus, it appears too general. Hence, in this research, it was initially supposed that all processes are located at two possible quality spaces, above/below the standard level. The purpose of this paper is to propose a two-criterion QQLF, in which each criterion is specifically proper to one of the quality spaces.

Since 1.33 is a literarily standard or satisfactory value for two most important process capability indices C_p and C_pk, its upper/lower spaces are assumed as high-/low-quality spaces. Then the indices are integrated into traditional QQLF, of type nominal the best (NTB), to develop a two-criterion QQLF, in which each criterion is more suitable for each quality space. These two criteria have also been innovatively embedded in the plan-do-check-act (PDCA) cycle to help continuous improvement. Finally, the proposed function has been examined in comparison with the traditional one in Feiz Hospital in the province of Isfahan, Iran.

Results indicate that the internal process of the studied case is placed on the lower quality space. So the first criterion of revised QQLF gives a more relevant evaluation for that process, compared with the traditional function. Moreover, this study has embedded both proposed criteria in the PDCA cycle as well.

Formulating the two-criterion QQLF only for observations of normal and symmetric distributions, and offering it solely for NTB characteristics are limitations of this study.

Two more relevant quality loss criteria have been formulated for each process (service or manufacturing). However, in order to show the comprehensiveness of the proposed method even in service institutes, emergency function of Feiz Hospital has been examined.

The traditional loss function of type NTB merely and implicitly targets zero defect for variance. In fact, it calculates quality loss of all processes placed on different quality spaces using a same measure. This study, however, provides a practitioner with opportunity of targeting excellent or satisfactory targets.

This paper proposes and tests a model to explain the outcomes of three different information presentation formats. Based on cognitive fit theory, information visualization formats that best fit task characteristics are expected to lead to improved decision-making outcomes. We apply the Judgment and Decision-Making framework (Bonner, 2008) to investigate how certain factors can impact decision quality.

This study tests whether certain production variance presentation formats (percentages, dollar amounts, and schematic faces), task complexity, understanding of the presentation format, motivation, and effort increase the accuracy of a supervisor’s bonus calculation. A total of 281 students and professionals participated in this experiment. Their responses were examined using regression analysis.

Our results indicate that individuals mostly prefer the percentages presentation format and that the use of the percentages presentation format, a lower level of task complexity, and a better understanding of the variance presentation format lead to more accurate calculations in the experimental task.

Our study provides a call for further research on factors that influence the choice of presentation format as a potentially fruitful area for management accounting researchers.

We exhort practicing management accountants to exert direct influence on employees’ decision making through the use of variance presentation formats that fit their tasks and promote understanding.

Our experiment introduced two major innovations: it uses an interactive data visualization approach allowing subjects to select their preferred presentation format; and it focuses on production variances, a topic that has received less attention in the academic managerial accounting literature, but is still very relevant to practitioners.

This commentary on Kenny and Livi (2009) expands on aspects of leadership categorization theory that are consistent with the application of the social relations model (SRM). It critically considers limits to the generalization of the variance components analysis results described in Kenny and Livi's first example, and briefly summarizes results of an additional study that supports their findings. Finally, this commentary suggests interpretational issues of interest to researchers who wish to continue to apply the SRM to multi-level issues in the study of leadership.

Hall, Lord, and Foster (2009) have commented on whether variance partitioning in the social relations model would be the same in long-term groups and when groups have formal leaders. This reply follows their lead and speculates on how the variance partitioning would change. It considers the design and analysis issues in natural workgroups as well as the estimation of group effects.

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.

The purpose of this paper is to examine the impact of supply chain lead‐time averages and variability on an organization's financial performance.

The “executive” list for manufacturers, consisting of 1,264 individuals of the Institute of Supply Management provided the study's sampling frame, with surveys sent to 402 firms and responses obtained from 210 firms. The empirical model is tested using LISREL.

The results show that as variance in supply chain lead‐times increases, the financial performance of the organization decreases. Of equal significance, the results show that average supply chain lead‐times have no direct impact on financial performance. The results also indicate that demand uncertainty associates with greater supply chain lead‐time variance and that production technology routineness associates with lower supply chain lead‐time variance. Product complexity and organizational size have no impact on supply chain lead‐time variance or supply chain lead‐time average.

The research is an initial effort to understand variance in supply chain systems. An ongoing challenge in this area is operationalization of measures and data collection techniques that go beyond a single firm and examine a network of organizations cooperating in a value‐added supply chain.

The results suggest that managing the variance in a supply chain system may be more important to an organization's financial performance than managing averages.

This is particularly significant since organizations often act contrary to these findings, focusing scarce resources on reducing average lead‐times rather than on reducing variability in supply chain lead‐times.

SPEAKING at a meeting of the Engineering Industry Marketing Group of the Institute of Marketing recently, Sir Montague Finniston, FRS, FMS, made an attack on the future plans of the British Steel Corporation. He maintained that to make substantial cuts in the Corporation's steelmaking capacity was “absurd”.

Throughout the world of the Less Developed Countries (LDC’s) there exists a complex maze of export promotion and incentive schemes which reflect the mental agility of economists, lawyers and legislators, in providing special favours and benefits for the export sector.