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The purpose of this paper is to improve the information quality of bankruptcy prediction models proposed in the literature by building prediction intervals around the point estimates generated by these models and to determine if the use of the prediction intervals in conjunction with the point estimated yields an improvement in predictive accuracy over traditional models. The authors calculated the point estimates and prediction intervals for a sample of firms from 1991 to 2008. The point estimates and prediction intervals were used in concert to classify firms as bankrupt or non-bankrupt. The accuracy of the tested technique was compared to that of a traditional bankruptcy prediction model. The results indicate that the use of upper and lower bounds in concert with the point estimates yield an improvement in the predictive ability of bankruptcy prediction models. The improvements in overall prediction accuracy and non-bankrupt firm prediction accuracy are statistically significant at the 0.01 level. The authors present a technique that (1) provides a more complete picture of the firm’s status, (2) is derived from multiple forms of evidence, (3) uses a predictive interval technique that is easily repeated, (4) can be generated in a timely manner, (5) can be applied to other bankruptcy prediction models in the literature, and (6) is statistically significantly more accurate than traditional point estimate techniques. The current research is the first known study to use the combination of point estimates and prediction intervals to in bankruptcy prediction.

Although prior research has found that employee participation is key to successfully implementing quality management initiatives (Baird et al., 2011; de Menezes, 2012; Lagrosen and Lagrosen, 2005), little research in operations management exists that investigates which management actions and behaviors lead to employee commitment to such initiatives. The purpose of this paper is to address this gap in the operations management literature by investigating which influence tactics are the most effective in soliciting employee commitment to continuous improvement tasks. The paper also examines how influence tactics affect the supervisor-subordinate relationship and the manager’s effectiveness in implementing continuous improvement initiatives.

A survey instrument was used to measure supervisor-subordinate relationship quality, usage of influence behaviors and participants’ task commitment to continuous improvement initiatives.

The results indicate that five of the 11 influence tactics identified in the prior literature, i.e., collaboration, consultation, ingratiation, inspirational appeals, and rational persuasion, are significant and strong predictors of employee commitment to continuous improvement initiatives. Further, analyses show that these influence tactics are significant drivers of the quality of the supervisor-subordinate relationship, which was found to partially mediate the relationship between influence tactics and the supervisor’s effectiveness in implementing continuous improvement projects.

Since the extant CI and Total Quality Management literature has looked at the plant or program level rather than the worker-level as in the research, the findings offer one explanation as to why earlier studies investigating the relationship between quality management programs and increased organizational performance reported mixed results.

Increasing managers’ awareness and usage of influence tactics may increase the success rate of continuous improvement projects as well the quality of the relationship with the manager’s subordinates.

While the extant literature has argued that management support and employee commitment are key components of a continuous improvement project implementation, little has been written about the specific management actions and behaviors that lead to success.

In this study, the construct validity and effectiveness of a newly identified influence tactic, organizational appeal, is tested. Utilizing a sample of practicing professional accountants, study results show that organizational appeal is distinct from other influence tactics, is perceived to be used frequently by supervisors, and is effective at influencing subordinates. The organizational appeal influence tactic could be particularly useful in situations where accounting supervisors and managers use proactive tactics to influence others to complete tasks or make decisions; to influence outsiders (e.g., suppliers, clients, government agents) over whom they have little authority; and where other influence tactics are not effective or appropriate.

A procedure for plotting load paths and load flow in structures from a finite element analysis is described. The load flow is indicated by pointing vectors and the load paths are determined by plotting contours tangent to these vectors. The procedure is applied to assembled structures. An explanation is given for “eddies” that can appear in regions not contributing to the load path.

Design engineers use the term load path to describe, in general terms, the way in which loads path through a structure from the points of application to the points where they are reacted. In contrast, stress trajectories are more clearly identified by the direction of the principal stress vectors at a point. The first author proposed a simple definition of the term load path in 1995 and proposed procedures to determine load paths from two‐dimensional finite element solutions. In this paper, the concept of load paths will be further explored and related to stress trajectories and Michell structures. The insight given when determining the load transfer near a pin‐loaded hole will be demonstrated. In addition a cantilevered beam will be considered and an introduction to plotting load paths in three‐dimensional structures is given.

In recent years, a novel method for computing loadflow orientations and loadpaths, which is based on iterative solutions of non‐linear equations and finite element results, has emerged in the literature. In the present investigation, the prior formulation and approach has been enhanced by deriving explicit expressions for computing loadflow orientations. The new equations produce more accurate loadflow orientations and improve the fidelity of calculated loadpaths. In particular, for a typical loaded plate containing a hole, the density of loadflow lines is also shown to provide accurate values of stress concentration factor. Subsequently, loadflow visualisation for biaxially loaded plates containing non‐optimal and optimal holes is undertaken to identify key features of the stress distributions. It is found that regions of “recirculation” are apparent for non‐optimal hole shapes, whereas no recirculation zones are present for optimal shapes. In general, it is considered that loadflow visualisation is a simple but powerful tool for use by structural designers and analysts.

The electronics industries are relying increasingly on robotics for their production. Wafer handling robots are used to transfer wafers between wafer processing stations. A pick‐measure‐place method is typically utilized to transfer wafers accurately. The measurement step is performed using an aligner, which is time‐consuming. To increase wafer transfer efficiency, it is desirable to speed up the measurement process or place it in parallel with other operations. To solve the problem, optic sensors are installed at each station to estimate the wafer eccentricity on‐the‐fly. The eccentricity values are then applied to control the robot to place the wafer directly onto another station accurately without using the aligner. However, current methods face problems to achieve high accuracy requirements to meet the electronic manufacturing needs. The purpose of this paper is to develop a technique to improve the wafer handling performance in semiconductor manufacturing.

The kinematics model of the wafer handling robot is developed. Two sensor location calibration algorithms are proposed. Method I is based on the wafer handling path. Method II uses the offset paths from the wafer handling path. The results from these two methods are compared. To compute the wafer eccentricity on‐the‐fly, a wafer eccentricity estimation technique is developed.

The developed methods are implemented using a wafer handling robotic system in semiconductor manufacturing. The wafer eccentricity estimation errors are greatly reduced using the developed methods. The experimental results demonstrate that Method II achieves better results and can be used to improve the wafer handling accuracy and efficiency.

The proposed technique is implemented and tested many times on a wafer handing robotic system. The notch alignment in the wafer handling needs further research.

The developed method is validated using a system in semiconductor manufacturing. Hence the developed method can be directly implemented in production if the notch of a wafer can be identified.

This paper provides techniques to improve the wafer handling accuracy in semiconductor manufacturing. Compared with the results using other methods, Method II greatly increases the wafer handling accuracy to satisfy the semiconductor manufacturing needs.

The purpose of this study is to examine how the nature of consumers' relationship with a brand influences brand evangelism, which represents an intense form of brand support behavior. Specifically, the study investigates the influence of two consumer-brand relational constructs, brand trust and brand identification, on brand evangelism. Brand evangelism, conceptualized as an amalgam of adoption and advocacy behaviors, is operationalized in terms of three supportive behaviors: purchase intentions, positive referrals, and oppositional brand referrals.

Drawing from prior research on consumer-brand relationships, a framework of brand relationships and brand evangelism is developed. To provide a more robust test of theory, consumers' extraversion, gender, and brand experience are included as control variables. Structural equation modeling is used to test the proposed hypotheses.

The findings reveal that consumer-brand relationships influence brand evangelism, albeit in different ways. Whereas brand trust influences purchase intentions and positive referrals, brand identification influences positive and oppositional brand referrals. Overall, the findings reveal the power of consumer-brand relationships in engendering brand evangelism, relative to other factors such as extraversion, gender, and brand experience.

In today's consumption society, where it is increasingly easier for consumers to demonstrate extreme devotion and derision toward brands, it is important for marketers to understand the drivers of behaviors directed toward brands. This study suggests that marketers can cultivate brand evangelism by building brand trust and brand identification.

Marketing researchers and practitioners are only recently beginning to understand brand evangelism. This study demonstrates that consumer-brand relationships, rather than personality, gender, and usage experience, trigger brand evangelism and offers directions for future researchers to further explicate brand evangelism.