The utilization of financial and non-financial measures in the evaluation of manufacturing organizations' performance is studied for a sample of 79 Portuguese financial analysts. Cluster analysis and multiple regression analysis are used to study the extent of use, importance and availability of information for 63 financial and non- financial measures. The results derived from this study point to the increasing importance of non- financial measures in the evaluation of manufacturing performance. Organizational and managerial implications of the findings are discussed, and a framework for future research is presented.

In the face of increasing pressure to improve patient satisfaction, the health-care industry must continue to seek improved methods to measure the effects of its continuous improvement efforts. While measurement instruments in this area abound, most are global in perspective and inflexible in form, sometimes leading to less than optimally germane outputs. Patient satisfaction information is critically important to the health-care provider, and this paper presents the results provided by an instrument that was locally designed to provide the most utile aggregation and presentation of patient satisfaction information for individual health-care providers. These results provide substantial evidence to support the notion that local, rather than global, measurement instruments are needed to provide the most relevant and useful results when assessing patient satisfaction as part of a continuous improvement effort.

Competitive pressures in the global manufacturing environment are forcing manufacturing organizations to re-engineer in order to become more competitive in the marketplace. Toward that end, management of these organizations is paying closer attention to the changing nature of manufacturing performance, and the systems, processes and measures used in its evaluation. Examines the literature concerned with issues related to the different facets of manufacturing organizational performance. Reviews and classifies articles published in relevant journals between 1988 and 2000. Based on this extensive literature review, identifies and discusses several issues relevant to both practice and theory of manufacturing performance measurement. Concludes by presenting a conceptual framework outlining the evolution of manufacturing performance measures and measurement in an organizational context.

This study compared the longitudinal performance of two groups of toddlers with palatal clefts and an age-matched group of children without palatal clefts on measures of elicited symbolic play at 18, 24, and 30 months. The results indicated that the group with isolated cleft palate differed significantly from both the cleft lip and palate group and the noncleft group on all but 1 play measure. Correlational analyses for each group indicated significant positive correlations between a number of the play variables at 18 months and productive vocabulary and MLU at 24 and 30 months of age. The findings suggest that assessment of early play gestures may assist clinicians in identifying children with clefts who are at risk for later language impairment.

The health care industry can expect an expanding need to measure and report the quality of performance and related outcomes. This article presents a flexible application operationalizing the strategies of total quality management and continual and rapid improvement in the area of assessing patient satisfaction. Mountain States Health Alliance established seven strategic criteria for the Outcomes Assessment Strategy and Information System (OASIS) design based on its own strategic initiatives and quality improvement principals. These initiatives are supported by the software application referred to as ContAct. Substantial process improvements have resulted. As pressures from stakeholders continue to mount, it will become increasingly important that patient satisfaction information be used to improve processes. The system presented provides one piece of an overall approach that will result in a rise to world-class status for the health care industry.

This paper seeks to investigate the reasons why, in an increasingly competitive health care milieu, patients choose certain hospitals over others. It introduces the modified importance-performance analysis technique and presents the method and findings of an empirical study which applied importance-performance analysis in a health care setting. The strategies derived from the study findings are discussed.

This research tests for correlation between corporate performance and use of financial measures, nonfinancial measures, and number of balanced scorecard categories used. Literature notes a preference for managing by nonfinancial measures because financial measures are lagging indicators, but little empirical evidence is available on the relationship between nonfinancial measures and financial performance, and few companies are found to realize the benefits of nonfinancial measurements. The balanced scorecard has been studied to find the impact of diversity of performance measures, and anecdotal improvements have been reported, but there is a paucity of empirical evidence regarding how the use of a balanced scorecard impacts organizational performance. These issues are investigated in this research with a web based survey distributed to a sample of publicly traded companies using a systematic selection process based on randomly selected numbers generated for each 3-digit NAICS category. The dependent variable is a rank of high, medium or low performance based on 12-month rolling average stock price comparisons from January 2005 to January 2009. These averages are analyzed as a percent change for each company, with performance standardized by 3-digit NAICS category to eliminate cross industry variance in performance ranking. Kruskal-Wallis one-way ANOVA is used to test for correlation. High performers show greatest utilization of both financial and nonfinancial measures, followed by medium performers, with low performers utilizing both measures the least. Nonfinancial performance measures are more correlated to firm value than financial measures with the high performers' mean score for nonfinancial measures being higher than for financial measures. By contrast, medium and low performers exhibit the opposite: higher mean scores for financial measures than for nonfinancial measures [p ≤ 0.05 for nonfinancial measures and p ≤ 0.1 for financial measures]. Correlation is found to be borderline significant (p = 0.06) for the number of balanced scorecard categories used with high performers utilizing the highest number of categories and low performers utilizing the lowest number of categories [p = 0.009 with inclusion of two respondents reporting no usage of balanced scorecard categories].

Most training performance measurement tools rely heavily on quantitative metrics that do not consider factors impacting knowledge transfer and behavioral change such as social relationships and company culture. This study observed a training performance measurement tool for a major U.S.-based airline. Analysis of the measurement tool consists of: a pilot study providing a baseline for the current gaps in training performance measurement, a survey of flight attendants to understand how company cultural and social factors impact learning and knowledge transfer, and focus groups to provide an in-depth analysis of what the underlying company cultural and social factors are. Both quantitative and qualitative analysis were utilized to identify the impact of cultural factors and social relationships on performance measurement to provide in-depth understanding of the role of tacit knowledge transfer in the training environment. Results show that cultural factors such as empathy, coaching, and on-the-job training, negatively impact the accuracy of flight attendants' ability to measure learning and knowledge transfer. A second finding shows social factors, personality, and agreement, show a strong trend towards negatively affecting the ability to accurately measure learning and knowledge transfer. The proposed knowledge transfer measurement model was further modified to reflect the findings and the results of this study. Further recommendations include altering the measurement tool, prioritization of skills, and communicating purpose.

The amount of information available on both public and private networks continues to grow at a phenomenal rate. This information is contained within a wide variety of objects, including documents, e-mail archives, medical records, manuals, pictures and music. To be of any value, this data must be easily searchable and accessible. Information Retrieval (IR) is concerned with the ability to find and gain access to relevant information. As electronic data repositories continue to proliferate, so too, grows the variety of methods used to locate and access the information contained therein. Similarly, the introduction of innovative retrieval strategies—and the optimization of older strategies—emphasizes the need for an infrastructure capable of measuring and comparing the performance of competing Information Retrieval solutions, but such an environment does not yet exist. The purpose of this research is to develop an infrastructure wherein Information Retrieval solutions may be evaluated and compared. In 1979, an expert in the field believed the need for a system-independent benchmarking utility was long overdue—twenty-five years later, progress in this area has been minimal. Contrastingly, new theories have emerged; new techniques have been introduced; all with the goal of improving retrieval performance. The need for a system-independent analysis of retrieval performance is more critical now.

Although the nearing end of Moore’s Law has been predicted numerous times in the past, it will eventually come to pass. In forethought of this, many modern computing systems have become increasingly complex, distributed, and parallel. As software is developed on and for these complex systems, a common API is necessary for gathering vital performance related metrics while remaining transparent to the user, both in terms of system impact and ease of use. Several distributed performance monitoring and testing systems have been proposed and implemented by both research and commercial institutions. However, most of these systems do not meet several fundamental criterion for a truly useful distributed performance monitoring system: 1) variable data delivery models, 2) security, 3) scalability, 4) transparency, 5) completeness, 6) validity, and 7) portability. This work presents dCAMP: Distributed Common API for Measuring Performance, a distributed performance framework built on top of Mark Gabel and Michael Haungs’ work with CAMP. This work also presents an updated and extended set of criterion for evaluating distributed performance frameworks and uses these to evaluate dCAMP and several related works.