Narrow Results

This is an evaluation study of the expressiveness provided and the performance delivered by the coordination language S-NET in comparison to Intel’s Concurrent Collections (CnC). An S-NET application is a network of black-box compute components connected through anonymous data streams, with the standard input and output streams linking the application to the environment. Our case study is based on two applications: a face detection algorithm implemented as a pipeline of feature classifiers and a numerical algorithm from the linear algebra domain, namely Cholesky decomposition. The selected applications are representative and have been selected by Intel researchers as evaluation testbeds for CnC in the past. We implement various versions of both algorithms in S-NET and compare them with equivalent CnC implementations, both with and without tuning, previously published by the CnC community. Our experiments on a large-scale server system demonstrate that S-Net delivers very similar scalability and absolute performance on the studied examples as tuned CnC codes do, even without specific tuning. At the same time, S-Net does achieve a much more complete separation of concerns between compute and coordination layers than CnC even intends to.

Hedge funds are collective investment vehicles fast becoming popular with high net worth individuals as well as institutional investors. These are funds that are often established with a special legal status that allows their investment managers a free hand to use derivatives, short sell and exploit leverage to raise returns and cushion risk. Given that they have substantial latitude to invest, it is instructive to examine the performance of hedge funds as compared to other forms of managed funds. This paper provides an overview of hedge funds and discusses their empirical risk and return profiles. It also poses some concerns regarding the empirical measurements. Given the complexity of hedge fund investments, meaningful analytical methods are required to provide greater risk transparency and performance reporting. Hedge fund performance is also beset by a number of practical issues generating "practical risks". These risks are not fully addressed by the usual risk-adjusted performance measures in the literature. A penalty function to discount these extraneous risk dimensions is proposed. The paper concludes that further empirical work is required to provide informative statistics about the risk and return of hedge funds.

The purpose of this paper is threefold: to assess the performance of 55 international tourist hotels in Taiwan in 2001 in terms of managerial, occupancy, and catering efficiencies; to analyze hotel operating characteristics, which might explain the variation in managerial efficiencies across these hotels; and to measure productivity growth in the 34 international tourist hotels over the years 1990–2001. Empirical results indicate that (1) the marketing for lodging services was not operated efficiently in 2001; (2) the hotels operated poorly both at the levels of occupancy and catering efficiencies in 2001; (3) there is a weak tendency for a hotel with relative high catering efficiency to go with good occupancy efficiency; (4) differences in operating variables, such as the floor space of catering department, the number of guest rooms, the closeness of a hotel to CKS international airport, and the number of employees do have a significant influence upon hotel performance; and finally, (5) about 61.76% of hotels had annual productivity changes over time.

Precedent research based on data envelopment analysis (DEA) has been conducted to rank and benchmark the achievements of participating nations/regions in the Olympics, while this paper contributes to the Asian Games, with further concerns on two main issues, namely the common comparison basis for ranking decision making units (DMUs) and the reference feasibility between the inefficient DMUs and their benchmark targets. This paper extends previous DEA research by introducing an improved context-dependent DEA model, in which empirical results establish a unique and fair ranking system for all participating nations/regions, implying two corresponding suggestions for rank improvement. A series of stepwise learning targets are further identified, alternatively providing a gradual performance improvement path for the inefficient participants. The above results will be helpful for strategic decision making in sport management of the Asian nations/regions.

Utilizing a case study methodology, this study investigates ways in which fast growth small-to-medium enterprises (FGSMEs) measure firm performance. This investigation, involving 21 interviews with 18 companies, revealed that FGSMEs seem to adopt a multi-level approach involving different sources and contexts to performance measurement. Apart from the application of standard financial performance measures such as profits and growth, FGSMEs also utilize measures of customer satisfaction, attainment of industry awards, receipt of client reports, website popularity, number and quality of successful innovations adopted, objective employee performance indices, and staff retention. Founders highlight the importance of providing employees with flexible environments and career opportunities as a way to reduce churn. These organizational characteristics signal non-financial benefits and incentives of working in these firms to potential employees and customers. These findings are in accord with extant literature and the balanced scorecard perspective, advocating associations between performance measurement systems and management strategies.

In recent years, researchers and practitioners have invested considerable effort in the development of new investment fund performance measures that account for mean, variance and the higher moments of the return distribution. To justify the application and necessity of the new performance measures in decision-making, some authors argue that the theoretical conditions required to use the Sharpe ratio are violated by high skewness and kurtosis in empirical asset return data. In this note, we highlight that high levels of skewness and kurtosis and even cross-sectional variations in skewness and kurtosis do not allow a decision-theoretic rejection of the Sharpe ratio. However, we also point out that while it is hard to discard the measure on decision-theoretic grounds, it can be challenged on technical grounds because it has several undesirable properties.

This research focuses on developing a model that can be used to assess the performance of Small to Medium-Sized Manufacturing Enterprises (SMEs). The model will result from the integration of a decision tool called the Analytical Hierarchy Process (AHP) and a data analysis model called Data Envelopment Analysis (DEA). This research demonstrates that by eliminating flaws and taking advantage of each methodology's specific characteristics in identifying and solving problems, the new integrated AHP/DEA model appears to be a logical and sensible solution in multi-criteria decision-making problem.

The rapid development of modern information technology has led to fierce competition in today's telecommunication industry. Telecommunication firms' accountability demands that operating efficiency be measured, maximized, and benchmarked. This study proposes an alternative context-dependent data envelopment analysis (DEA) technique to explore the managerial performance and the benchmarks of 24 global leading telecom operators. The analysis measures the relative attractiveness and progress of global telecom operators on a specific performance level against operators exhibiting poorer and/or better performance. The set operators are grouped into different levels of efficiency frontiers. Each efficiency frontier on a specific performance level is then used as an evaluation context for the relative attractiveness and progress. The performance of the efficient telecoms changes as the inefficient telecoms change their performance. It is shown that the context-dependent DEA can be used to differentiate and benchmark the performance of efficient DMUs. These benchmarks may give a first guideline for performance improvement of global telecommunication operators.

Information visualization can accelerate perception, provide insight and control, and harness this flood of valuable data to gain a competitive advantage in making business decisions. Although such a statement seems to be obvious, there is a lack in the literature of practical evidence of the benefit of information visualization. The main contribution of this paper is to illustrate how, for a major European apparel retailer, the visualization of performance information plays a critical role in improving business decisions and in extracting insights from Redio Frequency Idetification (RFID)-based performance measures. In this paper, we identify — based on a literature review — three fundamental managerial functions of information visualization, namely as: a communication medium, a knowledge management means, and a decision-support instrument. Then, we provide — based on real industrial case evidence — how information visualization supports business decision-making. Several examples are provided to evidence the benefit of information visualization through its three identified managerial functions. We find that — depending on the way performance information is shaped, communicated, and made interactive — it not only helps decision making, but also offers a means of knowledge creation, as well as an appropriate communication channel.

It is known that Data Envelopment Analysis (DEA) does not perform full ranking because DEA only classifies all of the efficient units as one in the Pareto sense. In this research, a hybrid approach, VFAD, that integrates the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology with Fuzzy Analytic Hierarchy Process (FAHP) and DEA is proposed to overcome this problem. Data collected from 50 fast food chain stores in Taipei City was used to verify the performance of the proposed VFAD approach. The result shows that the rank order of overall efficiency (OE) estimated by the DEA method alone and by VFAD approach are strongly and positively correlated. Moreover, the proposed VFAD method can fully rank the alternatives with multiple inputs and outputs. Thus, our empirical results conclude that some chain stores with equal efficiency in the Pareto sense can be more successfully ranked by our new ranking mechanism. Our proposed VFAD approach results in better performance in full ranking than the DEA method alone.

Intellectual assets are strategic resources that libraries can use to add value to services, but their intangible attributes make them hard to evaluate. An exploratory case study used document analysis, interviews and a questionnaire to develop and test indicators of intellectual assets and related performance measures at three university libraries in Thailand. The study demonstrated the feasibility of applying an intellectual capital perspective and a scorecard process model to design a workable system for evaluating library intangibles, particularly where libraries have a pre-existing interest in knowledge management and a culture of assessment.

Medical laboratories are complex facilities in which managing knowledge could impact patients’ lives. This paper presents a comprehensive and phased framework for knowledge management (KM) developed and applied within the Research and Medical Analysis Laboratory of the Gendarmerie Royale in Morocco. The model is built according to the PDCA wheel, and the four pillars of methodology are: leadership, knowledge core process, performance evaluation, and finally elements for its continuous improvement. This KM framework will help identify the knowledge needs and expectations of the medical laboratory’s relevant interested parties, support medical laboratory professionals with the decision-making process, and therefore enhance the quality of the services they provide.

In the logistics service supply chain (LSSC), performance measurement is an important approach that can improve competitiveness of the overall supply chain. In the complicated measurement system, it includes various quantitative and qualitative indices with uncertain problems. However, classical measurement methods were based on subjective suggestion to weigh each index in the measurement system; moreover, there is no well-established performance measurement system (PMS) for evaluation of LSSC. For those reasons, this paper aims to present Bijective soft set approach to deal with the performance measurement of LSSC, which ensures the objective of the weight of each index and gets the core indices of the PMS. Based on the overall LSSC operation, customer service, and corporate management — the three parts in the proposed system of LSSC — the indices, and consistency of the metrics have been selected. Finally, an empirical analysis of developed framework for performance measurement is conducted and tested.

This paper presents a unit-load automated storage and retrieval system’s (AS/RS) throughput analysis that uses an S/R machine for diagonal aisle transportation and a structure for both vertical and horizontal transportations. Although many methods are available to compute the AS/RS throughput rate, the method recommended by the Material Handling Institute (MHI) is more suitable for real or practical cases. This method assumes (i) randomized storage with constant vertical and horizontal speeds of the S/R machine, and (ii) simultaneous travel in both directions. We consider a new simplified and more efficient approach for MHI’s method to predict the throughput performance of the AS/RS.

This paper examines how 169 executives from leading North American electronics businesses assess their competitive operations abilities and performance, trends in business and manufacturing performance, technological readiness and manufacturing strategies. Comparative analysis reveals that the world-class electronics performers are accelerating their overall competitiveness, both internally by investing in technology and human assets and externally by forging strong relationships with customers. As a result, the most successful firms display heightened levels of organizational agility and performance.

This paper is concerned with comprehensive performance measurement (PM) of new product development (NPD). The idea of "life cycle conscious" NPD performance measurement is introduced by conducting a conceptual analysis combining product life cycle (PLC) thinking and NPD Performance Measurement (NPD PM). The empirical base of the paper is six case studies that focus on product life cycles and their characteristics within different industrial environments.

The paper indicates that there are several ways that NPD PM would benefit from life cycle thinking. Life cycle orientation would provide companies with a feasible framework for constructing the performance measures of NPD, and the framework is likely to reduce the short-termism typically associated with NPD PM. In addition, life cycle could provide help for weighting the criteria and the measures utilized in NPD, for finding a balance for the measurement system, and for directing proper attention towards the comprehensive effects of new products.

Although theoretical approaches to research and development (R&D) performance measurement are widespread, empirical investigations into the application of these theories are far less diffused. Therefore, we started a research project aimed at studying the R&D performance measurement practices adopted by Italian technology-intensive firms. This paper discusses the earliest empirical results of the project; it deeply investigates the experience of an Italian contract research organisation in designing a system of performance measures for its research activities.

The studied case is interesting for the following reasons: (i) it witnesses the increased interest by technology-intensive companies towards R&D performance measurement; (ii) it enlightens the lack of consolidated practices capable of guiding the design of an appropriate performance measurement system; (iii) it elaborates a practical framework that can help fill this gap. In fact, a systematic approach for linking different contextual variables (i.e. the company's strategy, the type of R&D activity undertaken, the purpose of the measurement and the R&D unit's organisational structure) to the critical design choices (i.e. the choice of the performance indicators and the structure of the system) is suggested.

Although measuring the performance of a firm's R&D activities is a very challenging task, the critical role played by R&D in creating and sustaining a firm's competitive advantage has raised the need to adopt appropriate performance measurement systems (PMSs) in R&D units. Therefore, management scholars have been studying this issue and PMSs have diffused in the R&D departments of most R&D-intensive companies. Nevertheless, empirical investigations into the diffusion and practical use of PMSs in R&D units mainly concern Anglo-Saxon countries, where R&D information disclosure requirements have been in place for a long time. The purpose of this paper is to study the diffusion and practical use of PMSs in the R&D units of firms that are not subject to these types of external institutional influences. With this aim, the results of a survey on the R&D performance measurement practices adopted by a sample of Italian R&D-intensive firms are discussed. They allow to understand why and how R&D-intensive companies design and use a PMS in their R&D units for managerial purposes.

In today's challenging economic climate it is more important than ever for companies to acquire comparable competitive advantage in their market. While previous research has investigated the performance measurement of R&D as a whole organization, very little research has been done into the performance management for just the research function itself. This, however, is of particular interest to larger organizations. This paper (1) introduces a framework for performance measurement for industrial research, and (2) presents a set of clusters, representing the content dimension for measuring research organizations. Based on the clusters, we were able to evaluate the extent to which performance measurement in practice in different companies can be compared. We discovered that the clusters follow a particular consistent distribution across organizations when the clusters are ranked by importance. For this empirical analysis, data was collected through in-depth case studies including more than 60 interviews and thorough document analyses.

This paper contributes to the limited but growing body of literature on the topic of new product development performance within the world-class UK fast moving consumer goods industry. It reports the findings of the second phase of an applied research project called that involved Asda and six of its leading private-label suppliers. Based upon questionnaire responses that characterise the performance of 283 new product lines developed over a twenty-month period, this paper details the baseline operational (technical) and commercial performance of the standard Asda product development process called Bullseye. This data includes its innovation profile, success profile, value adding profile and time-based performance (cycle time and lead time). The paper highlights a number of relationships within this data that contravene some of the key findings in the existing literature. It also provides insight into the resulting interventions necessary to both the Bullseye process itself and its supporting performance measurement system in order to achieve significant performance improvement.