Was it good for them? Reflections on the use of MENTOR and changes in course design using general performance measures

This paper considers the use of general performance measures in evaluating specific planning and design decisions in higher education and reflects on the students' learning process. Specifically, it concerns the use of the MENTOR multimedia computer aided learning package for helping students learn about OR as part of a general business degree. It includes the transfer of responsibility for a learning module to a new staff member and a change from a single tutor to a system involving multiple tutors. Student satisfaction measures, learning outcome measures and MENTOR usage patterns are examined in monitoring the effects of the changes in course delivery. The results raise some questions about the effectiveness of general performance measures in supporting specific decisions relating to course design and planning.

Spatial ecological complexity measures in GRASS GIS

Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes.

International stock portfolio selection and performance measures recognizing higher moments of return distributions

Since the seminal works of Markowitz (1952), Sharpe (1964), and Lintner (1965), numerous studies on portfolio selection and performance measure have been based upon the mean-variance framework. However, several researchers (e.g., Arditti (1967, and 1971), Samuelson (1970), and Rubinstein (1973)) argue that the higher moments cannot be neglected unless there is reason to believe that: (i) the asset returns are normally distributed and the investor's utility function is quadratic, or (ii) the empirical evidence demonstrates that higher moments are irrelevant to the investor's decision. Based on the same argument, this dissertation investigates the impact of higher moments of return distributions on three issues concerning the 14 international stock markets.^ First, the portfolio selection with skewness is determined using: the Polynomial Goal Programming in which investor preferences for skewness can be incorporated. The empirical findings suggest that the return distributions of international stock markets are not normally distributed, and that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of his optimal portfolio. The evidence also indicates that an investor will trade expected return of the portfolio for skewness. Moreover, when short sales are allowed, investors are better off as they attain higher expected return and skewness simultaneously.^ Second, the performance of international stock markets are evaluated using two types of performance measures: (i) the two-moment performance measures of Sharpe (1966), and Treynor (1965), and (ii) the higher-moment performance measures of Prakash and Bear (1986), and Stephens and Proffitt (1991). The empirical evidence indicates that higher moments of return distributions are significant and relevant to the investor's decision. Thus, the higher moment performance measures should be more appropriate to evaluate the performances of international stock markets. The evidence also indicates that various measures provide a vastly different performance ranking of the markets, albeit in the same direction.^ Finally, the inter-temporal stability of the international stock markets is investigated using the Parhizgari and Prakash (1989) algorithm for the Sen and Puri (1968) test which accounts for non-normality of return distributions. The empirical finding indicates that there is strong evidence to support the stability in international stock market movements. However, when the Anderson test which assumes normality of return distributions is employed, the stability in the correlation structure is rejected. This suggests that the non-normality of the return distribution is an important factor that cannot be ignored in the investigation of inter-temporal stability of international stock markets. ^

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Ecological indicators for system-wide assessment of the greater everglades ecosystem restoration program

Developing scientifically credible tools for measuring the success of ecological restoration projects is a difficult and a non-trivial task. Yet, reliable measures of the general health and ecological integrity of ecosystems are critical for assessing the success of restoration programs. The South Florida Ecosystem Restoration Task Force (Task Force), which helps coordinate a multi-billion dollar multi-organizational effort between federal, state, local and tribal governments to restore the Florida Everglades, is using a small set of system-wide ecological indicators to assess the restoration efforts. A team of scientists and managers identified eleven ecological indicators from a field of several hundred through a selection process using 12 criteria to determine their applicability as part of a system-wide suite. The 12 criteria are: (1) is the indicator relevant to the ecosystem? (2) Does it respond to variability at a scale that makes it applicable to the entire system? (3) Is the indicator feasible to implement and is it measureable? (4) Is the indicator sensitive to system drivers and is it predictable? (5) Is the indicator interpretable in a common language? (6) Are there situations where an optimistic trend with regard to an indicator might suggest a pessimistic restoration trend? (7) Are there situations where a pessimistic trend with regard to an indicator may be unrelated to restoration activities? (8) Is the indicator scientifically defensible? (9) Can clear, measureable targets be established for the indicator to allow for assessments of success? (10) Does the indicator have specificity to be able to result in corrective action? (11) What level of ecosystem process or structure does the indicator address? (12) Does the indicator provide early warning signs of ecological change? In addition, a two page stoplight report card was developed to assist in communicating the complex science inherent in ecological indicators in a common language for resource managers, policy makers and the public. The report card employs a universally understood stoplight symbol that uses green to indicate that targets are being met, yellow to indicate that targets have not been met and corrective action may be needed and red to represent that targets are far from being met and corrective action is required. This paper presents the scientific process and the results of the development and selection of the criteria, the indicators and the stoplight report card format and content. The detailed process and results for the individual indicators are presented in companion papers in this special issue of Ecological Indicators.

Salinity and Chlorophyll a as Performance Measures to Rehabilitate a Mangrove-Dominated Deltaic Coastal Region: the Ciénaga Grande de Santa Marta–Pajarales Lagoon Complex, Colombia

Salinity, water temperature, and chlorophyll a (chl-a) biomass were used as performance measures in the period 1999–2001 to evaluate the effect of a hydrological rehabilitation project in the Ciénaga Grande de Santa Marta (CGSM)–Pajarales lagoon complex, Colombia where freshwater diversions were initiated in 1995 and completed in 1998. The objective of this study was to evaluate how diversions of freshwater into previously hypersaline (>80) environments changed the spatial and temporal distribution of environmental characteristics. Following the diversion, 19 surveys and transects using a flow-through system were surveyed in the CGSM–Pajarales complex to continuously measure selected water quality parameters. Geostatistical analysis indicates that hydrology and salinity regimes and water circulation patterns in the CGSM lagoon are largely controlled by freshwater discharge from the Fundacion, Aracataca, and Sevilla Rivers. Residence times in the CGSM lagoon were similar before (15.5 ± 3.8 days) and after (14.2 ± 2.0 days) the rehabilitation project and indicated that the system is flushed regularly. In contrast, chl-a biomass was highly variable in the CGSM–Pajarales lagoon complex and not related to discharge patterns. Mean annual chl-a biomass (44–250 μg L−1) following the diversion project was similar to values recorded since the 1980s and still remains among the highest reported in coastal systems around the world owing to its unique hydrology regulated by the Magdalena River and Sierra Nevada de Santa Marta watersheds and the high teleconnection to the El Niño Southern Oscillation (ENSO). Our results confirm that the reduction in salinity in the CGSM lagoon and Pajarales complex during 1999–2000 was largely driven by high precipitation (2500 mm) induced by the ENSO–La Niña rather than by the freshwater diversions.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Exchange-Trade Funds Evaluation using Performance Measures Distribution

In this study we propose the use of the performance measure distribution rather than its punctual value to rank hedge funds. Generalized Sharpe Ratio and other similar measures that take into account the higher-order moments of portfolio return distributions are commonly used to evaluate hedge funds performance. The literature in this field has reported non-significant difference in ranking between performance measures that take, and those that do not take, into account higher moments of distribution. Our approach provides a much more powerful manner to differentiate between hedge funds performance. We use a non-semiparametric density based on Gram-Charlier expansions to forecast the conditional distribution of hedge fund returns and its corresponding performance measure distribution. Through a forecasting exercise we show the advantages of our technique in relation to using the more traditional punctual performance measures.

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.

Input-orientated data envelopment analysis framework for measuring and decomposing economic, environmental and ecological efficiency : an application to OECD agriculture

This paper presents an input-orientated data envelopment analysis (DEA) framework which allows the measurement and decomposition of economic, environmental and ecological efficiency levels in agricultural production across different countries. Economic, environmental and ecological optimisations search for optimal input combinations that minimise total costs, total amount of nutrients, and total amount of cumulative exergy contained in inputs respectively. The application of the framework to an agricultural dataset of 30 OECD countries revealed that (i) there was significant scope to make their agricultural production systemsmore environmentally and ecologically sustainable; (ii) the improvement in the environmental and ecological sustainability could be achieved by being more technically efficient and, even more significantly, by changing the input combinations; (iii) the rankings of sustainability varied significantly across OECD countries within frontier-based environmental and ecological efficiency measures and between frontier-based measures and indicators.

Measurement as legitimacy versus legitimacy of measures : Performance evaluation of social enterprise

Purpose The purpose of this paper is to review the growing emphasis on quantifiable performance measures such as social return on investment (SROI) in third sector organisations – specifically, social enterprise – through a legitimacy theory lens. It then examines what social enterprises value (i.e. consider important) in terms of performance evaluation, using a case study approach. Design/methodology/approach Case studies involving interviews, documentary analysis, and observation, of three social enterprises at different life-cycle stages with different funding structures, were constructed to consider “what measures matter” from a practitioner's perspective. Findings Findings highlight a priority on quality outcomes and impacts in primarily qualitative terms to evaluate performance. Further, there is a noticeable lack of emphasis on financial measures other than basic access to financial resources to continue pursuing social goals. Social implications The practical challenges faced by social enterprises – many of which are small to medium sized – in evaluating performance and by implication organisational legitimacy are contrasted with measures such as SROI which are resource intensive and have inherent methodological limitations. Hence, findings suggest the limited and valuable resources of social enterprises would be better allocated towards documenting the actual outcomes and impacts as a first step, in order to evaluate social and financial performance in terms appropriate to each objective, in order to demonstrate organisational legitimacy. Originality/value Findings distinguish between processes which may hold symbolic legitimacy for select stakeholder groups, and processes which hold substantive, cognitive legitimacy for stakeholders more broadly, in the under-researched context of social enterprise.

Determinants and measures of export performance – comprehensive literature review

As one of the key indicators of the firm’s ability to leverage successfully its resources and capabilities in the international context, export performance has been one of the most extensively studied phenomena. A plethora of studies have been conducted pertaining to provide better understanding of the factors (firm- or environment-specific) and behaviours (e.g., export strategy) that make exporting a successful venture. Following a comprehensive literature review undertaking in this study the current state of the export performance literature could be summarisedas (i) methodologically fragmented in that there is a variety of analytical and methodological approaches, (ii) conceptually diverse, a large number of determinants have been identified as having direct or indirect influence on the firm’s export performance, and a large number of indicators have been used to conceptualise and operationalise the export performance measures, and (iii) inconclusive, the studies have produced inconsistent results of the impact of different determinants on export performance.