The use of correspondence analysis to develop a scale to measure workplace morale from multi-level data

This paper focuses on the issue of comparing social groups or collectivities using measures derived from individual-level multivariate data. In this case, groups need to be differentiated such that: (a) between-group differences are maximized; (b) within-group differences are minimised; and (c) `differences' are calibrated to a scale that reflects a set indicators or observed variables.This paper demonstrates empirically how correspondence analysis can achieve this. It presents a scale of `workplace morale' derived from the responses of employees in a large sample of workplaces to questions concerning satisfaction with various facets of their job and their workplace. The scale derived through correspondence analysis is shown to achieve the three criteria described above.

Producing a GIS based multiple criteria analysis tool for regional sustainability assessment: the problem of weighting

Decision support tools will be useful in guiding regions to sustainability. These need to be simple but effective at identifying, for regional managers, areas most in need of initiatives to progress sustainability. Multiple criteria analysis (MCA) is often used as a decision support tool for a wide range of applications. This method allows many criteria to be considered at one time. It does this by giving a ranking of possible options based on how closely each option meets the criteria. Thus, it is suited to the assessment of regional sustainability as it can consider a number of indicators simultaneously and demonstrates how sustainability can vary at small scales across the region. Coupling MCA with GIS to produce maps, allows this analysis to become visual giving the manager a picture of sustainability across the region. To do this each indicator is standardised to a common scale so that it can be compared to other indicators. A weighting is then applied to each indicator to calculate weighted summation for each area in the region. This paper argues that this is the critical step in developing a useful decision support tool. A study being conducted in south west Victoria demonstrates that the weights chosen can have a dramatic impact on the results of the sustainability assessment. It is therefore imperative that careful consideration be given to determining indicator weights in a way that is objective and fully considers the impact of that indicator on regional sustainability.

An index of regional sustainability : a GIS-based multiple criteria analysis decision support system for progressing sustainability

GIS (Geographical Information Systems) based decision support tools will be useful in helping guide regions to sustainability. These tools need to be simple but effective at identifying, for regional managers, areas most in need of initiatives to progress sustainability. Multiple criteria analysis (MCA) has been used as a decision support tool for a wide number of applications, as it provides a systematic framework for evaluating various options. It has the potential to be used as a tool for sustainability assessment, because it can bring together the sustainability criteria from all pillars, social, economic and environmental, to give an integrated assessment of sustainability. Furthermore, the use of GIS and MCA together is an emerging addition to conducting sustainability assessments. This paper further develops a sustainability assessment framework developed for the Glenelg Hopkins Catchment Management Authority region of Victoria, Australia by providing a GIS-based decision support system for regional agencies. This tool uses multiple criteria analysis in a GIS framework to assess the sustainability of sub-catchments in the Glenelg Hopkins Catchment. The multiple criteria analysis based on economic, social and environmental indicators developed in previous stages of this project was used as the basis to build a model in ArcGIS1. The GIS-based multiple criteria analysis, called An Index of Regional Sustainability Spatial Decision Support System (AIRS SDSS),
produced maps showing sub-catchment sustainability, and environmental, social and economic condition. As a result, this tool is able to highlight those sub-catchments most in need of assistance with achieving sustainability. It will also be a valuable tool for evaluation and monitoring of strategies for sustainability. This paper shows the usefulness of GIS-based multiple criteria analysis to enhance the monitoring and evaluation of sustainability at the regional to sub-catchment scale.

Multiple-criteria decision analysis for integrated catchment management

Implementation of integrated catchment management (ICM) is hampered by the lack of a conceptual framework for explaining how landowners select farming systems for their properties. Benefit–cost analysis (a procedure that estimates the costs and benefits of alternative actions or policies) has limitations in this regard, which might be overcome by using multiple-criteria decision analysis (MCDA). MCDA evaluates and ranks alternatives based on a landowner's preferences (weights) for multiple-criteria and the values of those criteria. A MCDA approach to ICM is superior to benefit–cost analysis which focuses only on the monetary benefits and costs, because it: 1) recognizes that human activities within a catchment are motivated by multiple and often competing criteria and/or constraints; 2) does not require monetary valuation of criteria; 3) allows trade-offs between criteria to be measured and evaluated; 4) explicitly considers how the spatial configuration of farming systems in a catchment influences the values of criteria; 5) is comprehensive, knowledge-based, and stakeholder oriented which greatly increases the likelihood of resolving catchment problems; and 6) allows consideration of the fairness and sustainability of land and water resource management decisions. A MCDA based on an additive, multiple-criteria utility function containing five economic and environmental criteria was used to score and rank five farming systems. The rankings were based on the average criteria weights for a sample of 20 farmers in a US catchment. The most profitable farming system was the lowest-ranked farming system. Three possible reasons for this result are evaluated. First, the MCDA method might cause respondents to express socially acceptable attitudes towards environmental criteria even when they are not important from a personal viewpoint. Second, the MCDA method could inflate the ranks of less profitable farming systems for the simple reason that it allows the respondent to assign non-zero weights to non-economic criteria. Third, the MCDA might provide a better framework for evaluating a landowner's selection of farming systems than the profit maximization model.

Impact of comorbidities and gender on the use of coronary interventions in patients with high-risk non-ST-segment elevation acute coronary syndrome

OBJECTIVES: To determine the impact of gender and comorbidity on use of coronary interventions in patients diagnosed with high-risk non-ST-segment acute coronary syndrome (NSTEACS). BACKGROUND: Guidelines recommend the use of coronary angiography for all patients diagnosed with NSTEACS with high-risk features, except in the presence of severe comorbidities. However, little is understood about the relationship between gender, comorbidity, and the use of coronary interventions. METHODS: Retrospective analyses of the Victorian Admitted Episodes Data Set (VAED) including all patients diagnosed with NSTEACS with high-risk features on their first admission for ACS between June 2007 and July 2009. Hierarchical logistic regression models and correspondence analyses were used to understand the relationship between gender, comorbidities, and the use of coronary interventions. RESULTS: Out of 16,771 NSTEACS patients with high-risk features, 6,338 (38%) were female. Females were older than males (aged ≥75: 62% vs 39%, p < 0.001) and more likely to have multiple comorbidities (≥2: 66% vs 59%, p < 0.001). After adjusting for potential confounders, females were more likely to receive no coronary intervention than males with a similar number of comorbid conditions (no comorbidities: OR 1.62, 95% CI 1.28-2.05; 1 comorbidity: OR 1.67, 95% CI 1.44-1.93; 2 comorbidities: OR 1.93, 95% CI 1.66-2.23; ≥3 comorbidities: OR 1.42, 95% CI 1.27-1.60). CONCLUSIONS: Lower rates of coronary intervention in females persisted after adjusting for number of comorbidities which suggests that gender may bias decisions regarding referral for coronary intervention in high-risk NSTEACS independent of other factors.

Linking environmental uncertainty to non-financial performance measures and performance : a research note

Several previous research studies have reported mixed results concerning the direct association between non-financial performance measures and  performance. The presence of environmental uncertainty on this relationship has not been established. This paper makes a contribution to this area by proposing that it is in conditions of environmental uncertainty that non-financial measures are most useful in improving organizational performance. It analyses empirical data from a sample of New Zealand manufacturing organizations to test the hypothesis that non-financial measures of performance would lead to improved organizational performance under conditions of increased environmental uncertainty. Multiple regression analysis of the data suggests that performance should be a declining function of the size of the ‘mismatch’ between an organization's environment and use of the different combinations of non-financial performance measures. Further, the paper concludes that prior mixed results may be attributed to the omission of environmental uncertainty.

Methodological shifts in ratio-based modelling of corporate collapse

The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-based modelling of corporate collapse. This was facilitated by the introduction of a new statistical tool called Multiple Discriminant Analysis (MDA). However, it did not take long before other statistical tools were developed. The primary objective for developing these tools was to enable deriving models that would at least do as good a job asMDA, but rely on fewer assumptions. With the introduction of new statistical tools, researchers became pre-occupied with testing them in signalling collapse. lLTUong the ratio-based approaches were Logit analysis, Neural Network analysis, Probit analysis, ID3, Recursive Partitioning Algorithm, Rough Sets analysis, Decomposition analysis, Going Concern Advisor, Koundinya and Purl judgmental approach, Tabu Search and Mixed Logit analysis. Regardless of which methodological approach was chosen, most were compared to MDA. This paper reviews these various approaches. Emphasis is placed on how they fared against MDA in signalling corporate collapse.

Does the use of computer assisted learning packages improve performance in accounting?

This study examines the factors affecting student performance in an undergraduate financial accounting course, utilising Computer Assisted Learning (CAL). Multiple regression analysis on student performance shows that positive perceptions of the usefulness of CAL significantly influenced performance. It was also found that International students had significantly poorer performance than local students. This result may be attributed to transitional problems experienced by these students, given their different pathways to university study Prior studies of accounting and computing at secondary school level, together with gender, were not significant influences on performance. The results have implications for accounting educators utilising CAL in courses as a means of improving students understanding of accounting concepts and as a means of providing efficient and effective educational instruction to maximise learning outcomes in accounting.

A dynamic ratio-based model for signalling corporate collapse

The recognition of behavioural elements in finance has caused major shifts in the analytic framework pertaining to ratio-based modeling of corporate collapse. The modeling approach so far has been based on the classical rational theory in behavioural economics, which assumes that the financial ratios (i.e., the predictors of collapse) are static over time. The paper argues that, in the absence of rational economic theory, a static model is flawed, and that a suitable model instead is one that reflects the heuristic behavioural framework, which is what characterises behavioural attributes of company directors and in turn influences the accounting numbers used in calculating the financial ratios. This calls for a dynamic model: dynamic in the sense that it does not rely on a coherent assortment of financial ratios for signaling corporate collapse over multiple time periods. This paper provides empirical evidence, using a data set of Australian publicly listed companies, to demonstrate that a dynamic model consistently outperforms its static counterpart in signaling the event of collapse. On average, the overall predictive power of the dynamic model is 86.83% compared to an average overall predictive power of 69.35% for the static model.

Geographical dislocation and adjustment in university students: the impact of attachment, autonomy and coping behaviour on stress and well-being

The relative contribution of geographical dislocation, attachment styles, coping behaviours, and autonomy, to successful student adjustment, was examined in relation to stress and well-being. A sample of 142 on campus first year university students, across four Victorian university campuses completed self-report questionnaires. Questionnaires included demographic, social network, intrapsychic (attachment and autonomy), and coping variables. Multiple regression analysis revealed that being female, not having made a friend to confide in personal matters, lower achieved autonomy, and use of emotion-focused coping predicted higher levels of student stress. A second multiple regression analysis revealed that living away from home, and preferring others to approach oneself to initiate conversation or friendships predicted lower well-being, whilst increased frequency of phone and email contact, and greater secure parent and peer attachment, predicted greater well-being. Pearson's correlations indicated that securely attached students used more problem focused coping and social support, whereas insecurely attached students used more emotion focused coping. Qualitative data indicated student concerns about being away from family and friends, finance, course direction and structure, social opportunities on campus, and generally adjusting to the university culture. It was concluded that first year on-campus students would benefit from program initiatives targeting enhancement of on-campus social opportunities, development of autonomy, problem focused coping behaviour, interpersonal and social assertiveness.

The role of computer assisted learning packages in determining learning outcomes of accounting students

This study examines the factors affecting student performance in an undergraduate financial accounting course, utilising Computer Assisted Learning (CAL) and use of a commercial software package. Multiple regression analysis was undertaken to examine the influences of perceptions of CAL and QuickBooks Pro, together with background variables such as gender, entry pathway and prior knowledge had on student performance. The results show that perceptions of CAL together with entry pathway were significant predictors of student performance. However, perceptions of the ,usefulness of QuickBooks Pro, prior studies of accounting and computing, together with gender, were not significant influences on performance. In terms of entry pathway it was found that International students, many of whom entered the university at the second year level having obtained advanced standing credits, had significantly poorer performance than local students. This result may be attributed to transitional problems experienced by these students, given their different pathways to university study.

The results have implications for accounting educators utilising CAL in courses as a means of improving students understanding of accounting concepts. The study also provides reflections on the use of CAL and a commercial software package as a means of providing efficient and effective educational instruction to maximise learning outcomes in accounting.

Benchmarking new statistical techniques in ration-based modelling of corporate collapse

Up until 1979, Multiple Discriminant Analysis (MDA) was the primary multivariate methodological approaches to ratio-based modelling of corporate collapse. However, as new statistical tools became available, researchers started testing them with the primary objective of deriving models that would at least do as good a job as MDA, but that rely on fewer assumptions. Regardless of which methodological approach was chosen, most were compared to MDA. This paper analyses 84 studies on ratio based modelling of corporate collapse over the period 1968 to 2004. The results indicate that when MDA was not the primary methodology it was the benchmark of choice for comparison; thereby, demonstrating its importance as a foundation multivariate methodological approach in signalling corporate collapse.

Upregulation of peroxisome proliferator-activated receptor gamma coactivator gene (PGC1A) during weight loss is related to insulin sensitivity but not to energy expenditure

Aims/hypothesis We investigated whether skeletal muscle peroxisome proliferator-activated receptor gamma coactivator-1 (PGC1A; also known as PPARGC1A) and its target mitofusin-2 (MFN2), as well as carnitine palmitoyltransferase-1 (CPT1; also known as carnitine palmitoyltransferase 1A [liver] [CPT1A]) and uncoupling protein (UCP)3, are involved in the improvement of insulin resistance and/or in the modification of energy expenditure during surgically induced massive weight loss.
Materials and methods Seventeen morbidly obese women (mean BMI: 45.9 ± 4 kg/m2) were investigated before, and 3 and 12 months after, Roux-en-Y gastric bypass (RYGB). We evaluated insulin sensitivity by the euglycaemic–hyperinsulinaemic clamp, energy expenditure and substrate oxidation by indirect calorimetry, and muscle mRNA expression by PCR.
Results Post-operatively, PGC1A was enhanced at 3 (p = 0.02) and 12 months (p = 0.03) as was MFN2 (p = 0.008 and p = 0.03 at 3 and 12 months respectively), whereas UCP3 was reduced (p = 0.03) at 12 months. CPT1 did not change. The expression of PGC1A and MFN2 were strongly (p < 0.0001) related. Insulin sensitivity, which increased after surgery (p = 0.002 at 3, p = 0.003 at 12 months), was significantly related to PGC1A and MFN2, but only MFN2 showed an independent influence in a multiple regression analysis. Energy expenditure was reduced at 3 months post-operatively (p = 0.001 vs before RYGB), remaining unchanged thereafter until 12 months. CPT1 and UCP3 were not significantly related to the modifications of energy expenditure or of lipid oxidation rate.
Conclusions/interpretation Weight loss upregulates PGC1A, which in turn stimulates MFN2 expression. MFN2 expression significantly and independently contributes to the improvement of insulin sensitivity. UCP3 and CPT1 do not seem to influence energy expenditure after RYGB.

Adiponectin in umbillcal cord blood is inversely related to low-density lipoprotein cholesteril but not ethnicity

Context: Adiponectin is a recognized protective risk marker for cardiovascular disease in adults and is associated with an optimal lipid profile. The role of adiponectin at birth is not well understood, and its relationship with the neonatal lipid profile is unknown. Because ethnic disparities in cardiovascular risk have been attributed to low adiponectin and its associated low high-density lipoprotein cholesterol (HDL-C), investigation at birth may help determine the etiology of these risk patterns.

Objective: Our objective was to investigate the relationship between neonatal adiponectin and lipid profile at birth in two ethnic groups in cord blood.

Design, Setting, and Participants: Seventy-four healthy mothers and their newborns of South Asian and White European origin were studied in this cross-sectional study at St. Mary’s Hospital, Manchester, United Kingdom.

Main Outcome Measures: Serum adiponectin, total cholesterol, HDL-C, low-density lipoprotein cholesterol (LDL-C), and triglyceride levels were measured in umbilical venous blood at birth and in maternal blood collected at 28 wk gestation.

Results: Cord adiponectin was significantly inversely associated with cord LDL-C (r = –0.32; P = 0.005) but not HDL-C. In a multiple regression analysis, cord LDL-C remained the most significant association of cord adiponectin (ß = –0.13; P < 0.001). We did not find any significant ethnic differences in cord adiponectin or lipids with the exception of triglycerides, which were significantly lower in South Asian newborns (P < 0.05).

Conclusion: This is the first report of an inverse relationship between cord adiponectin and LDL-C at birth. In contrast to adult studies, we found no significant association between adiponectin and HDL-C in cord blood. Our results and the strong independent association between adiponectin and HDL-C observed in adult studies suggest a role for adiponectin in lipid metabolism. Ethnic differences in adiponectin may arise after birth.