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Component analysis is a simple technique which can be readily used by all those in general management to determine which are the most profit sensitive variables over which they have control. Using basic financial data, the analysis has five steps starting with the now familiar return‐on‐investment tree and ending with a ranking of the firm's performance sensitive components according to feasibility for improvement. Using this analytical approach, general managers are able to concentrate their scarce time on a small number of activities that will produce the greatest amount of profit and the maximum return‐on‐investment. A modified form of component analysis has been successfully used over the past eighteen months in all the subsidiary companies of a recently formed conglomerate.

This study aims to identify systematically the factors that can often influence labour productivity directly and indirectly, to build a model that can evaluate the significance of these factors. The model can be used as a tool for assisting field construction mangers responsible for productivity.

The factors were first identified by undertaking a literature review. The scope and method for measuring labour productivity were then determined. The final analysis model was built through a statistical analysis conducted with the chosen factors.

The results of the analysis indicate that the work management component (e.g. the manager's abilities) and the work technique component (e.g. work continuity) have greater impact than the worker component (e.g. the workers' capability) and the work characteristic component (e.g. work difficulty).

This research focuses on the qualitative perspective of site managers on labour productivity. Although the process of translating qualitative opinions into quantitative data is a matter for debate, the result of this research, when compared to other quantitative studies, can be used to establish a strategy and an action plan for managing labour productivity.

Qualitative aspects that were considered to establish a labour productivity model can be evaluated by site construction managers. Despite the importance of these qualitative aspects, they have, by and large, been neglected, as models to date tend to consider more directly measurable quantitative factors. In particular, they can be used to develop a strategy for increasing labour productivity at the initial planning stage.

This research explores the differences between a subjective perception and the objective reality of labour productivity.

The purpose of this paper is to explore and map the intellectual structure of biofuel research.

The study attempts to present the structure of biofuel research through document co‐citation patterns of core references. Document co‐citation analysis was performed using the Web of Science of the Thomson‐ISI database. A sample of 26 cited references was identified and the co‐citation frequencies were analyzed and represented them systematically within groups of similar researched topics.

The study shows the co‐citation analysis method suitable for depicting structure of biofuel research in document clusters by performing multivariate analysis: cluster analysis, factor analysis, multidimensional scaling and network analysis.

The study is limited to research articles and co‐citation data for the first author only. For the co‐citation analysis, the cited references rather than the cited authors were used as the units for analysis.

Co‐citational analysis using multivariate tools provides a useful technique to explore and document the development of the field supplementing the insights normally available from the routine co‐citational analysis.

Specialties in biofuel research are identified and this may provide a valuable building block for future research.

This paper aimed to contextualize the process of public hospital providing services, based on the measurement of the performance of Federal University Hospitals (HUFs) of Brazil, using the technique of multivariate statistics of principal component analysis.

This research presented a descriptive and quantitative character, as well as exploratory purpose and followed the inductive logic, being empirically structured in two stages, that is, the application of principal component analysis (PCA) in four healthcare performance dimensions; subsequently, the full reapplication of principal component analysis in the most highly correlated variables, in module, with the first three main components (PC1, PC2 and PC3).

From the principal component analysis, considering mainly component I, with twice the explanatory power of the second (PC2) and third components (PC3), it was possible to evidence the efficient or inefficient behavior of the HUFs evaluated through the production of medical residency, by specialty area. Finally, it was observed that the formation of two groups composed of seven and eight hospitals, that is, Groups II and IV shows that these groups reflect similarities with respect to the scores and importance of the variables for both hospitals’ groups.

Among the main limitations it was observed that there was incomplete data for some HUFs, which made it impossible to search for information to explain and better contextualize certain aspects. More specifically, a limited number of hospitals with complete information were dealt with for 60% of SIMEC/REHUF performance indicators.

The use of PCA multivariate technique was of great contribution to the contextualization of the performance and productivity of homogeneous and autonomous units represented by the hospitals. It was possible to generate a large quantity of information in order to contribute with assumptions to complement the decision-making processes in these organizations.

Development of public policies with emphasis on hospitals linked to teaching centers represented by university hospitals. This also involved the projection of improvements in the reach of the efficiency of the services of assistance to the public health, from the qualified formation of professionals, both to academy, as to clinical practice.

The originality of this paper for the scenarios of the Brazilian public health sector and academic area involved the application of a consolidated performance analysis technique, that is, PCA, obtaining a rich work in relation to the extensive exploitation of techniques to support decision-making processes. In addition, the sequence and the way in which the content, formed by object of study and techniques, has been organized, generates a particular scenario for the measurement of performance in hospital organizations.

Automotive industry is one of the most important industries in the economy of countries due to its extensive relationship with other industries; high production and employment rate play a significant role in the sustainable development of countries. Therefore, the improvement of value creation integration strategies in this industry is very important because it is related to the level of economic sustainability of countries. The purpose of this study is to analyze the integration matrix of the creating sustainable value process in the automotive industry.

This research is a development/mixed methodology that aims to symmetrically combine the relationship between the components of sustainable value creation integration through Mick Mac matrix analysis to identify the most effective drivers of the research subject in the Iranian automotive industry. Therefore, in this study, first, in the qualitative part, meta-synthesis analysis and Delphi analysis were used to identify the thematic components of the integration of the process of creating sustainable value and to determine the theoretical adequacy of the components. Then, in a small part, an attempt was made to explain the approved components, based on the symmetric matrix analysis in the Mic Mac diagram, in the automotive industry to determine a more stimulus for integrating the sustainable value creation process, with the participation of 16 automotive executives.

Based on the results in the qualitative section, 8 thematic components were identified to evaluate the integration of the sustainable value creation process, and after Delphi approval, these components were approved in terms of theoretical adequacy. The results in the quantitative part based on matrix analysis showed that the most motivating component in integrating the process of creating sustainable value in the automotive industry is the development of innovative ideas. To create integration in creating sustainable value, it is necessary to create a positive impact of creative ideas in the three components of balancing performance with the changing needs of K3 customers, the dynamics of communication with K8 suppliers, reducing the diversity of materials used in K5 production.

This paper is considered as a research that contributes to the broader research area of the automotive industry by unpacking the concept of value creation from a sustainability perspective. This is the first study to review extensively of integrating sustainable value creation process into the automotive industry. Although an area of research importance in terms of developing theoretical literature and applied basis in increasing the effectiveness of competitive strategies. But less research has examined this issue, and conducting this research and expanding it to the level of sustainability value literature can enhance its institutional and research capacities at the international level and contribute to the coordination of the development of theoretical.

The aim of this study was to evaluate the performance of fuel flow processes in a network of eight gas stations, located in the mesoregion of Alto Paranaíba and Triângulo Mineiro.

Two multi-criteria decision support methods were applied, respectively, of a statistical and mathematical nature, namely, Principal Component Analysis (PCA) and Data Envelopment Analysis (DEA). The research method used was quantitative, with a brief complement of qualitative research, and descriptive in purpose, supported by the inductive method. The data collection stage took place with the support of interviews, with the application of a structured questionnaire, and non-probabilistic sampling, for convenience.

It was possible to verify that the gas station that stood out the most was station 2 (GS2), which achieved maximum efficiency, a fact that can be justified by the analysis resulting from the application of PCA, as for the product purchase variable (PP), the GS2 is the one that buys the most fuel, and is also the one with the largest storage capacity (C), and the highest volume of product sales (PS), which suggests signs of balance between supply and demand for this station, justifying its prominence.

The limitations of the study were related to the DEA technique, which requires a number of variables/indicators three times smaller than the number of DMUs considered, and the difficulty in obtaining financial data on the DMUs analyzed. Considering the security and anonymity of the gas station network, it was not possible to use this data.

The performance assessment of fuel flow processes carried out in this study promotes the efficient use of available resources as well as identifying efficient DMUs that represent benchmarks for improving management processes and performance of inefficient DMUs.

From a social perspective, this study promotes the improvement of the quality of flow processes and effective management of the fuel supply chain, ensuring the safe storage and transportation of fuels to customer supply. Performance management in this sector moves other sectors of the economy, since an efficient unit represents a balance between supply and demand, and consequently, boosts the regional economy, promoting economic growth of the population. Hiring qualified labor for this purpose also represents one of the implications of the study. From an environmental perspective, optimizing flow processes generates a reduction in greenhouse gas emissions and encourages the formulation of public policies aimed at consolidating sustainable practices.

Performance management applied to the context of the fuel supply chain is a relevant topic that has been little explored in scientific research, with a low level of information detail. This study using the inductive method allows the generalization and replication of this management pattern in other organizations in the sector in order to increase the efficiency of the fuel distribution system, with the perspective of maximizing outputs and reducing input consumption. In this aspect, the study introduces possibilities for advancement in social and environmental perspectives based on the effective management of fuel logistics.

The purpose of this paper is to better understand the spatial structure of the Lyon urban area focusing on real estate. For this, two aims are formulated. The first aim is to identify and geographically analyse latent structure underlying apartment variables and location. The second aim is to decrease a number of explanatory variables in a hedonic model of real estate prices applying latent constructs.

For the first aim of a parsimonious representation among measured variables, exploratory factor analysis is applied. For the second aim of data reduction, principal component analysis (PCA) is used. The exploited regression methodologies are global and geographically weighted ordinary least squares.

Four factors are extracted, of which two represent apartment attributes and other two – location attributes. Principal components provide better insight into location attributes dividing the service employment centres into two geographical groups. The inclusion of principal components in hedonic price equation instead of initial location variables decreases goodness of fit, but does not gradually change non‐location estimates and other parameters.

Differently from previous applications of factor analysis and PCA in the real estate domain, oblique rotation is applied, which allows the extracted factors or components to be correlated. The scores of factors and components are interpolated from points to raster maps creating a continuous geographical distribution. Hedonic models with and without principal components are compared in detail.

This paper seeks to explore and detect underlying relationships between identifiable primary causes of defects in local authority housing stock with the view to identifying which groups of building components are associated with one another. It is primarily based on responses to a questionnaire from building surveyors who were involved in the day‐to‐day diagnosis of defects of a large local authority housing stock. The intercorrelations among the primary defect‐causing factors demanded the application of principal component analysis to determine the factors affecting deterioration of the building fabric. This resulted in the extraction of nine significant factors which combine to exert their influence on the building.

The paper presents reliability, maintainability and life cycle cost (LCC) analysis of a computerized numerical control (CNC) turning center which is manufactured and used in India. The purpose of this paper is to identify the critical components/subsystems from reliability and LCC perspective. The paper further aims at improving reliability and LCC by implementing reliability-improvement methods.

This paper uses a methodology for the reliability analysis based on the assessment of trends in maintenance data. The data required for reliability and LCC analysis are collected from the manufacturers and users of CNC turning center over a period of eight years. ReliaSoft’s Weibull++9 software has been used for verifying goodness of fit and estimating parameters of the distribution. The LCC of the system is estimated for five cost elements: acquisition cost, operation cost, failure cost, support cost and net salvage value.

The analysis shows that the spindle bearing, spindle belt, spindle drawbar, insert, tool holder, drive battery, hydraulic hose, lubricant hose, coolant hose and solenoid valve are the components with low reliability. With certain design changes and implementation of reliability-based maintenance policies, system reliability is improved, especially during warranty period. The reliability of the CNC turning center is improved by nearly 45 percent at the end of warranty period and system mean time between failure is increased from 15,000 to 17,000 hours. The LCC analysis reveals that the maintenance cost, operating cost and support costs dominate the LCC and contribute to the tune of 87 percent of the total LCC.

The proposed methodology provides an excellent tool that can be utilized in industries, where safety, reliability, maintainability and availability of the system play a vital role. The approach may be improved by collecting data from more number of users of the CNC turning centers.

The approach presented in this paper is generic and can be applied to analyze the repairable systems. A real case study is presented to show the applicability of the approach.

The proposed methodology provides a practical approach for the analysis of time-to-failure and time-to-repair data based on the assessment of trends in the maintenance data. The methodology helps in selecting a proper approach of the analysis such as Bayesian method, parametric methods and nonparametric methods.

Participants in Internet net news bulletin board discussions can argue with others whom they do not know. The nature of each message in a discussion can be characterized by the frequency with which keywords appear in the message. This incidence or frequency can be summarized as a principal component score. By deriving two characteristic indexes – auto‐correlation coefficients and power spectra – from the principal component scores, we have come up with a novel method. Applying this method to analyze three large net news threads, the index plots revealed two‐generation cyclic fluctuations. Comparing these plots with actual points of conflict obtained by reading the message contents, a fairly good correlation was obtained between the two and it was found that most of the conflicts were among participants with different cultural backgrounds.