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The purpose of this study was to investigated the importance of environmental attributes for office building adaptation and whether the importance of environmental attributes for adaptation has changed over time from 1998-2008 to 2009-2011. With 1-2 per cent added to the total stock of buildings each year and the need to take action to mitigate the impacts of predicted climate change (IPCC, 2013), it is necessary to focus efforts on adaptation of existing buildings.

This research adopted a quantitative approach, using a database of office building attributes and applying principal component analysis to ascertain the respective importance of various building attributes in adaptation. Using two databases; the first dating from 1998 to 2008 and comprising 5,290 adaptation events and the second covering the period 2009 to 2011 and comprising 1,272 adaptation events, a comparison of results was undertaken.

The findings indicate the importance of some environmental attributes in building adaptation has changed and that legislation and changes market perceptions towards to promote built environment sustainability may be having a positive impact. The research demonstrates that different property attributes vary in importance over time and used existing buildings in an international city to confirm application to urban settlements elsewhere where existing buildings can be adapted to reduce the effect of climate change.

The databases are limited to Melbourne, Australia and to these specific points in time. It is possible that other cities are seeing changes in adaptation practices to accommodate increased awareness and the growing importance attributed to environmental issues; however, additional studies would be required to ascertain whether the level of importance was stronger or weaker than that found in Melbourne.

The impacts of the mandatory The National Australian Built Environment Rating System energy rating tool and the Green Star voluntary tool provide actionable data for property stakeholders and the academic community. Policy-makers can see that building owners are integrating environmental attributes into their stock and that the market is shifting towards increased sustainability. This study uses real world data to feed the scholarship process, with real economic and commercial impacts. New buildings account for about 1-2 per cent of the total building stock annually and existing buildings must be adapted, and thus the questions of the success of voluntary or mandatory measures are essential to future environmental decision-making.

This research reports on data covering all office building adaptation conducted from 1998 to 2011 in the Melbourne CBD. As such, it is a comprehensive analysis of all works undertaken and how the significance of different physical, social, economic and environmental attributes is changing over time.

The purpose of this paper is to empirically examine the issue of convergence in the monthly returns, rental growth and yields for ten market segments in the UK direct real estate market, using monthly data over the period from January 1987 to December 2014.

The methodology used to determine convergence is principal component analysis as it provides an assessment of the extent to which the variance of the market segments can be represented by a single common factor, explaining their long-run behaviour, and the degree of independence between the market segments.

The results suggest that there is strong evidence of convergence over the entire sample period in relation to monthly returns and yields but less evidence of convergence in rental growth, which confirms the findings in previous studies in international markets.

The evidence also suggests that convergence has increased over the sample period and that convergence is period specific and was particularly strong during and after the period of the Global Financial Crisis, which implies that the UK direct real estate market is largely integrated and as a consequence the extent of diversification potential in the market is still severely limited.

The convergence in returns has crucial implications for investors as it leaves investors exposed to the same structural shocks and so magnifies the importance of volatility spillover effects, limits their ability to create well-diversified portfolios and make it more difficult for fund managers to outperform the market.

This is the first paper to examine the convergence in the UK direct real estate market.

The purpose of this paper is to verify the applicability of proposed lean production system (LPS) framework in the Indian manufacturing industry.

The authors conducted a cross-sectional study to collect responses from five major sectors, namely, automobile, process, machines and equipment, electronics and components and textile. They collected 200 responses to perform empirical validation from Indian manufacturing industry. They performed reliability analysis on the proposed framework of LPS in the Indian manufacturing industry.

The findings revealed that all the elements and sub-elements have a high value in reliability. Subsequently, the study performed principles component analysis on LPS framework. The empirical investigation revealed that the proposed LPS framework has a high level of reliability as well as validity in the Indian manufacturing industry. Hence, the study concluded that the LPS framework is helpful to implement lean principles in a structured manner in any Indian manufacturing industry to achieve excellence in organizational functions.

The authors conducted an empirical survey to verify the applicability of the proposed LPS framework in the Indian manufacturing industry. They observed that many researchers proposed various LPS frameworks, but none of the researchers focused on verifying the proposed frameworks. To overcome, the same limitations, the study verified the proposed framework with the larger sample size.

This paper is a contribution to the literature on the branding of cultural institutions. In particular it focuses on visitor motivation in the field of museums and galleries. Measurement of visitor motivations and associated brand strength of cultural institutions is a relatively new concern for marketers. The need to develop further understanding of how best to market museums in the twenty‐first century motivates this research. Repertory grid analysis was used as the survey method in order to get data that were “rich” in terms of concepts, but also malleable in terms of statistical analysis. The results of an exploratory study of museum brand associations are reported, along with a discussion of the method of repertory grid analysis that was used to obtain the data. A total of 11 museums in London were targeted, with a special focus on the Tate Gallery.

The purpose of this paper is to develop a new suit sizing system based on up‐dated data, using data mining techniques, to improve the final quality and reduce the waste of fabric. This paper aims to investigate the effect of data reduction on the final fitness of the sizing chart.

Principal component analysis is applied to reduce the sizing variables, non‐hierarchical clustering approach is used to segment the heterogeneous population to more homogeneous one, and the aggregate loss of fitness is used to evaluate the resulted sizing chart.

The results show that, when principal component analysis reduces the ten sizing variables to two main components, the final fitness for the resulted sizing chart is the best. These two main components are height and circumference. The hierarchical clustering approach could effectively group all body type to seven clusters. The resulted sizing chart could be used as a reference for suit manufacturers.

Due to wide differences in race, nutrition and climate, people who live in different countries have their own body size; also, most of current sizing systems are out‐dated, so there is an urgent need to develop a new sizing system. Due to the growing rate of globalization, the final results will be useful for those companies wanting to connect to global business chains.

This work introduces the first suit sizing systems, based on data mining, for Iranian males, that has more fitness in comparison to the current sizing chart. The effect of the number of principal components on the final fitness of a sizing system is introduced as an innovative way, to avoid losing useful data during data reduction process with principal component analysis.

The purpose of this paper is to develop several predictive models for estimating the structural construction cost and establish range estimation for the structural construction cost using design information available in early stages of residential building projects.

Information about residential building projects is collected based on project documents from construction companies with regard to the design parameters and the actual structural construction costs at completion. Storey enclosure method (SEM) is fundamental for determining the building design parameters, forming the potential variables and developing the cost estimation models using regression analysis. Nonparametric bootstrap method is used to establish range estimation for the structural construction cost.

A model which is developed from an integration of advanced SEM, principle component analysis and regression analysis is robust in terms of predictability. In terms of range estimation, cumulative probability-based range estimates and confidence intervals are established. While cumulative probability-based range estimates provide information about the level of uncertainty included in the estimate, confidence intervals provide information about the variability of the estimate. Such information could be very crucial for management decisions in early stages of residential building projects.

This study could provide practitioners with a better understanding of the uncertainty and variability included in the cost estimate. Hence, they could make effective improvements on cost-related management approaches to enhance project cost performance.

This article uses a series of data mining techniques to analyze body types and introduce a new sizing chart in order to produce garments for males. A principle component analysis and hierarchical and non-hierarchical clustering approaches are used to form a new sizing chart. All variables are grouped into two main components with a principle component analysis. Agglomerative hierarchical clustering is used to determine the number of clusters, and then a k-means algorithm is applied to segment the heterogonous population to actually form the clusters. The resultant innovations in designing garments have improved both non-price and price factors, the fittings of garments on all bodies have effectively improved and fabric waste has decreased, so the main goals which include improvement in quality with more comfort and a lower price have been met.

The purpose of this research is to explore the structure and impact of police officers' social support network on health and well-being. Social integration promotes opportunities for regular positive experiences and a set of stable, socially rewarded roles within one's work and life domains. Identifying the structure and impact areas of police officers' social support network provide guidance for initiatives in improving psychological health for the department and individual officers.

Survey of 162 police officers' sources of support provided a holistic representation of their social network across seven sources. Principle component analyses were conducted to explore the structure of one's social network. Multiple regression analyses were conducted to examine overall impact of one's social support network and relative contributions of support sources in terms of increased well-being and reduced strain.

A three-component structure of social support was partially supported. Overall models of the impact of one's social support network related to increased well-being and reduced strain was supported. Relative contributions of support sources show different patterns based on outcome of interest.

Provides guidance for addressing the psychological well-being needs for officers holistically. In other words, treating officers as whole beings, whose system of support and psychological health is integrated, not piecemeal.

Examination of principle effects of support provides a parsimonious approach to considering the holistic value of one's support system, apart from specific stressors or conditions.

This paper aims to evaluate innovation capability of companies based on comprehensive methods.

This paper used principal component analysis (PCA), kernel principal component analysis (KPCA) and principal component cluster (PCC) analysis to analyze the listed companies’ innovation capability. On these bases, mean method, Borda method, Copeland method, alienation coefficient method and fuzzy Borda method were used separately for the comprehensive evaluation.

The results show that the comprehensive evaluation can overcome the shortage of the single method and improve the reliability of the innovation ability evaluation. In addition, the method also reveals that the innovation ability of the listed companies is closely related to the innovation investment and their industry and further regional economic development level of each province (city and area).

This paper uses PCA, KPCA and PCC to evaluate and study their innovation ability. On the basis of these, five methods (mean method, Copeland method, Borda method, divorced coefficient method and fuzzy Borda method) are applied respectively to combine the sort results of PCA, KPCA and PCC. The results show that combination methods have better theoretical and practical significance for innovation ability.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.