Assessment of potential energy saving using cluster analysis: A case study of lighting systems in buildings

Petcharat, Siriwarin; Chungpaibulpatana, Supachart; Rakkwamsuk, Pattana

doi:10.1016/j.enbuild.2012.06.006

Cited by 49 publications

(23 citation statements)

References 11 publications

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“…Esty et al, 2012;Wackernagel and Rees, 1996), enabling the identification and understanding of key variables that each group faces. Cluster analysis has proven helpful in leading to more efficient policy development by means of a finergrained approach for managing energy problems, for example, by setting differentiated energy reduction goals for different types of entities (Petcharat et al, 2012;Xia et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Once these dimensions were defined, we used cluster analysis to subsequently create four groups of nations conforming an empirical typology of alternative paths towards sustainability. In selecting the method for this study, we draw on prior research that emphasize Principal Component Analysis (PCA) and cluster analysis as relevant and novel approaches to deal with certain neglected areas of the environmental aspect of SD (Petcharat, et al 2012;Xia, et al 2011). Appendix A for variable explanation).…”

Section: Research Method Data Collection and Analysismentioning

confidence: 99%

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Transitions dynamics in context: key factors and alternative paths in the sustainable development of nations

Rodrigo

Wright

2015

Journal of Cleaner Production

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The spatial dimension of sustainability transitions is central to understanding how systems change, yet current literature falls short when it comes to explaining transitions dynamics in context, and the central factors and alternative paths through which particular spaces move towards or away from sustainable development efforts. We conduct an exploratory factor analysis and a post-hoc cluster analysis of sustainability transition dynamics at a spatial level in 99 nations. Based on our analyses we establish a multi-dimensional measurement tool of nation sustainability that considers place, time and directionality. The analysis yielded four key dimensions -governance quality, industrial pollution, socio-environmental conditions and clean wealth creation -upon which we elaborated clusters of nations representing four distinct empirical types of transition pathways, crossroaders, compliers, athletes and laggards. In doing so we provide a holistic view of the phenomenon, which is relevant for both further theorizing and policy development. *Manuscript Click here to view linked References AbstractThe spatial dimension of sustainability transitions is central to understanding how systems change, yet current literature falls short when it comes to explaining transitions dynamics in context, and the central factors and alternative paths through which particular spaces move towards or away from sustainable development efforts. We conduct an exploratory factor analysis and a post-hoc cluster analysis of sustainability transition dynamics at a spatial level in 99 nations. Based on our analyses we establish a multi-dimensional measurement tool of nation sustainability that considers place, time and directionality. The analysis yielded four key dimensions -governance quality, industrial pollution, socio-environmental conditions and clean wealth creation -upon which we elaborated clusters of nations representing four distinct empirical types of transition pathways, crossroaders, compliers, athletes and laggards. In doing so we provide a holistic view of the phenomenon, which is relevant for both further theorizing and policy development.Keywords: Sustainability transitions; Nation-level sustainability measurement; Empirical typology; Sustainability pathways; Factor analysis Highlights  It conducts a quantitative exploration of sustainability transition dynamics at a spatial level  It identifies sets of distinct factors and paths of sustainable development at national level  It conducts an EFA of 22 factors at the national level  It identifies 4 key dimensions relevant to capturing transition dynamics  It conducts a cluster analysis of 99 countries and develops an empirical typology of paths towards SD  It recognizes several policy implications for the four distinct groups of nations  It provides a promising start for the identification of key variables in sustainability research 2 1

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Section: Discussionmentioning

confidence: 99%

Section: Research Method Data Collection and Analysismentioning

confidence: 99%

Transitions dynamics in context: key factors and alternative paths in the sustainable development of nations

Rodrigo

Wright

2015

Journal of Cleaner Production

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“…Cluster analysis, also called clustering, is a statistical approach that attempts to find groups of closely related observations so that observations that belong to the same cluster are more similar to each other than observations that belong to other clusters (Bishop, 2006;Petcharat et al, 2012). The ideal number of clusters can be determined graphically by creating a dendrogram, a tree diagram commonly used in CA (Manly, 1994;McKenna, 2003).…”

Section: Cluster Analysismentioning

confidence: 99%

“…The ideal number of clusters can be determined graphically by creating a dendrogram, a tree diagram commonly used in CA (Manly, 1994;McKenna, 2003). As a common classification method, CA has long played an important role in a wide variety of fields (Petcharat et al, 2012). In the field of forestry, CA has been applied to the recognition and zoning of forest fire risk (Orozco et al, 2012;Li et al, 2015;Chang et al, 2015), the classification of forest management into subdivisions (Ma et al, 2015), and the classification of forest welfare services (Cha, 2015).…”

Section: Cluster Analysismentioning

confidence: 99%

Dynamic assessment of forest resources quality at the provincial level using AHP and cluster analysis

Wang

Yao

et al. 2016

Computers and Electronics in Agriculture

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a b s t r a c tThe aim of this study was to quantitatively assess and analyze the dynamic changes and current problems of Chinese forest resources based on the National Forest Inventory (NFI). In this study, a hierarchical model was established using the analytic hierarchy process to assess forest resources quality (FRQ) at the provincial level. Four criteria were used, including forest quantity, forest productivity, forest structure, and forest health and each criterion was further composed of multiple factors. Among these assessment factors, stock volume per unit area was the most important, while canopy structure was the least important. The ranges of FRQ Indies across China during the 6th NFI (1999( -2003( ), 7th NFI (2004( -2008, and 8th NFI (2009)(2010)(2011)(2012)(2013) were 0.3031-0.6366, 0.3499-0.7186, and 0.3534-0.7555, respectively. From the 6th to 8th NFI, forest quality improved by different degrees for all provinces, whereas the other three criteria presented an increasing or decreasing trend. In general, the implementation of ecological projects has significantly improved the FRQ at provincial and national levels. During the 8th NFI, the FRQ levels were excellent for 3 provinces, good for 15 provinces, medium for 12 provinces, and only one province exhibited an inferior level of FRQ. Based on cluster analysis, Chinese forest resources during the 8th NFI could be grouped into four clusters according to the provincial administrative region, and each cluster had its own advantages and disadvantages. Stock volume increment and forest calamity were in a very good state, while canopy structure was the key factor limiting the FQR for all the clusters. Some relevant measures were proposed to improve the existing conditions of Chinese forest resources. The results of this study are significant in that they can provide theoretical and technical references for future adjustment and sustainable management of forest resources in China.

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“…To determine group-weighting vectors (i.e., priorities), the different actors' profiles were considered along with the support of cluster analysis, a method used for statistical data analysis [40,41]. To avoid arbitrariness in specifying the initial number of clusters, a hierarchical clustering approach was adopted, since non-hierarchical methods require the user to determine the desired number of clusters in advance.…”

Section: Determining Policy Decision-making Priorities Scenarios Basementioning

confidence: 99%

How Can the Context Affect Policy Decision-Making: The Case of Climate Change Mitigation Policies in the Greek Building Sector

2016

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Abstract:The influence of context dynamics in the course of the climate change mitigation policy instruments' (PIs) deployment cycle, usually causes a need for policy adaptation mechanisms to ensure that policies can meet the sector needs efficiently and effectively. In this paper, we argue that important contextual factors are the ones that are perceived to have a great impact over policy effectiveness by key related actors. By examining more thoroughly those effects over PIs, as perceived by policy and market actors, useful feedback on observed policy adaptations can be highlighted. In this context, the aim of this paper is to present a conceptual framework which seeks to investigate the impact of key external factors on policy decision-making. This framework is then applied to policies intended to foster sustainability in the Greek building sector. Contextual parameters that are influential over the effectiveness of the national energy conservation measures are identified through a stakeholder survey. Cluster analysis is then employed for the elicitation of three distinct decision-making priorities' scenarios. General macroeconomic trends, energy costs, characteristics of the building sector and socio-institutional factors are prioritized differently from various types of actors and induce certain types of PI changes. Distinguishing among the different types of PI change can help explain better under which contextual circumstances policy adaptations occur and provide guidance to other policy makers when found in similar decisional contexts.

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Assessment of potential energy saving using cluster analysis: A case study of lighting systems in buildings

Cited by 49 publications

References 11 publications

Transitions dynamics in context: key factors and alternative paths in the sustainable development of nations

Transitions dynamics in context: key factors and alternative paths in the sustainable development of nations

Dynamic assessment of forest resources quality at the provincial level using AHP and cluster analysis

How Can the Context Affect Policy Decision-Making: The Case of Climate Change Mitigation Policies in the Greek Building Sector

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