Every organisation from the scale of whole countries down to small companies has a list of system developments which have ended in various forms of disaster. The nature of the failures varies but typical examples are: cost overruns; timescale overruns and sometimes, loss of life. The post-mortems to these systems reveal a wide range of reasons all the way from hardware failures, through software errors right to major system level mistakes. More importantly a large number of these systems share one attribute: complexity. This paper presents a fresh look at the nature of complexity in the building of computer based systems.

http://ieeexplore.ieee.org/iel3/4458/12639/00581896.pdf

Complex systems

Structural equation modeling , Structural equation modeling , کتابخانه دیجیتال جندی شاپور اهواز

Structural Equation Modeling

Cause and Correlation in Biology. A User's Guide to Path Analysis, Structural Equations and Causal Inference with R, Second edition, Bill Shipley. Cambridge University Press (2016), (ISBN: 978-1-107-44259-7, 314 pp., £39.99, paperback)

Considering the vast and rapidly growing area of buildings, LCA research is being led in numerous different areas ranging from building materials and components level to whole building analysis. This review aims to explore the application of LCA to the various areas in the buildings sector. The areas of embodied energy and building certification systems have seen the maximum growth in the most recent years. Related challenges and research opportunities from these and other areas that require research are discussed. This paper also reviews the use of LCA in buildings industry and reports the associated developments and future research opportunities. The research areas identified include, comparison issues of LCA studies, difference in calculated and actual impacts, refurbishment analysis for whole buildings, system boundary selection procedure, standard data collection procedure, missing data, embodied energy indicator, deconstruction analysis, implementation of dynamic LCA, use of LCA in industry and difference in results from LCA integrated certification and LCA of buildings.

Recent developments, future challenges and new research directions in LCA of buildings: A critical review

Soil microorganisms act as gatekeepers for soil-atmosphere carbon exchange by balancing the accumulation and release of soil organic matter However, poor understanding of the mechanisms responsible hinders the development of effective land management strategies to enhance soil carbon storage Here we empirically test the link between microbial ecophysiological traits and topsoil carbon content across geographically distributed soils and land use contrasts We discovered distinct pH controls on microbial mechanisms of carbon accumulation Land use intensification in low-pH soils that increased the pH above a threshold (~62) leads to carbon loss through increased decomposition, following alleviation of acid retardation of microbial growth However, loss of carbon with intensification in near-neutral pH soils was linked to decreased microbial biomass and reduced growth efficiency that was, in turn, related to trade-offs with stress alleviation and resource acquisition Thus, less-intensive management practices in near-neutral pH soils have more potential for carbon storage through increased microbial growth efficiency, whereas in acidic soils, microbial growth is a bigger constraint on decomposition rates

/pdf/land-use-driven-change-in-soil-ph-affects-microbial-carbon-349bvyja33.pdf

Land use driven change in soil pH affects microbial carbon cycling processes

This review was developed to introduce the essential components and variants of structural equation modeling (SEM), synthesize the common issues in SEM applications, and share our views on SEM’s future in ecological research. We searched the Web of Science on SEM applications in ecological studies from 1999 through 2016 and summarized the potential of SEMs, with a special focus on unexplored uses in ecology. We also analyzed and discussed the common issues with SEM applications in previous publications and presented our view for its future applications. We searched and found 146 relevant publications on SEM applications in ecological studies. We found that five SEM variants had not commenly been applied in ecology, including the latent growth curve model, Bayesian SEM, partial least square SEM, hierarchical SEM, and variable/model selection. We identified ten common issues in SEM applications including strength of causal assumption, specification of feedback loops, selection of models and variables, identification of models, methods of estimation, explanation of latent variables, selection of fit indices, report of results, estimation of sample size, and the fit of model. In previous ecological studies, measurements of latent variables, explanations of model parameters, and reports of key statistics were commonly overlooked, while several advanced uses of SEM had been ignored overall. With the increasing availability of data, the use of SEM holds immense potential for ecologists in the future.

https://link.springer.com/content/pdf/10.1186%2Fs13717-016-0063-3.pdf

Applications of structural equation modeling (SEM) in ecological studies: an updated review

Spatial-temporal assessment of water footprint, water scarcity and crop water productivity in a major crop production region

Integrating culture into sustainable development (SD) has been an ongoing research topic, but has not yet been of interest to the green building community. Existing green building programs, including standards, certification and auditing schemes, focus on technical assessment. By assuming that a building is a cultural resource, which reflects the past and shapes the future of a society, we added cultural sustainability for green buildings by recognizing the three roles of cultural SD proposed by COST Action Cultural Sustainability: (1) ‘culture in SD’ – a fourth dimension to be safeguarded; (2) ‘culture for SD’– a mediating and balancing factor for other dimensions; and (3) ‘culture as SD’ – an essential foundation to achieve SD. We proposed cultural sustainability criteria and indicators as a framework to be adopted by green building communities through an in-depth review of the relevant indicator systems, ecosystem services, sustainable regional/urban planning and existing green building programs. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment

Incorporating Culture Into Sustainable Development: A Cultural Sustainability Index Framework for Green Buildings

Current aggregate and topâ€ down approaches in life cycle sustainability assessment (LCSA) generally fail to account for spatial, temporal, and emergent behavioral dynamics simultaneously during the inventory stage. We discuss the key characteristics captured by complex system approaches (agentâ€ based modeling [ABM] in particular) in the context of LCSA. It is understood that by integrating ABM, temporal, spatial, and behavioral dynamics can be addressed during the life cycle inventory stage. We propose a general concept to integrate ABM into current building life cycle assessment standards. We then use a hypothetical example of green building development to compare the ABM approach with a predefined static policy model. Simulation results from the agentâ€ based model confirm that there are temporal and spatial variations caused by behavioral dynamics. The results are integrated into the calculation of temporally dynamic LCSA indicators on an annual basis. Spatially distributed simulation results can also be used in spatially dynamic LCSA.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jiec.12666

Agent-Based Modeling of Temporal and Spatial Dynamics in Life Cycle Sustainability Assessment

The social life cycle impact assessment (SLCIA) incorporates either a type I or type II characterization model. We improved both models by introducing explicit causality by using statistic modeling through development of (1) a quantitative approach to simultaneously identify impact pathways of type II models with multiple impact categories, targeting SLCIA method developers and (2) a new hybrid model to establish causality between inventory indicators and subcategories, targeting social life cycle assessment practitioners. Causality establishments for type II impact pathways and the new hybrid model are the core requirements for this study. We used structural equation modeling (SEM) to identify the impact pathways for type II characterization models, therefore resolving the issues of unobservability and unvalidatibility in type II models. Using country-level data from the World Bank, the method was applied to an example impact pathway at macro-scale. We applied Bayesian networks in our hybrid model to address the issues of relevance and representativeness in type I models, assuming the unobservable social performances of an organization are the causes for observable inventory indicators. The method was applied to a hypothetical example for the stakeholder of the worker at company scale. Temporal precedence (i.e., lag effects) was incorporated into both models. The results from the confirmatory SEM supported our hypotheses that comprised the impact pathway from economic development to health outcomes, which were fully mediated by health expenditures and health access. A 1-year lag between each impact category resulted in the best model fit. Limitations on the data as well as subjective choice of indicators to represent impact categories are subject to criticism. The results from the hybrid model showed that, depending on the likelihood of the inventory indicators, the posterior probability of subcategories either deviated from their prior probability or behaved similarly. The construction of proper conditional probability tables and the choice of probability distribution for the likelihood are major challenges for the hybrid model. This study was the first attempt in using statistic causal models to quantitatively identify unobservable impact pathways of the type II model and to develop a hybrid model for SLCIA. A SEM that incorporates temporal precedence enables identification of impact pathways with multiple unobservable impact categories. The hybrid model using Bayesian networks represents the subcategories in posterior probabilities instead of absolute scores, helping companies to better develop instructions for future management practices.

Susie Ruqun Wu

Papers

Applications of structural equation modeling (SEM) in ecological studies: an updated review

Spatial-temporal assessment of water footprint, water scarcity and crop water productivity in a major crop production region

Incorporating Culture Into Sustainable Development: A Cultural Sustainability Index Framework for Green Buildings

Agent-Based Modeling of Temporal and Spatial Dynamics in Life Cycle Sustainability Assessment

Causality in social life cycle impact assessment (SLCIA)