Toward dynamic sustainability assessment in the digital age
Toward dynamic sustainability assessment in the digital age
复制标题
数字时代的动态可持续性评估
DOI：
10.1007/s10098-022-02416-9
复制
发表时间：
2022
影响因子：
4.3
通讯作者：
Huang, Yinlun
中科院分区：
文献类型：
--
作者：
Huang, Yinlun
联合国可持续发展目标（SDG）于2015年制定，旨在2030年实现。这些高度相互关联的目标反映了经济、环境和社会可持续性平衡发展的必要性。在实现目标的众多途径中，工业可持续性一直发挥着深远的作用。越来越多的证据表明，将可持续性作为目标的公司正在取得竞争优势。工业可持续性通常通过催化、规划和交付变革来实现，并通过一条有望实现预设目标的最佳转型路径（Tonelli et al. 2013; Moradi Aliabadi and Huang 2016 a）。在此过程中，产业组织需要确定当前可持续发展的状况和趋势，应该维持什么，有哪些瓶颈和挑战，如何最佳地维持，以及如何有效地采取战略和行动，其中可持续性评估是第一个关键步骤。可持续性评估是一个识别、测量和分析系统性能，并评估技术和其他解决方案对性能改进的潜在影响的过程。在过去的二十年中，引入了许多类型的可持续性度量系统，其中指标是使用规范性自上而下方法或与问题相关的自下而上方法在一个组合过程中定义的（Halla和Binder 2020）。前者是一个操作过程，从确定可持续性的构成要素开始，通过确定可持续性目标、适用可持续性原则，直至制定指标;后者是一个背景化过程，根据有关系统的具体问题生成指标。由于可持续性是基于三重底线的，每个指标体系都包含三套指标，分别用于评估经济，环境和社会的可持续性。这就对每个可持续性层面的个别指标提供的信息的汇总以及涵盖所有三个层面的总体可持续性提出了挑战。通过汇总，创建了综合可持续性绩效指数。Sikdar及其同事指出，将所有可用指标合并为一个综合指标以使绩效比较更容易被认为是可取的（Sikdar等人，2012年）。常见的汇总方法包括简单平均数（即算术平均数）、加权平均数和（加权）几何平均数。然而，没有科学的方法来唯一地确定权重。在实践中，权重通常是基于对知情个人偏好的调查和价值判断来选择的。另一个挑战是数据的可用性和质量，这会影响指标的选择，并可能影响可持续性评估的全面性和准确性（Diwekar et al. 2021; Moradi Aliabadi and Huang 2016 b）。如果能够获得大量真实的时间和质量数据，就有可能更频繁、更广泛和更可靠地评估可持续性绩效。如今，各行业正处于技术创新和产品制造方式的重大而引人注目的变革之中。这在很大程度上受到以数字化为主要特征的工业4.0的影响。新的和相对低成本的智能传感和操作技术，传感器节点之间的快速数据通信，数据库，互联网和制造现场的云服务开始被使用。这些都为我们提供了各种各样的机会……
The United Nations’ Sustainable Development Goals (SDGs) were set up in 2015 and are intended to be achieved by 2030. Those highly interlinked goals reflect a need for the balanced development of economic, environmental, and social sustainability. Among numerous ways for goal achievement, industrial sustainability has been playing a profound role. It is increasingly shown that companies making sustainability as a goal are achieving competitive advantage. Industrial sustainability is commonly pursued through catalyzing, planning, and delivering changes through a hopefully optimal transformation path toward a preset goal (Tonelli et al. 2013; Moradi Aliabadi and Huang 2016a). In the process, an industrial organization needs to determine what current sustainability status and trend are, what it should sustain, what bottlenecks and challenges are, how to sustain optimally, and how effective strategies and actions could be, among which sustainability assessment is the first, critical step. Sustainability assessment is known as a process of identifying, measuring, and analyzing a system’s performance, and evaluating the potential impacts of technologies and other solution alternatives on performance improvement. Over the past two decades, numerous types of sustainability metrics systems have been introduced, where indicators are defined in a combined process using a normative top-down approach or a problem-related bottom-up approach (Halla and Binder 2020). While the former is an operationalization process, starting from identification of constitutive elements of sustainability, through determination of sustainability goals, application of sustainability principles, to indicator development, the latter is a contextualization process, where indicators are generated based on the specific problems/questions of a system of interest. As sustainability is triplebottom-line-based, every metrics system contains three sets of indicators for assessing economic, environmental, and social sustainability separately. This has posed a challenge about the aggregation of the information provided by individual indicators in each sustainability dimension as well as the overall sustainability covering all three dimensions. The aggregation leads to creation of composite sustainability performance indices. Sikdar and co-workers stated that it is deemed desirable to consolidate all usable indicators into one aggregate metric to make performance comparison easier (Sikdar et al. 2012). Common aggregation methods include simple mean (ie, arithmetic average), weighted mean, and (weighted) geometric mean. However, there is no scientific method to uniquely determine weights. In practice, the weights are commonly selected based on survey of preferences of informed individuals and value judgment. The other challenge is about data availability and quality, which affects the selection of indicators and could influence the comprehensiveness and preciseness of sustainability assessment (Diwekar et al. 2021; Moradi Aliabadi and Huang 2016b). It is possible that if a large amount of real time, quality data are accessible, sustainability performance could be evaluated more frequently, broadly, and reliably. Today, industries are in the midst of significant, compelling transformation regarding technology innovation and the ways products are manufactured. This is largely impacted by Industry 4.0, which is mainly featured by digitalization. New and relatively low-cost technologies for smart sensing and operation, fast data communication among sensor node, database, internet, and cloud services in manufacturing sites start to be used. These provide a variety of opportunities for …
DOI：
10.1017/9781108574334.003
发表时间：
2020
期刊：
Sustainability Assessment of Urban Systems
影响因子：
--
作者：
P. Halla;C. Binder
通讯作者：
C. Binder
影响因子：
13.2
作者：
Diwekar, U.;Amekudzi-Kennedy, A.;Theis, T.
通讯作者：
Theis, T.
影响因子：
--
作者：
Rui Carvalho-;A. Silva
通讯作者：
Rui Carvalho-;A. Silva