Social sustainability in the supply chain: Construct development and measurement validation

Research on social sustainability in developing countries has recently gained importance for both academics and practitioners. Studies in the supply chain management field take either a supplier or a manufacturer perspective that address predominantly corporate social responsibility (CSR) issues referring to the internal stakeholders. Our research integrates the literature on supplier, manufacturer, and customer responsibility and proposes the concept of supply chain social sustainability (SCSS) that refers to addressing social issues within the overall (upstream and downstream) supply chain. Furthermore, we develop and empirically validate scales for measuring SCSS using in-depth interviews and a survey in the Indian manufacturing industry. Our results suggest that SCSS consists of six underlying dimensions, namely equity, safety, health and welfare, philanthropy, ethics, human rights, in a 20-item valid and reliable scale. We discuss the implications of the findings for research and practice and suggest future research avenues.     

Comment on “Assessing water quality of five typical reservoirs in lower reaches of Yellow River,China: Using a water quality index method” by Wei Hou,Shaohua Sun,Mingquan Wang,Xiang Li,Nuo Zhang,Xiaodong Xin,Li Sun,Wei Li,and Ruibao Jia (2016) [Ecological Indicators, 61, 309–316]

Hou et al. (2016) recently developed a water quality index (WQI) for assessing water quality of five typical reservoirs. Despite all the merits of the practical WQI, it suffers from lack of uncertainty consideration; a fact that motivated the present discussion focusing on mitigation of uncertainty in water quality assessment. In this regard, superiority of employing fuzzy WQI (FWQI) rather than crisp WQI is emphasized. Due to robustness of FWQI in handling uncertainties surrounding data acquisition, employment of fuzzy concept can improve water quality assessment and monitoring to generate results which are more consistent with real world conditions.     

A strategy to assess river restoration success

1. Elaborate restoration attempts are underway worldwide to return human‐impacted rivers to more natural conditions. Assessing the outcome of river restoration projects is vital for adaptive management, evaluating project efficiency, optimising future programmes and gaining public acceptance. An important reason why assessment is often omitted is lack of appropriate guidelines. 2. Here we present guidelines for assessing river restoration success. They are based on a total of 49 indicators and 13 specific objectives elaborated for the restoration of low‐ to mid‐order rivers in Switzerland. Most of these objectives relate to ecological attributes of rivers, but socio‐economic aspects are also considered. 3. A strategy is proposed according to which a set of indicators is selected from the total of 49 indicators to ensure that indicators match restoration objectives and measures, and that the required effort for survey and analysis of indicators is appropriate to the project budget. 4. Indicator values are determined according to methods described in detailed method sheets. Restoration success is evaluated by comparing indicator values before and after restoration measures have been undertaken. To this end, values are first standardised on a dimensionless scale ranging from 0 to 1, then averaged across different indicators for a given project objective, and finally assigned to one of five overall success categories. 5. To illustrate the application of this scheme, a case study on the Thur River, Switzerland, is presented. Seven indicators were selected to meet a total of five project objectives. The project was successful in achieving ‘provision of high recreational value’, ‘lateral connectivity’ and ‘vertical connectivity’ but failed to meet the objectives ‘morphological and hydraulic variability’ and ‘near natural abundance and diversity of fauna’. Results from this assessment allowed us to identify potential deficits and gaps in the restoration project. To gain information on the sensitivity of the assessment scheme would require a set of complementary indicators for each restoration objective.     

Rethinking of risk communication: lessons from the decision sciences

Risk communication involves three primary elements: process, content and intent. Much has been written about the first two. Much is known, for example, about the guiding principles that should be considered during the design of a risk communication. Likewise, many studies have been conducted about how best to establish the technical and informational content of a risk communication. Very little attention, by contrast, has been devoted to the intent of risk communication, which is to inform decision making for risk management. While appropriate information upon which to base risk management decisions is important, so to is an understanding of how people instinctively approach decision making under conditions of risk. Work in the decision sciences provides this often-missing perspective for many risk communication efforts and is, therefore, the focus of this paper.

从生态学的观点看城乡发展问题

阐述了城乡发展的意义,提出了城乡发展中所面临的人口、环境和资源等三大问题.为使城乡发展建立在科学的基础上,必须合理利用自然资源,保护生态环境,使得城乡生态系统的收支、结构和功能保持平衡,真正把城乡建成功能齐全、环境优美、生产发展和生活舒适的场所.     

森林资源可持续状况评价方法

为了准确、快速地评估森林经营单位的森林资源可持续状况,提出了森林资源可持续状况的评价指标、评价方法和评价结果分级。森林资源可持续状况评价指标包括森林资源质量状况、森林资源利用状况和森林受干扰状况3个方面共28个评价指标。通过参照技术规定、查阅专业用表和使用经验数值等3种方法确定评价指标的基准值;根据基准值把评价指标测定值分级为\"好\"、\"中\"、\"差\"3个等级,并分别赋值1.0、0.62和0.38。利用专家咨询法或层次分析法,根据森林经营单位的主要经营目标和森林主导功能,确定森林资源质量状况评价指标的权重。根据评价指标的实测值、赋值和权重,计算森林资源质量状况指数、森林资源利用状况指数和森林受干扰状况指数,进而计算森林资源可持续状况指数。根据森林资源可持续状况指数值的大小,将森林经营单位的森林资源可持续状况划分为优、良、中和差四个等级。     

Fuzzy logic for phytosociology

The present paper aims to give an analysis of properties of the phytosociological language, which relates to the vagueness of some concepts in vegetation science.A translation of the simplest synsystematic propositions into possibility distributions has been proposed. Inferential relationships between sentences mentioned using the concept of semantic entailment have been reported.Sentences describing habitat requirements of syntaxa are in fact disguised conditionals; their paraphrases have been given the form of implication. Since these sentences include fuzzy predicates their meaning is a fuzzy relation. The latter may constitute the basis of prediction by means of the compositional rule of inference.     

北缘地区柑桔生态区划模糊决策系统

以年平均极端最低气温、活动积温、最冷月平均气温、年平均气温等作为区划决策的重要指标,综合年降水量、最低气温≤-9℃年平均日数及地貌与海拔、水体调节、冷风屏障和土壤营养丰度、PH值等立地条件,建立了北缘地区柑桔生态区划决策系统．引入L-R型模糊数,确立了模糊识别模式,并把模糊推理模型放在知识库里,将精确推理与模糊推理置于同一系统中进行复合推理,使决策系统具有更广泛的实用性．以安徽柑桔生态区划为例,对系统进行了验证．本系统的开发为北缘地区发展柑桔生产提供了决策工具．     

Assessment of sustainable livelihoods of different farmers in hilly red soil erosion areas of southern China

Livelihood vulnerability in environmentally fragile areas is emerging as a key issue due to its positive feedback to environmental degradation. Assessment of sustainable livelihoods is a crucial prerequisite for targeting interventions. However, aggregated analysis usually obtained ambiguous conclusions because they ignored the heterogeneity of rural households. Here, we evaluated the livelihood sustainability of different rural households by constructing an improved Livelihood Sustainability Index (LSI) in hilly red soil erosion areas of southern China. Changting County was selected as the study case by virtue of its unique representativeness in soil erosion and poverty. The results showed that livelihood sustainability among rural households was far from equivalent. Different from previous studies, higher nonfarm income share was not always consistent with higher extent of livelihood sustainability. Besides nonfarm employment, agricultural specialization could be another viable pathway to attain sustainable livelihoods. We also found that intergenerational sustainability was one primary cause for long-term livelihood differentiation of rural households. The poor education in rural areas would aggravate livelihood vulnerability of the poor and threaten the sustainable livelihoods of specialized agricultural households. Policy implications include further investment in rural infrastructure, irrigation and drainage, and stimulus for land transfer and concentration to facilitate agrarian specialization; enhancing investment in rural education to improve intergenerational sustainability; as well as targeting of the most vulnerable households, for example, promoting development of social insurance, social relief, and medical services for orphans and widows.