Identification and Chaining of Water Accounting Data Stakeholders

Ryan Prater, Barbara Eisenbart
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引用次数: 0

Abstract

Purpose – Multiple water accounting techniques exist and suffer from data gaps and mis- aligned stakeholders which creates standardization and consolidation problems in the data of the industry. This study identifies domain-based stakeholders and defines stakeholder data relationships to improve inter-stakeholder data efficiency.Design/methodology/approach – The research design follows an inductive data col- lection of qualitative cross-sectional data through semi-structured expert interviews. The recorded interviews were transcribed, thematically coded, and the findings summarized.Findings – The result is an improved specificity of water accounting data stakeholders which have different data input and output requirements. Our research found that these stakeholders can be chained together based on their data relationships which enables iden- tifying inter-stakeholder relationships and improved data efficiency.Social Implications – Water is a vital resource for humans and the United Nations Sustainable Development Goals. More precise description of stakeholders and data factors enable more efficient data flow which can improve the efficacy of terminal impact.Originality/value – The awareness of problem is refined by increasing stakeholder speci- ficity and identifying data input/output requirements. This enables chaining of stake- holders and data to clarify stakeholder data requirements and improve data efficiency for purposes such as collaboration and policy guidance.
水会计数据利益相关者的识别与链接
目的-存在多种水会计技术,并遭受数据差距和不一致的利益相关者,这造成了行业数据的标准化和整合问题。本研究识别基于领域的利益相关者,并定义利益相关者的数据关系,以提高利益相关者之间的数据效率。设计/方法论/方法-研究设计遵循通过半结构化专家访谈的定性横截面数据的归纳数据收集。对记录的访谈进行转录、主题编码,并对调查结果进行总结。结果是提高了具有不同数据输入和输出要求的水会计数据利益相关者的特异性。我们的研究发现,这些利益相关者可以根据他们的数据关系链接在一起,从而可以识别利益相关者之间的关系,提高数据效率。社会影响-水是人类和联合国可持续发展目标的重要资源。更精确地描述利益相关者和数据因素,使数据流更有效,从而提高终端影响的有效性。独创性/价值——通过增加利益相关者的特殊性和识别数据输入/输出要求来改进对问题的认识。这使得利益相关者和数据链能够澄清利益相关者的数据需求,并提高数据效率,用于协作和政策指导等目的。
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CiteScore
1.60
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