管理市场:重塑战后历史上的购物中心

IF 1.6 3区 社会学 Q4 ENVIRONMENTAL STUDIES Urban Policy and Research Pub Date : 2022-07-03 DOI:10.1080/08111146.2022.2104438
Andrew Allan
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While we can identify patterns from large pools of data, made possible by big data and digital technologies, using quantitative methods in this way only tells us the outcome (i.e. the most common routes people take) but not the why. Granted, Yadav et al. combine interviews and geo-spatial simulation modelling, in Chapter 21, to construct a “perceptive design” (p. 407) of homelessness in Brisbane, Australia. In the same vein, Osaragi, Yamada, and Kaneko (Chapter 12) compare their simulation of pedestrian behaviour with observations of a university campus and found the results from the twomethods in fact matched. In Chapter 16, Rout and Willet also conduct semi-structured interviews and participatory design sessions with architects (but as a way to understand how their proprietary software technology might benefit practitioners). These papers were the only articles that included qualitative methods as part of the findings, and even so, they were administered to “check” or complement the quantitative data. Further research on these topics should incorporate qualitative methods, beyond using it to confirm quantitative findings, but to produce conflicting and nuanced research. With only a few out of the thirty chapters in the book that implement some sort of qualitative method, the book clearly favours quantitative research. Big data alone can be highly impersonal and generalising; and failing to capture and understand the complexity of human behaviours can have detrimental impact on planning outcomes, financially, politically, and socially. Urban scholars also need to reconsider the role of academia. The researchers in this book believe that universities, governments, and private enterprises should collaborate on the delivery of urban informatics. 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引用次数: 0

摘要

Tal合作将有助于使城市更加“有弹性、可持续和公正”(第13页)。然而,许多技术和方法,如使用地理标记和地理空间技术或社交媒体的数据,讲述了一个不完整的故事。例如,人们如何在城市中移动或在网上展示自己,与各种其他社会因素——性别、能力、年龄、收入等——纠缠在一起。即使是人们在采访中可能做出的回应方式(一些研究人员用来与大数据结果进行比较的方法),也充满了代表性、立场性和权力等方法论问题,这些问题都没有得到检验。虽然我们可以通过大数据和数字技术从大量数据中识别模式,但以这种方式使用定量方法只能告诉我们结果(即人们最常见的路线),而不能告诉我们原因。诚然,在第21章中,Yadav等人结合访谈和地理空间模拟建模,构建了澳大利亚布里斯班无家可归者的“感知设计”(第407页)。同样,Osaragi, Yamada和Kaneko(第12章)将他们对行人行为的模拟与对大学校园的观察进行了比较,发现两种方法的结果实际上是一致的。在第16章中,Rout和Willet还与架构师进行了半结构化访谈和参与式设计会议(但作为一种了解他们的专有软件技术如何使从业者受益的方式)。这些论文是唯一将定性方法作为研究结果的一部分的文章,即使如此,它们也被用来“检查”或补充定量数据。对这些主题的进一步研究应该结合定性方法,而不是用它来证实定量的发现,而是产生相互矛盾和微妙的研究。在全书的30个章节中,只有少数几个章节采用了某种定性方法,这本书显然更倾向于定量研究。大数据本身可能是高度客观和泛化的;如果不能捕捉和理解人类行为的复杂性,可能会对规划结果产生不利影响,无论是在经济上、政治上还是社会上。城市学者也需要重新思考学术界的角色。本书的研究人员认为,大学、政府和私营企业应该在城市信息学的交付上进行合作。然而,学术界绝不能成为政府和企业寻找证据来强化某些议程的地方。相反,学者必须扮演仲裁者的角色,质疑这些关系,以确保研究有利于人类、环境和未来,而不仅仅是政府和商业精英。对于那些声称使用人体实验数据将有助于政府和企业取得成功的研究,即使它暗示更广泛的社会也会进步,我们也有必要保持一种健康的谨慎意识。我们必须提醒自己,谁将从“城市信息学”中受益,以及它将如何以不同的方式影响公众。
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Managing the Marketplace: Reinventing Shopping Centres in Post-War History
tal collaboration will help make cities more “resilient, sustainable, and just” (p. 13). However, many of the technologies and methods, such as the use of data from geo-tagging and geospatial technologies or social media, tell an incomplete story. How people move around in a city or represent themselves online, for instance, are entangled with all sorts of other social factors – gender, ability, age, income, and so on. Even the ways in which one might respond in an interview, a method used by some of the researchers to compare against big data results, is imbued with methodological issues of representation, positionality, and power, which all go unexamined. While we can identify patterns from large pools of data, made possible by big data and digital technologies, using quantitative methods in this way only tells us the outcome (i.e. the most common routes people take) but not the why. Granted, Yadav et al. combine interviews and geo-spatial simulation modelling, in Chapter 21, to construct a “perceptive design” (p. 407) of homelessness in Brisbane, Australia. In the same vein, Osaragi, Yamada, and Kaneko (Chapter 12) compare their simulation of pedestrian behaviour with observations of a university campus and found the results from the twomethods in fact matched. In Chapter 16, Rout and Willet also conduct semi-structured interviews and participatory design sessions with architects (but as a way to understand how their proprietary software technology might benefit practitioners). These papers were the only articles that included qualitative methods as part of the findings, and even so, they were administered to “check” or complement the quantitative data. Further research on these topics should incorporate qualitative methods, beyond using it to confirm quantitative findings, but to produce conflicting and nuanced research. With only a few out of the thirty chapters in the book that implement some sort of qualitative method, the book clearly favours quantitative research. Big data alone can be highly impersonal and generalising; and failing to capture and understand the complexity of human behaviours can have detrimental impact on planning outcomes, financially, politically, and socially. Urban scholars also need to reconsider the role of academia. The researchers in this book believe that universities, governments, and private enterprises should collaborate on the delivery of urban informatics. However, academia must not be a place for governments and businesses to seek out, to gain evidence that reinforce certain agendas. Instead, academics must play the role of arbiter and question these relationships to ensure the research is in favour of people, the environment, and the future, and not just for governments and business elites. A healthy sense of caution is necessary toward research that claims using data on human subjects will help governments and businesses succeed, even if it insinuates that broader society advances as well. We must remind ourselves who benefits from “urban informatics” and how it might impact the public in different ways.
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自引率
11.10%
发文量
56
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