Home Hub-of-all-Things (HAT) as Platform for Multi-sided Market powered by Internet-of-Things: Opportunities for New Economic & Business Model

这一研究项目旨在利用新一代传感器和设备提供的数据来开发新的经济模型。为此，我们将进行以下工作：首先，我们将在现有研究的基础上开发一个原型家庭集线器，该原型建立在一个扩展的家庭路由器的基础上，能够将不同的信息集合捕获到该项目的5个成员的家中。现有的家庭自动化方法通常提供使用家庭集线器作为他们对未来家庭的愿景中的中央控制点(例如Intel Home或Microsoft HomeOS)。然而，我们认为，家庭枢纽更有可能以零碎的方式到达家庭环境。因此，我们建议采取一种进化的方法，在家庭作业项目中基于现有的数字经济研究来补充现有的技术。为了补充这些定量数据，我们将使用民族志方法，包括技术参观、日记研究、经验抽样以及一系列现场研究，这些研究围绕着揭开事物内部网络中每件文物的日常生活而构建。其次，我们将结合扎根的理论和计量经济学技术来分析数据并建立一系列理论模型。这样的模型将是对现实世界的简化，但将提供可检验的预测。我们将分析这些数据的使用模式，一个例子说明了这一点。考虑一下“泡茶”这项活动。这包括一些次级活动，包括；将茶包放入壶中，装满茶壶，沸腾，倒水到茶中，让茶浸泡，确定茶何时足够浓，将茶倒入杯子，添加牛奶，添加糖等。茶壶、水壶、奶壶、杯子等上的传感器将提供例如使用次数、使用频率、使用时间、旅行距离的代理等的定量数据。继续类比，定性的人种学数据可以提供关于何时泡茶、还有谁在场的上下文，还有哪些活动是巧合等。我们将能够共同开发出一种功能形式的活动‘泡茶’。第三，运用联合分析方法对理论模型进行检验。联合分析要求用户从一系列权衡中做出选择，这反过来又确定变量的相对重要性和敏感度，以及它们与某些货币价值(价格)的关系。回到前面的例子，这将使我们能够确定哪些活动对制茶活动最重要，以制作或多或少的茶或不同的茶，从而实现对更多资源的潜在需求。每个集群将被操作成一个算法，以开发成一个软件应用程序。第四，这些算法将被开发成产品，然后被放置在H.A.T.上，用来模拟使用Dropletpay支付平台的市场系统。我们将利用WMG内的国际产品和服务创新研究所(IIPSI)的设施，发展一项‘H.A.T.’-FEST。在这里，开发商、投资者和中小企业将基于个人数据集的商品化创建新产品，应用为嵌入其产品而创建的算法，从而为新产品创建一个多边市场，以服务于作为此类产品买家的住户、房东或建筑经理。然后将监测市场平台上此类产品的结构、行为和表现，以测试其可持续性。

This research project aims to exploit the data available from a new generation of sensors and devices to develop new economic models. To do this we will carry out the following:Firstly, we will build on existing research to develop a prototype home-hub that builds upon an extended domestic router capable of capturing a diverse collection of information into the home of 5 members of the project. Existing approaches to home automating have often proffered the use of home hubs as central points of control (e.g. Intel Home or Microsoft HomeOs) within their visions of a future home. However, we believe that the home hub is much more likely to arrive in the home setting in a piecemeal fashion. Consequently, we propose to adopt an evolutionary approach, to supplement the existing technologies in the home based on existing Digital Economy research in the Homework project. To supplement this quantitative data we will use ethnographic methods including technology tours, diary studies, experience sampling as well as a range of in-situ studies structured around unpacking the everday life for each artefact in the intranet of things.Secondly, we will combine grounded theory and econometric techniques to analyse the data and build a series of theoretical models. Such models will be a simplification of the real world, but will supply testable predictions. We will analyse this data for patterns of use, an example illustrates the point. Consider the activity 'making tea'. This consists of a number of sub-activities including; putting the tea bag into the pot, filling the kettle, boiling the kettle, pouring water onto tea, allowing the tea to steep, deciding when the tea is strong enough, pouring tea into cup, adding milk, adding sugar etc. Sensors on the tea pot, kettle, milk jug, cup etc will provide quantitative data on for example, times of use, frequency of use, timings on use, proxies for distances travelled etc. Continuing with the analogy, the qualitative ethnographic data may provide context on when tea is made, who else is present, what other activities are co-incident etc. Together we will be able to develop a functional form of the activity 'making tea'. Thirdly, we will test the theoretical models using conjoint analysis. Conjoint analysis requires the user to make choices from a series of trade-offs which in turn identifies the relative importance and sensitivities of the variables and their relationship to some monetary value (price). Returning to our previous example, this will enable us to identify which of the activities are most important to the tea-making activity to make more or less tea or different teas, operationalising the latent need for more resources. Each cluster will be operationalised into an algorithm for development into a software app.Fourthly, the algorithms will be developed into offerings which will then be placed on the H.A.T. to 'sell back' such offerings, simulating a market system using the Dropletpay payment platform. We will use the facilities of the International Institute of Product and Service Innovation (IIPSI) within WMG, to develop a 'H.A.T.'-fest. Here, developers, investors and SMEs will create new offerings based on the commodification of the personal data set ,applying the algorithms created to embed in their offerings, thereby creating a multi-sided market for new offerings to serve the home occupant, landlord or building manager as buyers of such offerings. The structure, conduct and performance of such offerings on the market platform will be then monitored to test its sustainability.