Abstract
While applications of big data have been extensively studied, discussion is mostly made from the perspectives of computer science, Internet services, and informatics. Alternatively, this article takes the big data approach as an institutional innovation and uses the problem of illegal subdivided units (ISUs) in Hong Kong as a case study. High transaction costs incurred in identification of suspected ISUs and associated enforcement actions lead to a proliferation of ISUs in the city. We posit that the deployment of big data analytics can lower these transaction costs, enabling the government to tackle the problem of illegal accommodations. We propose a framework for big data collection, analysis, and feedback. As the findings of a structured questionnaire survey reveal, building professionals believed that the proposed framework could reduce transaction costs of ISU identification. Yet, concerns associated with the big data approach like privacy and predictive policing were also raised by the professionals.
Highlights
“Big data” is a poor term, lacking a universally agreed definition [1,2]
In order to make illegal subdivided units (ISUs) enforcement in Hong Kong more effective, we propose that the ISU search can be facilitated with the use of big data analytics
It was believed that with the application of big data analytics, identification of ISUs would not cause any gratuitous nuisances to the building occupants
Summary
“Big data” is a poor term, lacking a universally agreed definition [1,2]. It is “an all-encompassing term for any collection of data that is very large or complex, and difficult to analyze using conventional data-processing applications” [3]. While applications of big data in urban management have been widely explored and discussed in the literature, most of the research has concentrated on technical and legal issues. Using the case of enforcement against illegal subdivided units (ISUs) in Hong Kong, we illustrate in this article that the high transaction costs incurred in various stages of public enforcement lead to the enforcement failure. The ISU problem in Hong Kong is overviewed and relevant literature on the applications of big data approach in urban management is reviewed. As at 30 April 2013, about 2.4% of the total population in Hong Kong or 171,300 persons lived in 66,900 micro units produced by flat subdivision [11].
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