In this section, the failure of government interventions in curbing ISU problem in Hong Kong was explained from the perspective of institutional economics. In view of such failure, we put forward an institutional innovation.
4.1. High Transaction Costs of Government’s Enforcement
In spite of the efforts of the HKSAR Government in fighting against ISUs, the ISU problem in the city still remains very serious. The failure of government’s enforcement actions can be explained from the angle of institutional economics. Institutional economics supplements classical economics with the concepts of institutions and transaction costs [
43,
44,
45]. Institutions are the game rules in a society, shaping the contexts for economic behavior [
44]. Institutions come in different forms, including formal rules (e.g., laws and constitutions) and informal rules (e.g., societal norms and customs) [
46]. On the other hand, transaction costs are the costs of making and enforcing agreements, which also include the rules such as laws and regulations. The costs of searching and information collection are also important transaction costs in many different institutional settings [
47,
48,
49]. In the building control system, transaction costs are incurred in the law making and law enforcement processes. This research focusses on the law enforcement process only.
As
Figure 3 shows, there are several stages in a law enforcement process against ISUs and different enforcement costs are involved in these stages. For example, at the start of the enforcement exercise, the public officials in the Buildings Department need to figure out which properties in the existing building stock have been subdivided unlawfully. Then, the public officials have to collect sufficient evidence for subsequent enforcement actions, such as the issuance of statutory reinstatement orders or direct prosecutions. These two initial stages of the enforcement exercise involve prohibitively high transaction costs, leading to law enforcement incapacity.
Unlike other types of UBWs, such as flower racks and metal cages erected on the external walls of buildings, ISU works are undertaken inside a flat so their presence is not so readily observable from the outside. Several years ago, public officials relied on some noticeable signs to identify ISUs in a building. These signs included multiple doorbells, mailboxes, and water meters installed for a single flat or dwelling unit, as illustrated in
Figure 4. Through learning from previous enforcement experience, landlords and renters of ISUs are getting smarter. Households of different micro units within an ISU now share the same doorbell, mailbox, and water meter, hiding the existence of the ISU from outsiders. Therefore, it becomes more and more difficult for the public officials to identify ISUs without entering a premise.
In practice, the officials of the Buildings Department inspect a property or properties in a building for suspected ISUs either because the building is targeted in a large-scale operation or the department receives complaints from the public. In the first scenario, the Buildings Department picks a sample of target buildings based on a number of criteria, such as building age and building management regime (e.g., formation of incorporated owners and appointment of third-party management agent). However, these criteria may not be good predictors for the level of ISU proliferation in a building. Older, unmanaged buildings do not necessarily have more ISUs. Erroneous shortlisting may result in inefficient use of public resources. More importantly, there is a need for the public officials to enter the properties in the targeted building for inspection. Otherwise, the public officials cannot ascertain whether the properties have been illegally subdivided for subsequent actions.
In the second scenario, although the suspected ISU has been spotted by a member of the public, the government officials still need to collect sufficient hard facts or evidence on the existence of ISUs (e.g., number and dimensions of the illegal micro units and types of UBWs carried out for flat subdivision) for further enforcement actions. In other words, for both scenarios, getting access to the property interior is crucial. Nonetheless, the ISU residents, in most cases, deny the access of public officials to the subdivided flats because they do not want to risk losing their current relatively affordable accommodation.
On the other hand,
Section 2.2 of the
Buildings Ordinance stipulates that the power of entry or breaking into the premises or upon land by the Building Authority in the presence of a police officer is restricted to emergency situations only. To further facilitate in-flat inspection of suspected ISUs, the
Buildings (Amendment) Ordinance 2011 introduced a new measure to empower the Building Authority to apply to the court for a warrant for entry into the interior of individual premises for inspection or other enforcement actions. Before the issuance of the warrant, a magistrate must be satisfied by information on oath that:
There are reasonable grounds for suspecting any of the following matters:
building works have been or are being carried out to the premises or land in contravention of any provision of the Buildings Ordinance;
the use of the premises or land has contravened any provision of the Buildings Ordinance;
the premises have been, or the land has been, rendered dangerous, or the premises are, or the land is, liable to become dangerous;
the drains or sewers of the premises or land are in a defective or insanitary condition; or
a notice or order served under the Buildings Ordinance has not been complied with;
The Building Authority has made attempted entry on at least two different days; and
A notice of intention to apply for a warrant has been served on the owner or occupier of the premises.
In spite of the facilitation of in-flat inspection through law amendment, transaction costs for in-flat inspections for ISUs are still very high. The Buildings Department officials need to visit the property suspected of having illegal subdivisions twice before applying to the court for an entry warrant. Moreover, to substantiate their warrant application, they have to provide sufficient evidence to the court that there are UBWs in the subject property. As discussed above, the task of evidence collection in ISU enforcement is a really thorny issue. From the above, it is clear that the existing enforcement system in Hong Kong fails to stop the ISU problem due to the prohibitively high transaction costs of searching and information collection.
4.2. Institutional Innovation for ISU Enforcement with the Use of Big Data Analytics
In order to make ISU enforcement in Hong Kong more effective, we propose that the ISU search can be facilitated with the use of big data analytics. Big data has been used in many cities for combating different urban problems, such as crime, illegal parking, and traffic congestion [
5,
37,
38,
50,
51]. In some cities, the local governments also employed big data to fight against substandard housing. For example, big data is used to register and track each housing-related complaint in New York City [
52]. The data collected are then analyzed to point out those properties with the highest chances of code violation. In the past, building inspectors used their personal experience or gust feelings to prioritize cases for follow-up. Nevertheless, this mode resulted in a low enforcement efficiency as the inspectors could not find property conditions adverse enough to warrant a vacate order in 87% of the cases. Later, the employment of big data analysis brought about a fivefold improvement in the building inspectors’ efficiency. Prioritizing inspections based upon the results of big data analysis, building inspectors served vacate orders on over 70% of the properties they inspected. In New South Wales of Australia, the state government harnesses big data to blitz Sydney’s illegal boarding houses [
53]. Data from the utility bills, electoral rolls, and other sources are collected and used to find where there is an unusual increase in the number of residents.
The same idea can be applied to the identification of the ISUs in the existing building stock in Hong Kong. The big data approach proposed in this article has five key stages, as shown in
Figure 5. In Stage 1, information required to address the ISU problem and data necessary to derive the required information are identified. In the case of an ISU search, the information required is the level of risk of a property or building with ISU proliferation. To derive such information, useful data such as monthly utility consumption of each property or building are needed. If a property is subdivided to create more micro units, the total number of occupants in the property is expected to rise. In normal situations, utility consumption increases with the number of occupants. Consequently, it can be the first alert of a subdivided unit if a dwelling unit has a much higher monthly consumption of water, gas, and electricity than a similar standard unit. Abnormal rises in the utility bills can indicate the illegal subdivision of a dwelling unit. To facilitate the subsequent comparative analysis, both historical and current data should be obtained.
Apart from the utility consumption, other information, such as the number of complaints or reports about water seepage in a building, may also give public officials some hints about the existence of ISUs in the building. In most cases, the conversion of a lawful flat into illegal micro units involves the installation of new toilets or bathrooms and alterations to existing pipework. All these works may increase the chances of water leakage from the pipes and water seepage through walls and slabs. Accordingly, it is reasonable to expect that a dramatic rise in the number of water seepage reports in a building is a good indication of ISU proliferation in that building.
Stage 2 is the collection of the required data. Utility consumption and usage is usually reflected in the utility bills. In this regard, the data required can be collected from various utility providers (e.g., Water Supplies Department, CLP Power Hong Kong Limited (Hong Kong, China), HK Electric Investments Limited (Hong Kong, China) and Hong Kong and China Gas Company Limited (Hong Kong, China)). As for the number of reports about water seepage, the data can be collected from the Joint Offices for Investigation of Water Seepage Complaints. We assume that monthly records of water, electricity, and town gas bills and water-seepage reports of all dwelling units in Hong Kong in a three-year moving window are necessary for a meaningful analysis for identifying problematic properties. Given that there are around 1,174,628 dwelling units in private housing in the city at as the end of 2017 [
54], the dataset for analyses in the subsequent stage will have at least 211,433,040 entries (1,174,628 buildings × 12 months × 3 years × 5 columns) in the spreadsheet.
In Stage 3, the data collected in Stage 2 are consolidated and analyzed. In the data analysis, both cross-sectional and longitudinal comparisons can be made. In the cross-sectional analysis, utility bills of similar properties (e.g., properties of similar ages and sizes) are compared. Those properties with monthly or quarterly utility bills far exceeding the average figures are screened out. Similarly, properties with abnormally high number of water-seepage reports are identified. In the longitudinal analysis, the quarterly utility bills of the same property in different time periods are compared after adjusting for the seasonal factors. An abrupt, significant increase in utility bills may indicate potential illegal flat subdivision in the property. Apart from the unit-based analysis, data from the same building can be aggregated such that the big data analysis can be conducted on a building basis. In addition to utility bills, numbers of water-seepage reports can be deployed in the building-based analysis.
In Stage 4, properties or buildings at higher risk of illegal subdivision are identified based on the analysis results in Stage 3. These high-risk premises will become the black spots that warrant the government’s priority enforcement actions. In Stage 5, the inspectors of the Buildings Department investigate those black spots to see if ISUs exist or not. There is a feedback loop such that the inspection results can be taken as an input, which helps the government improve black spot identification. For instance, the government can learn by trial and error what the optimal differential threshold for the utility bills should be. At the same time, the big data analytics can be further extended to enable predictive analysis. Predictive analysis can be a powerful tool for law enforcement or crime prevention. The public authorities can apprehend law-breakers based on foreknowledge of their future misdeeds. For instance, by looking into the characteristics of buildings with higher risks of ISU proliferation, the public authorities can identify a set of determinants. These determinants can be used to predict which buildings will be riskier and will warrant more attention in the future. Again, the accuracy of the prediction can be improved through the feedback mechanism.
The proposed big data approach is a kind of institutional innovation that aims to reduce the transaction costs incurred in the early stages of ISU enforcement by the public authorities. By analyzing the big data, the HKSAR Government can identify the ISU black spots on a property basis and a building basis with significantly reduced information costs. The property-based identification helps the Buildings Department to locate the properties that have very probably been subdivided illegally. This trims down the search costs for ISU enforcement. Moreover, based on the findings of building-based identification, the Buildings Department can have a more informed selection of target buildings for large-scale operations, directing the limited public resources to the neediest buildings. In addition, the valuable information of abnormal utility consumption is a piece of evidence that the Building Authority can use for substantiating its applications to the court for entry warrants.