Technologies empowering digital rights and their impact on the real estate sector’s digital strategies

As water rights were instrumental in the first industrial revolution (Rose, 1990), digital rights are central in the so-called fourth industrial revolution. Digital strategies can be built around property owners’ and tenants’ entitlements in smart space. These entitlements are mediated by technologies implemented in buildings. So far in the analysis, the manner in which space is first dominated by technology, and then appropriated has been ignored. Assumption is made that digital rights holders control the full process as well as technologies at work.

In practice, smart space is not as abstract as it might appear in light of the twelve axioms presented here. There is a concrete, technical side to smart space which has been of keen interest to computer scientists for years. The digitalisation of real estate requires a myriad of technologies, each with potentially unique contractual arrangements involving external parties (e.g. cloud computing operators, software developers, loT device providers, big data management experts).

The analysis presented in this book explicitly refers to state-of-the-art technologies centred on the cloud computing paradigm. As technologies embedded in the built environment keep progressing, computing paradigms might evolve, but irrespective of the dominant paradigm, digital rights attached to smart buildings should remain, exactly like property rights are not affected by construction technologies?1 To bring some technological perspective to the analysis of digital rights, let’s cover briefly the fundamentals of cloud computing. The objective is to highlight the interplay between technologies’ service models, digital rights, and digital rights holders’ strategies in smart space.

• The cloud computing paradigm

According to the definition of the US National Institute of Standards and Technology (Mell and Grance, 2011),

cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Cloud computing’s service models can materialise into three formats: SaaS (Software as a Service), PaaS (Platform as a Service), laaS (infrastructure as a Service). Bayrak, Conley and Wilkie (2011) explain:

Software as a Service is the service model in which the capability provided to the consumer is the ability to use the cloud provider’s applications running on a cloud infrastructure. [...] Platform as a Service is the service model in which the capability provided to the consumer is a development or runtime environment, programming languages and application programming interfaces (APIs) to design and deploy infrastructure consumer-created applications onto the cloud. [...] Infrastructure as a Service is the service model in which the capability provided to the consumer is processing, storage, networks, and other fundamental computing resources.

A variant of the cloud computing paradigm mentioned in the computer sciences literature is the CloudloT paradigm which integrates cloud and loT (Botta et al., 2016). The concept which seems especially relevant to the built environment has been dubbed “Everything as a Service”, from Sensing as a Service (SaaS) to Database as a Service (DBaaS) and Video Surveillance as a Service (VSaaS). In essence, all technology-powered activities in smart buildings can be integrated with a cloud “whose capabilities in terms of storage and processing power [are] virtually unlimited”.

The quality of service provided by clouds (QoS) is defined in Service Level Agreements (SLA) between operators and users. QoS measures “the levels of performance, reliability, and availability offered by an application and by the platform or infrastructure that hosts it” (Ardagna, Casale, Ciavotta, Perez, Wang, 2014). To allow for optimal and dynamic allocation of resources in clouds, negotiation of SLAs between participants should allow for “automatic allocation to multiple competing requests” (Buyya, Yeo and Venugopal, 2008).

• Strategic dimensions of technological choices in smart buildings

In any computing paradigm, the important features for the real estate sector will be the underlying service models and their strategic implications as assessed by digital rights. Specifically, how does the choice of a particular service model impact on property owners’ Digital Access Rights and tenants’ Digital Usage Rights? Digital rights are a yardstick for attributing value generated in smart space. If technologies’ service models interfere with digital rights, there could be a shift, ever so slightly, in value allocation among contracting parties to the point that digital rights might ultimately become empty shells for their holders. This is especially the case for new real estate resources such as data.

The fact is that as of today, many real estate players do not have in-house technological expertise and capabilities enabling them to dominate and appropriate space without partnering with external parties who might be more attuned to value creation in non-physical space than, say, developers or classic brick-and-mortar property companies. Having an understanding of digital rights rooted in technology is essential to get a full picture of the power struggle that will inevitably take place over value created in smart buildings between commercial real estate’s usual actors (i.e. property owners, tenants), on the one hand, and new entrant smart space solutions providers (e.g. technology giants), on the other hand.

A few key points should guide building owners and tenants when deciding on which service models to implement at different stages of smart space’s life:

i Space domination: Ownership of DARs entitles their holders to decide on the mode of domination for physical space. Poor quality of domination would affect Digital Usage Rights’ value and eventually the value of physical space. High-quality domination, on the other hand, would underlie premium smart spaces. If the domination multiplier briefly mentioned before is less than 1, then domination wastes physical space in creating a less than maximum quantity of smart space, which would have an opportunity cost for owners. By the same token, the quality of physical space domination will be instrumental in fostering a building’s future proofing abilities through its so-called smart readiness, i.e. a building’s “full potential to deliver increased smart services [...] provided existing constraints are released over time” (Lecomte, 2019a). Nevertheless, owning technologies implemented for space domination is not crucial whereas leveraging on physical spaces to generate the best possible domination given demand for smart space by tenants is key. Technology partners’ service models gearing towards “everything as a service” would provide flexibility to the real estate sector, and enable owners to easily adapt their buildings to a wide range of uses in the spirit of the ‘omni-use’ property type (Lecomte, 2019b). Markedly, since DARs carry significant legal responsibilities for their holders, building owners should be able to critically assess the domination process. This should give them a strong motivation to develop in-house expertise in order to keep control over dominated physical spaces, whether or not they actually own the ICT infrastructure embedded in their buildings.

ii Space appropriation: Ownership of DURs entitles their holders to appropriate smart space, by adding user-centric utilities to tenanted dominated spaces. Due to the presence of an appropriation multiplier in the model, tenants are strongly incentivised to develop their own expertise in smart space appropriation and not to depend on landlords’ expertise. Furthermore, as specific interactions play an instrumental role in the total user-centric utility generated in a smart building, DURs holders should be aware of the intellectual property value involved in spatial appropriation. Protecting intellectual property linked to smart space will lengthen the time it takes for specific interactions to become commoditised, thus guaranteeing the value of DURs for their holders for a prolonged period. By neglecting appropriated smart spaces’ high IP content, DURs holders might unwillingly transfer value to third parties and deprive themselves of valuable real estate resources. Service models enabling space appropriators to nurture and protect their unique appropriation know-how, such as PaaS or laaS, should be favoured.

iii Space operation and maintenance: Service Level Agreements (SLAs) defining Quality of Service (QoS) will be central in the smooth functioning of smart space. As appropriated smart space is first and foremost dominated physical

Digitalisation of commercial real estate 125 space, DAR holders (i.e. landlords) will play a big role in ensuring QoS for tenants’ smart space. Experiences of the real estate sector in running longterm service partnerships (such as PPP) will be useful in that respect.

iv Data management and analytics: Once smart space is functional, the central issue becomes data. In the proposed digital rights regime, data ownership comes with Digital Usage Rights. Owners and tenants should be careful that collaborations with third parties do not jeopardise their full ownership of data. Full data ownership means the ability to collect, store, and use data. Because of the legal responsibilities attached to DURs, rights holders should be mindful of issues related to cyber security, data protection, and privacy, so much so that a thorough risk assessment should always inform the decision to outsource data management and analytics. Finally, owners and tenants should be careful when opting to give up (in full or in part) their rights on data collected in smart space as this would represent a long-term loss of real estate value. Only real estate actors with short-term investment horizons might justify the transfer of data ownership to third parties, knowing that in the event of property resale, the gap in data ownership would negatively affect property value.

BOX 2.4: Data collection yield in smart buildings

  • • The ability of appropriated smart space to collect valuable data for Digital Usage Rights holders is a crucial feature of smart real estate.
  • • To gauge smart buildings’ data collection potential, an indicator can be defined as the data collection yield per unit of appropriated smart space in a building. If T is the data collection yield, then total data collected in a building Dy is given by T times total appropriated space Ay in the building, or T = D-p/Ay
  • • The same concept can be applied at the interaction level where Ti is the data collection yield of interaction i in smart space so that Ti = Di/ Ai where Di is the quantity of data collected through interaction i and Ai is the quantity of appropriated space necessary for interaction i to take place.
  • • All three smart space indicators presented in this chapter are intertwined: the domination multiplier X can impact the appropriation multiplier

  • • New indicators in real estate analysis are necessary to account for real estate’s digital realm and capture the new processes of space production and value creation in smart buildings. As a prerequisite, these indicators require a consensus about the relevant metrics applicable for smart space.
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