1 New business model in smart cities : Emerging trends and methods of analysis Paolo Neirotti Politecnico di Torino Department of Management and Production Engineering smart City Finance & Technology Program Master smart cities Politecnico di Torino Torino 11 Aprile 2013. Goals of the lecture Understand business modes for the delivery of smart . services How is economic value created? How do the private and public sectors appropriate economic value? win win relationships? Provide concepts and tools to interpret business models and value generation (Rich Picture, business model Ontology). Understand new value chains in the smart city : Technologies ICT related services Discuss the main critical elements in the technological choices that cities must take Politecnico di Torino Outline of the lecture smart cities initiatives may require innovation in business models, namely new ways through which the private and public sector generate and distribute economic value business models as.
2 New rules to generate economic and social value in smart cities : current trends and critical points (part 1 theory and facts)..new flows through which economic value is generated, new coordination mechanisms among different actors (part 2 value chains).. methods and tool to assess the economic and contractual sustainability of new initiatives (part 3 . business model representation). Part 1. Some theory and facts on how economic value can be generated in the smart city Innovation in smart cities : discontinuities smart city as rise of new behavioural patterns: Acceptance of new from property to service, increased technologies and practices environmental awareness, more civic can be troublesome: participation, new patterns of consumption, Usage of smart new ways for managing social relationships, meters in 2009 a in new financing mechanisms.
3 Bakersfield (CA) has been sued through a class action againts PG&E. Radical Techno . logy Techno epiphany Investments in new infrastructure are logical needed: long pay back, long change installation times, uncertainty on the Incremental evolution of costs and performance for the enabling technologies, lock in Incremental Radical risk, difficult to estimate Changes in meanings complementarities among Source: adapted from Verganti, R. (2009). Design Driven technologies, Innovation Changing the Rules of Competition by Radically Innovating What Things Mean: Harvard business Press Creation of value in the smart city Stakeholders della Driver di valore economico e sociale citt . Public sector (City 1. Economic development ( growth of GDP, employment, managers) exports, Foreign Direct Investment).
4 2. Quality of life indicators 3. Cost to serve the citizen 4. Environmental sustainability (less emissions). 5. Social sustainability (less divides). 6. Less negative externalities (dynamic pricing may favour internalization of externalities). Firms 1. New markets and new revenue opportunities 2. Productivity growth Citizens 1. Cost savings (in energy, transportations, etc.). 2. Higher productivity (savings in time). 3. Empowerment (see the Iceland's quite revolution). Politecnico di Torino smart cities in the world: some findings The number of domains covered by smart initiatives is related: Curvilinearly to city size (taking a U . shaped relationship). Population density Population (logarithimic scale). 31 100 316 Population (thousands omitted). Today there is no correlation between city's Great heterogeneity in the wealth and domains covered initiatives.
5 Not a flat world. From a sample of about 100 cities world wide Politecnico di Torino smart cities in the world: some findings European cities are more active on projects related to smart grids, renewable energies, and policies for entrepreneurship and human capital ( Lisbon Agenda effect ). Asian cities are active on a higher number of domains due to: There are no systemic approaches to the 1. Most critical needs ( Climate and design of smart cities population density). Prevalence of technology push 2. Fewer financial constraints and more initiatives (in Italy, in particular). centralized decision making Politecnico di Torino smart cities in the world Why a U shaped effect in the relationship between city size and number of domains covered by smart initiatives?
6 On the one hand, small are the ideal settings for pilot projects Deal with shorter installation time when an investment in new infrastructure is needed ( street lighting, smart waste) Less inertia in IS infrastructure (green field). On the other, Large cities . have more critical needs Already have the information system infrastructure Have the critical mass of users for new technologies and practices ( new businesses can more quickly scale up > Buschecker). Can more easily attract more human and financial capital An example of a non repeatable business Electric Vehicles (EV) 3 problems the battery of EV. 1. Price (dai 6 a 12 k ) VC funds 2. Recharging time (equity). 3. Duration government tax incentives/discount on EV. (debt Package of electricity for a given # Km per year capital) Electricity The consumer owns Better Place spot the car annual subscription fee Leases battery to market (But not the battery) electricity car owners No CO2 Electricity emissions!
7 Supply Charged battery Charge spot Green Energy Systems EV . (lump sum). Battery switch stations Lower CO2 Coordination for Car manufacturer standard in battery emissions! and interfaces An example of a non repeatable business model Stakeholder Economic Value Changes required Motorist Reduction in the Total cost New process of purchase of the of ownership (where, how and when recharge the battery?). Firm New market, new revenues Build the supply chain of a new sector Define and enforce standards and the achitecture for the EV. Public sector Less CO2 emissions Create the conditions for an development of the local efficient and competitive clean tech cluster electricity supply. Tax incentives to motorists purchasing an EV. Limited scalability/replicability of business model > it works where: 1.
8 The supply of clean energies is already well developed(Israel solar energy, Denmark for wind energy). 2. Driving distance are limited small and isolated countries 50%. Covered domains in Italian cities vs. Rest of the World . E government Social inclusion Eneterpreneurship Public spaces 40%. Culture Renewable energies Italy (% cities with initiatives). City logistics E dem. Mobility services 30% Hospitality Entertainment Pollution control Trasparency PA smart Grid 20%. Infomobility Education Waste Public safety Healhcare Human capital 10%. Public lighting Housing quality E Procurement PA smart Building Facility mngmt Agricolture Water man. (services). 0% Cultural heritage 0% 10% 20% Rest of the world 30% 40% 50% 60% 70%. (% cities with initiatives) Politecnico di Torino Obstacles to smart city developments Financial Budget availability for smart city initiatives follows the economic cycle: big top down project have been delayed ( Masdar, Songdo) most successful initiatives are frugal and bottom up ( Amsterdam).
9 New business model must be created. How to share economic value between public and private partners? Who are the residual claimants ? Which city level metrics for measuring the impact of smart initiatives? Before decide the strategy, then choose the metrics . Obstacles to smart city developments Technological Many domains of interventions (logistics, energy, water, waste, surveillance, etc.) but information sylos still exists Lack of technology standards for data, technologies, etc. Greenfield investments ( Songdo) can achieve a native integration of IS in the various domains Digital divide (it leads to a social divide and to the empowerment of elites)? The duration of the investments in infrastructure can be longer than the life cycle of the technology ( smart street lighting) Obstacles to smart city developments Organizational Governance of smart cities investments.
10 Who has the accountability for deciding and executing investments in new initiatives? Which type of governance model among the various entities in a city? Monarchy? Feudal? Federal? Governance of smart city initiatives A central body: Designing the smart strategy for the city Defining how IT can serve to the execution of the city strategy Prioritizing IT investments Defining and enforcing technological standards Attention to backward compatibility of information systems , especially for investments in infrastructure that require long period of installation ( in a large city the entire installation of smart street lamps may take 10 years). Recap Not a dominant paradigm of a smart city City size matters Small cities are ideal for frugal approaches and pilot projects Prevalence of non systemic and technology push approaches to smart cities Analogies with the problem encountered in IT investments in large enteprises A federal governance is needed Delay of Italian cities in the domains where: Investments in the infrastructure are needed Public private partnerships are needed New business models must be created Technological, organizational and financial obstacles exist Part 2.