Many believe that “big data” will transform business, government, and other aspects of the economy. But there is little framework or formulation for application of big data in realization to apply to innovation framework. In this article we discuss how big data takes the role to explain impact of open innovation with cities and suggest specific framework for open innovation of cities. Also we outline some of the challenges in accessing and making use of this framework.

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CYCLIC OPEN INNOVATION FRAMEWORK WITH
BIG DATA OF CITIES
HELEN LEE
MBA 35th Candidate, Politecnico Di Milano, Italy
e-mail: HyeYoung.Lee@mip.polimi.it

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CYCLIC OPEN INNOVATION FRAMEWORK WITH BIG DATA OF CITIES
Many believe that “big data” will transform business, government, and other aspects of
the economy. But there is little framework or formulation for application of big data in
realization to apply to innovation framework. In this article we discuss how big data takes
the role to explain impact of open innovation with cities and suggest specific framework
for open innovation of cities. Also we outline some of the challenges in accessing and
making use of this framework.
Understanding Open Innovation Framework Approach
Open innovation is a paradigm that assumes that firms can and should use external ideas
as well as internal ideas, and internal and external paths to market, as the firms look to
advance their technology 1
. To understand open innovation, it is necessary to define open
innovation framework as many researchers have developed theories of this concept in
various ways. Lichtenthaler2
showed distinction among knowledge processes as
knowledge exploration, retention, and exploitation which can function internally or
externally.
One approach for identifying effective open innovation processes is by taking a typology
from literature, e.g., the distinction between inbound, outbound and coupled activities3
, and
then defining various practices for each of these activities. Van deVrande et al.4
distinguished between the processes of technology exploitation and technology exploration
and defined various practices for each of them. Lichtenthaler2
developed an integrated
technology exploitation roadmap to support out-bound decisions. Other models focus on

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the stages in open innovation. Wallin and vonKrogh5
focus on managing knowledge
integration and define a different five stages process, namely (1) define the innovation
process, (2) identify innovation-relevant knowledge,(3) select an appropriate integration
mechanism, (4) create effective governance mechanisms, and (5) balance incentives and
controls. Besides, Enkel et al.5
presented open innovation maturity framework to help
companies to use it as benchmarking tool of themselves.
Evolving Cities with Open Innovation
At a time when cities face declining budgets and complex issues in contrast to increasing
population, open innovation has been emerged to help them. Openness makes city to
involve communities with knowledge and experience sharing for added value into growth
of city. Open innovation processes have potential to adapt to changing environments
depending on sharing and collaborative behaviors of stakeholders in cities. The popularity
of open innovation is seen in the swell of enthusiasm of social innovation which has many
overlapping principles: collaboration across diverse groups, involvement of the user as well
as a joint focus on solving complex problems for the good of the public.
Relating to how to drive collaboration and participation inside cities, there have been
many researches about open innovation framework. Leading cities started to strive value
added framework adding open innovation. Through developing economy and focusing on
welfare, cities have been centralized and delivered innovative services to people. However,
cities are required to have capabilities to capture changes, expect future and apply
innovative ways for cities’ sustainable growth and development. To deal with these,
nowadays, open governance structure is shown which emphasizes citizen empowerment

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and social innovation. To commit to meet challenges, city itself has become self-aware
operation structure by utilizing technologies and relationship with citizen and
organizations. Urban system has been evolved with clear and responsive interface for
citizen. Citizen can find many opportunities to check urban system and engage in activities
which city governments operate with continuous learning. Additionally, ICT and
innovative technologies have supported cities to build new system of mobility and
flexibility based on urban informatics.
Figure 1 Open government, a framework for citizen empowerment in governments and cities
European Commission ‘A vision for public services’, 2013
Smart city solution for open city enables city not only to provide more efficient service
with citizen but also affect behaviors of city government, business and citizens for
sustainable development. Intelligent infrastructure of smart city is composed of sensor,
cloud and infra sharing environment, civil data collected from operation management
continuously. Smart City is furthermore used to discuss the use of modern technology in
everyday urban life. This includes not only ICT but also, and especially, modern transport

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technologies. Through activation of construction of smart cities, scale of big data would be
built on ICT smart city initiatives in area of administration, security, traffic control, energy,
health medicine, climate change and related others. This helps cities to consider ways for
complex issues and build services for better living of citizen. Additionally, public
expectations for sustainable economic growth make city governments think about open
innovation strategies as demand is increasing continuously.
Open innovation has fundamental principle of collaboration and participation to resolve
conflicts and build cohesive communities by continued and interactive interaction between
different groups. Citizens from all backgrounds have access to information about how the
city is run6
. In cities, developing more relevant innovations importantly means cost savings
and risk reduction7
. Cities to give citizen incentives for active attendances of making
innovations in Cities can get useful outputs which have potential to apply to actual policies.
Moreover, emergence of new communication media in area of SNS induce activities to
make a meaningful social impact. Additionally, most of cities applying open innovation
have taken a proactive approach to combine opinions came from stakeholder groups in
activities to define urban sustainability challenge, develop initiatives and implement new
ways for urban improvement. Porter also pointed out the importance of collaboration and
partnerships, community development and citizen participation for open innovation in
cities. Smart city can delivery public services more effectively by taking advantage of
varied range of technologies. Among them, big data plays a key role to describe activities
of stakeholders, reveal patterns by analysis and create better simulation to apply to
interconnected urban system. Integrated sustainable city concept accelerates cities to turn
into self-transformation with collaborative participation of stakeholders in cities. Inter-

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connecting urban systems facilitate connection and stakeholders’ feedback loops with
balanced mode. The strategic value of open innovation of cities are derived from embedded
data of activities in cyclic process. It enables empowerment the collective intelligence and
co-creation of innovative living models in a contemporary approach.
In social and environmental areas, there have been complex and difficult challenges to
handle in cities. Open innovation shows cities potential for opportunities to meet needs of
stakeholders and to seek viability for themselves. ICT based open innovation added values
into cities to process user-driven open innovation in wider city eco system. It enables to
mobilize stakeholders to drive innovation initiatives for cities. A top down and systemic
view of existing innovation strategies from city government is consist of structured layers
as urban development, processes, network infrastructures, etc. based on technology push.
Another emerging approach for open innovation in cities is bottom up strategy to help cities
generate intelligent and stimulate involvement of stakeholders for creation of sustainable
and impactful services for cities. Smart cities have capabilities to develop strategies and
migration paths by utilizing exploratory and participatory basis with public-private
partnerships for exploitation and intelligent infrastructure with technologies. How to
access, use, and exploitation sharing knowledge and experiences is core for cooperation
and collaboration strategies. Desirable applications reacting to needs of citizens and
strategic objectives for economic and social development are supported of a smart
infrastructure with collaboration and engagement to target behavior changes of cities.
Cities have different and differentiated stages of open innovation framework depending on
culture, status and approach to technical design, operational framework, organizational
structure, policies and communication strategies to transform cities.

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Big Data with Smart Cities
According to AOM8
, big data is generated from an increasing plurality of sources,
including Internet clicks, mobile transactions, user-generated content, and social media as
well as purposefully generated content through sensor networks or business transactions
such as sales queries and purchase transactions. Big data is activated in all areas which can
capture data mainstreams using instrumentation and extract real meaning by analysis.
Currently as cities make stakeholders access data for resolving challenges and putting
priorities of issues by utilizing smart infrastructure, they can make strong collaboration
relationship to accelerate innovation process. Providing more data in scope of privacy non-
violation encourages stakeholders to become more active and empowered to participate for
smart living in cities.
Main features of big data include volume, velocity and variety which connect to value
creation instead of data complexities even if IDC or Mckinsey defines differently. In
indispensable analysis methodologies for realization, text-opinion mining, social network
analysis and cluster analysis are focused as atypical data analysis. Establishments of
solution systems for data storage, batch distribution parallel processing, data streaming
processing would be expected to apply to service for more comprehensive insights to
customers of car, eco energy, health care, medicine, telecommunication, distribution etc.
McKinsey projects that China’s urban population will expand from 572 million in 2005 to
926 million in 2025 and by 2030, China’s urban population is on track to reach one billion.
Currently not nation but city competes for human resource, idea and capital and smartness
of city become to be powerful advantage for development. To make better city, lots of

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cities including Songdo of South Korea have pursued to seek out smart city standards with
advanced technologies. Smart city solution enables city not only to provide more efficient
service with citizen but also affect behaviors of government officer, business and citizens
for sustainable development. Intelligent infrastructure of smart city is composed of sensor,
cloud and infra sharing environment, civil data collected from operation management
continuously. Through activation of construction of smart cities, scale of big data would
be built on ICT smart city initiatives in area of administration, security, traffic control,
energy, health medicine, climate change and related others. Smart City is furthermore used
to discuss the use of modern technology in everyday urban life. This includes not only ICT
but also, and especially, modern transport technologies. Logistics as well as new transport
systems as “smart” systems which improve the urban traffic and the inhabitants’ mobility.
Moreover various other aspects referring to life in a city are mentioned in connection to
the term Smart City like security/safe, green, efficient & sustainable, energy etc. As the
smart city definition is based on greater resource for dynamic economic changes, physical
infrastructure and budgets with ICT, smart city initiatives are still under the progress to
develop in initial time but it is not difficult to see development status of smart city from
Netherlands, Sweden, Malta, United Arab Emirates, Portugal, Singapore, Brazil, South
Korea, China, Japan, EU smart city strategy programs.
Open Innovation Framework of Smart City
For developing open innovation framework of smart city, it is necessary to review existing
smart framework theories.

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Figure 2 Smart City Integrative Framework
Currently, some projects provide examples of collaboration models for smart city
innovation framework by utilizing resources, various methodologies. One of approaches
to integrate different perspectives and view for smart city framework is developing
integrative framework to explain the relationships and influences of key factors for smart
initiatives 9
. Commonly, two different layers of collaborative participation based on smart
city infrastructure are divided. The first layer is collaboration within the innovation process
based on underlying interaction among research, technology and applications development
in practical policy. Still, many issues need to be clarified such as how the different
resources in a network, can be utilized for access and adaptation to change variables to
resolve challenges in cities’ concept of smart infrastructure. Second layer shows that
ecology system surrounding technology, organization and policy is composed by
representing invisible and visible environment, end-user and decision making entity for
innovation. To drive cities into smart city with open innovation framework includes

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consideration of user-driven ecosystem and participation activities to determine success
factors of open innovation projects. William Mitchell10
realized it as Living-Lab.
Michael Porter11
showed national competitive advantage focusing on urban development
policies to drive urban innovation systems based on collaboration for sustainable
innovation. This framework for open innovation of cities consists of physical and
immaterial infrastructure, networks and collaboration, entrepreneurial climate and business
networks, demand for services and availability of advanced end-users. It focuses on
creation of public-private partnership and stimulating the building of networks and
enhancement of innovative conditions. Instead of interactive activities within entities,
living labs has significant role to make infrastructure, business condition and stimulate
innovation based on communication of stakeholders with strong linkage connection in
support of government.
Figure 3 Conceptualization of smart city value creation and innovation system
(Michael Porter, 1990)

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Cyclic Open Innovation of Smart City with Big Data
From previous perspectives, open innovation framework of smart city tried to approach
to create collaborative and participatory layer among the main stakeholders from business,
research, policy and citizen groups by achieving balanced alignment of resources. To
realize cyclic open innovation with big data, big data has responsibility to draw this total
process from awareness to adaptation of behavior by acquisition, integration and analysis
of information connected to city. Convergence of various technologies drives big data to
interact with stakeholders to create innovation for communities and cities. Big data
becomes facilitator for cyclic process of open innovation of smart city in parallel by making
process of operating framework of open innovation framework based on whole entities’
attendance (Figure 4).
Figure 4 Cyclic Open Innovation Framework of Smart City with Big Data

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1) Awareness Domains
Awareness Domains includes acquisition and analysis of Big Data from a variety of
domains: environmental (temperature, humidity, noise etc.), people biometric (heart rate,
body temperature, etc.), communications (telecommunication, SNS activities etc.), traffic
(transportation flow, accident rate, etc.) regarding human and surrounding space conditions
by technical devices. Massive context Big Data from domains, after processed by data
mining and artificial intelligence, are stored and matured with unique life cycle adjusted
by policies and needs.
2) Adaptation – Data Analysis
Using analyzed big data profiling, people and things adapt to better interact and improve
reactions themselves. In case of smart phone, it can be customized to control to modify
setting depending on several variables, such as location, battery charge capacity
automatically. Buildings open and close blind of windows regulating sun lights by analysis
of light (direction, depth, frequency) information. After analysis by capturing big data and
making insights, all modified information are flowed and protected in own right
management system for privacy and ethnic establishments.
3) Modeling Simulation
Urban Behavior is executed to retrieve and simplify meaningful contexts from various
City (Entity) extracted sources of directions based on modeling of data analysis. Integration
of simulation is progressed and each parties for decision making in City act for
improvement in City design, plan and operation management.

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4) Urban Improvement with shared economy
Every entity has right and responsibility for access and utilization about centered urban
big data. Policy implementation for urban improvement by utilizing big data is built up by
voluntary collaboration of stakeholders in cycle. Sharing resources and knowledge in basis
of collaborative partnership within citizen, public and private organizations can perform as
an enabler for innovative governance with shared economy. Seeing improvement of urban
life would give each entity pride to share consciousness of participation in phase of urban
improvement. Urban improvement is not closed eternally by connecting to city awareness
with urban development sustainability. In order to unlock the potential of big data we must
establish collaborative platform to continue role of community interactions and
communications closely for urban dwellers extending big data framework activities. As
communities of the city develop by sharing resources in seamless cycle, overall issues of
privacy and anonymity would be mitigated with more flexible and responsive behaviors of
citizens. Also this enables citizens to act in mutual support and “sustainability"
development of big data system into actions would be developed depending on
collaborative action required for concerted efforts. Citizens hold the ultimate key of success
of urban improvement in user centered context.
The following case offers valuable understanding of suggested framework and
demonstrate that innovation ecosystems are evolving through a combination of top down
and bottom up initiatives, leading to networking and collaboration among stakeholders in
support of big data utilization. Policy maker outline components of a strategic thinking.

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And big data is flowed, analyzed and applied for improvement of policies through cycle of
involvement by multiple attendees.
Seoul government of South Korea had involved in challenges which have conflicts
among citizens with different interests as same as big cities globally. As city has become
more complex in operation and management for sustainable growth and development,
planning policies requires more intelligent and innovative strategies for effective and
efficient government. Seoul government targeted open government as basis of making
policies to adapt to dynamic changing environments and elements of city governance.
Therefore, they have started big data analysis platform to collect, filter and publish public
data as big data strategy. To utilize big data and make optimized policy, communication
channels have opened for each stakeholder to join and communicate interactively to engage
to build-up ideas for policy improvement in collaborative atmosphere. Seoul city decided
to process big data to enhance utilization of big data analysis and create policies based on
incorporation of big data. The ideas connecting to urban big data analysis have been
measured, analyzed and implemented as key factors to set-up policies to transform city into
smart city.
One of the most significant case showed that they have successfully operated public
transportation in the night based on utilization of big data analysis. To resolve traffic issues
to secure citizen’s safety and keep comfort, To select the lines, the city government
analyzed over 3 billion mobile phone calls during the late night and their locations as big
data and finally decided them considering the floating population of specific populated area
on its successful application of Big data analysis which includes the “owl buses” it
continuously introduces big data analysis in its policies such as location analysis for leisure

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facilities for the elderly people. Now, the city government is planning to develop a platform
to share and apply big data by dumping out 927 million won to offer useful transportation
service by analyzing various big data. Aside from the taxi match-making, it will develop
various transportation-related services including a scheme to reduce traffic accidents and
consulting for the operation of call taxis for the handicapped.
1) Awareness Domain
Seoul city government has developed public policies for operation and welfare services
for citizens. They exerted to gather needs of citizens by operating call center and SNS
communications. They found that one of serious issue was transportation in night during
communicating with citizens. Citizens who wanted to use public transportation had trouble
in returning to home as buses did not operate in the late night. Seoul city government
planned transformation process to resolve transportation issue based on big data analysis
in building phase, task including detailed activities as below.

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Figure 5 Seoul Government Innovation Process by Big Data
In the beginning, Seoul city government set various demand factors with location data
from mobiles which people take during moving when building bus pathways and durations.
They built integrated team which was consisted of groups of citizen, research, business and
policy to utilize big data analysis. They had goal to make policy with reliability and
scalability driven from finding potential opportunities of big data analysis and forecasting.
2) Adaptation – Data Analysis
Seoul city applied big data analysis and the trial was successful with over 220,000
passengers and by survey among Seoul also found out that 88% of the people support bus
services throughout the night. Based on its successful application of big data analysis

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which includes the “owl buses” it continuously introduces big data analysis in its policies
such as location analysis for leisure facilities for the elderly people. Now, the city
government is planning to develop a platform to share and apply big data by dumping out
927 million won to offer useful transportation service by analyzing various big data. To
select the optimized lines of night bus, the team analyzed over 3 billion mobile phone calls during
the late night and their locations as big data and finally decided them considering the floating
population.
3) Modeling Simulation
By creating the subsequent simulation model based on problem-solving model
development, it enables to understand effect and expect results to improve operation
system. The team built-up visualization to show how optimized operation of night buses in
Seoul can function. They could evaluate and integrate the expected results from simulation
without difficulties. Then Integration of simulation was progressed and each parties for
decision making in city act for improvement in city design, plan and operation
management.
4) Urban Improvement with shared economy
Seoul has established the optimal route for its late night bus service provided by support
of the team including groups of citizen, research, business and policy. This project gave
people more convenient usage of bus, reliable public bus branding and helped bus drivers
working in the higher wage condition. The city went through two significant processes –
awareness of current problems and environments and adaptation to problem by insight
discovery of opportunities and resolution exploitation of opportunities with shared

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economy. The city could improve capabilities to control transportation system with not
much efforts with public branding. In order to unlock the potential of big data utilization
we must establish collaborative platform to continue role of analysis of real-time situations
and feedback from people in cites.
Conclusions and Outlook
I hypothesize that the big data accelerate city to adapt to dynamic environments and
change to smart city. The first reason is that big data analysis offers city to resolve
myriads problems surrounded by physical, biological and social phenomena without
theory. Most of successful examples in urban management and policy were not
implemented with simulation of algorithms. Open innovation policy offers one way to
improve policy performance and meet citizens rising expectations. Merging big data and
open innovation policy can lead to collaborative engagement in support of stakeholders
of city. As communities of the city develop by sharing opinions and feedbacks of evolved
systems, overall issues of privacy and anonymity would be resolved with more flexible
and responsive behaviors of citizens. Also this enables citizens to act in mutual support
and “sustainability" development of smart city system into actions would be developed
depending on collaborative action based on big data. Citizens hold the ultimate key of
success of smart city realization which we are still developing. Big data helps to make
simplification of performance metrics and factors which affects to solve conditions.
Secondly, big data provides intelligent ways for planners to plan and innovate smart city
systems based on forecasting and decision making. Seoul city government could capture
the complexity of bus transportation system and has drawn ideal bus services for citizen
based on big data analysis framework to monitor, collect, analyze and integrate.

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Notes
1 Chesbrough and Henry William,Open Innovation: The New Imperative for Creating and
Profiting from Technology. HBS Press, 2003;
2. Lichtenthaler, U., Lichtenthaler, E., A capability-based framework for open
innovation: complementing absorptive capacity. Journal of Management Stu-
dies 46 (8), 1315–1338, 2009;
3. Gassmann, O., Enkel, E., Towards a Theory of Open Innovation: Three Core
Process Archetypes. In: Paper presented at R&D Management Conference,
Lisbon, 2004;
4. Van de Vrande, V., de Jong, J.P.J., Vanhaverbeke, W., de Rochemont, M., Open
innovation in SMEs: trends,motives andmanagement challenges. Technovation
29, 423–437, 2009;
5. Enkel, E.; Bell, J. and Hogenkamp, H., Open Innovation Maturity Framework.
International,Journal of Innovation Management, 15 (6): 1161–1189, 2011;
6. Bakici, T., ‘State of the Art - Open Innovation in Smart Cities’.
ESADE report,
http://ec.europa.eu/information_society/apps/projects/logos//6/270896/080/deliverables/0
01_D11StateoftheArtOpenInnovation.pdf, 2011;
7. Bason, C.,‘Leading Public Sector Innovation, Co-Creating for a
Better Society’ Policy Press, 2010;
8. Academy of Management Journal, Big Data And Management. Vol. 57, No. 2, 321–326,
2014;

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9. Hafedh Chourabi et. al, Understanding Smart Cities, An Integrative Framework, 2012;
45th Hawaii International Conference on System Sciences, 2012;
10. European Commission, DG INFSO, Advancing and Applying Living Lab
Methodologies, 2010;
11. Porter, M., The Competitive Advantage of Nations. Free Press, New York, 1990;