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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;