Technology Adoption in Smart City Initiatives: Starting Points and

Influence Factors

Christian Bremser

, Gunther Piller

and Markus Helfert

Business Information Technology, University of Applied Sciences Mainz, Lucy-Hillebrand-Straße 2, Mainz, Germany

School of Computing, Dublin City University, DCU Glasnevin Campus, Dublin, Ireland

Keywords: Technology Adoption, Smart City, Digitization.

Abstract: The concept of smart city is considered as a new paradigm of urban development. Information and

communication technologies are expected to transform cities into smart cities and improve the citizens’

quality of life. However, smart city initiatives still have difficulties to leverage value from technology

opportunities. How smart city initiatives start to examine the possibilities of new technologies for smart

services is therefore a highly interesting question. Based on a multiple case study we describe two different

approaches and identify factors that were crucial for the course of action. As a result, we found on the one

hand smart city initiatives that consider the involvement of citizens as essential and start technology

adoption from a need perspective. On the other hand, we found initiatives that see new technology and

standardized data exchange as a unique opportunity and therefore start with a systematic build-up of

technology and data platforms. Innovation adoption research is used as a theoretical basis.

1 INTRODUCTION

According to the latest UN forecast, 70 percent of

the world's population will live in cities by 2050

(United Nations, 2018). This means that 2.5 billion

people will move to urban areas in the next 30 years.

Problems such as housing scarcity, overloaded

infrastructures and CO2 pollution caused by public

transport will continue to worsen as the number of

city inhabitants increases. In recent years, numerous

smart city initiatives have been launched to tackle

these problems (Zelt, 2017). Their aim is to leverage

developments in digitization to create new solutions

for improving the efficiency of urban services and

the quality of citizens’ life (Neirotti et al., 2014).

The politicians' conviction that technology can

contribute to make the city a more liveable and

sustainable place is also reflected in the figures of

funding programmes. The EU is providing €718

million for smart, green and integrated transport

innovations as part of the European Horizon 2020

programme (European Commission, 2018). Such

high funding also attract the private sector.

Multinational information technology (IT)

companies such as IBM or Cisco have discovered

the smart city market as a growth driver for their

business. These companies offer a variety of

integrated solutions for different smart city scenarios

(e.g. IBM's Intelligent Waste Management Platform

(IBM, 2015)). Collaborations between private and

public sectors have also led to criticism of the smart

city concept. Brown (2014), Söderström et al. (2014)

and Schaffers et al. (2011) criticise them as

inefficient and driven by IT vendors. The

inefficiency is also criticized by the European

Commission (2016) which stated in a working

paper, that “city planners, administrators, citizens,

entrepreneurs and all other stakeholders must

reconsider the way they have approached urban

services” to gain value from technology

opportunities. Also Anttiroiko, Valkama and Bailey

(2014) state that the public sector has difficulty

exploiting the value from new technologies. Despite

these findings, there have been few attempts in

science to understand how smart city initiatives

leverage value of new technologies.

The introduction of new technologies is

described by innovation adoption theories. The

process of innovation adoption typically involves

two phases (Rogers, 2003): initiation and

implementation. Within these phases, new

technologies have to overcome several hurdles

before being used productively, i.e. being integrated

Bremser, C., Piller, G. and Helfert, M.

Technology Adoption in Smart City Initiatives: Starting Points and Inﬂuence Factors.

DOI: 10.5220/0007702700700079

In Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2019), pages 70-79

ISBN: 978-989-758-373-5

into an existing IT landscape and deployed at full-

scale (Fichman, 2000). For technology innovations,

the initiation phase, where organizations search for

ways to use a new technology, poses a first serious

obstacle (Curry, Dustdar, Sheng and Sheth, 2016).

This initial step towards the exploration of

technology potentials is the focus of our study. In

particular we formulate the following research

question:

What approaches do smart city initiatives use when

they initially explore the potential of new

technologies for smart services and which factors

influence their choice of approach?

To address our research questions, a multiple case

study with eight smart city initiatives was

conducted. The organizational innovation adoption

process (Rogers, 2003) in combination with the

Technology-Organization-Environment framework

(TOE) (Tornatzky, Fleischer and Chakrabarti, 1990)

and the push-pull theory (Schon, 1967; Zmud, 1984)

has been used as a theoretical foundation. The TOE

describes the impact of technological, organizational

and environmental aspects on organizational

decision-making with respect to technology

innovations (Tornatzky et al., 1990). The push-pull

theory distinguishes innovation adoption approaches

in a technology-push and need-pull driven

perspective (Schon, 1967; Zmud, 1984).

This paper is organized as follows: The current

research on technology adoption research in smart

city is summarized in the next section. Section 3

presents our conceptual framework. Section 4

introduces the research design. Section 5 presents

the findings from our smart city cases. A discussion

of the results in section 6 and a summary of the main

points in section 7 complete this work.

2 CURRENT RESEARCH

The term “Smart City” has been widely used in

academia, consultancies and governments.

Nevertheless, there is still a lot of confusion on what

it really means to be a “smart” city (Caragliu, Bo

and Nijkamp, 2009; Nam and Pardo, 2011;

Angelidou, 2017). According to Anthopoulos,

Janssen and Weerakkody (2016) a smart city is an

innovative city that uses information and

communication technology to improve citizens’

quality of life and the efficiency of urban services.

To meet these goals, smart cities need to introduce

new technologies and realize smart services that

address the concerns and needs of citizens

(Anthopoulos et al., 2016; Pourzolfaghar and

Helfert, 2017).

Smart services are considered as core element of

a smart city and understood as an outcome of

innovation (Anthopoulos et al., 2016). The term

summarizes the services that a smart city delivers to

its stakeholders by the use of the city’s intangible

resources (e.g. people, knowledge, methods) and

tangible resources, in particular information systems,

data, and corresponding technologies (ITU-T Focus

Group on Smart Sustainable Cities, 2014;

Anthopoulos et al., 2016; Angelidou, 2017).

Previous work in the context of technology

adoption in smart cities is still scarce and focuses

primarily on influencing factors. These are either

investigated for the general adoption of the smart

city concept or for the adoption of a specific

technological solution. For example, Neirotti et al.

(2014) used in an empirical analysis a sample of 70

cities to investigate context variables that support the

adoption of the smart city concept. As a result, they

show that economic development and structural

urban variables (e.g. demographic density, city area)

drive the initiation of smart city programs in urban

areas. Nam and Pardo (2011) and Caragliu et al.

(2009) argue that a successful adoption of the smart

city concept depends on investments in human and

social capital, investments in modern and traditional

infrastructure and the participation of citizens.

Batubara, Ubacht and Janssen (2018) use the TOE to

describe main challenges in the adoption of

blockchain technologies in smart cities. As a result,

it has been shown that a lack of legal and regulatory

support and new governance models are considered

as main barriers of blockchain adoption.

So far an investigation of the technology

adoption process in smart cities has only been

carried out by van Winden and van den Buuse

(2017). They used a multiple case study to

investigate the implementation phase of smart city

projects. Based on twelve smart city initiatives they

identify three types of full-scale deployments in

smart city projects: roll-out, expansion, and

replication. They also identify corresponding

influencing factors, e.g. upscaling in the

implementation stage is often hindered by an

absence of knowledge transfer, a lack of funding and

missing standards such as data models or IT

systems.

In comparison to existing studies, our research

focuses on the initial phase of innovation adoption.

We investigate how cities initially explore the

potential of new technologies for smart services and

factors that influence their choice of approach.

Technology Adoption in Smart City Initiatives: Starting Points and Inﬂuence Factors

3 CONCEPTUAL MODEL

The goal of this research is to describe how cities

approach new technologies for smart services in the

initiation phase of innovation adoption, and whether

there are factors that have a significant impact on

their choice of approach.

For our study, we use the innovation adoption

process (Rogers, 2003), the push-pull theory (Schon,

1967; Zmud, 1984), and the TOE framework

(Tornatzky et al., 1990).

According to Rogers (2003), the process of

innovation adoption is described by two major

phases: initiation and implementation, with both

phases being separated by an adoption decision. The

initiation phase consists of the stages agenda-setting

and matching and covers all activities that are

necessary to explore the capabilities of an

innovation. If advantages are expected, the

implementation phase is triggered and all activities

and decisions necessary to deploy an innovation at

full-scale are carried out (Rogers, 2003).

Following the push-pull theory, innovation

adoption is either approached form a technology-

push or need-pull perspective (Schon, 1967; Zmud,

1984; Di Stefano, Gambardella and Verona, 2012).

The technology-push perspective describes the

driving force behind the adoption as the expectation

of enhancing performance by introducing new

technologies (Chau and Tam, 2000). The need-pull

perspective describes stakeholder needs as a key

driver for the adoption of new technologies (Chau

and Tam, 2000).

To investigate the factors that influence the

decision on how to approach in the technology

adoption, the TOE provides a good theoretical

foundation. The TOE describes the factors

influencing the adoption of technology innovations.

These factors are clustered into three dimensions:

technology, organization and environment

(Tornatzky et al., 1990). The technology dimension

encompasses the characteristics of available

technologies which are relevant to an organization.

The organizational dimension covers organizational

attributes, such as size, formal and informal linking

structures, competencies and the amount of slack

resources. The organization’s environment and its

influence are described in the environmental

dimension. It includes competitors, industry

specifics and regulation. As a very generic

framework, the TOE is extensively used in adoption

research (for examples see e.g. (Oliveira and

Martins, 2011; Baker, 2012)) and can be adapted to

different research contexts in a straightforward way

(Baker, 2012). For our research the technological

dimension reflects attributes describing existing and

new technologies that are relevant for a smart city.

The organization dimension covers organizational

aspects of the city and its smart city initiative. The

environment dimension describes the influence of

the multiple stakeholders that surround a smart city.

In conclusion, the conceptual framework used in

this research combines the initiation phase of the

innovation adoption process (Rogers, 2003), the

push-pull theory (Schon, 1967; Zmud, 1984) and the

TOE (Tornatzky et al., 1990), as shown in figure 1.

Figure 1: TOE framework.

4 RESEARCH DESIGN

This study uses a qualitative research methodology

because we have little understanding of how cities

explore the potential of new technologies for smart

services and why they choose certain strategies. A

qualitative approach allows us to obtain detailed

descriptions of adoption behaviour. For our research

purpose, we choose a case study method. This

method is especially appropriate whenever research

deals with “how” and “why” questions and

facilitates analyses of contemporary phenomena in a

real word context (Benbasat, Goldstein and Mead,

1987; Darke, Shanks and Broadbent, 1998; Dubé

and Paré, 2003; Yin, 2003). Our main information

sources are in-depth expert interviews with key-

informants (i.e. smart city representatives) and

public documents from smart city initiatives.

In the sense of a strict implementation of the

research design, four established quality criteria

were used (Yin, 2003): external validity, internal

validity, construct validity and reliability. The

external validity focusses on the generalizability of

SMARTGREENS 2019 - 8th International Conference on Smart Cities and Green ICT Systems

the results. This is ensured by replicating the case

studies. Therefore we selected a multiple case study

design following the “literal replication logic”. The

literal replication logic ensures an analytical

generalization by selecting cases from a similar

contextual background to predict similar results

(Dubé and Paré, 2003; Yin, 2003). In order to ensure

a comparable organizational and technological

context, we followed the smart city

conceptualization of Angelidou (2014) and selected

existing major European cities with matured

infrastructure. In addition, the selected cities and

corresponding smart city initiatives have been

validated by the smart city framework of Giffinger

(2007), which consists of six main components

(smart economy, smart people, smart governance,

smart mobility, smart environment, and smart

living). Against this background, we selected only

cities which are active in at least two categories.

Table 1 shows the cases under study.

Table 1: Participants of case study.

# City Role of Interviewee

1 Amsterdam Program ambassador

2 Barcelona Catalan smart city coordinator

3 Dublin Smart city coordinator

4 Cologne Smart city project manager

5 Copenhagen Head of IT

6 Berlin Policy advisor smart city

7 Vienna Expert for urban innovation

8 Zurich Deputy director urban

development

Following Eisenhardt (1989), an a priori

specification of constructs helps researchers to shape

the initial design of theory-building research. In

order to ensure internal validity, we followed this

argumentation and developed the interview

guideline on the basis of the conceptual framework

described in section 3 of this paper. The expert

interviews were semi-structured and we kept our

questions open to allow interviewees freely to speak.

The first part contained general questions about the

role and responsibility of the interviewee and the

general goals of the smart city initiative. The second

part of our questions concentrated on activities

related to the beginning of technology adoption. For

example, we asked how specific needs for

technology innovations are recognized, how they are

prioritized and whether specific objectives for

technology adoption exist. We also asked about

factors that have influenced the first decisions about

dealing with new technologies. Hereby we covered

in particular the TOE dimension of our conceptual

model. The third and most extensive set of questions

was directed upon “why” and “how” the initiatives

explore the potentials of new technologies. These

questions concerned, e.g. the methods and

challenges during the identification of technology

opportunities, the evaluation of technology

potentials and the criteria applied therein.

Yin (2003) suggests triangulation to ensure

construct validity. Within the case studies, different

data sources were therefore used. In addition to the

key-informant interviews the rich body of public

documents of smart city initiatives was analysed to

validate the information retrieved from the key-

informant interviews. Table 2 provides an overview

of case information sources.

Table 2: Information sources.

Data source Description

Interviews with smart

city representatives

13 interviews were conducted

(8 key informants + 5

supplementary interviews

with other smart city officials)

Publicly available

documents from

members of the smart

city initiative

151 technology adoption

related press articles, blog

entries, white papers, annual

reports and conference

presentations were screened

In order to minimize errors and biases, the

reliability of the case study analysis was ensured by

establishing a case study database. There, we stored

all information about the data collection process, the

data itself and the case study results. According to

Yin (2003), this helps to provide the same results in

repeated trials and makes the data available for

independent inspections.

The data collection started in February 2018 and

stretched over a period of five months. The

conversations were recorded and transcribed.

Shortly after each interview, the main points and key

findings were recapitulated in a contact summary

sheet (Miles, Huberman and Saldana, 2013).

The analysis of the cases was carried out in a

twofold way. First, we have used a within-case

analysis (Yin, 2003) to extract all characteristic

content (i.e. trigger of the process, activities in

agenda-setting and matching) and influencing

factors related to the agenda-setting of individual

cases. For this purpose, we followed the deductive

content analysis method (Mayring, 2008) and used

first-level coding (Miles et al., 2013) supported by

the software f4analyse. In the second step, a cross-

case analysis (Yin, 2003) was conducted and the

cases were compared to each other. The results of

these analyses are shown in chapter 5 and discussed

in chapter 6.

Technology Adoption in Smart City Initiatives: Starting Points and Inﬂuence Factors

5 RESULTS

Innovation adoption can be approached from a

technology-push or need-pull perspective (Schon,

1967; Zmud, 1984; Di Stefano et al., 2012). Based

on this distinction, we were able to divide the smart

city initiatives and their corresponding approaches in

the initiation phase into two groups: need-pull and

technology-push initiatives. Table 3 and 4 present

the cases on the basis of the main case

characteristics (i.e. exemplary statements, which

were particularly emphasized) and a brief

description of the initiatives’ first technology

adoption activities.

Need-pull smart city initiatives (table 3):

initiatives in this category explore technological

potentials from a stakeholder-need perspective. They

initially focus on the collection of potential

applications solving smart city challenges (e.g.

through virtual collaboration platforms, design

thinking projects). Identified use cases are then

evaluated on how they contribute to the

superordinate smart city goals (e.g. CO2 reduction

through improvements in public mobility). If this is

verifiable, corresponding technologies are imple-

mented and the application is tested as a prototype.

For example in case 1, the initiative launched a

central web portal to connect different stakeholders,

receive user-initiated project proposals (e.g. ideas,

how new technologies can be used to solve

challenges) and attract people to launch projects as

Table 3: Need-pull smart city initiatives.

# Main Case Characteristics Sample Quote First Technology Adoption

Activities

1  implementation of innovative projects is

expected to favour sustainable economic

development

 empowerment of citizens and local start-

ups is perceived as important for the

identification of potential smart services

 transparency in political decision on

project proposals is perceived as important

to increase citizen's engagement

“Co-creating and co-developing

urban solutions requires

involvement and empowerment

of citizens in the innovation

process. This should enhance [..]

accepted solutions that work and

create value for all involved

parties, including citizens.”

(Public Documents)

establish web portal to connect

smart city stakeholder; creation of

smart city team that asses the user

initiated project proposals for

potential smart services; focus on

smart services that solve city

challenges

4  no dedicated smart city budget;

dependence on third party funds

 expectation of economic returns by solving

city’s challenges with smart services

 coordination and communication of

different projects within the city is

perceived as important to identify

synergies and valuable smart services

“Smart city Cologne is at the

same time a coordination and

communication platform for

various projects for climate

protection, energy and transport

change and improved energy

efficiency.” (Interview)

connect the different smart city

stakeholders and share plans,

strategies, activities between them;

utilize design thinking and other

creativity methods to identify

needs of city stakeholders

7  empowerment of the private sector is

perceived as important for identification of

use cases

 single focus on smart city technologies is

expected to neglect citizen participation

and exacerbate the digital divide

 initial identification of lighthouse use cases

is expected to attract further capital and

strengthen confidence in the initiative

“In Vienna, a demand-oriented

approach [for the introduction of

new technologies] is chosen. If a

problem requires a new solution,

the appropriate means are sought

to develop a suitable solution -

these of course often include

digital or technological

components.” (Interview)

collect urban problems via app

and develop solutions by using

concepts like co-creation labs or

industry-meets-makers; projects

within the smart city Vienna

initiative are first developed as

pilots using dedicated

technologies and data sources;

integration aspects are not initially

considered

8  existing technology infrastructure is

perceived as sufficient for current

digitization efforts

 synergies for new smart services are

expected by the coordination of municipal

companies that are already working on

their own digitization projects

 the creation of "good practices" strengthens

confidence in the smart city initiative and

promotes motivation to participate

“By comparison, the

[technology] infrastructure in

Switzerland and here in the city

of Zurich is already well

developed and will be further

optimized.” (Interview)

definition of a smart city strategy

with focus on the challenges of the

city and the needs of city's

stakeholders; identification of the

needs via innovative methods (e.g.

design thinking) and a so-called

virtual “participation portal”;

development of solutions for the

identified needs in collaboration

with public and private companies

SMARTGREENS 2019 - 8th International Conference on Smart Cities and Green ICT Systems

pilots. The smart city initiative assesses the project

proposals. If the assessment proof successful, the

project proposals are conducted as pilots in

designated city areas. The lessons learned from the

pilots are then used for refinements and a further

evaluation whether the goals could be achieved (e.g.

people accept the technology, CO2 pollution could

be reduced).

Technology-push smart city initiatives (table 4):

In the technology-push approach, cities initially

invest in cyber-physical systems (i.e. combination of

computational components with mechanical and

electronic parts) and develop platforms that integrate

different new technologies for data acquisition,

integration and storage. These platform capabilities

are then advertised and communicated to attract

private organizations (e.g. companies, start-ups,

local communities) to drive the identification and

exploration of use cases for smart services, e.g.

through hackathons. This approach often initially

concentrates on certain domains of a smart city (e.g.

smart transportation, smart energy).

For example in case 6, the connection of

innovative technologies with existing infrastructure

was one goal of the city’s first efforts. Requirements

for infrastructure projects were therefore utilized to

anchor new technologies (e.g. sensors in lampposts)

in the city’s infrastructure. In cooperation with state-

Table 4: Technology-push smart city initiatives.

# Main Case Characteristics Sample Quote First Technology Adoption

Activities

2  welfare of citizens is expected to

increase due to an open and modern

technology platform

 new technologies are intended to make

business processes of public

administration more accessible,

efficient, effective and transparent

 synergies are expected by standardized

information sharing within the city’s

companies

“Through investment in IoT for

urban systems, Barcelona [will

achieve] a wide array of benefits.

From reduced congestion and lower

emissions, to cost savings on water

and power [..]” (Public Documents)

built public private partnership to

realize technology platform;

systematic development of data

platform and integration of

different public data sources

3  modern technology infrastructure is

seen as a unique prerequisite for

solving urban problems

 new technologies are intended to

increase the efficiency of the city’s

overall management

 building of information systems is

perceived as complex

“[Our technology and data] platform

should lead to improved economic

development by speeding up the

advancement of services based on

data[..]” (Public Documents)

focus on improvements in the

public transportation system and

water management; public private

partnership to collect and analyse

traffic and consumption data; join

and integrate existing data bases

with newly collected data;

provision of smart services based

on the acquired information

5  availability of data is perceived as a

unique starting point for developing

smart services

 modern technology platform is

perceived as key for later smart city

developments

 new businesses and a highly skilled

workforce are expected to be attracted

by a modern technology platform

“The City Data Exchange for

Copenhagen is a solution for making

public and private data accessible so

that the data can help power

innovation [..] If we combine data

from the private sector and data from

the city then it is expected that we

can make new solutions and new

products out of it.” (Interview)

release of a smart plan describing

which technologies are needed to

get smarter; big data identified as

key technology; city data

exchange concepted and

established based on a public

private partnership

6  data and information are perceived as

essential resources of an information

society

 technology innovations are perceived

as complex but seen as unique

opportunity for the future development

of the city

 coordination of digitization activities

in public companies within the city is

perceived as important in order to

guide the development of city wide

technology and data platform

“We have a supervisory board

function in the state owned

companies. This means that we can

actively discuss and shape guidelines

for project contracting.” (Interview)

realize existing infrastructure

projects with new technologies;

systematic anchoring of sensors

in the urban infrastructure; open

up new data sources for a data

driven identification of smart

services

Technology Adoption in Smart City Initiatives: Starting Points and Inﬂuence Factors

Table 5: Overview TOE factors and link to main case characteristics.

Technology Organization Environment

 perceived complexity (the use of new

technologies is perceived as complex

[+] or not [-])

 technology landscape (existing

technology landscape is perceived as

sufficient [+] or not [-])

 information exchange (standardized

information exchange is perceived as

essential [+] or not [-])

 unique benefits (it is expected that a

modern technology platform

supersedes other measures for city

development [+] or not [-])

 financial readiness (dedicated smart

city budget is substantial [+] or

limited [-])

 role of smart city initiative (smart

city initiative is primarily seen as

coordination platform [+] or not [-])

 economic returns (direct economic

(e.g. job creation) returns are

expected [+] or not [-])

 information systems (IS) fashion

(the use of new technologies is

perceived as important [+] or not [-

])

 citizen involvement (raise citizens’

involvement is a primarily goal of

city [+] or not [-])

 role of private sector (it is expected

that innovative use cases come from

private sector [+] or not [-])

owned companies central data storages were built

and different data sets were harmonized and

integrated. A public-private partnership was utilized

to advertise for the data and technology capabilities.

6 DISCUSSION

Following the TOE framework we collected all

influencing factors from the investigated cases. We

then abstracted and assigned them to the appropriate

TOE dimensions. The result is shown in Table 5,

including brief comments and explanations. As a

result we found ten factors describing the influence

on how smart city initiatives start with the

exploration of new technologies.

Table 6 visualize the factors which had influence

on a city’s choice of approach. We found that cities

with a need-pull approach typically expect that

innovative smart services come from private sector

and only leverage value when concerns and needs of

citizens are considered. In order to link innovations

with citizens’ needs, the collaboration of smart city

stakeholders is perceived as highly relevant. This

high perceived relevance of collaboration is also

reflected in the governance model of these smart city

initiatives. It considers them as a central platform for

the coordination of projects between public and

private sector. The city’s goal to increase the

involvement of citizens in urban development also

supports the choice to a need-pull approach. For

example, in case 7, the smart city initiative argued

that the city administration sees the citizen

participation as crucial to the success of smart city

development. They therefore wanted to enable the

city’s residents to participate more actively. A

collaboration app should contribute to this goal and

simplify and foster the communication between city

administration and citizens.

A high perceived complexity of new

technologies and a low financial readiness prevents

initiatives in this approach from creating innovative

smart services on their own and emphasizes the

dependency on the private sector as external source

for innovations. For example, in case 4, the

interviewee argued that the financing of projects is a

constant challenge as the city does not have a

dedicated smart city budget. In order to identify use

cases, a public-private partnership was formed. This

public-private partnership enabled the smart city

initiative to conduct design thinking projects or

hackathons.

Initiatives that follow a technology-push

approach perceive a standardized information

exchange as a driver for innovations from public and

private companies. Implemented modern

technologies are seen as unique opportunity to

increase efficiency of urban services and attract

private companies as well as start-ups. The

initiatives hope that these companies will in turn

create new local jobs and identify and provide smart

services. Despite the technology focus of the

initiatives in the technology-push approach, the

existing technology landscape is perceived as

insufficient for future requirements. For example, in

case 3, the city stated that new technologies led to

SMARTGREENS 2019 - 8th International Conference on Smart Cities and Green ICT Systems

Table 6: Abstracted TOE factors assigned to the different dimensions and cases.

need-pull technology-push

1 4 7 8 2 3 5 6

perceived complexity + + + + + + + +

technology landscape - - + + - - - -

information exchange - - - - + + + +

unique benefits - - - - + + + +

financial readiness + - - - + - + -

role of initiative + + + + + - - +

economic returns - + + - + + + +

IS fashion + + + + + + + +

citizen involvement + + + + - - - -

role of private sector + + + + + + - +

improvements, for example in water management

(e.g. reduced leakage through automated pressure

management), but that there is still a need to

increase the sensor network over the city to improve

results.

Additionally, we found IS fashion as a general

trigger of the adoption process in all observed

initiatives as it reflects the hype that surrounds

technology innovations such as blockchain or big

data. At the same time, these new technologies are

perceived as complex. A frequent argument for the

perceived complexity was a lack of IT know-how in

public institutions and limited financial resources

that impedes the acquisition of external knowledge.

Furthermore, most of the interviewed initiatives

perceived their financial readiness as low and

reported that they are highly dependent on regional,

national or international funding schemes.

7 SUMMARY

In this paper we have investigated through an

analysis of eight cases how smart city initiatives

start exploiting potentials of new technologies.

We could describe two different approaches for

the initiation phase of technology innovation

adoption: a need-pull and technology-push

approach. In the need-pull approach, smart city

initiative focus initially on the identification of use

cases for potential smart services that will meet

citizens’ needs and solve urban challenges. In the

technology-push approach, the systematic build-up

of a technology and data platform for a future

identification of potential smart services is in the

centre of first activities.

The choice for a particular approach is

influenced by external and internal factors, which

could be assigned to the technology, organization

and environment dimensions of the TOE. In

particular we found three discriminating factors:

information exchange, unique benefits and citizen

involvement. The perceived importance of

standardized information exchange and expected

unique benefits of new technologies were crucial for

the technology-push approach. An increased

involvement of citizens was considered most

relevant in the decision for a need-pull approach.

The theoretical and practical contributions of this

research are as follows: Our study shows that the

innovation adoption process and TOE can

successfully be used to describe and understand the

exploration of new technologies in smart cities. The

study further contributes new factors to the existing

IS adoption literature and provides a starting point

for further quantitative and qualitative adoption

research. From a practical point of view, cities

initiating a smart city program can compare their

planned activities with the different approaches and

drivers identified in this paper, to possibly re-

consider their way of action. Providing a method for

the identification of use cases for smart services is

planned as a next step in our research agenda. The

corresponding design-oriented approach will benefit

from the insights gained in this study.

We are sensible that our study faces limitations

which should be addressed in future research: A

possible restriction may result from the point in time

of observation. We investigated how smart city

initiatives start to adopt new technologies. During

our research we have observed that the approaches

of cities change over time and can coexist as the

initiative progresses. A longitudinal study could help

to describe and understand these changes.

Our identified approaches also open the door for

further research: On the one hand, a detailed analysis

of the processes within the different approaches

could help to provide smart cities a suitable method

for the successful identification, evaluation and

adoption of smart services. On the other hand, the

Technology Adoption in Smart City Initiatives: Starting Points and Inﬂuence Factors

choice of approach and the impact on the success of

smart service implementation could be investigated

in order to provide recommendations for

practitioners on what approach they should take

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