Abstract

Projects have become vital in initiating urban sustainability changes. In this study, we address the research gap regarding the dual role of a project in advancing change in public organizations and helping them to adopt roles in initiating and steering urban sustainability transitions. From a practice-theory perspective, we present longitudinal participatory action research on the activities of a project management team in a city organization. Our results show how praxes of a project team without hierarchical authoritative power to give orders or delegate change-related activities in the host organization create organization-level outcomes in the city’s organization and urban living lab contexts amongst external stakeholders. We contribute to project management studies by increasing the understanding of how short-term project activities foster long-term strategic changes in siloed and departmentalized host organizations while at the same time creating outcomes in the external urban living lab context. This provides novel insights into the evolving intermediary roles of projects that support city organizations in acting as leaders in urban sustainability transitions.

Introduction

Projects have become vital in initiating urban sustainability changes and there is a call for project studies focusing on sustainability transitions. Increasingly, cities and other host organizations use projects to become credible actors for sustainability. Sustainability transitions research (Köhler et al., 2019) has developed approaches to analyse the systemic nature of transitions, including the multi-level approach (MLP) and other, more horizontal approaches applied particularly in research on urban sustainability transitions (von Wirth et al., 2019). In project research, there is a rising orientation toward sustainability transitions. Most recently, Winch (2022) envisaged that projects in sustainability transitions will begin a new era in project research, Daniel (2022) developed an integrative framework between MLP and project research, and Bos-de Vos et al. (2022) studied system transformations through context dynamics, albeit not using the transition vocabulary. We contribute to the rising research orientation on projects supporting sustainability transitions with a focus on sustainability projects in city organizations.

Cities are key organizations in urban sustainability transitions. These transitions are multi-actor, multitemporal and multi-regime societal transformations coordinated by the city (Frantzeskaki et al., 2017). Niches that can instigate transitions in urban areas include urban living labs (ULL), in which sustainability innovations are created and experimented in collaboration between the city, companies, citizens, research institutes and other actors (Jørgensen, 2012, von Wirth et al., 2019). The transition accelerates when the niche innovations are translated and scaled up within and across cities to increase their transformative capacity. When they challenge the unsustainable regimes with the support from incumbent actors, they can gradually turn urban development into more sustainable pathways (Frantzeskaki et al., 2017). We recognize that sustainability transition in cities requires attention to two parallel directions. First, while cities are expected to be enablers of ULLs and the main leaders of urban sustainability transitions, they are not unitary actors, but rather divided into siloed bureaucratic departments in city administration. Each department tends to defend its own interests, conventional mindset, and budgetary status quo, and if these fragmented interests and practices are not aligned with the promotion of sustainability transitions, the city administration will lack the motivation to support multi-objective ULL projects and their continuities. Second, because experiments and projects are central to ULLs and essential to wider urban policy agendas for sustainability, it is questionable whether these short-term activities can support the long-term trajectories required for urban sustainability transitions (Torrens & von Wirth, 2021). While only the second challenge is in the focus of sustainability transitions research, the challenges are independent and create a dual-context problem in which a city organization has both internal and external barriers that hinder the promotion of urban sustainability transition.

Conclusions

Urban sustainability transitions that involve changes both in city organizations and the urban context represent a topical yet sparsely researched subject. By using project-as-practice approach and based on in-depth longitudinal action research to study a sustainability transition project in a city organization this research elucidates the ways in which a project enacts a dual role as both a niche intermediary in the urban context and an endogenous change facilitator within the city organization. Thus, the temporary short-term project increases the city organization’s transformative capacity to strengthen the city’s role as a leader in urban sustainability transitions in the long term. We show that the project practitioners’ enactment of sustainability transition in situated and emergent practices created favourable conditions for people to engage in sustainability change, challenged organizational boundaries and created commitment to sustainability transition across departments. This is evidence that the praxes in a sustainability project constitute and instantiate a macro-level sustainability change in the internal organizational context and the external ULL context.

The results of this paper have theoretical implications for the ongoing discussion of the roles of projects in sustainability transitions (Daniel, 2022; Winch, 2022; see also Winch et al., 2023). Daniel (2022) and Winch (2022) emphasize that projects with their teams and individuals are necessary on the level of technical execution, whereas host organizations promote the transition on the meso‑level through projects, portfolios, and programs. In terms of key aspects of project management (Pich et al., 2002), this division is based on instructionism (project using detailed, directive project planning and risk management) and selectionism (host organization putting several projects to work and then selecting the most promising results).

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Abstract

In recent years, the world’s population living in cities has been rapidly increasing. Cities are transforming their infrastructure in a smarter and more efficient way so that sustainable development forms part of their long-term strategy. However, this transformation does not always result in expected benefits due to a variety of factors such as an absence of social acceptance, a lack of holistic design and the development of unilateral interventions. An analysis of the scientific literature related to the evaluation of the impact of smart city actions revealed a gap in the holistic methods for their assessment. To this end, an accurate evaluation of implemented smart solutions focusing on the energy domain is necessary in order to assess the expected and realized impact of each solution. This paper proposes a seven-step methodology for assessing the impact of smart city interventions and presents a use case for the city of Espoo. A number of major findings were the outcome of our research and development work, such as the need for a thorough analysis of the long-term vision of the city, a combined top-down and bottom-up approach and the ongoing cooperation between all stakeholders involved in urban planning and transformation, in which necessary Key Performance Indicators (KPIs) are defined.

1. Introduction

1.1. The Necessity of Impact Assessment
According to the United Nations [1] 68% of the world’s population is projected to live in urban areas by the year 2050; cities, therefore, are anticipated to face new challenges in sustainably integrating further populace, such as a lack of appropriate infrastructure for sustainable energy and automated systems, applications and commercial arrangements, digital security, network connectivity and data capacity [2]. Cities will be required to transform their infrastructures in a smarter, more efficient and resilient way so that sustainable development forms part of their long-term strategy and a better quality of life is assured to their citizens. The concept of the smart city is multidimensional [3], with the aim of increasing urban sustainability and quality of life while pursuing economic development among its citizens [4]. Additionally, sustainability has gained popularity among scholars, environmental policy makers and government agencies [5]. However, a smart city is not just about creating technically viable urban areas and stimulating economic growth; it requires a multifaceted and multidimensional approach that promotes a structural transformation in the urban ecosystem, directing the development of cities towards their “smartness” in areas such as economy, governance, social, environment, mobility and ICT [6].

Abstract

1. Introduction

2. Methodology

3. Characteristics of a Happiness Driven Smart City

4. Key factors contributing to characteristic performance in a Happiness Driven Smart City system

5. Mechanism for developing Happiness Driven Smart City

6. Strategic measures and assessment process for the application of HDSC mechanism

7. A Greater Manchester case study

8. Discussion and conclusion

CRediT authorship contribution statement

Acknowledgment

Appendix

References

Abstract

     Smart City conception has become a global trend with the advancement of Information and Communications Technologies (ICTs). Many cities have proposed Smart City development strategies to capture the opportunities brought by ICTs. However, little attention has been given to investigate whether and how Smart City acts upon human happiness. To fill this gap, this study introduces a Happiness Driven Smart City (HDSC) mechanism to better guide the development of Smart City towards a more human-centered direction. HDSC mechanism includes a three-layer interrelated structure and is underpinned by a set of Strategic Measures. The assessment criteria have also been established for applying HDSC mechanism to investigate the performance of Smart City initiatives. The HDSC mechanism established in this study is a first attempt to assess the performance of Smart City development from the lens of human happiness. By applying HDSC mechanism in investigating Manchester’s Smart City initiatives, the mechanism is proven effective to help decision makers understand the status quo of Smart City development in their urban context, based upon which the strength and weakness in the process of HDSC development can be drawn out. Consequently, Smart City blueprint can be better achieved towards a happiness-driven direction via dynamic assessment and adjustment.

Introduction

     Smart City is expected to provide better solutions for the intensified socioeconomic and environmental challenges associated with the unprecedented urbanization by embracing advanced Information and Communication Technologies (ICTs), where challenge like climate change, energy crisis, or social inequality could all find its way out through the development and application of state-of-the-art technologies (Manville et al., 2014; Michalec et al., 2019; United Nations, D.o.E.a.S.A., 2019; Yigitcanlar et al., 2019). The idealized narrative of Smart City has been widely accepted and turned to global movement at an appreciable speed for economic expansion and societal transformation (Cheng et al., 2020; Deloitte, 2018; Vu et al., 2020). It was reported that more than 1000 cities globally have introduced the Smart City initiatives with Europe, North America, Japan and Korea at the leading position (Deloitte, 2018). By applying Smart City initiatives, some global cities keep their central position in the landscape of innovation and knowledge generation (Yigitcanlar et al., 2016), and others have revitalized their urban economy to foster, attract and retain innovation abilities (Holland, 2015). However, it appears that Smart City’s influence upon human happiness has been paid with only marginal attention amid the practices of Smart City development.

Discussion and conclusion

     This paper argues that human happiness should be embodied as a key element in the process of Smart City development. The study embarks with the research question that whether and how Smart City acts upon human happiness in the trendy development of Smart City globally. By conceptualizing the Happiness Driven Smarty City (HDSC) and capturing the Characteristics and Factors of HDSC, a Happiness Driven Smart City Mechanism has been established, which is underpinned by various applicable and measurable Strategic Measures. To our knowledge, the HDSC Mechanism is a first attempt to assess the performance of Smart City development from the lens of human happiness, which integrates human happiness into the planning, constructing and delivering process of Smart City strategies. The established HDSC Mechanism in this study provide an applicable toolkit to urban governors for better harnessing Smart City blueprint towards a happiness-driven and human-centered direction. The applicability and effectiveness of HDSC mechanism has been validated via the empirical investigation to Greater Manchester’s Smart City initiatives.

Abstract

Introduction

Review of literature

Methodology

Integrated smart city model

Conclusion

Appendix

References

Abstract

     In smart city architecture, information and communication technologies are used to improve living standards and its management by citizens and government. Most researchers have divided this structure into six main components: smart people, the smart government, smart environment, smart transportation, smart economy, and smart life. Due to the connection between smart cities and the challenges resulting from their implementation and especially its integration, there exists no perfect solution for the concept of an integrated smart city so far according to our studies. Some more general concepts such as security, ICT infrastructure, and knowledge are not seen integrative in these structures. Therefore, it seems that new sub-components and general extra-components should be added to the existing models to form an integrated structure in such a way that the executive projects are located in their proper place in this structure and create and guarantee the integration of the smart city. Therefore, the requirements engineering of the smart city can also be explained more precisely. This study presents a model of an integrated graph in such a way that besides maintaining and improving the model of the smart city and existing models, it will fully cover the integration and requirements engineering and methodologies of the smart city in the future.

Introduction

     The process of urbanization is currently taking place at a rapid pace on a global scale. Every year, millions of people migrate from rural to urban areas to gain comfort and economic opportunities. According to the United Nations (UN), 6. 5 billion people will live in cities by 2050, and more than 60% of the world’s population will be concentrated in cities (Schuurman and Baccarne 2012). On the global scale, International Data Corporation (IDC) estimates that the steady increase in smart cities’ expenses will rise to $ 158 billion by 2022 (Twice as much as $ 80 billion in 2018) (Visan and Ciurea 2020). Rapid population growth, besides putting considerable pressure on current cities, will pose serious threats to the future, leading to increased demand for services, housing facilities beyond the capacity of cities, as well as irreparable damage to the environment. As a result, cities face many challenges as their resources and infrastructure increase under increasing pressure (Breetzke 2016). Therefore, they always suffer from adverse consequences. Also, the sudden emergence of problems such as the recent Panorama of Covid-19 as well as advances in telecommunications, especially the Internet, along with the development of electronic devices, have changed people’s everyday life and their minds in all aspects of economic and social fields (Das and Zhang 2020).

Conclusion

     In previous research based on the current situation and thematic literature, the concept of smart city was mostly proposed and implemented as an island with six main components in different societies. Also due to the increase in urbanization and the connection of smart cities with the challenges that arise in implementing and integrating the urban model, a suitable solution for the concept of integrated smart city Was not provided to your best knowledge and some essential concepts such as security, ICT infrastructure and knowledge are not seen integrative in these structures. In order to integrate, prevent data redundancy, ease of access, create security at different levels, the present study Provides a flexible, integrated, localizable dynamic model with a new approach that breaks down six core components into several sub components that creates a graph-like model, in which each sub component represents a set of implementable smart projects in different communities.

Abstract

1. Introduction

2. Literature review

3. Empirical framework

4. Empirical findings

5. Conclusion and discussion

Disclosure statement

Notes on contributors

References

Abstract

     The aim of the present study is to reveal the causal effects of Smart City policies on urban innovation. Using the panel data harvested from 103 cities in China, the constructed sample was analysed rigorously based on the combination of the strength of Propensity Score Matching (PSM) and Difference-in-Differences (DID). As suggested by the empirical results, Smart City policies indeed positively and significantly impact urban innovation . Besides, whether policy effects vary with the regional location and city scale is explored; the results reveal that the impact is significantly positive only for the megacities as well as cities in central China.

Introduction

     Since the late 1990s, smart city projects have been rolled out globally. According to Deloitte Touche Tohmatsu’s report (Deloitte, 2018), the constructions of over 1,000 smart cities have been launched worldwide with 500 policy pilot areas in China, which noticeably outclasses Europe’s 90 of the second place. The mentioned projects are capable of not only enhancing the intelligence of specific socio-economic aspects of daily life, but also presenting a considerable number of other benefits, which cover fostering a competitive economy (Giffinger & Haindl, 2010), boosting more feasible governance (Nam & Pardo, 2011), expediting the innovation process (Paskaleva, 2011; Schaffers et al., 2012), advancing social capital (Hodgkinson, 2011), protecting diversity and individuality (Lind, 2012), etc. Nevertheless, some have argued that the potentials or benefits of smart cities have been overestimated; they considered that smart cities may not be as ‘smart’ as their name suggests (Hollands, 2008). Though considerable capitals have been invested in the advancement of smart cities, smart cities have not achieved their original goals (Yigitcanlar & Lee, 2014). Numerous risks also exist in the application of smart city strategies, e.g., the digital divide resulting from unequal use of ICT (Coe et al., 2001), the replication of technology solutions (Townsend et al., 2010), the overlook of city’s requirements and priorities (Caragliu & Del Bo, 2019), the slow progression attributed to budgetary issues and inadequate planning (Shwayri, 2013), etc.

Conclusion and discussion

     The present paper aims to evidence whether Smart City policies make cities more innovative – in the case of Chinese cities. To accurately estimate the policy effect, Propensity Score Matching (PSM) and Difference-in-Differences (DID) are integrated to eliminate some biases that might affect the effectiveness of this study. To be specific, PSM technique is adopted to construct the matched control group that possesses similar observable city characteristics with treatment group. Subsequently, DID approach is employed to estimate the differences of those groups’ treatment effects before and after the policy implementation. Besides, our results comply with several existing studies (Caragliu & Del Bo, 2019; Veeckman & Graaf, 2014), revealing that Smart City policies indeed stimulate urban innovation. Though innovative is not a major objective of implementation of Smart City policies, our findings have demonstrated a positive spill-over effect of the policies on urban innovation. Compared with similar non-pilot cities, pilot cities of smart city policy are granted more patents.

Abstract

Introduction

What are smart cities?

Methodology

Analysis of smart city initiatives

Comparing PSI in HK and SG

Discussion

Conclusion

Acknowledgements

References

Abstract

     Since the 2000s, Hong Kong (HK) and Singapore (SG) have been working to reinvent themselves as smart cities. Despite their similarities, SG has consistently ranked ahead of HK on several smart city indices. To explain this gap, the smart city initiatives of both cities were categorized using a six-factor typology of public sector innovation. Further analysis indicated that SG was ahead of HK because its government has been more aggressive in funding and fostering innovation. This paper suggests that a government’s financial support for public sector innovation, as well as its ability to redirect resources within the public sector and get citizens involved, will catalyse transformational efforts into a smart city.

Introduction

     The cities of Hong Kong (HK) and Singapore (SG) are often compared as a result of their similarities—a colonial history (Kratoska, 2006; Onimaru, 2019; Tan, 1997), values and culture (Chia et al., 2007), relatively high levels of human development (Delang & Yu, 2015; Ramesh & Holliday, 2001), strong economic competitiveness (Li et al., 2013; Schwab, 2018), as well as being two of the four ‘Asian tigers’ and important regional transport and financial hubs (Huat et al., 2004; Jarvis, 2011; Woo, 2015). The IMD World Competitiveness Center ranked HK at third place in 2018, second in 2019, and fifth in 2020; SG was ranked second in 2018, and first in both 2019 and 2020. A separate ranking by the Global Competitiveness Report ranked HK at fourth place in 2018, third in 2019; while SG ranked second in 2018 and first in 2019 (at the time of writing, rankings were not available for 2020). Overall, the two cities are very close rivals in global rankings of governance and development, and they are in competition for foreign investment and global talent.

     Although SG and HK have been relatively close rivals in various areas, SG has consistently ranked ahead of HK on indices related to smart cities. These include the IMD Smart City Index 2020 which ranked SG first and HK 32nd, the Global Innovation Index 2020 where SG ranked eighth and HK ranked 11th (Cornell University, INSEAD, and WIPO, 2020), and the IESE Cities in Motion Index 2019 which ranked SG ranked seventh and HK 11th (Berrone et al., 2019). The disparity is curious, especially since the governments of both cities had been proactively seeding and steering various initiatives to transform them into smart cities.

Conclusion

     Both HK and SG need to thrive economically, while ensuring sustainable development and building up capital for the future. While the two cities are unique, one would expect more similarities in their global standing as smart cities. The comparison of the two cities in this paper sheds light on how PSI and governance has affected the development of the cities. Smart city initiatives often require support from both the public and private sectors. Both the design and delivery of public services need to change, so innovation needs to come from within the public sector. Using private sector resources and funding, the SG government has been more effective than HK in creating a smart city. However, it has also been more exposed to criticism when initiatives have failed. The paper shows that the development of smart cities is also accompanied by new challenges, such as the risk of cyber-attacks and citizens’ reluctance to use new technologies. Governments need to be prepared to handle these challenges. Future studies should examine how well the governments of smart cities have adapted and innovated in response to the Covid-19 pandemic.

Introduction

One of the most noteworthy arcs of the 21st century has been the explosive growth seen in the usage and deployment of technology. More specifically, the advancement of information and communications technology (ICT) has been the foundation for many of the innovations seen over this century thus far. The wide-spanning adoption of the Internet for social media, e-commerce, news consumption, and more has redefined much of our everyday lives and industries across the world. Due to the advancements of ICT, there are many exciting opportunities for what is yet to come. One longstanding opportunity for the future is the vision of the smart city.

There are countless different ideas and definitions for what exactly qualifies as a smart city. A more general definition, provided by Bakıcı et al. in [1], defines smart cities as being high-tech cities that serve to connect people, information, and city-wide infrastructure and resources using advances in technology to improve sustainability, innovation, and overall quality-of-life. The extent to which how pervasive (or intrusive) technologies are incorporated to accomplish such goals is often a point of contention in the literature [2]. However, the many different visions for what define smart cities all generally involve heavy utilization of technology to improve the maintenance of cities to further improve and/or optimize city-specific operations for different stakeholders (e.g., citizens, the environment).

Realizing the ambitious vision of smart cities requires seamlessly making decisions for a host of different applications and domains with minimal sacrifice with respect to performance and resource costs. Some applications of interest for smart cities include, but are not limited to, smart traffic light control, smart information spread (or advertisement), smart energy distribution, smart waste management, etc. Ideally, data generated in urban environments can be collected in smart cities using CT-powered infrastructure to train and inform models designed for these applications to make realtime decisions. For instance, insistent collection of traffic congestion data from roadside units(RSU) and other sources can be sent to ICT infrastructure to train machine learning models how to make optimal decisions related to traffic lights to reduce congestion. This approach is becoming more within reach given the advances in vehicular ad hoc networks (VANET) [3, 4, 5] and other Internetof-Vehicles (IoV) systems [6, 7, 8].

Making smart decisions in a timely fashion will require a powerful pipeline ready to support intense amounts of data collection, analytics, and adaptive decision-making. For instance, video feeds at road intersections — to empower models for smart traffic light control — are large in size (in terms of bytes) and will require automated processes to make meaningful decisions in real-time. However, video cameras that provide such video feeds will be unable, on their own, to perform such analytics and decision-making. Such tasks would require more computational resources than would be available at video cameras and other similar sensors that can be found in urban environments. Thus, for such applications, smart cities will need to be able to provide heavy computational power on-demand, even for devices that do not have such resources locally. Applications (e.g., big data analytics, video classification) all require large amounts of compute resources in order to adequately process. Because Internet-of-Things (IoT) devices like smartphones are often ill-equipped to meet the needs of such processes [9, 10], a standard approach for providing these services on these devices is to rely on remote resources.