Scaling Up Smart City Logistics Projects: The Case of the Smooth Project
Abstract
:1. Introduction
1.1. Problem Statement
1.2. Research Purpose and Research Question
Which factors influence the scalability potential of the SMOOTh Smart City Logistics pilot project?
1.3. Disposition
1.4. Delimitations
1.5. The SMOOTh Project
2. Literature Review
2.1. Smart City Logistics Definition
- Digitalization and Big Data Analytics: Improved data sharing is fundamental to extract the maximum value from the available big data on transport, contributing to wider data sharing amongst the transport stakeholders, and leads to improved products and services [11]. An Intelligent Transport System (ITS), which represents an advanced system of the combination of technology, infrastructure, service and planning, and operation methods, supports real-time data collection related to track and trace [12,13]. The tolls which are deployed for ITS includes sensors, actuators, controllers, GPS devices, mobile phones, cloud computing and IoT [13]. These tools enable ITS to offer secure and economic on-demand services. The resulting increase in vehicle productivity has positive effects in terms of CO2 emissions [14].
- Collaboration across stakeholders: A change in paradigm, which is ongoing in the transportation sectors, also has an effect and enhances the importance of a collaboration of multiple and diverse stakeholders [5]. In this case, the aim for a successful collaboration is increasing the transparency and communication between players through the process of digitalization [11]. The managers’ and workers’ culture and training are key ingredients for success in a smart city project, which go beyond the simple infrastructure and assets. The main stakeholders and their relationships are detailed in the paragraph 2.1.2.
- Flexible deliveries through multimodal transport: Multimodal transport indicates the transportation of goods, performed under the terms of a single contract, which involves more than one mode of transport. Multimodal logistics allows more efficient and sustainable delivery and has therefore become an important logistical component worldwide. Its use is encouraged by government directives and shaped by the ITS [15]. In addition, the flexibility which characterizes a dynamic decision-making approach is fundamental to control real-time changes.
- Urban Consolidation Center: Urban Consolidation Centers (UCCs) or Urban Freight Centers are defined by Browne et al. (2005) as logistic facilities located in relative proximity to the geographic area that they serve. UCCs arose as a potential solution for reducing the pollution from last-mile freight transportation [16]. These centers collect packages from many logistics companies, consolidate them, and then proceed with delivery to the city customer [1]. Consequently, UCCs serves as a terminal for multimodal transport, as previously introduced. UCCs aim to counteract the disadvantages deriving from the lack of a holistic system which causes prolonged travel routes and a consequent cost increase, as well as negative impacts on the environment. The deriving freight flow integration allows citizens to access goods, while supporting cities’ sustainable developments [17]. Nevertheless, UCCs still represent a concept for multiple urban stakeholders [18,19]. In this regard, several authors identified the KSFs for a UCC-based scheme corresponding to: (1) concertation and political support, (2) supporting regulations, (3) governance and financing viability, (4) strategic location and (5) the organization of the last-mile transport.
- Specialized fleets: Electrified fleets and pedal-powered vehicles represent an additional key component able to decrease the carbon footprint of a society. These vehicles are particularly suitable for small parcels, as opposed to big parcels which may need a higher volume and traction power.
2.2. Stakeholders Involved
2.3. Scale Up of Smart City Project
2.3.1. Typologies of Scaling-Up
2.3.2. Overview of the Scaling-Up Typologies
2.3.3. Scalability: Roll-Out
2.3.4. Scalability: Expansion
2.3.5. Replication
2.4. Conditions for Scaling-Up
2.4.1. Technical
2.4.2. Economic
2.4.3. Organizational
2.4.4. Legislative and Regulatory
3. Methodology
3.1. Research Strategy
3.2. Research Design
3.3. Research Method
3.3.1. Secondary Data Collection
3.3.2. Primary Data Collection
3.3.3. Data Analysis
3.4. Research Quality
3.4.1. Credibility
3.4.2. Transferability
3.4.3. Dependability
3.4.4. Confirmability
4. Empirical Findings
4.1. Key Scalability Factors
4.2. Economic-Related Factors
4.2.1. Vision of Scale
“We need a successful small-scale demonstration to show that it works: the systems’ tasks must be met (transports delivered on time and without extra damage), traffic must be reduced, a better way to the receiver must be provided, and transportation companies must be able to save money.”Sonke Behrends
4.2.2. Economically Feasible Business Model
4.3. Technical Factors
4.3.1. IT System Interoperability
“It is important to make the collaboration among different players easy and this can be achieved by exploiting an information system.”Sönke Behrends
4.3.2. Existing Infrastructure
4.4. Stakeholder-Related Factors
4.4.1. Consortium Composition
“SMOOTh project has an opportunity related to the involvement of some different actors which is definitely a plus.”Michael Browne
4.4.2. Consensus
“Initially, the team may be associated with a group of blindfolded people who are touching the same elephants while trying to describe it aloud. Someone is touching a foot, and someone is touching an ear, etc.… It is the same elephant, but the challenges come from the fact that no one sees the whole picture.”Ronja Roupé
4.4.3. Co-Creation
“Trust requires understanding of the fact that we are all doing it together for the same reason and for a common goal.”Ronja Roupé
4.5. Legislative and Regulatory Factors
4.5.1. Supporting Regulation
4.5.2. Political Will
“Political will is a critical factor to make upscaling possible and to develop vehicle free zone.”Magnus Jäderberg
5. Discussion
5.1. Key Scalability Factors
5.2. Business-Model-Related Factors
5.2.1. Vision of Scale
5.2.2. Economically Feasible Business Model
5.3. Technical Factors
5.3.1. IT System Interoperability
5.3.2. Existing Infrastructure
5.4. Stakeholders–Related Factors
5.4.1. Consortium Composition
5.4.2. Co-Creation
5.4.3. Consensus
5.5. Legislative Factors
5.5.1. Supporting Regulation
5.5.2. Political Will
6. Conclusions
6.1. Answering the Research Question
6.2. Future Research
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A. Interview Guide
Appendix A.1. Introduction
- Introducing the authors and the research purpose.
- Asking permission for recording and citing the interviewee name in the study.
Appendix A.2. Interview Questions
Stakeholder Overview | Could You Describe Your Work within the Organization? |
Which Is the Motivation That Led Your Organization to Join the SMOOTh Project? | |
Upscaling | Can you describe the SMOOTh project future vision and desired scale? |
Does your company have the interest toward project upscaling and the capacity needed? | |
Which do you think would be the technical, organizational, economic and regulatory critical success factors for project scale up in the inner city? | |
Which are the steps that make up the pathway to scale up? | |
What do you think are the barriers to upscaling? | |
According to you which is the best way to motivate and incentivize the company to stay committed and comply to the main goal of the project over time? | |
What kind of incentives would facilitate data sharing within the system for the stakeholders? | |
How does communication happen within the project? | |
Pilot phase | What is necessary to be tested during the pilot study to assure future scalability? |
What are the main difficulties that emerged during the evolution of the project and how would these lessons learned be relevant to the scale up phase? |
Appendix A.3. Concluding Questions
- Is it okay if I send you the summary of the interview and maybe you validate it?
- Would you be interested in the final report and results?
Appendix B. Coding Table
Contribution to a Better City Environment (Less Traffic and Pollution) | ||
Creation of a system of systems | Vision of Scale | Business Model |
Inspiration for other cities | ||
Reducing by 40% the amount of traffic | ||
Identify proper revenue stream | Sustainable Business Model | |
Define the ideal price for the service | ||
Successful demonstration on pilot project scale | ||
Visualize potentials risks and barriers | ||
Preserve flexibility | ||
Go beyond economical KPI | ||
Sustainability reports | ||
Define the players that should be involved | Consortium Composition | Stakeholder |
Define incentives to involve them | ||
Large logistic companies, real estate companies and administrators | ||
Vision needs to be accepted by various stakeholders | Consensus | |
Different interests among players | ||
Communicate the potential benefits to each stakeholder by elaborating different messages | ||
Maintain consensus over time | ||
Establish a give-and-take process | Co-creation | |
Trust is necessary | ||
Create synergies within the SoS | ||
Properly distribute value created among stakeholders | ||
Make it easy to collaborate | ||
Necessity of data for expansion | IT System Interoperability | Technical |
Define incentives to share data | ||
The system must appear as secure | ||
Different data sources must be accepted | ||
Define the capacity needed | Infrastructure Capacity | |
Evaluate the increase in number of city and suburban hubs | ||
Dealing with publicly owned infrastructure may be challenging | ||
Environmental policies can drive development | Supportive Regulation | |
Fossil-free cities or restriction of truck movements | ||
Vehicle-free zones | ||
Carrot and stick approach | ||
Politicians may be reluctant to approve vehicle-free zone | Political Will | |
Showing data to politicians is necessary | ||
Bureaucracy may make communication more difficult |
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Areas | Scalability Factors | Replicability Factors |
---|---|---|
Technical | Modularity | Standardization |
Technology evolution | Interoperability | |
Interface design | Network configuration | |
Software tools integration | ||
Existing infrastructure | ||
Economic | Economy of scale | Macro-economic factors |
Profitability | Market design | |
Business model | ||
Legislative and regulatory | Regulation | Regulation |
Stakeholder | Consent | Acceptance |
Categories | Factors | Roll-out | Expansion | Replication | Source |
---|---|---|---|---|---|
Technical | Data Interoperability | ☑ | ☑ | May et al. (2015) & Winden and Busse (2017) | |
Modularity | ☑ | ☑ | May et al. (2015) | ||
Existing infrastructure | ☑ | ☑ | May et al. (2015) | ||
Economic | Economies of scale | ☑ | ☑ | ☑ | May et al. (2015) & Winden and Busse (2017) |
Profitability | ☑ | ☑ | ☑ | May et al. (2015) | |
Standards to measure ROI | ☑ | ☑ | ☑ | Winden and Busse (2017) | |
Organizational | Knowledge transfer mechanisms and incentives | ☑ | Winden and Busse (2017) | ||
Effective management of ambidexterity | ☑ | ☑ | ☑ | Winden and Busse (2017) | |
Legislative and regulatory | Enabling regulatory, legal, and policy frameworks | ☑ | ☑ | ☑ | May et al. (2015) & Winden and Busse (2017) |
Acceptance | ☑ | ☑ | ☑ | May et al. (2015) |
Inclusion Criteria | Exclusion Criteria |
---|---|
Papers related to:
| Paper in which:
|
Respondents | Role and Company | Medium | Date | Length |
---|---|---|---|---|
Ronja Roupé | Business Designer, Volvo Group | Zoom | 4/01/2021 | 45 min |
Magnus Zingmark | Project Partner, Nordstan | Zoom | 4/01/2021 | 41 min |
Johan Erlandsson | Project Partner, Velove | Zoom | 4/13/2021 | 46 min |
Sönke Behrends | Researchers, SSPA | Zoom | 4/15/2021 | 43 min |
Michael Browne | Reference Group Member | Zoom | 4/27/2021 | 45 min |
Magnus Jäderberg | Project Partner, Trafikkontoret | Zoom | 5/04/2021 | 55 min |
Christoffer Widegren | Logistic Consultant, CW Logistic | Zoom | 5/11/2021 | 30 min |
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Sista, E.; De Giovanni, P. Scaling Up Smart City Logistics Projects: The Case of the Smooth Project. Smart Cities 2021, 4, 1337-1365. https://doi.org/10.3390/smartcities4040071
Sista E, De Giovanni P. Scaling Up Smart City Logistics Projects: The Case of the Smooth Project. Smart Cities. 2021; 4(4):1337-1365. https://doi.org/10.3390/smartcities4040071
Chicago/Turabian StyleSista, Eleonora, and Pietro De Giovanni. 2021. "Scaling Up Smart City Logistics Projects: The Case of the Smooth Project" Smart Cities 4, no. 4: 1337-1365. https://doi.org/10.3390/smartcities4040071
APA StyleSista, E., & De Giovanni, P. (2021). Scaling Up Smart City Logistics Projects: The Case of the Smooth Project. Smart Cities, 4(4), 1337-1365. https://doi.org/10.3390/smartcities4040071