Mitigating Urban Heat

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New paper co-authored with Matthias Tuczek, Kenan Degirmenci, Richard T. Watson, TanYigitcanlar, and Michael H. Breitner published in Urban Climate.

Mitigating urban heat with optimal distribution of vegetation and buildings

The impact of climate change on cities poses a growing global threat, which is exacerbated by the urban heat island (UHI) effect. The optimal distribution of vegetation and buildings in urban areas is critical to control the UHI effect and stabilize long-term temperature changes. In this article, we develop an optimization model to maximize revenue while limiting UHI intensity under several restrictions. We run simulations in two urban areas in Brisbane, Australia to test the model's theoretical predictions. Our results show that a revenue increase by AUD 4.32 billion in Brisbane City and by AUD 1.19 billion in Hamilton involves an increase of the maximum temperature difference between the developed and undeveloped sites from 4 to 5° C through an increase of buildings and thus a decrease of porosity and an increase of population density.

To access the paper [LINK].

A Typology of Chatbots in Public Service Delivery – IEEE Software

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New paper co-authored with Tendai Makasi, Alireza Nili, and Mary Tate has been published in IEEE Software.

Chatbots are being used in an increasingly wide range of public services and present several benefits for public service delivery. Our typology contributes to effective chatbot-mediated service delivery in the public service context.

To access the paper, please click [LINK]

Digital Transformation in the Resource and Energy Sectors

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New paper co-authored with Parisa Maroufkhani, Robert K.Perrons, and Mohammad Iranmanesh published in Resources Policy.

The forces of digital transformation have delivered significant benefits like sustainable development and economic growth in a range of early adopter industries such as retail and manufacturing but, despite these potential benefits, the resource and energy sectors have been relative latecomers to digitalization simply because they are frequently slower to absorb new technologies. Here we present the results of a systematic literature review identifying the ways in which digital technologies have been applied in the oil and gas, mining, and energy domains. We applied content and descriptive analysis to evaluate and discuss 151 academic articles selected from the Scopus database. Two particularly interesting trends emerge from the analysis. First, over 75% of the papers were about the energy sector excluding the oil & gas industry, and only a small minority were from the mining or oil & gas sectors. Second, the most frequently discussed objective of digital transformation was the reduction of operational expenses. By surveying the different ways in which these innovations have been used in these industries and identifying trends and patterns in how digital technologies have been applied, the findings of this review deepen our understanding of the current state of digital technologies within the resource and energy sectors and, in so doing, shine a useful amount of light on the contributions that digital transformation has made to businesses in these sectors. This paper also highlights for future scholars, practitioners, and policymakers the six research areas that they should focus on in the future to help the resource and energy sectors accelerate the digital transformation process and improve their ability to deliver value with these innovations.

To access the article, please click [LINK]

International Dialogue: Emerging Technology for Response and Recovery

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In a post-pandemic world, homeland security and border control agencies are being tasked with transforming how they respond and operate in a highly digitalized environment, while ensuring safety and prosperity of citizens and country.

Critical challenges that agencies face include the increasing volume of incidents and emergencies, overly complex trade and immigration processes, and evolving threats to borders and customs. Governments can leverage data, AI, intelligent automation, and other emerging technologies to address these complex challenges—while also freeing up critical human resources for high value missions.

To address these key issues, the IBM Center for The Business of Government hosted an international dialogue in September 2021 attended by CIOs and IT leaders with the Australia Department of Home Affairs, the Singapore Ministry of Home Affairs, and U.S. Department of Homeland Security Customs and Border Protection. These three dynamic leaders engaged in an interactive dialogue, joined by nearly 50 attendees from across the globe.

I draw on this discussion to produce a report providing keen insights about leveraging technologies to improve operations and security across borders. Participants addressed supply chain assurance, opening borders amidst the global fight against COVID-19, and the role of data, AI, and other technologies to support border security. The wide-ranging discussion also touched on addressing the needs of the future, anticipating new threats, and developing response strategies. These strategies—which rest on hybrid, multi-cloud environments—include operational capabilities that can stand up “on demand” to address rapidly shifting threats.

To read the report, please click here.

Interagency Collaboration within the City Emergency Management Network

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New paper co-authored with Bo Fan and Zhoupeng Li published in Disasters.

Interagency collaboration within the city emergency management network: a case study of Super Ministry Reform in China

Emergencies continue to become ever more complex; responding to them, therefore, often is beyond the capabilities and capacities of any single public agency. Hence, collaboration among these actors is necessary to prepare for, respond to, and recover from such events. This seldom occurs in an effective or efficient manner, however. Drawing on resource dependence theory and the concept of social capital, this paper reveals that different types of collaborative relationships exist within the collaborative network. Super Ministry Reform of Emergency Management in China serves as a case in point. By evaluating network efficiency and classifying the collaborative relationships of involved government agencies, four types are identified: resource-redundant; resource-complementary; resource-dependent; and resource-isolated. The different influences of collaborative relationships explain why the reform is not that effective, although it has led to the merger of several core departments in the emergency management network. The findings are a reminder to consider network structure and collaboration types when engaging in institutional design.

To access the article: [LINK]
To access a full-text, read-only version of the article: [LINK]

 

Surfacing and Responding to Paradoxical Tensions in Megascale Projects

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New paper co-authored with Anna Wiewiora published in International Journal of Project Management.

Surfacing and Responding Paradoxes in Megascale Projects

Megaprojects can deliver significant social and economic benefits. However, megaprojects are challenging to manage. They involve multiple stakeholders across various sectors and deliver novel and complex solutions that often require decision makers to deal with persisting tensions to balance conflicting demands. Hence, it is critical to pay attention to paradoxical tensions – contradictory and interrelated elements of the project that persist over time. Employing a systematic literature review, we elicit and catalogue seven categories of paradoxical tensions in megaprojects and outline approaches to manage these tensions discussed in the existing literature. We then propose a future research agenda for studying paradoxical tensions in megaprojects.

To access the article, please click this [LINK]

Artificial Intelligence in the Public Sector: A Maturity Model

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The IBM Center for the Business of Government released my new report today.

Artificial Intelligence in the Public Sector: A Maturity Model

The technology is revolutionizing the way we derive value and insights from data in order to improve our daily lives. In addition, governments gather a treasure trove of pertinent data that can be used to execute important missions and improve services to the citizen. An effective AI program can greatly enhance the ability of the public sector to deliver on that promise.

The challenge has always been to design and implement an AI program that has all the critical elements in place to successfully achieve the goal of improved mission delivery and citizen services. An initial report commissioned by the IBM Center for The Business of Government, Delivering Artificial Intelligence in Government: Challenges and Opportunities, proposed an initial maturity model that gave public agencies a starting point for developing an AI capability. Subsequently, we have had the opportunity to fine tune the model, based on extensive research on how the public sector was deploying AI, documenting successful use cases and highlighting pitfalls and lessons learned.

The revised maturity model was shared with experienced public sector practitioners and feedback from these discussions led to a further revision. The revised model was then shared with a final group of reviewers that included public sector executives (both within and beyond the information systems domain), academics, and consultants.

We hope that this report provides public sector leaders a view into the “art of the possible” by emphasizing how AI programs can accelerate the transformation of government programs to better serve the public and by providing them a framework for establishing a successful AI program. We will continue to explore this topic and will provide further updates as the use of AI in the public sector continues to evolve.

To access the report, please click [Report]

A blog post on the report by Margie Graves (Visiting Fellow, IBM Center for the Business of Government, former Deputy Federal CIO for the Office of Management and Budget) is available here: [Post]

What are the key factors affecting smart city transformation readiness? Evidence from Australian cities

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New paper co-authored with Tan Yigitcanlar, Kenan Degirmenci, and Luke Butler published in Cities.

Transformation into a prosperous smart city has become an aspiration for many local governments across the globe. Despite its growing importance, smart city transformation readiness is still an understudied area of research. In order to bridge this knowledge gap, this paper identifies the key factors affecting smart city transformation readiness in the context of Australian cities. The empirical investigation conducted in this study places Australian local government areas (n = 180) under the smart city microscope to quantitatively evaluate, through a multiple regression analysis, the key factors affecting their urban smartness levels—a proxy used for smart city transformation readiness. The findings disclose that the following factors determine about two-thirds (65%) of the smart city transformation readiness: (a) Close distance to domestic airport; (b) Low remoteness value; (c) High population density; (d) Low unemployment level, and; (e) High labour productivity. The study findings and generated insights inform urban policymakers, managers and planners on their policy, planning and practice decisions concerning smart cities.

To access the paper, please click [LINK]