Design of services or designing for service? The application of design methodology in public service settings

Curated on Posted on by Stefaan Verhulst

Article by Kirsty Strokosch and Stephen P. Osborne: “The design of public services has traditionally been conducted by managers who aim to improve efficiency. In recent years though, human-centred design has been used increasingly to improve the experience of public service users, citizens and public service staff (Trischler and Scott, 2016). Design also encourages collaboration and creativity to understand problems and develop solutions (Wetter-Edman et al., 2014). This can include user research to understand current experiences and/or testing prototypes through quick repeated cycles of re-design.

To date, there has been little primary research on the application of design approaches in public service settings (Hermus, et al., 2020). Our article just published in Policy & Politics, Design of services or designing for service? The application of design methodology in public service settings, seeks to fill that gap.

It considers two cases in the United Kingdom: Social Security services in Scotland and Local Authority services in England. The research explores the application of design, asking three important questions: what is being designed, how is service design being practised and what are its implications?…

The research also offers three important implications for practice:

  1. Service design should be applied pragmatically. A one-size-fits-all design approach is not appropriate for public services. We need to think about the type of service, who is using it and its aims.
  2. Services should be understood in their entirety with a holistic view of both the front-end components and the back-end operational processes.  However, the complex social and institutional factors that shape service experience also need to be considered.
  3. Design needs flexibility to enable creativity. Part of this involves reducing bureaucratic work practices and a commitment from senior managers to make available the time, resources and space for creativity, testing and iteration. There needs to be space to learn and improve…(More)“.

Can Mobility of Care Be Identified From Transit Fare Card Data? A Case Study In Washington D.C.

Curated on Posted on by Stefaan Verhulst

Paper by Daniela Shuman, et al: “Studies in the literature have found significant differences in travel behavior by gender on public transit that are largely attributable to household and care responsibilities falling disproportionately on women. While the majority of studies have relied on survey and qualitative data to assess “mobility of care”, we propose a novel data-driven workflow utilizing transit fare card transactions, name-based gender inference, and geospatial analysis to identify mobility of care trip making. We find that the share of women travelers trip-chaining in the direct vicinity of mobility of care places of interest is 10% – 15% higher than men….(More)”.

Civic Participation in the Datafied Society

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue by Arne Hintz, Lina Dencik, Joanna Redden, Emiliano Trere: “As data collection and analysis are increasingly deployed for a variety of both commercial and public services, state–citizen relations are becoming infused by algorithmic and automated decision making. Yet as citizens, we have few possibilities to understand and intervene into the roll-out of data systems, and to participate in policy and decision making about uses of data and artificial intelligence (AI). This introductory article unpacks the nexus of datafication and participation, reviews some of the editors’ own research on this subject, and provides an overview of the contents of the Special Section “Civic Participation in the Datafied Society.”… (More)”.

How to design an AI ethics board

Curated on Posted on by Stefaan Verhulst


Paper by Jonas Schuett, Anka Reuel, Alexis Carlier: “Organizations that develop and deploy artificial intelligence (AI) systems need to take measures to reduce the associated risks. In this paper, we examine how AI companies could design an AI ethics board in a way that reduces risks from AI. We identify five high-level design choices: (1) What responsibilities should the board have? (2) What should its legal structure be? (3) Who should sit on the board? (4) How should it make decisions and should its decisions be binding? (5) What resources does it need? We break down each of these questions into more specific sub-questions, list options, and discuss how different design choices affect the board’s ability to reduce risks from AI. Several failures have shown that designing an AI ethics board can be challenging. This paper provides a toolbox that can help AI companies to overcome these challenges…(More)”.

City data ecosystems between theory and practice: A qualitative exploratory study in seven European cities

Curated on Posted on by Stefaan Verhulst

Paper by Giovanni Liva, Marina Micheli, Sven Schade, Alexander Kotsev, Matteo Gori and Cristiano Codagnone: “The exponential growth of data collection opens possibilities for analyzing data to address political and societal challenges. Still, European cities are not utilizing the potential of data generated by its citizens, industries, academia, and public authorities for their public service mission. The reasons are complex and relate to an intertwined set of organizational, technological, and legal barriers, although good practices exist that could be scaled, sustained, and further developed. The article contributes to research on data-driven innovation in the public sector comparing high-level expectations on data ecosystems with actual practices of data sharing and innovation at the local and regional level. Our approach consists in triangulating the analysis of in-depth interviews with representatives of the local administrations with documents obtained from the cities. The interviews investigated the experiences and perspectives of local administrations regarding establishing a local or regional data ecosystem. The article examines experiences and obstacles to data sharing within seven administrations investigating what currently prevents the establishment of data ecosystems. The findings are summarized along three main lines. First, the limited involvement of private sector organizations as actors in local data ecosystems through emerging forms of data sharing. Second, the concern over technological aspects and the lack of attention on social or organizational issues. Third, a conceptual decision to apply a centralized and not a federated digital infrastructure…(More)”.

Towards High-Value Datasets determination for data-driven development: a systematic literature review

Curated on Posted on by Stefaan Verhulst

Paper by Anastasija Nikiforova, Nina Rizun, Magdalena Ciesielska, Charalampos Alexopoulos, and Andrea Miletič: “The OGD is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles, but also be of value, i.e., of interest for reuse by the end-user. This refers to the notion of ‘high-value dataset’ (HVD), recognized by the European Data Portal as a key trend in the OGD area in 2022. While there is a progress in this direction, e.g., the Open Data Directive, incl. identifying 6 key categories, a list of HVDs and arrangements for their publication and re-use, they can be seen as ‘core’ / ‘base’ datasets aimed at increasing interoperability of public sector data with a high priority, contributing to the development of a more mature OGD initiative. Depending on the specifics of a region and country – geographical location, social, environmental, economic issues, cultural characteristics, (under)developed sectors and market specificities, more datasets can be recognized as of high value for a particular country. However, there is no standardized approach to assist chief data officers in this. In this paper, we present a systematic review of existing literature on the HVD determination, which is expected to form an initial knowledge base for this process, incl. used approaches and indicators to determine them, data, stakeholders…(More)”.

Norm-Nudging: Harnessing Social Expectations for Behavior Change

Curated on Posted on by Stefaan Verhulst

Paper by Cristina Bicchieri and Eugen Dimant: “Nudging is a popular approach to achieving positive behavior change. It involves subtle changes to the decision-making environment designed to steer individuals towards making better choices. Norm-nudging is a type of behavioral nudge that aims to change social expectations about what others do or approve/disapprove of in a similar situation. Norm-nudging can be effective when behaviors are interdependent, meaning that their preferences are influenced by others’ actions and/or beliefs. However, norm-nudging is not a one-size-fits-all solution and there are also risks associated with it, such as the potential to be perceived as manipulative or coercive, or the difficulty to effectively implement interventions. To maximize the benefits and minimize the risks of using social information to achieve behavior change, policymakers should carefully choose what behavior they want to promote, consider the target audience for the social information, and be aware of the potential for unintended consequences…(More)”.

Data Privacy and Algorithmic Inequality

Curated on Posted on by Stefaan Verhulst

Paper by Zhuang Liu, Michael Sockin & Wei Xiong: “This paper develops a foundation for a consumer’s preference for data privacy by linking it to the desire to hide behavioral vulnerabilities. Data sharing with digital platforms enhances the matching efficiency for standard consumption goods, but also exposes individuals with self-control issues to temptation goods. This creates a new form of inequality in the digital era—algorithmic inequality. Although data privacy regulations provide consumers with the option to opt out of data sharing, these regulations cannot fully protect vulnerable consumers because of data-sharing externalities. The coordination problem among consumers may also lead to multiple equilibria with drastically different levels of data sharing by consumers. Our quantitative analysis further illustrates that although data is non-rival and beneficial to social welfare, it can also exacerbate algorithmic inequality…(More)”.

Big data proves mobility is not gender-neutral

Curated on Posted on by Stefaan Verhulst

Blog by Ellin Ivarsson, Aiga Stokenberg and Juan Ignacio Fulponi: “All over the world, there is growing evidence showing that women and men travel differently. While there are many reasons behind this, one key factor is the persistence of traditional gender norms and roles that translate into different household responsibilities, different work schedules, and, ultimately, different mobility needs. Greater overall risk aversion and sensitivity to safety issues also play an important role in how women get around. Yet gender often remains an afterthought in the transport sector, meaning most policies or infrastructure investment plans are not designed to take into account the specific mobility needs of women.

The good news is that big data can help change that. In a recent study, the World Bank Transport team combined several data sources to analyze how women travel around the Buenos Aires Metropolitan Area (AMBA), including mobile phone signal data, congestion data from Waze, public transport smart card data, and data from a survey implemented by the team in early 2022 with over 20,300 car and motorcycle users.

Our research revealed that, on average, women in AMBA travel less often than men, travel shorter distances, and tend to engage in more complex trips with multiple stops and purposes. On average, 65 percent of the trips made by women are shorter than 5 kilometers, compared to 60 percent among men. Also, women’s hourly travel patterns are different, with 10 percent more trips than men during the mid-day off-peak hour, mostly originating in central AMBA. This reflects the larger burden of household responsibilities faced by women – such as picking children up from school – and the fact that women tend to work more irregular hours…(More)” See also Gender gaps in urban mobility.

Judging Nudging: Understanding the Welfare Effects of Nudges Versus Taxes

Curated on Posted on by Stefaan Verhulst

Paper by John A. List, Matthias Rodemeier, Sutanuka Roy & Gregory K. Sun: “While behavioral non-price interventions (“nudges”) have grown from academic curiosity to a bona fide policy tool, their relative economic efficiency remains under-researched. We develop a unified framework to estimate welfare effects of both nudges and taxes. We showcase our approach by creating a database of more than 300 carefully hand-coded point estimates of non-price and price interventions in the markets for cigarettes, influenza vaccinations, and household energy. While nudges are effective in changing behavior in all three markets, they are not necessarily the most efficient policy. We find that nudges are more efficient in the market for cigarettes, while taxes are more efficient in the energy market. For influenza vaccinations, optimal subsidies likely outperform nudges. Importantly, two key factors govern the difference in results across markets: i) an elasticity-weighted standard deviation of the behavioral bias, and ii) the magnitude of the average externality. Nudges dominate taxes whenever i) exceeds ii). Combining nudges and taxes does not always provide quantitatively significant improvements to implementing one policy tool alone…(More)”.