Combining service design and discrete choice experiments for intervention design: An application to weather index insurance

Abstract

In this paper we provide a detailed description of the methodological steps involved in conducting a Service Design study in combination with Discrete Choice Experiments (DCEs). It complements the conceptual and epistemological argument developed for this methodological combination in Osborne et al. (2021, World Development, in review WD-19535). Service Design for the co-creative development of policy interventions in complex adaptive systems involves an iterative process of moving between the six methodological stages of (1) problem co-definition, (2) actor-centred mapping, (3) experience-based problem diagnosis, (4) rapid prototyping, (5) design and testing and (6) upscaling. We suggest using DCEs as a quantitative method that is contextually adaptable and comparatively fast and cheap to implement, as part of stage (6) design and testing. Whilst both methods can operate independently with their own strengths and limitations, we find their combination to add value to the processes and outcomes of each. We illustrate the general methodological approach with a step-by-step description of its application to Weather Index Insurance in eastern Uganda. Bullet points: • Service Design co-creatively develops well-targeted solutions in complex adaptive systems. • Discrete Choice Experiments quantitatively elicit actors’ preferences over the design of goods or services. • Their combination can bring deeply contextualised, user-centred, operational and experimentally verified ideas for development interventions prior to their implementation.

Devising Capabilities : Service Design for Development Interventions

“…The order of fieldwork activities broadly followed the model outlined in paper 1: problem co-definition, actor-centred mapping, experience-based problem definition, rapid prototyping and design, and testing of prototypes (Lambe, Ran, Jürisoo, et al, 2020). However, there was a degree of iteration of methods as new insights were gathered (for more detail, see Dehmel et al, (2021).…”

“…The initial 12 interviews lasted 1-2 hours and focused on mapping the annual agricultural cycle. Instead of asking leading questions regarding farming practices, we allowed the respondent to guide us through their daily lives and context (Dehmel et al, 2021). We used trigger materials such as picture cards depicting everyday items and tasks for the interviewees to use to support the mapping of activities over a time cycle of a day, a month and a year (Figure 3.2).…”

“…From there, we began to identify a general pattern in the risk response mechanisms of different households. To facilitate the development of our hypotheses, we shifted to conducting shorter, more targeted interviews (n = 23) in 30-minute sessions that, in addition to mapping risk responses, also explored households' agricultural and economic diversity, formal institutional and informal social networks (Dehmel et al, 2021). To better understand the role of these various support mechanisms, we conducted five semi-structured interviews of 1-2 hours with key informants along market value chains who had been identified by the respondents as trusted sources of financial support and advice, such as cotton agents (intermediaries between the community and the cotton development organization) and store owners (Dehmel et al, 2021).…”

“…Similar to the interviews, participants guided researchers through the mapping of daily, monthly, and annual cycles using trigger materials (see Figure 3.1) The FGDs were facilitated by lead researchers who posed questions along the main lines of inquiry. We also conducted additional FGDs (n = 4, of 4-6 participants in sessions of 1-2 hours) with members of village savings and loans associations (VSLA), burial groups (groups that form to save collectively for the cost of funerals), and merry-go-rounds (informal savings groups that make payouts to members on a rotating basis) and non-members to understand their reasons for not participating (Dehmel et al, 2021). with the presentation and validation of research findings, followed by a discussion on the viability of the various prototypes.…”

“…Their primary recommendation was to bundle WII with high-quality agricultural inputs and credit, and to provide this package to local risk-sharing groups, especially village savings and loans associations (VSLAs) (Verschoor, D'Exelle, Balungira, et al, 2016). However, the team of economists was concerned that the recommendation might not properly represent the local context because it was derived from data collected using lab-in-the-field experiments and was therefore based on behavior observed in artificial settings where hypotheses are tested about particular factors in isolation while keeping all other relevant factors, which typically determine behavior in the real world, at bay (Dehmel et al, 2021). In complex social-ecological settings, these other factors interact with the factors being tested, and may strengthen or negate the effect of the factor being studied.…”