J.S.C. van den Hoven
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This project investigates how to design a task-level AI adoption decision-support framework that helps UX researchers at Bynder adopt AI responsibly. It responds to a context in which AI adoption is organic and practitioner-led and aims at facilitating the development of standardized governance on AI adoption. The research phase combined a rapid literature scan that identified candidate AI adoption decision constructs, exploratory interviews that surfaced current practice inductively, and construct validation sessions that tested those constructs against UX researchers' own reasoning to confirm or reject those candidate constructs.
These insights were translated into three main interconnecting outcomes: 1. A conceptual reframing of the AI adoption decision from a binary AI use feasibility question into two distinct decisions: whether AI use is feasible, and how human verification of AI output is structured for a given task. 2. A three-layer decision framework operationalizes this through a gating layer, an AI output verification layer that maps task type to suitable verification approaches, and an intensified verification layer that surfaces risk conditions. 3. A prototyped tool, which is grounded in decision support system principles, that translate the framework logic into a tangible tool while preserving researcher judgement rather than automating it.
A formative evaluation engaged UX researchers in think-aloud walkthrough sessions against clarity, usability, and conceptual completeness. Participants found the tool usable, understandable, and coherent and its surfaced factors aligned with their own practice. They also highlighted refinements that were then incorporated into the refined prototype. ...
These insights were translated into three main interconnecting outcomes: 1. A conceptual reframing of the AI adoption decision from a binary AI use feasibility question into two distinct decisions: whether AI use is feasible, and how human verification of AI output is structured for a given task. 2. A three-layer decision framework operationalizes this through a gating layer, an AI output verification layer that maps task type to suitable verification approaches, and an intensified verification layer that surfaces risk conditions. 3. A prototyped tool, which is grounded in decision support system principles, that translate the framework logic into a tangible tool while preserving researcher judgement rather than automating it.
A formative evaluation engaged UX researchers in think-aloud walkthrough sessions against clarity, usability, and conceptual completeness. Participants found the tool usable, understandable, and coherent and its surfaced factors aligned with their own practice. They also highlighted refinements that were then incorporated into the refined prototype. ...
This project investigates how to design a task-level AI adoption decision-support framework that helps UX researchers at Bynder adopt AI responsibly. It responds to a context in which AI adoption is organic and practitioner-led and aims at facilitating the development of standardized governance on AI adoption. The research phase combined a rapid literature scan that identified candidate AI adoption decision constructs, exploratory interviews that surfaced current practice inductively, and construct validation sessions that tested those constructs against UX researchers' own reasoning to confirm or reject those candidate constructs.
These insights were translated into three main interconnecting outcomes: 1. A conceptual reframing of the AI adoption decision from a binary AI use feasibility question into two distinct decisions: whether AI use is feasible, and how human verification of AI output is structured for a given task. 2. A three-layer decision framework operationalizes this through a gating layer, an AI output verification layer that maps task type to suitable verification approaches, and an intensified verification layer that surfaces risk conditions. 3. A prototyped tool, which is grounded in decision support system principles, that translate the framework logic into a tangible tool while preserving researcher judgement rather than automating it.
A formative evaluation engaged UX researchers in think-aloud walkthrough sessions against clarity, usability, and conceptual completeness. Participants found the tool usable, understandable, and coherent and its surfaced factors aligned with their own practice. They also highlighted refinements that were then incorporated into the refined prototype.
These insights were translated into three main interconnecting outcomes: 1. A conceptual reframing of the AI adoption decision from a binary AI use feasibility question into two distinct decisions: whether AI use is feasible, and how human verification of AI output is structured for a given task. 2. A three-layer decision framework operationalizes this through a gating layer, an AI output verification layer that maps task type to suitable verification approaches, and an intensified verification layer that surfaces risk conditions. 3. A prototyped tool, which is grounded in decision support system principles, that translate the framework logic into a tangible tool while preserving researcher judgement rather than automating it.
A formative evaluation engaged UX researchers in think-aloud walkthrough sessions against clarity, usability, and conceptual completeness. Participants found the tool usable, understandable, and coherent and its surfaced factors aligned with their own practice. They also highlighted refinements that were then incorporated into the refined prototype.
Designing certainty in peer-to-peer sharing
Solving the value-effort imbalance to improve retention on Peerby
The sharing economy offers an alternative to traditional ownership, but most peer-to-peer platforms struggle with the same problem: users try them once and do not come back. Peerby, a Dutch platform for borrowing and renting items locally, is a clear example. Despite sufficient supply on the lender side, the platform keeps losing borrowers after their first experience. This thesis, conducted in collaboration with Peerby, investigates why that happens and proposes a design intervention.
This project follows the double diamond method (Design Council, 2019). The research phase examines the retention problem through four complementary lenses: a 5C analysis, a literature review on behavioural drivers in the sharing economy, semi-structured interviews with eight borrowers, and an online survey (n=82). Together, these lenses converge on a single finding: the primary barrier to retention is not physical effort, sustainability indifference, or social awkwardness. It is mental effort. The uncertainty of not knowing whether an item is available, whether someone will respond, and how to coordinate a pickup creates a cost that outweighs the benefit of cheap access. This dynamic is framed as the value-effort imbalance.
A co-creation session and a strategic alignment meeting with Peerby's CEO confirmed the design direction: operational predictability. This meant moving away from Peerby's original neighbourly chat model towards a more structured system, which is a significant shift for a platform built on informal community exchange. The goal is to make borrowing feel as reliable as buying from a webshop, without losing the human character of peer-to-peer exchange entirely. Three lender interviews during the design phase validated concept feasibility, as any change to the booking flow inevitably affects both sides.
The resulting concept, Peerby Direct, replaces the current chat-based coordination model with a structured booking flow. Borrowers select time slots, the system contacts lenders with a countdown timer, and if no one responds in time, the request automatically moves to a backup lender. A flexibility bar shows borrowers how their input affects their chances of a match. Lenders participate on their own terms through optional response commitments, and faster responders are rewarded with higher visibility through a Perks system. A secondary concept, Peerby Pouch, addresses the handover moment through a lockable bag that enables fully asynchronous exchange.
Peerby Direct was validated through prototype walkthroughs with nine participants and an online survey (n=68). 76.5% of survey respondents preferred the new system over the current chat-based model, and 70.1% indicated they would be more likely to return to a sharing platform that works this way. Backup willingness reached 88.2%. The walkthroughs confirmed that all participants could complete the booking flow independently, though several mechanisms require further refinement to become fully self-explanatory.
The thesis concludes with a phased implementation roadmap. Peerby Direct forms the foundation, followed by the Peerby Pouch for asynchronous handover, a centralised Rentmeester Hub, and a delivery option. Together, these form a four-horizon strategy for reducing coordination effort across the entire borrowing experience.
...
This project follows the double diamond method (Design Council, 2019). The research phase examines the retention problem through four complementary lenses: a 5C analysis, a literature review on behavioural drivers in the sharing economy, semi-structured interviews with eight borrowers, and an online survey (n=82). Together, these lenses converge on a single finding: the primary barrier to retention is not physical effort, sustainability indifference, or social awkwardness. It is mental effort. The uncertainty of not knowing whether an item is available, whether someone will respond, and how to coordinate a pickup creates a cost that outweighs the benefit of cheap access. This dynamic is framed as the value-effort imbalance.
A co-creation session and a strategic alignment meeting with Peerby's CEO confirmed the design direction: operational predictability. This meant moving away from Peerby's original neighbourly chat model towards a more structured system, which is a significant shift for a platform built on informal community exchange. The goal is to make borrowing feel as reliable as buying from a webshop, without losing the human character of peer-to-peer exchange entirely. Three lender interviews during the design phase validated concept feasibility, as any change to the booking flow inevitably affects both sides.
The resulting concept, Peerby Direct, replaces the current chat-based coordination model with a structured booking flow. Borrowers select time slots, the system contacts lenders with a countdown timer, and if no one responds in time, the request automatically moves to a backup lender. A flexibility bar shows borrowers how their input affects their chances of a match. Lenders participate on their own terms through optional response commitments, and faster responders are rewarded with higher visibility through a Perks system. A secondary concept, Peerby Pouch, addresses the handover moment through a lockable bag that enables fully asynchronous exchange.
Peerby Direct was validated through prototype walkthroughs with nine participants and an online survey (n=68). 76.5% of survey respondents preferred the new system over the current chat-based model, and 70.1% indicated they would be more likely to return to a sharing platform that works this way. Backup willingness reached 88.2%. The walkthroughs confirmed that all participants could complete the booking flow independently, though several mechanisms require further refinement to become fully self-explanatory.
The thesis concludes with a phased implementation roadmap. Peerby Direct forms the foundation, followed by the Peerby Pouch for asynchronous handover, a centralised Rentmeester Hub, and a delivery option. Together, these form a four-horizon strategy for reducing coordination effort across the entire borrowing experience.
...
The sharing economy offers an alternative to traditional ownership, but most peer-to-peer platforms struggle with the same problem: users try them once and do not come back. Peerby, a Dutch platform for borrowing and renting items locally, is a clear example. Despite sufficient supply on the lender side, the platform keeps losing borrowers after their first experience. This thesis, conducted in collaboration with Peerby, investigates why that happens and proposes a design intervention.
This project follows the double diamond method (Design Council, 2019). The research phase examines the retention problem through four complementary lenses: a 5C analysis, a literature review on behavioural drivers in the sharing economy, semi-structured interviews with eight borrowers, and an online survey (n=82). Together, these lenses converge on a single finding: the primary barrier to retention is not physical effort, sustainability indifference, or social awkwardness. It is mental effort. The uncertainty of not knowing whether an item is available, whether someone will respond, and how to coordinate a pickup creates a cost that outweighs the benefit of cheap access. This dynamic is framed as the value-effort imbalance.
A co-creation session and a strategic alignment meeting with Peerby's CEO confirmed the design direction: operational predictability. This meant moving away from Peerby's original neighbourly chat model towards a more structured system, which is a significant shift for a platform built on informal community exchange. The goal is to make borrowing feel as reliable as buying from a webshop, without losing the human character of peer-to-peer exchange entirely. Three lender interviews during the design phase validated concept feasibility, as any change to the booking flow inevitably affects both sides.
The resulting concept, Peerby Direct, replaces the current chat-based coordination model with a structured booking flow. Borrowers select time slots, the system contacts lenders with a countdown timer, and if no one responds in time, the request automatically moves to a backup lender. A flexibility bar shows borrowers how their input affects their chances of a match. Lenders participate on their own terms through optional response commitments, and faster responders are rewarded with higher visibility through a Perks system. A secondary concept, Peerby Pouch, addresses the handover moment through a lockable bag that enables fully asynchronous exchange.
Peerby Direct was validated through prototype walkthroughs with nine participants and an online survey (n=68). 76.5% of survey respondents preferred the new system over the current chat-based model, and 70.1% indicated they would be more likely to return to a sharing platform that works this way. Backup willingness reached 88.2%. The walkthroughs confirmed that all participants could complete the booking flow independently, though several mechanisms require further refinement to become fully self-explanatory.
The thesis concludes with a phased implementation roadmap. Peerby Direct forms the foundation, followed by the Peerby Pouch for asynchronous handover, a centralised Rentmeester Hub, and a delivery option. Together, these form a four-horizon strategy for reducing coordination effort across the entire borrowing experience.
This project follows the double diamond method (Design Council, 2019). The research phase examines the retention problem through four complementary lenses: a 5C analysis, a literature review on behavioural drivers in the sharing economy, semi-structured interviews with eight borrowers, and an online survey (n=82). Together, these lenses converge on a single finding: the primary barrier to retention is not physical effort, sustainability indifference, or social awkwardness. It is mental effort. The uncertainty of not knowing whether an item is available, whether someone will respond, and how to coordinate a pickup creates a cost that outweighs the benefit of cheap access. This dynamic is framed as the value-effort imbalance.
A co-creation session and a strategic alignment meeting with Peerby's CEO confirmed the design direction: operational predictability. This meant moving away from Peerby's original neighbourly chat model towards a more structured system, which is a significant shift for a platform built on informal community exchange. The goal is to make borrowing feel as reliable as buying from a webshop, without losing the human character of peer-to-peer exchange entirely. Three lender interviews during the design phase validated concept feasibility, as any change to the booking flow inevitably affects both sides.
The resulting concept, Peerby Direct, replaces the current chat-based coordination model with a structured booking flow. Borrowers select time slots, the system contacts lenders with a countdown timer, and if no one responds in time, the request automatically moves to a backup lender. A flexibility bar shows borrowers how their input affects their chances of a match. Lenders participate on their own terms through optional response commitments, and faster responders are rewarded with higher visibility through a Perks system. A secondary concept, Peerby Pouch, addresses the handover moment through a lockable bag that enables fully asynchronous exchange.
Peerby Direct was validated through prototype walkthroughs with nine participants and an online survey (n=68). 76.5% of survey respondents preferred the new system over the current chat-based model, and 70.1% indicated they would be more likely to return to a sharing platform that works this way. Backup willingness reached 88.2%. The walkthroughs confirmed that all participants could complete the booking flow independently, though several mechanisms require further refinement to become fully self-explanatory.
The thesis concludes with a phased implementation roadmap. Peerby Direct forms the foundation, followed by the Peerby Pouch for asynchronous handover, a centralised Rentmeester Hub, and a delivery option. Together, these form a four-horizon strategy for reducing coordination effort across the entire borrowing experience.