LibCal Seats: Library Space Booking

• LibCal Seats is a cloud-based booking module for academic libraries that enables precise, seat-level reservations and real-time check-in validations.
• Automated cancellation policies and extended slot booking have significantly improved occupancy rates from 78% to 87% while reducing no-shows from 22% to 13%.
• Integrated UI/UX enhancements, geolocation-based check-ins, and unified scheduling streamline study space management and ensure equitable access.

LibCal Seats is a cloud-based booking module, delivered as part of the Springshare LibCal platform, designed to enable granular reservation and management of individual study spaces within academic libraries. At the University of Liège (ULiège), it was deployed in September 2020 in response to COVID-19-driven demands for precise occupancy control and physical distancing. Originally a contingency mechanism, LibCal Seats has persisted as an organizational tool for managing peak-period demand, providing a technical and administrative infrastructure to optimize usage, limit seat “hogging,” and ensure equitable access (Renaville et al., 26 Jan 2026).

1. System Capabilities and Architecture

LibCal Seats provides robust, configurable features for study space management:

• Seat-level Reservation: Users reserve a specific seat for a defined date and time slot using an online form (“Book It”), which utilizes an interactive calendar grid and, optionally, a graphical seat map.
• Check-in/Check-out Workflow: Each reservation requires user confirmation of seat occupation via a unique alphanumeric code or QR code. Reservations are automatically canceled if not confirmed within a set grace period (30 minutes by default), ensuring seat availability reflects actual usage.
• Booking Policy Controls: Administrators can configure slot lengths (4- to 10-hour maximums), advance booking windows (3 days as of December 2023), maximum daily/advance bookings, and adjust parameters for different branches or periods.
• Notification System: Users receive confirmation emails containing check-in codes; reminder emails were discontinued due to user feedback.
• Interoperability: The system integrates with LibCal Spaces (room booking) and Events (workshops) modules, facilitating unified scheduling.
• Technical Stack: The front end employs HTML/CSS/JavaScript with a responsive grid and image mapping; core API endpoints and the reservation engine reside in Springshare’s cloud SaaS environment.
• Check-in Validation: The check-in service supports QR code and geolocation-based confirmation (enabled March 2024), with support for analytics and custom reporting via export functions.

2. User Interface and Workflow Design

Key UI and workflow features include a responsive web app (desktop and mobile support is ongoing), a calendar-style grid summarizing occupancy by seat and time slot, and a seat-map viewer with high-resolution floor plans (updated in 2023). The booking form collects date, time slot, and seat selection; upon reservation, a confirmation page and email display and highlight the check-in code.

Improvements in 2023 prioritized increased clarity of the check-in workflow and code visibility, resulting in 90.2% user approval for the enhanced display. Integration of an ICS calendar attachment and improved email subject lines further addressed user concerns regarding code retrieval and booking recall (Renaville et al., 26 Jan 2026). Planned features include deployment of fully interactive seat maps and streamlined mobile navigation.

The canonical LibCal Seats user flow can be compactly described:

$$\text{User selects seat} \rightarrow \text{Receives code} \rightarrow \text{Check-in within 30 min} \rightarrow \text{Seat activated}$$

3. Operational Metrics and Usage Trends

During peak sessions, key performance indicators included total unique users, average daily bookings, occupancy rate (O), and no-show rate (N), as detailed below:

Session	Unique Users	Avg. Daily Bookings	Occupancy Rate (O)	No-Show Rate (N)
May–Jun 2022	2,269	150	78%	22%
May–Jun 2023	6,737	430	87%	13%

The occupancy rate is defined as

%%%%1%%%%

with the no-show rate

$N = 1 - O$

Between 2022 and 2023, unique users increased fourfold, and average daily bookings nearly tripled. Enforcement of check-in and longer slot durations improved O from 78% to 87% and reduced N from 22% to 13%. Pre-COVID, peak-period occupancy (first-come, first-served) was estimated at ~65%. Post-pandemic, reservation-based usage stabilized at a mean ~83% occupancy, indicating substantial efficiency gains (Renaville et al., 26 Jan 2026).

4. User Perceptions and Survey Evidence

ULiège conducted two systematic surveys: the first in June–July 2022 (16.5% response, n=375/2,269 users), and a follow-up in October 2023 (4.7% response, n=315/6,737 users). Survey instruments combined Likert-scale ratings and qualitative comment fields.

Table: Selected User Satisfaction Indicators

Indicator	2022 Survey	2023 Survey
Booking practicality	81.6%	–
Ease of use	86.4%	–
Check-in workflow practical	52.8%	–
Removal of reminder email appreciated	–	53.7%
Visibility of check-in code improved	–	90.2%
Extension to 10h slots appreciated	–	91.4%
Layout/UI improvements appreciated	–	45.7%

Notably, 74% of first-survey respondents reported reduced stress over seat availability, and 64.3% admitted to exploiting the absence of formal reservations (“seat hogging”). Email confirmations were clear for 93.9% of respondents; 25.9% found reminder emails redundant, motivating their removal. 91.4% of 2023 respondents judged 10-hour slot limits sufficient.

Areas of dissatisfaction included the 30-minute check-in window, considered too restrictive by 32.8%, complex email management, and insufficient mobile usability (45.7% positive rating after improvements).

5. Identified Challenges and Remediation

Key implementation challenges emerged:

• Unoccupied Reserved Seats/No-Shows: The initial 22% no-show rate in 2022 decreased following automated release of unclaimed reservations (auto-release resolved ~40% of unoccupied bookings).
• Booking Workflow Complexity: Issues included difficulty locating check-in codes amidst multiple emails (35 specific comments), and suboptimal mobile interaction with the availability grid.
• Chain Booking and Advance Reservations: Excessive advance booking (up to 10 days) enabled “chain holdings” and long-term unused reservations. A subset (26.4%) desired full-day booking flexibility; others criticized the lack of predictability.
• Deviant Use: 74.1% experienced other users occupying their reserved seat at least once, underscoring the importance of seat-level enforcement.

Remedial measures included reducing advance booking to three days, extending slot length to 10 hours (to decrease frequency of re-booking and related email traffic), and introducing geolocation-based check-in to reduce remote abuse.

6. Policy Evolution, Technical Enhancements, and Outcomes

A sequence of policy and technical adaptations was implemented:

• Reserving and Releasing Mechanisms: Bookings are auto-canceled if no check-in is logged within 30 minutes; ULiège opted to maintain a short grace period during peak times to maximize fairness, despite vendor support for 120-minute delays.
• UI/UX Upgrades: Email templates were improved for immediate code visibility; calendar notifications (ICS attachments) now embed codes, promoting integration with user workflows.
• Search and Visualization: Adoption of Search by Space (June 2023) accelerated availability queries, and ongoing work targets interactive seat maps.
• Geolocation Validation: April 2024 saw the introduction of location-based check-in to inhibit remote (i.e., non-present) confirmation attempts.

Measured effects include reduction in the no-show rate from 22% to 13%, a significant increase in user satisfaction regarding code visibility (90.2%), and positive evaluations of day-long slot options (91.4%). UI revisions received more modest but notable improvement approval (45.7%).

7. Best Practices and Continuous Evaluation

Recommended best practices, as derived from ULiege’s operational experience, are as follows:

• Enforce check-in/out with automated release to achieve occupancy rates above 85%.
• Restrict advance reservation windows to three days or less, curbing chain booking.
• Adapt slot lengths in accordance with demand, extending to 8–10 hours off-peak and compressing to 2–4 hours during peaks.
• Employ geolocation for check-in validation to prevent system gaming.
• Ensure consistent, responsive, and branded UI with priority on interactive seat selection.
• Systematically evaluate through regular user surveys (≥10% target response), monthly monitoring of total bookings, occupancy (O), and no-shows (N).
• Integrate direct qualitative feedback channels and iterate both technical and administrative policies in light of observed trends.
• Participate in vendor forums and adopt new LibCal features promptly to maintain alignment with evolving needs (Renaville et al., 26 Jan 2026).

These measures support sustainable, adaptive space management, evidenced by long-term occupancy above 85% and user satisfaction consistently over 80%. The ongoing refinement of LibCal Seats at ULiège demonstrates that integrating enforceable workflows, dynamic parameterization, clear user communication, and systematic evaluation can successfully address both operational and user experience objectives in academic library contexts.