Management, Cooperation, and Sustainability: Unpacking the Data Practices of Housing Cooperatives

Research Background and Issues

• Identified Problems or Challenges: The paper investigates the role and related issues of nonprofit housing cooperatives (NXI) in data practices, including the use of financial, social, and building maintenance data and its impact on collaboration, sustainability, and operations. The study indicates that while NXI's current data practices are functional in the short term, the fragmentation, redundancy, lack of transparency, and insufficient detail of the data limit the cooperative's ability to achieve long-term sustainability.
• Significance: Given the critical role housing cooperatives play in addressing housing affordability in North American cities, studying cooperatives' data practices is not only essential for promoting sustainability but also provides valuable insights for other grassroots organizations.
• Research Motivation and Related Work: The authors note that while the HCI (Human-Computer Interaction) field has extensively studied data tools for nonprofit organizations and grassroots communities, there is limited focus on cooperatives' data practices. Cooperatives, as a model of democratic control and joint ownership, offer an important perspective for understanding how data can support grassroots organizations.

Solution

• Proposed Solution: Through 16 months of ethnographic research (including 24 interviews), the authors delve into NXI's operational data practices, analyzing how data supports NXI's daily maintenance, collaboration, and sustainability, while uncovering related tensions and shortcomings.
• Innovative Aspects: The study introduces the concept of "temporal affordances of data practices," analyzing the impact of data on organizations from both short-term and long-term perspectives. This framework aids in understanding how data practices support or constrain organizational goals within specific temporal contexts. Additionally, the study proposes directions for designing data tools, including distributed data governance and tools that account for temporal considerations.
• Implementation Steps and Techniques: The research methodology includes interviews, observations, and the integration of real-world data with digital tools for analysis. Open coding and thematic analysis were primarily employed to identify issues in data practices.

Research Outcomes

• Specific Findings: The authors found that while NXI's existing data practices support daily maintenance and collaboration in the short term, they fall short in enabling long-term sustainability. For instance, data fragmentation leads to information overload, and the lack of historical records constrains long-term decision-making. Furthermore, the centralized management of "membership fees" conflicts with the cooperative's principle of democratic economic participation.
• Advantages: The study explores data practices from the perspectives of collaboration and democratic participation, enriching the HCI literature on data management in small-scale nonprofit organizations and cooperatives. By addressing foundational issues, the research provides critical insights for designing data tools that support community governance and collaboration.
• Experimental or Evaluation Results: Limitations in data practices include inaccessibility of data, lack of financial transparency, and the diminishing efficacy of data over time (data decay). Additionally, current financial tools fail to fully support the cooperative's collaborative and shared values.
• Limitations and Future Directions: Although the study reveals numerous issues and potential solutions, it is limited to the case of a single cooperative organization. Future research could expand to other types of cooperatives or grassroots organizations and explore innovative solutions based on blockchain or distributed data governance to support long-term sustainability. Further studies could also investigate how to design tools that balance privacy protection with data-sharing needs.