Wahid bin Ahsan

Department of Human-Centered Design
Userhub

Abstract

Complex social problems such as environmental degradation, public health crises, and social inequity require a problem-solving framework that facilitates systemic change. The SEED (Search, Explore, Evolve, Deliver) framework addresses this need by bridging gaps in traditional approaches, emphasizing inclusive collaboration, iterative design, and a mixed-methods research approach for sustainable solutions. By breaking down problem-solving into four interconnected stages—Search, Explore, Evolve, Deliver—SEED fosters a multi-stakeholder process that is both adaptable and evidence-driven. This paper introduces the SEED framework, detailing its unique stages, alignment with contemporary societal considerations, and applicability in tackling complex, multi-faceted problems. SEED emerges as a practical and adaptive framework capable of facilitating practical and sustainable solutions to social issues. Researchers, practitioners, and social innovators are invited to explore how SEED can enhance their methods for addressing key social challenges.

Keywords: SEED Framework, Problem-Solving, Evidence-Based Decision Making, User-Centered Design, Innovation, Collaboration, Sustainability, Iterative Process, Adaptation, Complex Challenges, Social Impact, Social Innovation, Systems Thinking, Human-Centered Design, Social Impact Measurement, Agile Methodologies.

Introduction

In a world experiencing rapid social, environmental, and technological changes, traditional problem-solving methods often prove inadequate. These methods, designed for simpler contexts, frequently produce solutions that are too narrow, failing to address today’s complex challenges (Brown & Wyatt, 2010; Ries, 2011). To tackle these issues effectively, a new approach is needed—one that combines evidence-based practices with a commitment to sustainable and impactful solutions (Manzini, 2015; Norman & W. Draper, 1986).

Existing frameworks encounter several common problems. Traditional methods often emphasize product or service innovation while overlooking critical social, cultural, and environmental factors, limiting the scope and effectiveness of solutions (Manzini, 2015). Additionally, prioritizing immediate user needs over comprehensive data analysis can lead to superficial solutions that fail to address underlying issues (Sackett et al., 1996). Many models follow a linear path and do not incorporate iteration and adaptation in response to changing real-world contexts, resulting in rigid and less effective solutions (Ries, 2011). Furthermore, specialized frameworks often lack the flexibility needed to address the diverse landscape of modern problem-solving challenges (Pyzdek & Keller, 2009). Solutions often fall short when they do not address the root causes and interconnected nature of complex problems, underscoring the need for a holistic approach (Senge, 2006).

The SEED framework addresses these challenges directly by breaking down problem-solving into four interconnected stages: Search, Explore, Evolve, and Deliver. This structure promotes a collaborative, human-centered, and evidence-based approach necessary for tackling complex problems. From the thorough problem definition in the ‘Search’ stage to the detailed implementation and evaluation in the ‘Deliver’ stage, SEED provides a structured approach to translating insights into sustainable solutions.

This paper introduces the SEED framework, detailing its unique stages, alignment with contemporary societal considerations, and its applicability in addressing complex, multi-faceted problems. SEED is presented as a comprehensive and flexible framework aimed at addressing complex social issues. Researchers, practitioners, and social innovators are invited to explore how SEED can transform their approach to solving critical social challenges.

The SEED Framework

To overcome the limitations of traditional problem-solving methods, we introduce the SEED (Search, Explore, Evolve, Deliver) framework, a comprehensive and adaptable approach designed for today’s complex problem-solving environment. SEED builds on the strengths of existing models while introducing key innovations. This section provides an overview of each stage of the SEED framework, detailing their primary focus and activities.

1. Search: This stage lays the foundation for effective problem-solving by defining the problem, understanding its broader context, engaging stakeholders, and formulating a precise problem statement.
2. Explore: This stage involves a deep examination of the problem, using a mix of research methods to uncover patterns, relationships, and insights essential for crafting effective solutions.
3. Evolve: Insights are translated into practical solutions, balancing creative exploration with a pragmatic focus on feasibility, impact, and adaptability.
4. Deliver: The final stage transitions the solution from design to tangible impact, emphasizing meticulous implementation planning, phased execution, and robust evaluation.

Table 1: The SEED Framework: Stages of Systemic Problem-Solving

The table outlines the four primary stages of the SEED problem-solving framework. Each stage is detailed with its primary focus, the key activities that take place, and the expected outcomes. The SEED framework is designed to be iterative and cyclical, ensuring continuous improvement and adaptability to complex social challenges.

Stage	Focus	Activities	Outcome
Search	Problem Definition and Stakeholder Engagement	Define scope, gather information, engage stakeholders, develop problem statement	A clearly defined problem statement and comprehensive understanding of the issue
Explore	In-depth Research and Insight Generation	Conduct research, identify key insights, prioritize social research approaches	Deep insights into the problem, supporting the development of solutions
Evolve	Solution Development and Iterative Design	Ideate and brainstorm, evaluate and prioritize prototypes and iterate, apply agility	Solutions refined through feedback and tailored for effectiveness
Deliver	Implementation, Evaluation, and Learning Dissemination	Develop implementation plan, execute in phases, measure impact, share learnings	Implemented solutions with measured outcomes and shared insights for future cycles

By delineating the problem-solving process into these interconnected stages, the SEED framework encourages a synthesis of collaboration, innovation, and adaptability, aiming for solutions that are not only effective and user-aligned but also sustainable and socially impactful. This integrated approach positions SEED as a practical approach to contemporary challenges, offering a pathway to meaningful and enduring social change.

Stage 1: Search

The ‘Search’ stage is foundational for effective problem-solving, meticulously defining the problem, understanding its broader context, engaging stakeholders, and developing a clear problem statement. Unlike traditional models with a narrow focus, this stage lays the groundwork for comprehending the complex and interconnected nature of modern problems. Focusing on relevance, practicality, and meeting stakeholder needs, it ensures that solutions are well-guided and impactful (Checkland, 1999; Jonassen, 2000; Rittel & Webber, 1973).

Problem Definition and Contextual Understanding

To comprehensively define the problem, it is crucial to engage a diverse array of stakeholders, including clients, target users, domain experts, and those directly impacted by the issue. This inclusive approach ensures a well-rounded perspective, essential for understanding complex social systems and their intricacies (Barretti, 2020). Conducting a detailed examination of the problem’s history, previous solution attempts, and relevant social, political, and environmental factors further enriches this understanding (Exter et al., 2020; van der Bijl-Brouwer & Dorst, 2017). Additionally, identifying and articulating the desired outcomes and potential limitations—whether financial, technological, or regulatory—provides a realistic framework within which solutions can be developed and evaluated.

A mixed-methods approach is employed to gather comprehensive information about the problem space. This includes qualitative and quantitative research methods such as interviews, surveys, data analysis, and review of historical records (Palinkas et al., 2019). An exhaustive review of relevant academic literature, reports, and competitor analyses helps to gain a deep understanding of the existing landscape and identify gaps or opportunities for innovation. Researching current practices, trends, and emerging technologies within the relevant field ensures the solution adds value and does not duplicate existing efforts.

Stakeholder Engagement

Stakeholder engagement is pivotal in this stage. Conducting open-ended interviews and surveys allows for the emergence of unexpected insights, ensuring a rich understanding of the problem from multiple viewpoints (Deschepper et al., 2017). Maintaining a commitment to diversity among stakeholder groups helps to mitigate the risk of solution bias, representing a wide array of experiences and perspectives (Pronin & Hazel, 2023). Interactive workshops enable stakeholders to share knowledge, experiences, and ideas, promoting a shared understanding of the problem and collaboratively developing foundational solutions (Björling & Rose, 2019).

Developing a Problem Statement

The insights gathered from the previous steps are integrated to distill the core issue at hand. Proactive strategies are employed to identify and mitigate biases, as research indicates that even seemingly objective problem definitions can be influenced by unconscious biases (Pronin & Hazel, 2023). A concise, focused problem statement is then formulated, encapsulating the essence of the problem and serving as a guiding beacon for the solution development process. In cases where the problem is embedded within a complex social system, leveraging specific methods from complex systems thinking is necessary to fully comprehend the interconnected causes and potential ramifications (Zellner & Campbell, 2015).

The “Search” stage lays a robust foundation for the subsequent stages of problem-solving. The insights garnered during this phase directly inform the “Explore” stage, setting the stage for a deeper investigation into the problem’s complexities and the development of tailored, effective solutions. This comprehensive approach ensures that the problem is thoroughly understood, creating a solid base for innovative and impactful solutions.

Stage 2: Explore

The ‘Explore’ stage delves deeply into the problem, transitioning from a broad understanding to a detailed understanding of its intricacies. This phase employs a combination of qualitative and quantitative research methods, essential for uncovering patterns, relationships, and emergent insights that are foundational for crafting effective solutions.

Research and Insights

Utilizing a mixed-methods approach allows for a thorough understanding of complex social issues. By combining qualitative interviews with quantitative data analysis, a multifaceted perspective of the problem can be achieved. This diversity in methodology is crucial for examining intricate issues and providing comprehensive insights (Deschepper et al., 2017; Palinkas et al., 2019). Detailed data analysis can reveal important trends and connections within the problem space. Remaining open to unexpected findings during this process can significantly influence the development of potential solutions. Hypotheses derived from data should remain flexible, adapting to new evidence or insights. This adaptability is key to managing the complexities of social challenges and continuously refining proposed solutions.

Employing various analytical techniques such as thematic analysis ensures that insights are regularly improved, highlighting both challenges and opportunities within the problem space. Converting complex datasets into actionable insights clarifies the problem and guides the development of innovative and viable solutions. Staying alert to unexpected discoveries during research can reveal new solution pathways or unmet needs.

Prioritize Social Research Approaches

Integrating social research methodologies within a Human-Centered Design (HCD) framework creates a deep understanding of user needs, motivations, and barriers. This user-centric approach is vital for developing solutions that resonate on both personal and community levels (Chen et al., 2020). Employing participatory research methods, such as focus groups, community workshops, and co-design sessions, fosters collaboration with stakeholders, enriching the solution development process. This inclusive strategy leverages collective expertise and ensures that outcomes are meaningful and impactful, aligning with the principles of collaborative (Björling & Rose, 2019).

The exploration stage is crucial for driving the ideation process and shaping the development of solutions that are both human-centered and grounded in solid evidence. The insights gained through meticulous research directly inform the subsequent “Evolve” stage, setting the stage for creating practical and effective solutions.

Stage 3: Evolve

The “Evolve” stage translates insights into practical solutions, balancing creative exploration with a pragmatic focus on feasibility, impact, and adaptability. Utilizing the detailed findings from the “Explore” stage, this phase employs design thinking and agile methodologies to develop solutions that are both innovative and responsive to feedback and evolving needs.

Solutions Development

Workshops are designed to stimulate diverse thought and idea cross-pollination, drawing upon the contextual understanding and stakeholder insights previously gathered. This collaborative environment is essential for generating a range of solutions. Participants are encouraged to pursue unconventional solutions while considering the ethical implications and constraints identified during the initial stages. This balance fosters creativity while maintaining practical realism.

Solutions are assessed based on feasibility, potential impact, and alignment with user needs and the success metrics established in the “Search” stage. This assessment ensures that solutions are practical and impactful. Dynamic tools and methods are used to accommodate shifting priorities and feedback, particularly in complex or large-scale projects. Ongoing stakeholder engagement is vital for ensuring that solutions remain relevant and aligned with community needs and expectations (Uludağ & Matthes, 2020).

Prototyping and Iteration

Quick development of low-fidelity prototypes allows for early testing of core concepts and assumptions, inviting immediate user feedback and enabling swift iterations (Flood et al., 2021). Solutions are continuously refined based on testing outcomes, user feedback, and new challenges that arise. This iterative approach is crucial for ensuring solutions remain relevant and effective (bin Ahsan, 2024; Santos & de Carvalho, 2022). While SEED adopts agile methodologies, it also acknowledges the unique demands of social innovation projects. This requires adapting agile principles to consider shifting team dynamics and the broader social context (Espinosa‐Curiel et al., 2018; Shrivastava & Rathod, 2015).

Testing, Feedback, and Refinement

Solution testing is designed around the user, incorporating insights from earlier social research phases. Early testing of fundamental assumptions using low-fidelity prototypes helps validate concepts before committing to extensive development efforts (Flood et al., 2021). Establishing systematic feedback mechanisms during and post-development ensures continuous engagement with stakeholders. This process assesses functionality and evaluates the broader social impact, enabling further refinements (bin Ahsan, 2024; Saaty et al., 2022). Recognizing the need for solutions to evolve even post-launch, especially in social innovation where contexts and needs can shift significantly, is crucial. Unlike purely technical solutions, those addressing social issues must adapt in response to shifts in policy, community needs, or cultural values. This ongoing adaptation ensures solutions remain relevant and effective over time (Kowark et al., 2014).

The “Evolve” stage balances innovation with pragmatism, developing solutions that are human-centered and responsive to real-world contexts. Emphasizing adaptability, continuous refinement, and stakeholder-driven feedback, this stage sets the stage for the “Deliver” phase, where solutions transition from concept to tangible action. Informed by lessons learned and a commitment to lasting impact, the “Evolve” stage ensures that solutions are effective, sustainable, and aligned with the needs and realities of those they are designed to serve.

Stage 4: Deliver

The “Deliver” stage is the crucial final step that transitions the solution from design to tangible impact, emphasizing meticulous implementation planning, phased execution, and robust evaluation mechanisms. This stage is instrumental in realizing the envisioned change, with success measured by the solution’s ability to make a measurable difference, its adaptability to evolving contexts, and its sustainability over time.

Implementation and Execution

The implementation plan aligns with the success metrics identified during the “Search” stage and leverages implementation science for a strategic approach (Eagle et al., 2015). It also incorporates insights into change management for complex projects, emphasizing the need to remain adaptable as the solution is rolled out (Schuh et al., 2017). Adopting a proactive stance on identifying potential risks and developing contingency plans is essential, especially for complex projects where flexibility and the ability to pivot are paramount. Incorporating specific risk mitigation tools or change management frameworks can enhance practicality.

Introducing the solution in stages allows for real-world testing, learning, and adaptation before full-scale deployment. This phased approach minimizes disruption and enhances the solution’s fit to community needs. Applying agile methodologies with a specific focus on their capacity to enhance social initiatives promotes flexibility and a responsive approach to changing community needs (Shrivastava & Rathod, 2015).

Monitor & Evaluate

Integrating mechanisms for ongoing feedback from a broad spectrum of stakeholders ensures that the solution remains aligned with user needs and expectations even after its launch (bin Ahsan, 2024; Saaty et al., 2022). Utilizing a multi-pronged approach, incorporating both qualitative and quantitative metrics, assesses the solution’s social impact while remaining sensitive to community context (Battilana et al., 2019; Mertens & Wilson, 2012). Establishing regular evaluation points throughout implementation facilitates timely adjustments.

To navigate implementation complexities and respond to emerging needs, flexible and broadly applicable frameworks such as the “Generic Implementation Framework (GIF)” are employed. GIF, along with other frameworks like the “Exploration, Preparation, Implementation, Sustainment” (EPIS) model, “Reach, Effectiveness, Adoption, Implementation, Maintenance” (RE-AIM), and the “Consolidated Framework for Implementation Research” (CFIR), provides comprehensive guidelines adaptable to different contexts, ensuring robust and sustainable implementation (Aarons et al., 2011; Damschroder et al., 2009, 2022; Glasgow et al., 1999; Moullin et al., 2015). These frameworks support the SEED framework’s goal of creating solutions that consider interconnected social, cultural, and economic layers to ensure both functionality and acceptance within the community.

Developing multi-faceted solutions is essential for addressing the interconnected social, cultural, and economic barriers impacting solution adoption (Knoepke et al., 2019). The SEED framework advocates for solutions that consider these interconnected layers to ensure both the functionality of the intervention and its acceptance within the community.

Reflect and Share Learnings

Systematically documenting learnings, challenges, and successes throughout the project offers valuable insights for future initiatives. This process facilitates internal project reflection and aligns with the principles of ‘scaling deep’ for social innovation, ensuring that lessons learned contribute to broader value shifts within the field (Moore et al., 2015). Sharing the accumulated knowledge openly with all stakeholders, including the wider community and domain experts, through various channels such as white papers, conference presentations, and open-source tools, promotes a culture of continuous learning. This contributes to broader systemic change, fosters collaboration, and empowers other practitioners (Chen et al., 2020).

The “Deliver” stage represents not an endpoint but a vital link back to the beginning of the SEED process. The iterative learning and insights gained during this phase feed directly into the “Search” stage of future endeavors, embodying the cyclical nature of the SEED framework. This recursive process ensures that the framework continuously evolves, enhancing its capacity to drive meaningful and sustainable social change.

Conclusion

The SEED framework represents a structured approach to problem-solving, designed to meet the complex demands of today’s global challenges. By strategically dividing the process into four interconnected stages—Search, Explore, Evolve, and Deliver—SEED guides practitioners through a comprehensive journey that combines analytical depth with creative breadth. This ensures that solutions are both innovative and grounded in evidence.

The framework’s versatility offers a universal methodology adaptable across various industries and problem domains. By emphasizing context sensitivity, SEED acknowledges that one-size-fits-all solutions rarely succeed in addressing intricate societal issues (van der Bijl-Brouwer & Dorst, 2017). This adaptability is crucial in an era characterized by rapid change and interconnected problems. SEED promotes a collaborative ethos, advocates for decisions rooted in robust evidence, and fosters a culture of continuous learning and critical reflection.

SEED embodies a transformative philosophy, empowering problem-solvers to navigate and lead in developing lasting solutions to societal issues. This philosophy promotes innovation, supports adaptability, and focuses on sustainable impact, positioning SEED as an effective approach in the modern world.

Importantly, SEED is cyclical, not linear, emphasizing continuous evolution and learning. Each stage feeds into the next, with the final “Deliver” phase seamlessly transitioning into a new “Search” phase. This ensures the framework remains relevant and responsive to the evolving landscape of societal needs and challenges. By integrating a systems thinking perspective, SEED encourages solutions that consider interconnectedness and potential ripple effects (Phillips et al., 2015).

In summary, the SEED framework offers a comprehensive and adaptable approach to addressing contemporary problems. It highlights the importance of integrating diverse perspectives, leveraging evidence-based insights, and maintaining a focus on sustainable social impact. SEED provides a blueprint for problem-solvers everywhere, encouraging solutions that are proactive and forward-looking, building a more equitable and sustainable future.

Limitations and Future Study

The SEED framework may require significant adjustments to be effective in different cultural, social, and economic contexts. Implementing SEED can be time-consuming and costly, posing challenges for smaller organizations or projects with limited resources. Its comprehensive nature can make integration into existing processes difficult without additional training and support. Continuous feedback and iteration also complicate the assessment of long-term impact and success.

To address these limitations, future research should explore how SEED can be tailored for various contexts through case studies and pilot projects. Developing simplified toolkits for smaller projects and organizations can enhance accessibility. Integrating AI and data analytics may improve data gathering, analysis, and iterative processes. Creating standardized metrics and evaluation frameworks is essential for consistently measuring the long-term impact of SEED solutions. Additionally, developing training programs and support materials, such as online courses and workshops, will help practitioners implement SEED effectively.

By focusing on these areas, we can enhance the SEED framework’s effectiveness and adaptability, ensuring it continues to drive meaningful and sustainable social change.

---

References

Aarons, G. A., Hurlburt, M., & Horwitz, S. M. (2011). Advancing a Conceptual Model of Evidence-Based Practice Implementation in Public Service Sectors. Administration and Policy in Mental Health and Mental Health Services Research, 38(1), 4–23. https://doi.org/10.1007/s10488-010-0327-7

Barretti, M. A. (2020). Same Problem, Different Policies. Advances in Social Work, 19(1), 39–61. https://doi.org/10.18060/22603

Battilana, J., Butler, B., Kimsey, M., Mair, J., Marquis, C., & Seelos, C. (2019). Problem, person and pathway: a framework for social innovators. In Handbook of Inclusive Innovation. Edward Elgar Publishing. https://doi.org/10.4337/9781786436016.00012

bin Ahsan, W. (2024). The EDIT UX Framework: A User-Centered Approach to Effective Product Redesign. https://doi.org/10.58947/ZXKD-KLDQ

Björling, E. A., & Rose, E. (2019). Participatory Research Principles in Human-Centered Design: Engaging Teens in the Co-Design of a Social Robot. Multimodal Technologies and Interaction, 3(1), 8. https://doi.org/10.3390/mti3010008

Brown, T., & Wyatt, J. (2010). Design Thinking for Social Innovation. Development Outreach, 12(1), 29–43. https://doi.org/10.1596/1020-797X_12_1_29

Checkland, P. (1999). Systems Thinking, Systems Practice: Includes a 30-Year Retrospective. Wiley.

Chen, E., Leos, C., Kowitt, S. D., & Moracco, K. E. (2020). Enhancing Community-Based Participatory Research Through Human-Centered Design Strategies. Health Promotion Practice, 21(1), 37–48. https://doi.org/10.1177/1524839919850557

Damschroder, L. J., Aron, D. C., Keith, R. E., Kirsh, S. R., Alexander, J. A., & Lowery, J. C. (2009). Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science, 4(1), 50. https://doi.org/10.1186/1748-5908-4-50

Damschroder, L. J., Reardon, C. M., Widerquist, M. A. O., & Lowery, J. (2022). The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Science, 17(1), 75. https://doi.org/10.1186/s13012-022-01245-0

Deschepper, R., Six, S., Vandeweghe, N., De Couck, M., Gidron, Y., Depoorter, A.-M., & Bilsen, J. (2017). Linking numbers to perceptions and experiences: Why we need transdisciplinary mixed-methods combining neurophysiological and qualitative data. Methodological Innovations, 10(2), 205979911770311. https://doi.org/10.1177/2059799117703119

Eagle, J. W., Dowd-Eagle, S. E., Snyder, A., & Holtzman, E. G. (2015). Implementing a Multi-Tiered System of Support (MTSS): Collaboration Between School Psychologists and Administrators to Promote Systems-Level Change. Journal of Educational and Psychological Consultation, 25(2–3), 160–177. https://doi.org/10.1080/10474412.2014.929960

Espinosa‐Curiel, I. E., Rodríguez‐Jacobo, J., Vázquez‐Alfaro, E., Fernández‐Zepeda, J. A., & Fajardo‐Delgado, D. (2018). Analysis of the changes in communication and social interactions during the transformation of a traditional team into an agile team. Journal of Software: Evolution and Process, 30(9). https://doi.org/10.1002/smr.1946

Exter, M. E., Gray, C. M., & Fernandez, T. M. (2020). Conceptions of design by transdisciplinary educators: disciplinary background and pedagogical engagement. International Journal of Technology and Design Education, 30(4), 777–798. https://doi.org/10.1007/s10798-019-09520-w

Flood, M., Ennis, M., Ludlow, A., Sweeney, F. F., Holton, A., Morgan, S., Clarke, C., Carroll, P., Mellon, L., Boland, F., Mohamed, S., De Brún, A., Hanratty, M., & Moriarty, F. (2021). Research methods from human-centered design: Potential applications in pharmacy and health services research. Research in Social and Administrative Pharmacy, 17(12), 2036–2043. https://doi.org/10.1016/j.sapharm.2021.06.015

Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: the RE-AIM framework. American Journal of Public Health, 89(9), 1322–1327. https://doi.org/10.2105/AJPH.89.9.1322

Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85. https://doi.org/10.1007/BF02300500

Knoepke, C. E., Ingle, M. P., Matlock, D. D., Brownson, R. C., & Glasgow, R. E. (2019). Dissemination and stakeholder engagement practices among dissemination & implementation scientists: Results from an online survey. PLOS ONE, 14(11), e0216971. https://doi.org/10.1371/journal.pone.0216971

Kowark, T., Häger, F., Gehrer, R., & Krüger, J. (2014). A Research Plan for the Integration of Design Thinking with Large Scale Software Development Projects. In Design Thinking Research (pp. 183–202). Springer International Publishing. https://doi.org/10.1007/978-3-319-01303-9_12

Manzini, E. (2015). Design, When Everybody Designs. The MIT Press.

Mertens, D. M., & Wilson, A. T. (2012). Program Evaluation Theory and Practice: A Comprehensive Guide (2nd ed.). The Guilford Press.

Moore, M.-L., Riddell, D., & Vocisano, D. (2015). Scaling Out, Scaling Up, Scaling Deep: Strategies of Non-profits in Advancing Systemic Social Innovation. The Journal of Corporate Citizenship, 58, 67–84. http://www.jstor.org/stable/jcorpciti.58.67

Moullin, J. C., Sabater-Hernández, D., Fernandez-Llimos, F., & Benrimoj, S. I. (2015). A systematic review of implementation frameworks of innovations in healthcare and resulting generic implementation framework. Health Research Policy and Systems, 13(1), 16. https://doi.org/10.1186/s12961-015-0005-z

Norman, D. A., & W. Draper, S. (1986). User Centered System Design: New Perspectives on Human-computer Interaction. CRC Press.

Palinkas, L. A., Mendon, S. J., & Hamilton, A. B. (2019). Innovations in Mixed Methods Evaluations. Annual Review of Public Health, 40(1), 423–442. https://doi.org/10.1146/annurev-publhealth-040218-044215

Phillips, W., Lee, H., Ghobadian, A., O’Regan, N., & James, P. (2015). Social Innovation and Social Entrepreneurship. Group & Organization Management, 40(3), 428–461. https://doi.org/10.1177/1059601114560063

Pronin, E., & Hazel, L. (2023). Humans’ Bias Blind Spot and Its Societal Significance. Current Directions in Psychological Science, 32(5), 402–409. https://doi.org/10.1177/09637214231178745

Pyzdek, T., & Keller, P. (2009). The Six Sigma Handbook (3rd ed). McGraw-Hill Professional.

Ries, E. (2011). The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Crown Currency.

Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169. https://doi.org/10.1007/BF01405730

Saaty, M., Patel, J. V., Haqq, D., Stelter, T. L., & McCrickard, D. S. (2022). Integrating Social Media into the Design Process.

Sackett, D. L., Rosenberg, W. M. C., Gray, J. A. M., Haynes, R. B., & Richardson, W. S. (1996). Evidence based medicine: what it is and what it isn’t. BMJ, 312(7023), 71–72. https://doi.org/10.1136/bmj.312.7023.71

Santos, P. de O., & de Carvalho, M. M. (2022). Exploring the challenges and benefits for scaling agile project management to large projects: a review. Requirements Engineering, 27(1), 117–134. https://doi.org/10.1007/s00766-021-00363-3

Schuh, G., Gartzen, T., Soucy-Bouchard, S., & Basse, F. (2017). Enabling Agility in Product Development through an Adaptive Engineering Change Management. Procedia CIRP, 63, 342–347. https://doi.org/10.1016/j.procir.2017.03.106

Senge, P. M. (2006). The Fifth Discipline: The Art & Practice of The Learning Organization . Doubleday.

Shrivastava, S. V., & Rathod, U. (2015). Categorization of risk factors for distributed agile projects. Information and Software Technology, 58, 373–387. https://doi.org/10.1016/j.infsof.2014.07.007

Uludağ, Ö., & Matthes, F. (2020). Large-Scale Agile Development Patterns for Enterprise and Solution Architects. Proceedings of the European Conference on Pattern Languages of Programs 2020, 1–22. https://doi.org/10.1145/3424771.3424895

van der Bijl-Brouwer, M., & Dorst, K. (2017). Advancing the strategic impact of human-centred design. Design Studies, 53, 1–23. https://doi.org/10.1016/j.destud.2017.06.003

Zellner, M., & Campbell, S. D. (2015). Planning for deep-rooted problems: What can we learn from aligning complex systems and wicked problems? Planning Theory & Practice, 16(4), 457–478. https://doi.org/10.1080/14649357.2015.1084360