Appreciative Inquiry

Appreciative inquiry (AI) is a strengths-based approach to organizational change that identifies what drives success and builds on those positive elements to promote growth. Unlike traditional problem-solving methods, AI emphasizes collaboration and the exploration of future possibilities rather than analyzing past failures. By engaging stakeholders in a positive dialogue, appreciative inquiry helps organizations unlock their potential, foster innovation, and create lasting, meaningful change.

At your first management conference, you notice that many employees who aren’t present are being left underappreciated—with complaints about disengagement circulating around. Reflecting on your own recent experience as an entry-level employee whose ideas were often overlooked, you propose a shift: instead of focusing on what's missing, why not celebrate the talents and contributions already within the team? You suggest creating a space for employees to share what they’re proud of and how their ideas have made a difference, fostering a positive, inclusive approach to reimagining the organization’s future.

This shift in perspective is at the heart of appreciative inquiry (AI), an energizing and positive framework for leadership development, organizational change, and skill building. With the intention of increasing innovation, this strengths-based approach is collaborative in nature, where a shared vision is developed by individuals and teams based on a company’s core values. According to its creators, David Cooperrider and Suresh Srivastva, AI can be framed in several different ways—a philosophy, a process, or even a way of being. No matter the approach, there is always inquiry into an organization’s positive core: the “best” parts when considering all of its employees, relationships, and overall culture.¹

To develop a more solid grasp of appreciative inquiry’s foundations, first, we must clearly understand what “Appreciate” and “Inquire” mean in this context:²

1. Appreciate: When we identify, favor, and perceive judgments that provide value or gratitude. 
2. Inquire:When we reflect, explore, and discover what new opportunities may exist.

The Five Original Principles of Appreciative Inquiry

The philosophical foundation of appreciative inquiry is clearly defined by its five original principles. These pillars translate AI’s core beliefs into a structured way of thinking, shaping how we understand and engage with organizations by emphasizing strengths, fostering discussion, and inspiring new possibilities.¹

1. Constructionist Principle: This principle highlights how organizations are shaped by the conversations, relationships, and shared ideas of their employees. How we talk about the organization influences how we understand it and what it becomes, as collaboration creates new ideas and ways of thinking that drive its evolution. 
2. Simultaneity Principle: This principle emphasizes that change starts with what we decide to ask ourselves. Simply posing a question sparks new thoughts, discussions, and possibilities. For example, your manager asking, "What’s working well here?" shifts focus to the positive, shaping the direction of change before answers even start to emerge. 
3. Poetic Principle: This principle asserts that human-centered organizations are shaped by interpretation. Like a book, the organization’s story is “co-authored” by the people who work and interact within it. The topics chosen for inquiry actively guide how change unfolds—such as your colleagues telling stories of their proudest achievements to express agency in the workplace.
4. Anticipatory Principle: This principle welcomes the organization to ask further questions while also building a mutual understanding of both its current state and future visions. Humans act based on what they expect or anticipate to come, impacting the behavior of individuals, people, and the organization at large. 
5. Positive Principle: This principle strengthens and reinforces the other four by emphasizing the power of positivity in shaping organizational change. Positive questions (Simultaneity Principle) create constructive conversations (Constructionist Principle), which inspire shared, optimistic visions of the future (Anticipatory Principle). These visions, in turn, shape the organization’s evolving story (Poetic Principle) and drive long-term positive actions.

The Five Emergent Principles of Appreciative Inquiry

In addition to the five original principles, AI scholars have introduced five emergent principles—wholeness, enactment, free choice, awareness, and narrative—to expand AI’s application based on real-world insights. While both sets contain five principles, they don’t correspond directly; rather, the emergent principles broadly enhance and deepen the overall framework, reinforcing AI’s strengths-based, collaborative approach.¹

1. Wholeness Principle: This principle posits that all parts of a system should be considered when co-creating the future, where each part is related to the “whole” of an organization. To inspire co-creation, managers may invite employees from all departments to participate in workshops, ensuring every voice contributes to a vision that reflects the entire company’s aspirations.
2. Enactment Principle: This principle suggests that if an organization acts as though something is true, it helps bring that reality into existence. For instance, if a company wants to be a highly engaged workplace, it can start by celebrating small wins and recognizing employee achievements, reinforcing these behaviors by boosting morale.
3. Free Choice Principle: This principle emphasizes that when employees have the freedom to choose how they engage with change, they are more committed and motivated. If a company wants to foster innovation, for example, it can start by giving employees autonomy in decision-making, encouraging them to pursue creative ideas, and providing opportunities for self-directed learning.
4. Awareness Principle: This principle underscores that individual awareness of thinking, habits, and behavior fosters an AI-oriented approach guided by the original five principles. For instance, both leaders and employees reflect on their current habits and assumptions, consciously shifting to a strengths-based mindset that shapes their actions and decisions.
5. Narrative Principle: This principle calls attention to how stories have the power to transform operations in an organization. These narratives can be a reflection of the best possible realities. Your company may share success stories from employees as a means to inspire others and demonstrate what is possible when everyone gets involved.

Appreciative Inquiry in Action

With both the original and emergent principles as the foundations for AI “in theory,” now let’s turn to how the 5-D cycle puts AI into practice through its five perspectives: Define, Discovery, Dream, Design, and Destiny.¹ This cycle highlights the process of appreciative inquiry, where each of the five Ds represents a specific activity initiated by asking generative questions: open-minded, thought-provoking inquiries for generating new ideas and possibilities. 

When applied, the 5-D cycle can result in conversations that systematically guide an employee, team, or entire system toward positive change.¹ One example from the early 2000s is how British Airways applied AI as a means to improve their customer experience—especially for heightening the experience for when travelers reach their destination:³

At its core, appreciative inquiry upholds a positive orientation by shifting from problem-solving to possibility-building as a means to incite organizational change. AI is innovative in its ability to reframe old-school, outdated deficit thinking to optimistic, possibility thinking. As a collaborative approach, any individual can have their say on how they can contribute to the shared vision of their vocational setting. Around the world, AI has gained popularity in sectors like healthcare, business, and nonprofits, just to name a few, pushing us to ask the question: what ideal future do we want to see?

5-D cycle: The core framework of AI, consisting of five stages—Definition, Discovery, Dream, Design, and Destiny—that guide the inquiry process. The 5-D cycle formerly had 4 Ds, with the fifth one, “Define,” being added after various criticisms.

Define: The phase of the 5-D cycle where the focus of the project finds clarity. This may mean identifying a starting point, the greater purpose, and what has to be improved in an organization. The guiding question teams may ask themselves is: what is it that we focus on and want to succeed in together?

Discovery: The phase of the 5-D cycle where individuals or groups explore and identify the best aspects that currently exist within an organization, such as strengths, successes, and positive experiences. Through inquiry and reflection, participants uncover what’s working well and the factors that contribute to success, which serve as the foundation for future growth and development.

Dream: The phase of the 5-D cycle for envisioning a positive future for the organization, where participants imagine what could be if the strengths and possibilities discovered during the Discovery phase are fully realized. This may include a reflection on past achievements but with an emphasis on what could be next—with employees sharing their hopes or goals for the future.

Design: The phase of the 5-D cycle to co-create potential pathways to achieve the envisioned future through concrete actions and strategies. Here, the Discovery and Dream stages are put together to combine strengths for an ideal vision of the future.

Destiny: The phase of the 5-D cycle where the organization takes actionable steps to implement the design and bring the vision into reality, often through collective action and continuous improvement. Sometimes called delivery, this stage also investigates how well the design has been implemented in the organization and in group settings, which are key to organizational change. 

Positive core: The amalgamation of strengths, values, and successes within an organization that AI seeks to identify, amplify, and build upon. These aspects are usually identified during the Discovery phase of the 5-D cycle. In addition, the positive core highlights the Dream phase by helping organizations envision a future based on their strengths and successes, inspiring a shared vision that guides actions.

Dialogical approach: The use of open, positive, and collaborative conversations to engage stakeholders in discovering and envisioning the organization’s strengths and potential. This is key to the core of AI as a model, where discussion is meant to be open for proactive questions and exploration of ideas.⁶

Generative questions: Powerful, open-ended questions that are asked throughout the AI process to spark curiosity, foster engagement, and reveal new insights that support positive change. These questions are unconditionally positive and rooted in co-creation to help new visions come to life.⁸

Co-creation: The process of collaboratively designing new solutions and strategies, emphasizing the active involvement and implementation of all stakeholders in shaping the future of the organization. The 5-D cycle is integral to co-creation in action, where we ask what “the best” of the people and its organization looks like to propel the practical implementation of a shared vision.

Co-construction: The collective building or shaping of meaning, ideas, or frameworks based on shared insights. Co-construction focuses on how participants come together to create a common understanding or vision, often centered around a positive core or aspiration.

Generativity: Refers to the ability to inspire new ideas, conversations, and possibilities that lead to meaningful change. By focusing on strengths and positive potential, AI fosters generative dialogue that helps individuals and organizations envision and co-create a better future.⁹

During the last quarter of the 20th century, two innovative thinkers were tired of the way major organizations were trying to incite change through a fixation on negativity. In 1980, Dr. David Cooperrider and his then-advisor, Dr. Suresh Srivastva, collaborated in thought leadership and positive change to create appreciative inquiry.¹ During his doctoral studies at Case Western Reserve University, Cooperrider was working with a group at the Cleveland Clinic, where he was curious about the analysis of traditional diagnostic issues. When asking the organization what was  “wrong” with how the clinic runs its diagnostic operations, Cooperrider was pleasantly surprised by the positives of Cleveland Clinic: most people got along, thought outside of the box, and treated each other as equals. Srivastva encouraged Cooperrider to dig deeper, suggesting an investigation—or an inquiry of sorts.

Cooperrider approached the Clinic’s chairman to shift his focus in approaching the problem in a positive light: instead of looking into the diagnostics of the organization, he put an emphasis on the life-centric element in analyzing the Clinic. It was here that Cooperrider asked what elements helped the Cleveland Clinic function at its best in every way possible. In this sense, the Cleveland Clinic is exemplary of the first large-scale context with an intentional design for inquiry-oriented learning about an organization. The actual phrasing of “appreciative inquiry” had its first use in a footnote as a mere piece of feedback as Cooperrider and Srivastva were finding emerging themes at the Clinic. In 1986, the momentum of this report took on a new form in Cooperrider’s dissertation in introducing AI to organizational fields.⁴

In 1987, appreciative inquiry made a more definitive name for itself when Cooperrider and Srivastva published their paper “Appreciative Inquiry in Organizational Life,” signifying the first time AI was named in a professional publication.⁶ Throughout the paper, the two authors demand a shift from the gap and problem-focused theories of change to the positive, life-oriented theory such as AI. This marked a critical moment in the history of AI as it grew from a theoretical model to a full-on framework for organizational intervention.

Appreciative inquiry flourished in the 1990s as authors began publishing books on the process, with Sue Annis Hammond’s The Thin Book on Appreciative Inquiry being especially influential. Cooperrider avoided writing on AI, fearing it might dilute its philosophical vision, focusing instead on applying AI through experiments. However, these writings by other authors often simplified AI into a process centered on uncovering people’s “best of” stories, altering its broader perspective on organizational change.

In the late 1990s, Charles Elliot’s Locating the Energy for Change and Jane Watkins’ and Charles Mohr’s Appreciative Inquiry: Change at the Speed of Imagination shaped AI’s public perception.⁹ Elliot explored AI through a psychoanalytic lens in African community development, while Watkins and Mohr provided a consultant’s guide for AI courses at the U.S. National Training Laboratory, which helped establish AI as a standard in organizational development.

While AI enthusiasts developed their interpretations, Cooperrider refined the 4-D model—later expanded to the 5-D cycle with “Define”—to bring AI to life.⁹ Outlined in 1987 but solidified a decade later during work with Save the Children Africa, the model helped consultants apply AI to areas like customer service and workplace safety. The fifth “D” was added after input from the Clergy Leadership Institute, completing the 5-D cycle that enabled AI’s spread across diverse contexts globally.

Jacqueline Stavros became an important figure in the history of Appreciative Inquiry (AI) in the late 1990s and early 2000s. Her work with David Cooperrider, particularly in co-authoring Appreciative Inquiry: A Positive Revolution in Change, helped expand AI's application and accessibility in organizational development.⁵ Stavros' contributions included developing AI tools and methods, and she played a key role in applying AI to various sectors, including education, business, and healthcare, helping solidify AI's place as a widely-used approach for positive change.

Into the 2000s, appreciative inquiry exploded in popularity with monumental figures that could easily be bragged about implementing this framework. For instance, His Holiness the Dalai Lama used AI in Vancouver, B.C., to explore the power of positive dialogue for fostering global peace and compassion.⁵ Amidst all of the other publications, Cooperrider finally put out his own writing on AI, containing its key theories and practical statements. During this period, international appreciative inquiry conferences and summits also began to take place. One of the most notable of these events was the appreciative inquiry summit in 2005, which was an avenue for the UN's global impact and featured over 500 CEOs, civil society leaders, and UN leaders.

Today, appreciative inquiry looks back at its accomplishments, fulfilled promises, and new directions. With a plethora of new applications for AI evolving since its inception, its positive influence has sparked organizational change in fields like workplace diversity, sustainability, community development, healthcare, and startups. The ongoing pursuit of looking for the “best” in people and organizations continues, with innovative methods emerging to co-create positive visions of the future. And if you initially thought of AI as artificial intelligence rather than appreciative inquiry, you’re not alone—perhaps the intersection of the two will open new possibilities in the future.

David Cooperrider

David Cooperrider is the co-founder of appreciative inquiry, developing its core principles and methodologies alongside Suresh Srivastva.¹ His work, especially at the Cleveland Clinic, demonstrated AI’s power in transforming organizational culture by focusing on strengths and positive inquiry. 

Suresh Srivastva

Suresh Srivastva co-developed appreciative inquiry with Cooperrider, contributing to its foundational ideas on dialogical change and positive organizational transformation.¹ He emphasized the role of conversations and stories in shaping an organization's future.

Jacqueline Stavros

Jacqueline Stavros is a leading scholar and practitioner of AI, known for co-authoring Appreciative Inquiry: A Positive Revolution in Change.⁵ She has contributed to making AI practical for organizational change, offering tools like the AI 5-D model to foster engagement and positive transformation.

Appreciative inquiry is not as simple as embracing a positive demeanor when you’re at work (although that’s important, too!). Like any model for organizational change, there are some effective ways that AI can have an impact. According to AI scholars and practitioners, three benefits we should recognize are its generative nature, energizing change, and improvements in work culture.

It’s Not Only Positive, It’s Generative

A common misconception and criticism is that appreciative inquiry is simply about staying positive no matter what—when, in reality, its primary focus is generativity.⁹ Generativity refers to the process of discovering new concepts, visions, and frameworks that lead to collective goals, ultimately creating more possibilities for action and decision-making. True AI is about putting generativity into practice, where individuals act on a better-envisioned future,⁹ such as when a team collaboratively creates a strategy for a more accepting workplace and immediately takes steps to implement inclusive practices.

Focusing on what is going well fosters positive emotions, which in turn lead to generative thinking and behaviors, increasing the likelihood of productive actions and innovative solutions. AI emphasizes potential rather than deficiencies, directing attention to what works instead of what doesn’t. This doesn't mean ignoring problems; rather, AI encourages first identifying issues and then shifting toward strengths-based solutions. For example, when addressing low employee morale, AI asks, "What strengths can we build on to improve engagement?" As Cooperrider said in 1990, it is “the positive” that creates images for generating and guiding action.⁹

A Focus on Energizing Change

By focusing on strengths and future possibilities, AI promotes long-term, sustainable change rooted in the positive core of an organization. This distinct ability to create a robust list of appreciative questions inspires rapport and energy within team dynamics.¹¹ In today’s fast-paced, technology-driven world, any motivating model is welcomed. AI increases buy-in by engaging stakeholders in exciting conversations, focusing on strengths and potential, which fosters shared ownership of the change process.

One such way that AI can incite change effectively is by catalyzing strong relationships defined by open, generative conversations that build trust and understanding among stakeholders.⁵ AI induces change by actively considering all perspectives and relationships, including those of consultants and managers who also appreciate AI. One way to look at this is a “spread effect” of the positive stories: these optimistic versions of people’s experiences are contagious—though we have to be vigilant about how negative stories can be contagious, too.¹⁰ As a result, energizing tales create common goals for change.

Positive Changes to Work Culture

Appreciative inquiry can positively impact company morale by fostering a strengths-based culture that emphasizes what works well. This approach enhances key aspects of a healthy work environment, such as employee engagement, morale, and collaboration.¹¹ By focusing on shared success and potential, AI cultivates a supportive and empowering workplace rather than one that is problem-ridden and stagnant.

We may remind ourselves here of the previous mention of a generative mentality to create an innovative version of work culture, with a focus on what works over what does not. This flexible mentality can result in a difference in how employees think across an organization: new ideas are openly shared on a large scale, and everyone has a say in creative ideas. AI has been put into practice as a means to make changes in work culture for the better, such as for partnerships between drug courts and research teams as well as the U.S. Navy for its leadership development program.^12,13

Any theory, model, philosophy, way of life, or whatever it is you prefer to label appreciative inquiry as, has its criticisms. Along with AI’s popularization came its waves of critiques around just focusing on just “the positives.”

Not Enough Research

A common criticism of AI is its emphasis on the positive without enough empirical support.¹⁰ Critics from the late 1990s and early 2000s questioned whether AI could produce verifiable data, as its outcomes often focus on qualitative aspects like improved relationships or mindset shifts. These are subjective, hard to quantify, and not easily measured with traditional quantitative methods. This raises concerns about how much of AI’s impact remains immeasurable and whether we can truly assess its positive effects.

Critics argue that this obsession with positivity overshadows the importance of addressing gaps and challenges within an organization. They contend that without a balanced approach grounded in empirical findings, AI cannot provide a comprehensive and accurate diagnosis of what needs to change. As such, AI practitioners can quantify their results by tracking measurable changes in engagement, collaboration, and problem-solving outcomes while still emphasizing the positive shifts in mindset and relationships that are central to the approach—despite the inherent subjectivity of these changes.

Negative Experiences Matter, Too

A key nuance to the overarching criticism that AI is overly positive is that by focusing on hopeful stories and experiences—especially in the Discovery phase of the 5-D cycle—negative experiences may be overlooked. Participants who have faced challenges within their organization may feel invalidated, unheard, or outright excluded. This critique highlights an important point: acknowledging the negative can be essential before shifting toward the positive.

Some who raise this particular critique have even suggested that if AI nullifies these negative experiences of pain, injustice, or even trauma, then the framework may have the opposite unintended consequences of what it wishes to generate: a lack of trust, less feelings of value, and disengaging outcomes.¹⁴ With this limitation, we must be mindful of the “bad actors” that can exist among its practitioners—managers, consultants, or AI leaders who use positivity as a way to overshadow or dismiss underlying negative experiences that need to be addressed. But even with good intentions, organizations may unintentionally overlook dissenting voices, which is why iterative, open feedback is essential to ensuring AI remains a truly inclusive and strengths-based approach.

Appreciative Inquiry Casts a Shadow

While many AI practitioners may claim that any negative vision has the potential to become a positive one, AI critics may claim that each positive vision has a negative one hiding behind it. One metaphorical yet visceral way to comprehend this criticism is to see AI as creating a shadow that censors any negative thoughts or emotions within an organization.¹⁵ In its original conception, this shadow represents those negatives that are intentionally left out in AI’s practice—yet still continue to linger underneath the surface.

Some may argue that we must identify the shadows of our stories to constructively criticize an organization as a means to bolster employees’ self-value during times of change. An issue may be that AI does not make space for these shadows—instead, casting a shadow over employees themselves. Though this is symbolic of perhaps AI’s biggest overarching issue of hyper-optimism, surely modern AI leaders can find ways to embrace and make sense of the shadow while still retaining the model’s generative potential.

Appreciative Inquiry for the McDonald’s Employee Morale and Engagement

Appreciative inquiry may apply to other unexpected contexts—like burgers and fries. In the early 2000s, McDonald's, like many global companies, faced challenges with employee morale and engagement. Looking for innovative solutions to strengthen their organizational culture, McDonald's turned to appreciative inquiry for help.⁶ With AI's focus on positive change and uncovering strengths, the company embraced a new way to engage employees and improve overall performance. The results demonstrated how AI could transform workplace dynamics and foster lasting change.

Through AI, McDonald's launched an initiative where employees at all levels were asked to reflect on and share positive stories about the company. By focusing on what was working well, they were able to identify key strengths and successes that could be built upon. This shift in perspective allowed employees to feel more valued and empowered, creating a stronger connection to the company's mission and values.

AI-based conversations took place across McDonald's global operations, focusing on strengths and potential instead of problems. As employees worked together and shared their insights, leaders were able to implement new strategies that led to improved communication, recognition, and innovation. The AI process facilitated better collaboration and created a sense of shared ownership in the company’s success.

The McDonald's case demonstrates how AI can be used to not only improve employee engagement but also enhance overall organizational culture. By focusing on the positive core, AI encourages a collaborative, strengths-based approach to change, leading to healthier work environments and more innovative solutions. This case suggests that AI could have long-term benefits for organizations looking to foster engagement and create lasting cultural transformation.

Appreciative Inquiry for Community Development in Africa 

Cooperrider believed deeply in the potential for creative, positive possibilities despite critics of his optimism. He viewed organizational inquiry as liberating, where concepts could come to fruition through AI.⁹ In the mid-1980s, this belief led him to join the Social Innovations in Global Management (SIGMA) research study. SIGMA marked a shift from focusing on positive change in American organizations to exploring AI’s potential in Africa, taking the approach to a global stage.

During this time, Cooperrider partnered with OD consultant Jane Magruder Watkins, who shared his passion for global community development. Watkins introduced Cooperrider to the importance of non-governmental organizations (NGOs) and joined him in applying AI in South Africa. This partnership inspired Cooperrider, who brought lessons from the East back to Western organizations, further expanding AI’s scope and influence.

Building on theories of social innovation, Cooperrider and a Case faculty member explored how NGOs could serve as vehicles for organizing change.⁹ They argued that successful NGOs demonstrated how leaders could unite people, concepts, and resources to overcome challenging boundaries. By studying thriving NGOs, they aimed to uncover insights into effective decision-making and management practices that could benefit other sectors.

SIGMA officially launched when the Dean at Case Western approved Cooperrider’s vision and provided $150,000 to study select NGOs. The project led to the creation of the Global Excellence in Management (GEM) initiative, championed by Watkins. From 1990 to 1995, GEM secured over $7 million in grants, engaging more than 20 faculty members and 150 NGOs. This work highlighted AI’s potential to drive innovation and social change on a global scale.

SOAR Analysis

From appreciative inquiry comes a variety of management tools and techniques that all sorts of leaders can make use of. In this piece, columnist Isaac Koenig-Workman breaks down SOAR analysis as a strategic planning framework that has AI in its blueprints. The details of SOAR and its four definitive features of Strengths (S), Opportunities (O), Aspirations (A), and Results (R) are discussed. 

Halo Effect

Appreciative inquiry isn’t the only time when the positive may have a big impression on people. This article breaks down a common cognitive bias called the halo effect. Here, we explore why positive impressions of people, brands, and products in one area may have a positive influence on how we feel about other areas. 

1. Stavros, J. M., Godwin, L. N., & Cooperrider, D. L. (2016). Appreciative inquiry. Practicing Organization Development, 96-116. https://doi.org/10.1002/9781119176626.ch6
2. Stavros, J. & Cooperrider, D. & Whitney, D. (2008). Appreciative Inquiry Handbook for Leaders of Change. 
3. Whitney, D. D., & Trosten-Bloom, A. (2010). The power of appreciative inquiry: A practical guide to positive change. Berrett-Koehler Publishers.
4. Cooperrider, D. L., Whitney, D. (1999). Appreciative Inquiry: Collaborating for Change. Barrett-Koehler Communications, Inc. 46 
5. Cooperrider, D. L. 1986. “Appreciative Inquiry: Toward a Methodology for Understanding and Enhancing Organizational Innovation.” Unpublished dissertation at Case Western Reserve University in Cleveland, Ohio.
6. Appreciative inquiry - A brief history - The appreciative inquiry Commons. (2016, August 2). The Appreciative Inquiry Commons. https://aicommons.champlain.edu/learn/appreciative-inquiry-brief-history/
7. Bushe, G.R. (2013). Dialogic OD: A theory of practice.  Organization Development Practitioner, 45:1, 11‐ 17.
8. Generic process of appreciative inquiry. (2024, March 31). The Center For Appreciative Inquiry. https://centerforappreciativeinquiry.net/resources/the-generic-processes-of-appreciative-inquiry-5ds/
9. Bushe, G. R. (2007). Appreciative Inquiry Is Not (Just) About The Positive. OD Practitioner, 39(4), 30-35. https://www.gervasebushe.ca/AI_pos.pdf
10. Bushe, G. R. (2012). Foundations of Appreciative Inquiry: History, Criticism and Potential. AI Practitioner, 14(1). https://www.gervasebushe.ca/Foundations_AI.pdf
11. Ludema, J.D., Cooperrider, D.L. & Barrett, F.J. (2000) Appreciative inquiry: The power of the unconditional positive question. In Reason, P. & Bradbury, H. (eds.) Handbook of Action Research (189-199). Thousand Oaks, CA: Sage. 
12. Calabrese, R., Cohen, E., & Miller, D. (2013). Creating a Healthy Workplace Culture Using an Appreciative Inquiry 4-D Cycle, Organization Management Journal: Vol. 10: Iss. 3, Article 8. Available at: https://scholarship.shu.edu/omj/vol10/iss3/8 
13. What is appreciative inquiry? (2014, October 3). Investopedia. https://www.investopedia.com/terms/a/appreciative-inquiry.asp#toc-history
14. Oliver, C. (2005b) ‘Critical Appreciative Inquiry as Intervention in Organisational Discourse.’ In Peck, E. (ed.) Organisational Development In Healthcare: Approaches, Innovations, Achievements, 205-218. Oxford: Radcliffe Press
15. Fitzgerald, S. P., Oliver, C., & Hoxsey, J. C. (2010). Appreciative inquiry as a shadow process. Journal of Management Inquiry, 19(3), 220-233. https://doi.org/10.1177/1056492609349349