From Ideas to Streamlined Research: The Benefits of Full-Cycle Methodology

December 5, 2023

From Ideas to Streamlined Research: The Benefits of Full-Cycle Methodology

Becoming a lead researcher can be daunting, brimming with uncertainties and complexities. Which hypothesis should I test first? What steps should I take? When is a project really done?

While pursuing to become a lead researcher, I was taught to convert theoretical ideas into solid research and publications. However, I also encountered a type of knowledge that could not be easily articulated and transferred—intuitive skills and insights gained from research experience, akin to learning to ride a bike or understanding cultural nuances.

I initially thought working closely with seasoned researchers was the only way to learn these tacit skills and insights. However, my engagement in full-cycle research introduced me to a different perspective. When I first heard 'full-cycle research' in a department meeting, it appeared to be just another academic term. However, as I learned more about it, I started seeing its value.

Full-cycle research is far more than just a shift from traditional methods, and means to develop an idea from its beginning to the final creation of research output. This implies a dynamic interaction within the research process, enabling initial concepts to grow and adapt as the study progresses. Full-cycle research offers a streamlined approach, enhancing every phase of the research journey.

Learning about full-cycle research allowed me to understand the subtle techniques that experienced researchers use, supplementing my traditional educational experience. I want to share some of these strategies in this post. My goal is to provide a clear, practical guide for both new and seasoned researchers in social sciences, natural sciences, and humanities. In the following sections, I will clarify the concept of full-cycle research and how we can use it to do research more effectively.

What is Full-Cycle Research?

Full-cycle research is an interconnected endeavor, beginning with observing the world around us. It involves immersing yourself into the environment in which your research takes place, in order to understand real occurrences and uncover underlying reasons. This observational phase is pivotal in forming theories and hypotheses (1).

Suppose, for instance, that you want to study public support for a health policy by looking at relational bonds and social identification. Instead of starting with a hypothesis developed in your office, understanding the policy’s impact on the attitudes of its supporters and non-supporters necessitates observing the real world—yielding complexities that are hard to detect in labs. It is this kind of attendance to real-world phenomena that you find in great peer-reviewed and published work using full-cycle research. For instance, in “The Artisan and His Audience,” researchers observed actual artisans in Southern India, leading to discoveries about their pricing behaviors and motivations, which wouldn't have surfaced through other methods (2).

The next phase moves from observing to experimenting. This involves controlled studies and simulations to test theories, identify causal relationships, and specify the phenomena's boundary conditions through the controlled manipulation of variables. Experimental research plays a key role in deepening our understanding and broadening the generalizability of your findings (1). In the experimental phase of the artisan study, a field experiment was conducted to test the hypothesis that artisans offer lower prices to discerning customers—‘those knowledgeable about and appreciative of their work’—while offering market prices to non-discerning ones (2).

Crucially, full-cycle research is not linear. It continually evolves, with further observations and experiments leading to new insights and adjustments (1). This process requires flexibility, critical thinking, and an open mind. The artisan study beautifully demonstrates this. After the previous experiment, the researcher introduced surveys to explore the role of a related concept, product attachment, in artisans’ pricing behavior. This revealed that when artisans were more involved with the work process and more creatively engaged with their work (indicators of product attachment), they cared more that their customers appreciated their work. Therefore, artisans highly attached to their products were more likely to give greater discounts to appreciative buyers and charge non-discerning buyers higher as a penalty than the artisans who didn’t creatively engage with their work (2).

In essence, full-cycle research is a dynamic, ongoing process of learning, adapting, and integrating different research stages. It's about connecting dots and exploring complexities, yielding insights that are both theoretically and empirically grounded.

Full-Cycle Methodology for Social, Humanities, and Natural Scientists

Non-full-cycle researchers stand to gain immensely from embracing the comprehensive and iterative nature of the full-cycle research approach. Whereas traditional research might concentrate on a single method or follow a linear, either inductive or deductive progression, full-cycle research endorses a more dynamic exploration. It is comparable to a detective’s odyssey across various fields, each phase merging insights informing the next.

For instance, a researcher primarily focused on quantitative experimental methods could substantially enrich their study by incorporating observational or qualitative elements. This integration deepens the understanding of the phenomena and refines the research question more effectively. Conversely, a qualitative researcher could benefit from incorporating quantitative analysis to bring more rigor and scalability to their findings. Full-cycle research combines diverse approaches and perspectives—like melding field observations with controlled experiments or theoretical analysis—to prevent a project from getting stuck in a methodological or theoretical silo.

Let me now turn to some more examples of what doing full-cycle research looks like. Picture three researchers from different disciplines: a social scientist examining the impact of social media on mental health, a historian unraveling the complexities of an ancient civilization, and a marine biologist investigating ocean pollution. All of them could, in their own way, use the full-cycle methodology to make progress in their research agenda.

Each researcher commences with extensive observation: the social scientist delves into online behaviors or conducts preliminary surveys; the historian meticulously examines texts and artifacts; the biologist undertakes fieldwork in marine ecosystems. These preliminary observations set the stage for developing research questions and theories. The social scientist might probe the varying influences of social media platforms on user well-being, while the historian could investigate the role of cultural symbols in ancient societies, and the biologist may study the specific effects of pollutants on marine life. This first phase is characterized for each project by collecting extensive information, spotting patterns, anomalies, or themes pertinent to their disciplines, culminating in the formation of theories and hypotheses.

In the next crucial stage of their research, each specialist would rigorously test their developed theories with manipulative methods, seeking to uncover causal relationships and define the specific conditions under which these phenomena occur. The social scientist, delving into the intricacies of the psychological impact of social media, designs and executes controlled lab or field experiments. These are structured to investigate how social media usage influences mental health methodically. By manipulating variables like the amount of time spent on social media or the types of content interacted with, the social scientist aims to establish concrete causal links to understand if and how these factors directly affect mental well-being. 

The historian, meanwhile, uses an advanced agent-based modeling technique to create complex simulations of historical events. This digital reconstruction allows for manipulating various political, social, or cultural factors to observe their potential effects on historical outcomes. By altering these elements within the simulation, the historian can test specific hypotheses about the influence of certain cultural symbols or practices on the evolution of ancient societies. 

The marine biologist, focusing on the environmental sciences, conducts a series of controlled experiments to examine the impact of different pollutants on marine life. These experiments are designed to replicate various oceanic conditions, allowing the biologist to systematically observe how different types and concentrations of pollutants affect marine species. Through this process, the biologist can not only identify the specific harmful effects of each pollutant, but also generalize these findings to broader ecological contexts, enhancing our understanding of pollution’s impact on marine ecosystems.

All three researchers contribute to their fields through manipulation activities, using unique methods to dissect and interpret complex phenomena. In the next stage, the synthesis phase, they integrate their discoveries into a broader context. The social scientist might infer wider implications for societal well-being by analyzing the relationship between social media and mental health. The historian, leveraging agent-based modeling to simulate historical events, could offer fresh interpretations of ancient cultural practices. Similarly, by observing the effects of pollutants on marine species, the marine biologist might propose strategies to mitigate ocean pollution. This stage is pivotal for forming a cohesive narrative that enriches our collective understanding. 

Throughout this process, the researchers continually revisit and refine their work, embodying the cyclical nature of full-cycle research. They might return to earlier stages for deeper investigation or modify their hypotheses in response to new findings. This iterative process is an informal yet effective guide for developing and testing hypotheses, expanding upon them, and engaging in further observation and experimentation. It also necessitates an exhaustive blend of methodologies, from hands-on fieldwork to comprehensive theoretical analysis, in order to attain a thorough and enriched view of one’s research object. The social scientist returns to further observation and runs new experiments based on new insights; the historian engages in critical textual analysis to complement simulation findings; the biologist evaluates additional experimental data for ecological insights. They all connect various research stages, embracing the journey's twists and turns and persistently striving to advance the knowledge in their field.

Learning about the full-cycle research approach represented a paradigm shift in academic inquiry for me. It offered a dynamic, cyclical, and holistic pathway to evolve from initial curiosity to impactful work. Regardless of the discipline, it empowers us to seamlessly transition from vague curiosities to structured, insightful research projects. Personally, it reinvigorated me as a researcher, and showed me that academic work—which is often reduced to following predetermined methodological steps—can be more thoughtful, more dynamic, and lead to actual discovery. 


  1. Chatman, J. A., & Flynn, F. J. (2005). Full-cycle micro-organizational behavior research. Organization Science, 16(4), 434-447.
  2. Ranganathan, A. (2018). The artisan and his audience: Identification with work and price setting in a handicraft cluster in Southern India. Administrative Science Quarterly, 63(3), 637-667.