Against Conceptual Heterogeneity: A Case Study of Academic Knowledge Curation
Developing a working definition of Innovation Ecosystems
One Significant Challenge of the THEORY-PRACTICE Gap is Conceptual Heterogeneity.
What’s Conceptual Heterogeneity? It refers to different people using the same word to express different conceptual meanings. It leads to Knowledge Fragmentation inside one discipline. Also, it raises the cost of cross-boundary collaborative projects.
As mentioned in AAI: Cross-boundary Knowledge Curation, one task of cross-boundary collaborative projects is building shared conceptual reality and language.
Today I will share an example of Academic Knowledge Curation. From this case study, we can learn how scholars solve the problem of Knowledge Fragmentation, especially the Conceptual Heterogeneity issue.
The case study is about the following simple question:
What’s Ecosystem?
I will use the Concept Dynamic model for this case study.
A Practitioner’s View
Though I wrote a book titled Platform for Development in 2021, I didn’t pay attention to the topic of Ecosystems.
I am a practitioner who doesn’t have a background in deep academic knowledge engagement with the concept of “Ecosystem”. However, I have to mention that I read the book The Startup Community Way: Evolving an Entrepreneurship Ecosystem.
Do I have common sense about the term “Ecosystem” from the perspective of business? I think I have. I understand the term “Ecosystem” as a large system in which a firm (a business organization) connects to other firms and other non-business social entities. Of course, I am talking about it in the context of social life, especially in the Business world, not the world of plants and animals.
Now let’s use the Concept Dynamic framework to map my notion about the term “Ecosystem”. See the diagram below.
The Concept Dynamics framework suggests four views on a concept:
- Ecological Reality: real experience with a concept
- Conceptual Reality: idea about a concept
- Linguistic Reality: name of a concept or ordinary language
- Context: what’s the background of the situation?
We can start with Context. As mentioned, I am talking about the term “Ecosystem” from the perspective of the business world and social life in general.
As a Practitioner, my common sense about the term “Ecosystem” comes from my knowledge of the word “Ecosystem” from the perspective of Linguistic Reality. I understand its “eco” part from the word “environment” and its “system” part from the word “system”. Thus, the term “Ecosystem” refers to the environment—organization relationship, and the environment is a large system.
Ecological Reality is about my real experience with the term “Ecosystem”. For example, I have over twenty years of work experience in the business world including startups and pre-IPO companies. My career can be divided into three stages: the creative stage, the strategic stage, and the innovative stage. At the creative stage, I worked for the advertising and media industry as a creative copywriter and designer. I had real experience with a local marketing-media-communication ecosystem.
At the strategic state, I worked for pre-IPO stage enterprises as a business strategist and fundraising consultant. I had real experience with two types of ecosystems: an operational level ecosystem (R&D — Supply-Produce-Marketing-Logistic) and a strategic fundraising ecosystem (VC-PE-Law firms — Accounting firms — Investment Banks — PR — Stock Exchanges).
At the innovative stage, I worked on making brand new digital tools and platforms as a researcher and designer. I had real experience with a professional ecosystem: Software Development Ecosystem (Programming language — Programming Frameworks — Operational Systems — Amazon Web Services — Apple App Store — APIs — Open-source Software).
As a Practitioner, I didn’t think about the Conceptual Reality of the term “Ecosystem” because I didn’t need to do it. I can talk about it with others without giving it a definition. If you ask me to give a definition, I’d like to say the following sentence :
A large system in which a firm (a business organization) connects to other firms and other non-business social entities.
This definition refers to two meanings: 1) It is a System, then we can use System theoretical approaches to understand its complexity such as the dynamics of Connections between a firm and others, and 2) It is an environment where a firm connects to others. Then we can apply Ecological theoretical approaches to understand the Organism — Environment — Organism relationship.
The above discussion represents the perspective of a Practitioner. The rest of the article moves to the academic world.
A Scholar’s View
In the academic world, a Concept is a foundational object of a knowledge enterprise. Scholars have to deal with the Conceptual Reality of a Concept. In fact, a significant aspect of academic creativity is developing a brand new concept in order to change a discipline’s objects, directions, methods, etc.
The tendency to Creating Conceptual Reality leads to Conceptual Heterogeneity.
As mentioned above, Conceptual Heterogeneity refers to different people using the same word to express different conceptual meanings. It leads to Knowledge Fragmentation inside one discipline. Also, it raises the cost of cross-boundary collaborative projects.
Let’s see an example from a scholar’s view.
In 2020, Llewellyn D W Thomas and Erkko Autio published a paper titled Innovation Ecosystems in Management: An Organizing Typology in Oxford Encyclopedia of Business and Management. According to the authors, the concept of an “ecosystem” is increasingly used in management and business and it led to conceptual heterogeneity and terminological confusion.
Due to its attractiveness and elasticity, the ecosystem concept has been applied to a wide range of phenomena by a variety of scholarly perspectives and under varying monikers such as ‘innovation ecosystems’, ‘business ecosystems’, ‘technology ecosystems’, ‘platform ecosystems’, ‘entrepreneurial ecosystems’, and ‘knowledge ecosystems’. This conceptual and application heterogeneity has contributed to con- ceptual and terminological confusion, which threatens to undermine the utility of the concept in sup- porting cumulative insight.
The paper reviews how the ecosystem concept has been applied to variably overlapping phenomena. The authors find that there are two key dimensions for understanding the complexity of the “ecosystem” concept ecology.
- Unit of Analysis
- The Type of “ecosystem service”
Some concepts of “ecosystem” emphasize alternative “Unit of Analysis”:
- Community Dynamics
- Output co-generation, and
- Interdependence Management
The “Participant Interdependence” issue is the most widely referenced characteristic of ecosystem. Scholars have discovered three aspects of the issues in management:
- Technological Interdependence
- Economic Interdependence
- Cognitive Interdependence
The other dimension refers to three distinct ecosystem outputs:
- Ecosystem-level value offering to a defined audience
- Collective generation of business model innovation, and
- Collective generation of research-based knowledge
According to the authors, there is a tendency for Thematic Fragmentation too:
Related to the ‘unit’ of analysis dimension, different levels also tend to be associated with different thematic emphases, in the sense of key challenges being ad- dressed. Whereas spatial applications tend to focus on various ecosystem community dynamics (e.g., learning and knowledge spill-over processes), non-spatial dimensions tend to emphasize issues related to governance and coordination.
A possible solution to cope with knowledge fragmentation and thematic fragmentation is developing a framework to turn these different versions of concepts into a meaningful whole.
Based on the above two dimensions, the authors develop a typology of the concept of “Ecosystem”. See the figure below.
The authors also develop the following ecosystem vocabulary.
- Ecosystem: A community of hierarchically independent, yet interdependent heterogeneous participants who collectively generate an ecosystem output.
- Innovation Ecosystem: A community of hierarchically independent, yet interdependent heterogeneous participants who collectively generate an ecosystem output and related value offering targeted at a defined audience.
- Entrepreneurial Ecosystem: A regional community of hierarchically independent, yet interdependent heterogeneous participants who facilitate the start-up and scale-up of entrepreneurial new ventures who compete with innovative business models.
- Knowledge Ecosystem: A regional community of hierarchically independent, yet interdependent heterogeneous participants who advance the translation of advances in research knowledge into products and services.
- Ecosystem Output: An system-level output that has been collectively generated by heterogeneous ecosystem participants.
- Ecosystem Value Offering: An ecosystem output that is targeted at a defined audience whose needs it helps address.
In the conclusion of the paper, the authors emphasize four characteristics of ecosystems:
- Community heterogeneity
- Ecosystem outputs
- Participant interdependence, and
- Distinctive governance
The authors also propose a general definition of an ecosystem:
A community of hierarchically independent, yet interdependent heterogeneous participants who collectively generate an ecosystem output.
Finally, the authors accept that ecosystems in management are organic, coevolving phenomena and they point out four dynamic aspects of innovation ecosystems:
- Emergence
- Competition
- Coevolution
- Resilience
I made the following diagram to represent the authors’ conceptual model.
The model is based on the Stage meta-diagram which is used for developing an integrated framework. You can find an example in D as Diagramming: The Mind as Play Metaphor.
Why don’t the authors use “Business ecosystem” to name the concept?
In 2021, Erkko Autio, one of the authors, published a paper titled Orchestrating ecosystems: a multi-layered framework. He claims the following reason for selecting “Innovation Ecosystem” for his knowledge enterprise.
Finally, the reason why I like to refer to ‘innovation ecosystems’ instead of, e.g., ‘business ecosystems’ is in order to emphasise the generativity that is inherent in ecosystems but typically lacking in supply chains. Generativity is the ability of ecosystems to facilitate unprompted, unpredictable innovative outputs from large, uncoordinated audiences (Zittrain, 2006). Ecosystem participants join the ecosystem on their own volition, often with the motivation to offer innovative inputs such as, e.g., novel content or innovative applications and features. The features of those features are not defined and largely not even constrained ex ante. This is an important distinction from supply chains, where the required inputs are contractually defined prior to delivery. Even though suppliers may innovative (e.g., car parts supplier inventing a novel monitor to ensure that the car does not stray beyond its lane), any such innovations must be approved by the OEM manufacturer and contractually defined in the supplier contract. This robs supply chains of much of the spontaneous generativity that ecosystem arrangements are able to facilitate. I submit that ecosystems are inherently more innovative than supply chains, hence my preference for the term: ‘innovation ecosystem’.
Now we can adopt the Concept Dynamics framework to discuss this case. See the diagram below.
The above Stage diagram represents the Conceptual Reality of “Innovation Ecosystem”. The authors use four perspectives to set a framework for reviewing various versions of the concept of “ecosystem” and discover four dynamic aspects of “ecosystem”.
The Linguistic Reality of “Innovation Ecosystem” refers to its name. Please pay attention to the last sentence:
I submit that ecosystems are inherently more innovative than supply chains, hence my preference for the term: ‘innovation ecosystem’.
Do you accept this reason?
I think the term “Business Ecosystem” is a good term for his knowledge enterprise. Though the author emphasizes the difference between “Innovation Ecosystem” and “Supply Chains”, we don’t have to lock “Business Ecosystem” with “Supply Chains”.
If the meaning of “Business Ecosystem” equals “Supply Chains”, then we don’t need the word “Business Ecosystem”.
From the perspective of Linguistic Reality, the word “Innovation” refers to the “Innovation” aspect of “Ecosystem”. This means “Innovation Ecosystem” could be perceived as a sub-concept of the general concept of “Ecosystem” by audiences.
However, the authors aim to develop a general concept of “Ecosystem” for the field of management and business. The term “Business Ecosystem” refers to a general meaning.
For academic projects, Ecological Reality refers to empirical research. The paper is not empirical research, so we can’t directly find any information to support Ecological Reality. However, we can find some information about “Business ecosystem”, “Modular ecosystem”, “Platform ecosystem”, “Entrepreneurial ecosystem”, and “Knowledge ecosystem” in the paper.
- Busienss ecosystem: When the research emphasis is on the broader economic context which a focal firm must monitor and react to, an innovation ecosystem has generally been called a ‘business ecosystem’.
- Modular ecosystem: Modular ecosystems deliver their value proposition through a co-alignment structure expressed as a shared product or service architecture featuring architectural interfaces that allow the platform ecosystem to be partitioned into a relatively stable set of modules (Baldwin & Woodard, 2009; Tiwana, Konsynski, & Bush, 2010). Examples from literature include, e.g., the semiconductor lithography equipment industry and the photovoltaic solar panel industry (Adner & Kapoor, 2010; Hannah & Eisenhardt, 2018).
- Platform Ecosystems: Platform ecosystems are innovation ecosystems that emphasize the role of technological dependencies in the ecosystem and mostly focuses on a specific class of technologies—namely, a shared connectivity interface broadly referred to as a ‘platform’.
- Entrepreneurial Ecosystems: Entrepreneurial ecosystems differ from innovation ecosystems in important respects. First, there is no ecosystem value offering targeted at a defined audience… Entrepreneurial ecosystems are predominantly a regional phenomenon. Experimentation-driven collective discovery and related knowledge exchange regarding effective business model recipes are facilitated by geographical proximity.
- Knowledge Ecosystems: The concept of ‘knowledge ecosystems’ features generic research-based knowledge and associated applications as their system-level output. This concept has primarily been employed in the innovation literature, reflecting the increasingly open processes of R&D and innovation (Bogers et al., 2017; Von Hippel, 2007)…Because of the emphasis of collective learning and knowledge exchange processes, knowledge ecosystems have been primarily described at a regional level of analysis and in pre-competitive settings (Clarysse et al., 2014; Järvi et al., 2018).
Finally, I’d like to point out an issue between Linguistic Reality and Conceptual Reality. See the diagram below.
The authors define the concept of “Ecosystem” as “A community of hierarchically independent, yet interdependent heterogeneous participants who collectively generate an ecosystem output.”
It means: an Ecosystem is a Community.
A Community of […] participants who […] generate an Ecosystem output.
This definition has a Linguistic issue because it uses “an ecosystem output” to define it. What does the term “ecosystem” of “an ecosystem output” mean?
Also, the definition can lead to a reductive consequence. If we read the definition carefully, we can claim that “Innovation Ecosystem” is a sub-category of “Community”.
If this is the case, we can directly use “X Community” to name “A Community of […] participants who […] generate an Ecosystem output”.
It seems that the authors emphasize the “A Group of Actors” > “A Collective Output” process. Thus, this definition is a teleological concept because it gives a goal to “ecosystem”.
I can understand that the authors want to define a scope of research that emphasizes the perspective of firms. However, does an ecosystem have a goal?
More Scholars’ Views
Now let’s find more perspectives from other scholars. In 2020, Ove Granstrand and Marcus Holgersson published a paper titled Innovation Ecosystems: A conceptual review and a new definition. I will use it for our discussion.
In the Introduction, the authors tell us a different story:
A systems approach in studies of complex phenomena has a long tradition in a broad range of disciplines. The basic concepts and methodology of the approach have repeatedly been adopted, modified and further developed by new scholarly communities.
From time to time this popularity of the approach has resulted in a flurry of derivative concepts, paralleled by popular and less stringent use of them, constituting a phenomenon in itself.1
In innovation studies, the concept of innovation systems has been widely used, often with different qualifiers such as national innovation systems (Freeman, 1987; Lundvall, 1992) or sectoral innovation systems (Breschi and Malerba, 1997).
The authors clearly point out that the theme is “a systems approach to innovation studies”.
This story is different from the story told by Llewellyn D W Thomas and Erkko Autio.
The challenge of the new story is the “system v.s. ecosystem” issue. Why do we need “eco” for the systems approach?
During the last 15 years, the concept of innovation ecosystems has become popular with a rapidly growing literature (cf. Gomes et al., 2018), typically with a business and strategy origin and focus.
…
Oh et al. (2016) criticize the concept with regards to its usefulness and distinctiveness in relation to extant conceptualizations of innovation systems and with regards to the biologically inspired “eco” qualifier and its arguably flawed analogy to natural ecosystems.
Ritala and Almpanopoulou (2017) agree with the critique that the concept is used ambiguously, but suggest that the concept may nevertheless provide a useful addition to the conceptualizations of innovation and innovation management, and call for more conceptual and empirical rigor.
Finally, Baiyere (2018) observes a limited consensus among researchers about what innovation ecosystems actually are, despite the concept's widespread use. The innovation ecosystem concept has thus become not just a metaphor but also a persuasive definition and an essentially contested concept, calling for a conceptual review and analysis.
Against Conceptual Heterogeneity!
The authors set a goal to develop a synthesized definition of an innovation ecosystem in order to increase consensus with the following principle:
In general terms conceptualizations of social behavior should balance generality, simplicity, and accuracy (Weick, 1979). More specifically our proposed definition should fulfill certain requirements such as:
1. Filling an empirical and/or theoretical need in light of existing concepts
2. Being sufficiently precise, parsimonious, and logically consistent (without circularity)
3. Being possible to operationalize, qualify, typologize and use for taxonomies
4. Being syntactically and semantically compatible with common conceptualizations of related concepts, in our case the concepts system, innovation system and ecosystem
The authors use the following workflow for the project.
They did a basic search for “innovation ecosystem” in Web of Science and found 303 publications on Dec 25, 2018. They decided to use 120 articles for their research. Finally, they found a sample of 21 explicit and unique definitions of the innovation ecosystem concept.
The next step is hard. See the following details:
When the definitions had been identified, they were analyzed and the content of each definition was coded using open coding (Berg, 1989). This process led to a list of 24 component codes.
These component codes were analyzed in order to find joint themes of codes, leading to seven component themes. For example, codes covering knowledge, resources, products, and platforms all relate to artifacts in the innovation ecosystem, and are therefore thematically grouped within the coding theme artifacts. A few component codes are included in two different component themes. For example, the component code ‘co-creation’ is part of both ‘collaboration’ and ‘activity’, as it is an innovation activity that is performed jointly by several actors.
The scheme of component themes was then validated by coding all definitions again, but now based on the higher-level themes instead of open coding, and then comparing the coding. The resulting coding scheme is illustrated in Fig. 3.
The above results led to a new definition of an innovation ecosystem:
An innovation ecosystem is the evolving set of actors, activities, and artifacts, and the institutions and relations, including complementary and substitute relations, that are important for the innovative performance of an actor or a population of actors.
They also made a diagram for the new definition.
How to read the above diagram? There are three subsystems within an innovation ecosystem:
- Actors sub-system
- Artifacts sub-system
- Activities sub-system
According to the authors, “This idea of interconnected actor/artifact/activity subsystems of innovation ecosystems goes well in line with the concept of natural ecosystems, which are typically decomposable into subsystems”.
- In this definition artifacts include products and services, tangible and intangible resources, technological and non-technological resources, and other types of system inputs and outputs, including innovations.
- An innovation ecosystem could in other words include an actor system with collaborative (complementary) and competitive (substitute) relations with or without a focal firm, and an artifact system with complementary and substitute relations.
- Innovative performance is used rather than innovations or innovativeness in order to include related imitations in the system and to facilitate operationalizations in economic terms, and by so doing also avoid circularity.
The authors also test the new definition with several empirical examples. You can find more details in the original paper.
Let’s apply the Concept Dynamics model to this case too. See the diagram below.
This time I pay attention to the Ecological Reality aspect of this case. The authors share three empirical examples in their paper:
- The innovation ecosystems in video cassette recorders (VCRs): The multi-level “systems competition” between Sony's Betamax ecosystem and JVC's VHS ecosystem in the 1970s and 1980s is by now a classical case, well documented in the literature (…).
- The innovation ecosystems in mobile telecommunications: The case of the development of mobile telecommunication systems illustrates evolving innovation ecosystems over several decades, involving shifts between different technological generations. In this sequence of generation shifts the artifact system was radically transformed through creative destruction with entries and exits, as was the actor system. In each generation there was one or more technical compatibility standard(s), which enabled complementarities across a set of components in the system.
- Apple’s innovation ecosystem: One of the main actors in the mobile telecommunications ecosystem was Nokia, an active contributor to telecommunication standards and the world's largest mobile phone manufacturer during the first decade of the 2000s. However, after the introduction of Apple's iPhone, Nokia quickly lost its lead,…The most important one among these competitors was Apple. In its work with the music player iPod, Apple had successfully positioned itself as a systems integrator and managed to build up an ecosystem of complementary technologies and actors, including content providers (record companies/music publishers) (Schoemaker et al., 2018). Applying the same strategy in mobile telecommunications and smartphones proved to be extremely successful.
How can the authors put these three cases in the same category?
According to the authors, “In contrast to the Apple case the VCR case and the mobile telecommunications case both illustrated multi-centric ecosystems, and in contrast to the VCR case and the Apple case the mobile telecommunications case illustrated how an innovation ecosystem evolved over a sequence of generation shifts with creative destruction taking place in the artifact system as well as in the actor system, with a manageable rather than a rigid coupling between these two processes.”
The authors also emphasize the “systems approach” behind the concept, “In line with the spirit of a systems approach, innovation ecosystems could be decomposed into several innovation ecosystems, in which case they may compete or complement each other (cf. Adner and Kapoor, 2010).”
If we accept the “sub-ecosystem” and “ecosystem” for empirical research, then we can understand Apple’s innovation ecosystem as a sub-ecosystem of the innovation ecosystem of mobile telecommunications.
Three Issues of Conceptual Heterogeneity
The above discussion presents three definitions of the concept of “Innovation Ecosystem”:
#1
A large system in which a firm (a business organization) connects to other firms and other non-business social entities.
#2
A community of hierarchically independent, yet interdependent heterogeneous participants who collectively generate an ecosystem output.
#3
An innovation ecosystem is the evolving set of actors, activities, and artifacts, and the institutions and relations, including complementary and substitute relations, that are important for the innovative performance of an actor or a population of actors.
We can find several issues of conceptual heterogeneity in this discussion.
The gap between Naming and Conceptual Reality
This gap refers to the difference between Practitioners’ perspectives and Scholars’ perspectives. See the diagram below.
Practitioners tend to use concepts as names of things they are working on. In the daily life world, practitioners can’t use a word with a specific meaning for normal communication. For example, we can use the word “ecosystem” in the following definitions.
However, Scholars aim to produce new knowledge that leads to new conceptual creations.
The gap between Different Contexts
Inside the academic world, there is also a gap between different scholars. Two definitions of the above three cases are from the field of business and management study.
However, these authors work on different things. Authors of #2 care about the general concept of “ecosystem” in the field of management and business while authors of #3 focus on the “systems approach” to innovation research.
According to Ove Granstrand and Marcus Holgersson, “During the last 15 years, the concept of innovation ecosystems has become popular with a rapidly growing literature (cf. Gomes et al., 2018), typically with a business and strategy origin and focus. This focus is in contrast to the dominant policy and institutional focus in the innovation system literature and the two literature streams have so far been largely disconnected, despite the syntactic closeness of the two concepts. ”
The above diagram shows the complexity of this gap.
- The different contexts set different boundaries for the concept of “innovation ecosystem”. Two literature streams have their own boundaries.
- Empirical researchers tend to invent new concepts and names for their objects and new ideas without considering other researchers’ terms.
- Theoretical researchers tend to invent new theoretical concepts to explore new ideas.
These issues lead to Academic Knowledge Curation such as in the above two cases.
The gap between Problems and Solutions
The above two papers offer two solutions for defining the concept of “Innovation Ecosystem” for the field of business and management.
It seems that the results are not perfect. We still see a gap between problems and solutions.
How can we improve this type of Academic Knowledge Curation?
One idea is to make a distinction between Concept and Construct. See the diagram below.
Llewellyn D W Thomas and Erkko Autio mention Concept and Construct in their paper.
We deliberately refer to the term ‘ecosystem’ as a concept to underline the as-yet early stage of theoretical development in this area.
A ‘concept’ is a generally accepted term to refer to a phenomenon or instance that may or may not be well understood theoretically.
A ‘construct’ is a statement of a concept that is useful for theorizing;
a ‘construct’ lends itself for empirical operationalization, whereas a ‘concept’ may not (Suddaby, 2010).
If we adopt these two terms for the Concept Dynamics, we can see three types of activities:
- Theorizing: Construct
- Forming: Concept
- Naming: Word
The Theorizing Activity is about connecting Ecological Reality and Conceptual Reality. The outcome is a Construct that can define a theoretical concept for academic research.
The Forming Activity is about connecting Conceptual Reality and Linguistic Reality. If you have an idea about a conceptual creation, how do you present it in texts, diagrams, or other forms? For the present discussion, the term Concept is more about defining a general theme for a field of academic research.
The Naming Activity refers to normal life communicative practice which is about connecting Ecological Reality and Linguistic Reality.
We can also use “Theme/Concept” to replace “Concept/Construct”.
- Theorizing: Concept
- Forming: Theme
- Naming: Word
Finally, we reach the Conceptual Heterogeneity of “Concept”. This task is a really hard challenge.
If we return to the case of “Innovation Ecosystem”, it is clear that the above authors want to develop a Theme/Concept as a general term for their field.
I’d like to suggest they pay attention to the gap between Word and Concept. A general Theme/Concept should be simple as a normal Word.
Separate Approaches from Themes/Concepts
Moreover, we should separate Approaches from Themes/Concepts. For example, “systems approach” refer to the theory of systems approaches. We don’t have to describe it in the themes/concepts.
The #3 definition is similar to the Activity-theoretical approach. Let’s see the diagram of #3 again.
Activities, Actors, Artifacts, these words are close to Activity Theory.
Activity Theory or the “Cultural-historical activity theory (CHAT)” is an interdisciplinary philosophical framework for studying both individual and social aspects of human behavior. From the perspective of Activity Theory, human activity or ‘what people do’ represents the basic unit of analysis when studying human behavior. The most important aspect of Activity Theory is understanding both individual and collective aspects of human practices from a cultural and historical perspective.
Yrjö Engeström upgraded the activity theory from the individual activity level to the collective activity level with a conceptual model of “activity system” in order to apply activity theory to educational settings, organizational development, and other fields (Engeström,1987). See the diagram below.
Activity Theorists also use “Activity Network” to understand connected activity systems. See the diagram below.
This variation is a promising direction to connect Activity Theory with the current dynamic work landscape.
If we use the “Activity Network” perspective to re-read the above authors’ papers and their ideas, then we can find the #3 paper almost conduct a research project from the Activity-theoretical perspective.
In this way, #3 is a Construct that connects Activity Theory with Innovation Ecosystem research. It is not an ideal theme/concept for the field.
Definitions, Domains, and Dynamics
Though the authors’ results are not ideal. We can learn more about the concept from their papers.
Why? Because their papers offer details of their conceptual work.
Learning a concept is more than reading its definition.
We need to understand the conceptual creation process behind making the definition.
We need to identify the boundary of context and the real stories of the domain.
We need to see the whole picture of the “Naming — Theorizing — Forming” dynamics behind a concept.
