Exploration of metaphors as a way to understand socio-technical phenomena: An emergent framework

2.1 Metaphors

Information polity, digital government, and information system communities, in general, apply metaphors frequently to comprehend and communicate socio-technical phenomena. The anatomy of a metaphor is displayed in Fig. 1, where a sender and a receiver possess initial thoughts and initial words that they can apply to communicate the initial phenomenon to the receiver. A sender who encounters a new target phenomenon and experiences target thoughts about it but lacks target words can find it challenging to communicate. The sender can solve this problem by abstracting his thoughts about similar phenomena to produce a metaphor as a generalisation (Ogden & Richards, 1923).

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The sender borrows initial words to apply as target words (metaphors). A metaphor also borrows partial thoughts of one phenomenon to apply to a target phenomenon, a form of generalisation. Morgan (1998) describes that “[ … a] metaphor proceeds through implicit or explicit assertions that A is (or is like) B.” (Morgan, 1998, p. 4). As such, metaphors are a conceptual approach to recycling and expanding previous knowledge to the unknown. The receiver infers similarities between an initial phenomenon and a target phenomenon from a metaphor that excludes others (Lakoff & Johnson, 2008a). The receiver must, therefore, sort out the differences and focuses on the similarities (Glucksberg, 1989).

However, some similarities may only be superficial, which can make a metaphor misleading (Mars, Bronstein, & Lusch, 2012). A metaphor aids by providing a specific perspective on a target phenomenon. However, the receiver’s understanding of a metaphor depends on his experiences with the initial phenomenon (Lakoff & Johnson, 2008a). A metaphor implies a way of thinking as it brings a specific structure to target thoughts based on initial thoughts and a way of understanding the world (Lakoff & Johnson, 2008a; Morgan, 1998). For example, technical debt refers to a debt that should be repaid; however, this is not always the case for technical debt. As a result, a sender and a receiver can evaluate a metaphor as beneficial or disadvantageous based on how well it conveys target thoughts about the target phenomenon.

The application of metaphors in a community can be understood from the meme perspective (Dawkins, 2016). A meme is a convenient unit of cultural transmission (e.g., an idea or a tune) that can jump from one sender to another receiver through a process of imitation. A meme can be a metaphor, which we presume in this article. A metaphor spreads from sender to receiver through imitations where the metaphor can mutate or blend with other ideas (or metaphors). A metaphor spreads based on whether the receiver perceives the metaphor as having utility and appeal (Dawkins, 2016). A metaphor’s appeal relates to how well it can communicate a target phenomenon. The metaphor borrows the structure of the initial phenomenon to apply to the target phenomenon initially, and the focus is on the similarities between the initial phenomenon and the target phenomenon (Glucksberg, 1989; Lakoff & Johnson, 2008a; Ogden & Richards, 1923). A high-appeal metaphor entails being a well-known initial phenomenon and where the similarities between the initial and target phenomena are easily identified. The metaphor loses its appeal if the dissimilarities between the initial and target phenomenon create more problems than the similarities provide understanding. For example, the ‘e’ (electronic) is slowly dying as digital, online, and virtual is taking over (e.g., the eGovernment is becoming Digital Government). A beneficial and high-appeal metaphor can be characterised as self-explanatory (Ortony, 1975), while a low-appeal metaphor can generate confusion and despair (Ortony, 1975). However, a metaphor can have high appeal but also be disadvantageous, as such spreading quickly with consequences. On the other hand, a metaphor can lie dormant for years in various mediums (Dawkins, 2016), such as the metaphor “Technical debt”, which was first introduced in 1992 by Cunningham. It took a decade before it was picked up and discussed in the academic community (Tom, Aybuke, & Richard, 2012). A metaphor can co-adapt to ideas and other metaphors in its environment where associations are entrenched. It grows interdependent on other ideas and metaphors and can no longer exist without them. Possibly, they self-reinforce each other. This situation can lead to stable structures of assemblages of metaphors,1

We used a hermeneutic literature review with citation tracking and citation analysis (Boell & Cecez-Kecmanovic, 2014) to review previous metaphor research. We combined the keywords “metaphor” or “metaphor development” with “communities” or “organisations” in Google Scholar. We skimmed titles, abstracts, and if they were relevant also the content. Then, we determined whether it would enable us to understand metaphors and their development. We classified relevant literature following title, purpose, research problem, keywords, limitations, implications, explanatory power, and interesting statements. In total, we classified 21 articles and 2 books.

We synthesised an emergent analytical framework based on the relevant literature. Its purpose is to analyse the application of metaphors by senders. An analytical framework, like a theoretical framework, draws concepts from a theory to shed light on a phenomenon Imenda (2014). We understand that an analytical framework leaves certain concepts open to be filled with empirical material and, as such, allows for the generation of new explanations and insights. The analytical framework guided and enabled us in explaining and interpreting the empirical material Imenda (2014). Moreover, the method of synthesis was concept mapping where we defined concepts and their relationships (Maxwell, 2012). This part of the phase started with an online discussion where we compared the relevant literature to identify concepts and relationships. This discussion was supported by a cloud-based diagram software where we could represent the framework. We continued to develop the framework drawing on the literature and when needed, we arranged for new discussions. In this process, several tentative frameworks were developed and discarded or merged based on perceived utility. We iterated between synthesis, data collection, and data analysis, allowing the final analytical framework to emerge over time. The outcome was the emergent analytical framework labelled the CAOM framework (see Section 4).

3.2 Phase 2: Data collection

We selected OGD and TD communities because of our existing knowledge of the two communities, and their accessibility. Additionally, these communities are interesting because of their differences in community characteristics, their active metaphor usage for a present socio-technical phenomenon, and the communities containing a mix of researchers and practitioners.

We first analysed the empirical material in MaxQDA using a word frequency analysis and then in-depth based on the CAOM framework (see Section 4). Both methods used metaphor density to inform us about possible shifts in the communities’ application of metaphors. Density was calculated per metaphor for each year by summing metaphor applications in the year and dividing this amount by the number of documents for that year.

Metaphor Frequency Analysis. The word frequency analysis (WFA) (see Izwaini, 2003) resulted in statistics about the frequency of certain words in the empirical material. It provided us with an estimation for metaphor usage, as the method does not consider the word’s context. This analysis followed three steps. First, we identified search terms for a dictionary. We understand categories as metaphor groups where the search terms are possible metaphorical words (Table 3). To remove unnecessary words, we applied WFA with filters of word frequency above 19, length above two, and the standard stop list of MaxQDA. We sorted out everyday, non-metaphorical, fragmented words into a stop list or our dictionary and included metaphorical words into a dictionary. We discussed uncertain words and decided their status. For OGD, we started with 373.297 possible words and ended up with 190 metaphorical words. For TD, we began with 393.103 possible words and ended up with 76 metaphorical words. Second, we discussed and rearranged the metaphorical words into metaphor groups, and we decided to focus on six OGD groups and six TD groups. Third, we applied the metaphorical groups to the empirical material for their respective community using MaxQDA’s category matrix browser. We examined the matrix for patterns. If we identified anything unexpected or unusual, we browsed the metaphor group and its search terms in the respective documents. If a word was used more in a non-metaphorical manner than in a metaphorical manner, we divided it into more specific metaphorical words. For example, the search term climate counts climate change, as such, we divided it into the metaphorical words political climate, business climate, and organizational climate. On the other hand, some words could not be specified because of complexities in context, these words were deactivated in our dictionary. For example, in TD, we deactivated negative as it is primarily used to describe results rather than as a metaphor for an ‘Emotion’. We visualised the final statistics as charts in Excel to reveal patterns. The charts were based on the metaphor’s usage density. We discussed the charts to draw tentative conclusions about the communities’ application of metaphors. The charts presented the statistics by year divided over the practical and research parts of the communities. Then, we applied the CAOM framework and examined the charts for metaphor usage and expression. We analysed usage by studying changes in metaphor density for and between years (short-time changes, revealing the speed of replication), while we analysed expression by examining the usage over time (illustrated by six patterns Section 5, revealing stability over time). The assemblages of metaphors could only be explored in the qualitative analysis.

Qualitative Analysis. We discussed the patterns to decide on one metaphor per community to explore deeper. We decided to explore the application of ‘Ecosystem’ (for OGD) and ‘Technical debt’ (for TD) based on their differences in application and metaphor density. We created an analytical template based on our emergent analytical framework (see Section 4) that we filled out with the empirical material for the selected metaphors. We applied the framework for each year and examined the density and application of the metaphor. We used the emergent analytical framework to examine how it has changed over time within a community. We paid attention to deviant cases or negative cases to ensure the quality of our findings and framework. We examined the individual items or cases which appear to deviate from the developed framework (Mays & Pope, 2000).

7.1 The application of metaphors

In this section, we focus on the identified patterns and assemblage of metaphors in the communities (see Sections 5 and 6). Our findings show that researchers discuss, share, and apply metaphors for conceptual developments, whereas practitioners primarily apply metaphors. Researchers display a higher metaphor density than practitioners and cite previous research. It is, as such, easier to trace the development and changes of metaphors in the research part of the communities. This difference is most likely a reflection of the researchers developing knowledge about less known socio-technical phenomena while practitioners are encountering or creating these phenomena (Matthiasen & Nielsen, 2008; Van De Ven, 2007).

Communities’ Application of Metaphors. The first research question asked how and why metaphors had been applied in the OGD and TD communities’ conceptual developments. The Sections 5 and 6 provides an answer for the how, but the findings need further highlighting to give an idea about why the communities apply metaphors in a certain manner.

The communities apply several metaphors each playing a specific role within an assemblage. OGD is a name for the core socio-technical phenomenon (the data that are published and reused following certain principles (Attard et al., 2015) but needs metaphors to be further developed and give context. For example, ‘Ecosystem’, ‘Market’, and ‘Industry’ give terms to describe the larger systems of actors and interactions surrounding OGD. On the other hand, ‘Technical Debt’ is both a developing metaphor, but also the everyday name for a specific socio-technical phenomenon. TD community develops more the metaphor compared to OGD because TD is the core of the TD field. While the socio-technical phenomenon influences what metaphors senders decide to apply in their conceptual development (see Section 2), we see no clear relationship between a socio-technical phenomenon and how senders apply metaphors in their conceptual development. An outliner is that OGD researchers never applied the Ecosystem metaphor as a tool within the explored time period, but we know from previous OGD research that it has been used as a tool (e.g., Harrison et al., 2012). Rather, we propose that the significance of a metaphor’s role in its assemblage influences how senders apply metaphors. The findings show that a peripheral or insignificant role tends to come with high everyday usage. While it is consistent for 19 of 24 years, there are some negative cases: 2016 for OGD practitioners, 2015 and 2020 for TD practitioners, and 2017 and 2020 for TD researchers. These negative cases cannot be explained by the used research approach, as such opening new research avenues.

Additionally, the OGD and TD communities vary further in community type. OGD is an open public community with more complex interactions, making it challenging to separate concepts and metaphors. We expected that this openness would have contributed to a higher degree of development for the Ecosystem metaphor, as ideas and knowledge can easily flow in and out of the community. However, this was not the case. Instead, they had high usage of various metaphors. On the other hand, TD is a semi-private community, with a strong core of researchers and software developers who are developing the metaphor. They appear to take ownership of the socio-technical phenomenon and try to solve the challenges it poses. The phenomenon is expanding to other communities (e.g., engineering) and other job functions (e.g., management). A surprising insight is that an open community applies more peripheral metaphors through an everyday usage, while closed communities developed more core metaphors.

As an answer to the ‘why’-question, we propose that while the socio-technical phenomenon influences what metaphors senders apply in their conceptual development, the metaphors’ role within an assemblage and community type influence how senders apply them in their conceptual development. Thus, we expand on Lakoff and Johnson (2008a) arguments that metaphors structure our thinking and are influenced by how we perceive their origin.

Patterns in Metaphor Frequency. In the period between 2015 and 2020, we identified six patterns in the application of metaphors for the OGD and TD communities (see Section 5). While we identified no clear common patterns between the communities, we found that there are similarities in the patterns within the researchers’ communities and within the practitioners’ communities but not within the OGD communities nor the TD communities. This difference indicates that the community’s application of metaphors is more aligned between practitioners and between researchers than based on a common socio-technical phenomenon. At the same time, only the researcher communities contain the Rocket pattern; likewise, the Waver pattern is only apparent in the practice communities. Researchers could be more sensitive to the appeal of a metaphor, seeking to experiment and test it, while practitioners take longer to accept a metaphor because they need to have practical utility. Whereas the Bumper pattern is not visible in the TD researcher community, it appears in the remaining communities. The other communities might, thus, be more open to experimentation with metaphors. In a cross-comparison, the TD research community and OGD practice community display fluctuation in density. They are likely experimenting with metaphors or at least discussing them. It is possible that a useful assemblage of metaphors has not been generated. On the other hand, the findings show that the OGD research community and TD practice community are more stable in their metaphor density. They have likely found a useful assemblage of metaphors or do not need metaphors to describe the target phenomenon. This similarity could mean that different communities can express similar behaviours towards applying metaphors for conceptual development. This conclusion is in contradiction to Stubblefield (1998)’s statement that metaphors can have lifecycles, as our findings show that metaphors are part of ever-evolving processes following similar patterns.

Assemblage of Metaphors. Our findings show a tendency that assemblages of metaphors can be constructed to create a new logical syntax. For example, ‘Technical Debt’ is combined with ‘Repair’ rather than ‘Repay’. The metaphors fit with the target phenomena but could be understood as incompatible if compared to each other. However, Mészáros (1966) warns that the metaphorical fallacy is to draw a conclusion from something that is only metaphorically established. It is, as such, possible that senders and receivers create similarities and reasoning, which are not (fully) applicable to the target phenomenon. For example, in the OGD community, the ecosystem is combined with business and health. Where businesses and ecosystems behave differently (Mars et al., 2012) and health is a metaphor that originates in medicine for an organism and is now stretched to groups (Rapport, Gaudet, Constanza, Epstein, & Levins, 1998). As a result, the senders’ and receivers’ construction of assemblages of metaphors is similar to using their minds as a lab to discover new ways to express understanding and thinking about a target phenomenon by drawing on previous knowledge. This insight means that metaphors are more than a tool to economize a limited vocabulary, structure thinking, create new meanings, and generalize (Black, 1955; Lakoff & Johnson, 2008b; Ogden & Richards, 1923). Metaphors can be combined to go beyond traditional thinking, embracing new ways of reasoning and perceiving about socio-technical phenomena. In addition, our research indicates that senders can employ assemblages to help receivers sort similarities and differences. These assemblages can oscillate over time with some recurrent configurations (e.g., in the OGD community, ‘Ecosystem’ tends to be paired with ‘Business’ or ‘Production’). At the same time, Mészáros (1966) explains that a metaphor is more than a word, as it can help receivers to better understand the message. A metaphor can provide a logical syntax for thinking. The metaphor-assemblage approach opens questions about inter-metaphorical emergence, meaning senders and receivers could create new meanings through combinations of metaphors that could not be expressed by a single metaphor (as shown in the ‘Technical Debt’ example above). It is possible that the oscillations of the assemblages are attempts by the senders to capture target phenomena difficult to communicate. Also, senders and receivers can apply a metaphor as a tool to reason and make sense of new or complex phenomena (e.g., Hekkala et al., 2018; Stubblefield, 1998; Thibodeau & Boroditsky, 2011). Therefore, an assemblage of metaphors could help senders create new ways of reasoning and understanding (a new logical syntax) about a target phenomenon, which a single metaphor could not express even if the metaphors when literally compared would be incompatible. Thus, we expand on Stubblefield (1998)’s findings that metaphors are valuable as designing tools, as metaphor assemblages can be valuable as a tool to understand a new logical syntax, as Izwaini (2003) display in the various metaphors applied in relation to computers and the internet.

7.2 Studying metaphors

To our knowledge, other researchers have not studied the application of metaphors in relation to conceptual development using an approach similar to ours. Thus, our findings provide guidance to future research of interesting topics to explore further using similar methods to this article.

The study of metaphors in a community is complicated as several senders can participate in the communication through various outlets. Some senders explain their metaphors, while other senders assume the receivers will spring to the right spontaneous conclusions (Ogden & Richards, 1923). In addition, the application of metaphors can differ in usage, expression, and assemblage where they are sometimes not applied as metaphors or at least border between being a metaphor and being everyday language or an unfettered concept. Therefore, it can be difficult to determine the exact meaning of a metaphor. We can draw some lessons learned about researching metaphors related to the OGD and TD community characteristics, the emergent CAOM framework, the patterns in the application of metaphors, and understanding the application of metaphors from a COAM framework lens.

Community Characteristics. The community characteristics influence how senders communicate to receivers but also act as an entry barrier for newcomers to the community. The OGD community is open, public, and international, allowing easy access for receivers (and researchers). The challenge was to find relevant key outlets where the majority of essential communication happens (relevant empirical material). The format and quality of this communication varied, which made the research time-consuming, giving less gain per resource invested (as seen as an increase in the ‘Ecosystem’s role as insignificant in assemblages. See Table 5). Moreover, the TD community is semi-private and local, which can create an entry barrier for newcomers but also increase the quality of the material. It requires more effort from the researcher to access or become part of the community but also provides greater gains. The entrance barriers include cultural and language barriers (e.g., the researchers are very strict on what can be defined as technical debt).

The Emergent CAOM Framework. We synthesised the CAOM framework from previous research about metaphors and memes. The metaphor research gave a foundation for the framework, while the meme research provided an approach to studying and understanding the spread and application of metaphors within a community. This combination is an original contribution to previous research. The framework focused our attention on important parts of the empirical material while giving structure to the analysis. It enabled us to bridge the use of a quantitative and a qualitative method.

Patterns in the Application of Metaphors. The quantitative analysis used word frequency analysis to estimate the application of metaphors within the empirical material over time. While it required several iterations to become satisfactory, it was useful as a tool to gauge the senders’ application of metaphors, as it helped to identify patterns. However, this method does not consider the context of words, giving an estimation where the researchers need to decide to exclude or include words in the grey zone (words used in both a metaphorical and non-metaphorical manner). The analysis method is fast to apply but time-consuming to set up and difficult to get right. At the same time, the lack of consideration for context meant that assemblages of metaphors were only analysable in the in-depth analysis. This exclusion allowed the frequency analysis to focus on the usage and expression of metaphors over time. It revealed when a metaphor had a high potential to influence the conceptual development of a community but also when it could have limited potential.

The Application of Metaphors from a COAM Framework Lens. The in-depth analysis focused on a metaphor per community using the CAOM framework. It allowed a richer understanding of a metaphor’s usages, expressions, and assemblages (application). We saw a correlation between the density, usage, expression, and assemblage of metaphors. For example, the TD researcher community has a high density, tending to primarily apply the metaphor for development purposes, the expression is mixed, and the metaphor has a core role. Although the in-depth analysis was time-consuming, it helped to explain the usage and trends of metaphors within the two communities. It was an essential part to understand assemblages of metaphors.

7.3 Implications

Our research has some implications for practitioners’ and researchers’ application of metaphors in conceptual developments. They can actively experiment with assemblages of metaphors to create new logical syntax and meanings, considering the potential impacts metaphors could have on each other. Inter-metaphorical emergence can be beneficial but could lead to metaphorical fallacies or nonsensical communication. They should be aware that assemblages of metaphors can cause unwanted associations for receivers, as they are the catalyst who interpret the metaphor and its assemblage. As such, it is important for senders to be clear when communicating original assemblages of metaphors, highlighting important similarities and dissimilarities for the receivers. This approach could help to increase the benefits gained from conceptual developments using metaphors.

Research. Researchers can use the CAOM framework as an analytical lens. It captures the underlying mechanisms of metaphor usage, expression, and assemblage (application). The framework is developed to be used in mixed methods and qualitative research; as such, it is ample for use in case study research. Researchers could use the CAOM framework as part of their analysis, as an introductory guide to metaphors, and as a starting point for future research that seeks to theorize metaphor usage in communities (see Eisenhardt, 1989; Walsham, 1995). On the other hand, our findings imply that researchers should be aware of metaphors and their assemblages. We believe assemblages can give insights into what is perceived as new by practitioners and researchers, which could direct future research to original contributions. Similarly to practitioners, researchers could discuss the emergence of new meanings when combining various metaphors to increase the speed of conceptual developments. We recommend that digital government researchers include an action-oriented element when they develop or apply metaphors, as it can improve practitioners’ usage of their research.

Practice. Practitioners have a repertoire of actions and interpretations for the application of metaphors. They should reflect on what a metaphor entails for their thinking and actions, but also its possibilities. Senders could use the CAOM framework to analyze metaphors, which could help them avoid pitfalls in their communication and create assemblages that foreground what they seek to communicate. Receivers can use the CAOM framework to gain a deeper insight into a metaphor. Especially, if the sender is attempting to communicate something only expressed through the metaphorical emergence of an assemblage of metaphors. We recommend that practitioners approach metaphors as a serious tool that they can apply to quickly expand previous knowledge to encompass new and unknown socio-technical phenomena. This process can involve evaluations and reports on the success of a metaphor and its assemblage, but also a focus on the development of metaphors. We recommend that governments seeking to communicate with practitioners through policies or documents should draw on action-oriented metaphors, which can guide the practitioners towards an intended goal.