Perceived analogical communication in design teams: Development and validation of a scale

Perceived analogical communication in design teams: Development and validation of a scale Daniel Graff, College of Design and Innovation, Tongji University, No. 281 Fuxin Road, Yangpu District, Shanghai, China, Institute for Design Innovation, Loughborough University London, 3 Lesney Avenue, E15 2GZ, London, UK Nicoleta Meslec, Department of Organisation Studies, Tilburg University, PO Box 90153, 5000 LE Tilburg, the Netherlands Mark A. Clark, Kogod School of Business, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA Analogies have been shown to play a key role in design collaboration. However, research has been largely limited to the analogy itself and how it is used, overlooking the impact of analogy from the recipients’ perspective. This is a critical aspect, considering the imperfect information transfer between members in design teams. We address this gap by developing a measure of perceived analogical communication in teams, focusing on the interpretation of the use of analogy in internal design team communications. We test the resulting scale across 3 samples, totalling 252 multi-disciplinary teams with 1182 team members. Results show that the scale is an internally consistent, distinct construct, and holds predictive validity for relevant design team processes and outcomes. Ó 2019 Elsevier Ltd. All rights reserved.

Keywords: design cognition, analogical reasoning, collaborative design, information processing, communication

R Corresponding author: Daniel Graff, d.graff@lboro.ac.uk

esearch in design cognition and collaboration has begun exploring the role of analogies in the work of design teams (e.g. Christensen & Ball, 2016; Paletz, Schunn, & Kim, 2013). Analogies have been shown to be important throughout the design process to explain concepts, identify problems, and offer solutions (Christensen & Schunn, 2007). Scholars of design cognition and collaboration typically do not distinguish between the perspectives of those who send versus those who receive the analogies communicated in conversational practice, including subsequent influence on design processes and outcomes (e.g., Alipour, Faizi, Moradi, & Akrami, 2017; Ball & Christensen, 2009; Chan & Schunn, 2015). Despite the recognition of analogies as a means of communicating ideas between individuals in

www.elsevier.com/locate/destud 0142-694X Design Studies xxx (xxxx) xxx https://doi.org/10.1016/j.destud.2019.11.004 Ó 2019 Elsevier Ltd. All rights reserved.

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design teams and the importance of perception in a communication environment (Berlo, 1960), the perspective of the intended recipient of the analogy has not been incorporated into these contexts. The aim of this study is to develop a measure of analogical communication among design team members which accounts for recipient perceptions. To do so, we build on previous research in design cognition and collaboration and integrate insights from communication theory. From this perspective, senders encode messages which are in turn decoded by receivers (Berlo, 1960). A deep level of communication, aligning encoders’ intentions with decoders’ interpretation, is important for design collaboration (Chiu, 2002). Therefore, our perceived analogical communication construct measures the receiver’s recognition and interpretation of the analogy used by the sender. It is important to distinguish perceived analogical communication from more typically studied constructs in design, such as “analogy”, “analogical reasoning”, and “analogical communication”. Analogy refers to the link of a known source to an unknown target by establishing a goal-directed similarity between them (Gentner & Holyoak, 1997). For example, American automobile innovator Henry Ford used “a Model T is like a dead cow” to link beef processing to the assembly process, communicating a way to improve his company’s production methods (Pollack, 2014). As such, analogies emphasize underlying structural similarities rather than objective elements between sources and targets (Gentner, 1998). Analogical reasoning refers to the individual thought processes which are based upon an analogy (Bartha, 2016). Analogical reasoning is mostly studied on the individual level by focusing either on emergence or benefits. Design-byanalogy research on the individual level, for example, shows that individual preferences (Alipour et al., 2017) and level of expertise (Ozkan & Dogan, 2013) play an important role in the type of analogy created. In addition, research on the individual level indicates that analogical reasoning is positively related to problem solving (e.g., Gentner, Loewenstein, & Thompson, 2003) and creativity (Moreno et al., 2014). In these studies, analogical reasoning is often measured directly via verbal analogy selection (Jones & Estes, 2015) or indirectly influenced via experimental conditions (Gentner et al., 2003). Analogical communication refers to the explicit use of both the analogy source and target as a product of analogical reasoning, rather than simply sharing one or the other. Design researchers have generally studied analogical communication within design team meeting conversations, examining analogies and their emergence, type, and effects (Ball & Christensen, 2009; Chan & Schunn, 2015). Analogical communication is used in design teams to explain ideas as well as to identify and solve problems (Christensen & Schunn, 2007). The construct is often measured directly by counting analogies in conversations, which are

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then coded according to various parameters such as the type of analogy (e.g., Chan & Schunn, 2015). We identified two studies that linked counted instances of analogical communication to team processes; these studies do not, however, focus on the receivers’ perspectives. Paletz et al. (2013) examined the effect of analogical communication, finding that analogical communication can spark conflict, but also can emerge in response to conflict (Paletz et al., 2013). Christensen and Ball (2016) found that analogical communication was used more frequently when matched to functional knowledge (education) in a multi-disciplinary design student team, linking this to increased epistemic uncertainty. Together these studies represent a promising start for examining analogical communication, examining its content and linking it to process and outcome variables. However, the conceptualisation and measurement of analogical communication in these studies is not easily applicable to design teams. First, the extant analogical communication research does not distinguish between the sender or receiver of the analogy. However, because design teams depend on knowledge integration (Graff & Clark, 2018b), and interpretation of information may vary among team members (Clark, Anand, & Roberson, 2000), it is important to understand the perspective of recipient with regard to analogy use. Therefore, scholars interested in the effect of analogical communication in design teams should examine the receiver’s perception of the analogical communication. Second, merely counting analogies communicated in a selection of time-limited conversations (as opposed to recounting those analogies perceived) can restrict predictive utility, allowing mainly for links of analogy use to variables coded closely to the occurrence. Therefore, scholars might miss important consequences for design team processes and performance outcomes which occur later, or outside the recorded conversation. This research study contributes to the design cognition and collaboration literature in two main ways. First, this research adds to the design cognition literature by developing theoretically and testing empirically perceived analogical communication. The research complements past design research on the actual use of analogies, which showed that it can improve communication and problem solving (Christensen & Schunn, 2007). Second, this research broadens our understanding of analogical communication in design collaboration by taking a more holistic view of the benefits of analogical communication beyond improved communication and problem solving by showing how perceived analogical communication affects design team process, which in turn has consequences to team performance.

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Perceived analogical communication in teams

We define perceived analogical communication in teams as the usage observed by members of analogical sources and targets used in a team. Analogy refers to

Development and validation of a scale

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relational communication illustrating underlying structural relationships between objects, linking from sources to targets. Usage refers to the recognition by the receiver that analogies are communicated. There are two main reasons why analogical communication in teams differs from analogical communication on the individual level. First, compared to the individual level, it is difficult to judge ownership of the analogy in team contexts. It might be that the source and the target of an analogy are stated from two different team members during a team discussion. Second, analogical communication on the individual level depend largely on a person’s experience and expertise, as with other abstract communication (Hinds, Patterson, & Pfeffer, 2001). In a team, this experience is enlarged, and the expertise is broadened (e.g. multi-disciplinary design teams), which may allow teams to have more varied analogies than persons working alone (Christensen & Ball, 2016). Perceived analogical communication measures the shared property of analogies (Klein & Kozlowski, 2000), which is appropriate because the benefit of analogies comes through carrying meaning to others, which would not occur without recognized perceptions of the analogy. As such, it is important to measure the perceived use of analogies and aggregate it as a group mean from member responses. Scale items that measure individuals’ responses must remain meaningful when aggregated (Lewis, 2003). For example, if members’ responses are summed for the item, “team members explain new information by relating it to similar existing information,” the aggregate represents the extent to which members perceive the team has used analogical communication to explain new information. Lower aggregate scores imply that some members do not perceive information as explained through relational communication, and presumably, that analogical communication does not emerge within the team. Higher aggregate scores reflect frequent use of analogical communication. Because both high and low levels of the aggregated item remain consistent with the definition of the specialization dimension, aggregating this item is conceptually justified (Lewis, 2003). Because analogical communication has been considered to have different functional purposes from the sender’s perspective, we also develop items to test the receiver’s recognition of potential utility for inventive, explanatory, or persuasive aspects of analogies (Pollack, 2014; Ward, 1998). Inventive analogies are communicated to help team members develop new ideas or find solutions by applying knowledge from outside domains, whereas explanatory analogies link members’ knowledge domains with the aim of illustrating or improving understanding within the team (Ward, 1998). Finally, persuasive analogies are used to influence other team members of an idea or direction to follow (Pollack, 2014). Since this study asserts the relevance of receivers’ perspective, it will be important to develop items to test whether these aspects are distinctive to the receiver. This will constitute an inclusive theoretical approach, allowing

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either for development of a more nuanced measure, or a leaner scale focused on aspects of analogical communication that most effectively influence the receiver.

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Scale development

We developed and validated the perceived analogical communication scale in accordance with processes recommended by Wright, Quick, Hannah, and Hargrove (2017). We ran three studies to support our scale development. In Study 1, we generated preliminary scale items and tested internal consistency. We utilised an exploratory factor analysis (EFA) to identify the underlying structure of perceived analogical reasoning. EFA can be used when the structure of a measure is not known (Byrne, 2016) and is often used in the early phases of a scale development process (see for example Lewis, 2003). In Study 2, we used an experimental design to validate the measure. We tested discriminant validity (the extent to which the scale measurements differ from measurements of dissimilar constructs) through confirmatory factor analysis (CFA) (Lewis, 2003). A CFA is appropriate for verifying a suspected factor structure (Byrne, 2016), in this case testing how well the items generated in Study 1 reflect our latent variable. It is commonly used in validating new measures (see for example Lewis, 2003). Finally, in Study 3, we tested for additional discriminant validity, and criterion-related validity (the extent to which the scale is related to its theoretical causes, correlates, and effects). All studies sampled populations of working graduate students in one of two Western European countries, providing stronger evidence that the perceived analogical communication scale is valid (Lewis, 2003).

2.1

Preliminary scale development - study 1

The purpose of Study 1 was to establish an internally consistent scale that substantially represents the perceived analogical communication construct. The conceptual description and our literature review suggested perceived analogical communication may include multiple dimensions (explanatory, inventive, and persuasive). Thus, a conservative approach to scale development would test whether these dimensions are apparent to the communication recipients, or if a unidimensional scale would be a better fit. For this reason, we developed items for each dimension, then used EFA to statistically test the optimal dimensional configuration. These analyses were conducted at an individual level of analysis.

2.1.1

Item generation

Based on the insights gained from our analogical communication literature review, we created an initial pool of 54 items that represent three dimensions (innovative, explanatory, and persuasive) of the perceived analogical communication construct: 19 explanatory dimension items (e.g., “In my team at least one member brings insightful comparisons between apparently unrelated domains to enhance my understanding”; “In my team at least one member

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explains a new idea by connecting this idea to something familiar.”), 18 innovative items (e.g., “In my team at least one member identifies possible solutions by adapting them from other contexts”; “In my team at least one member solves problems by looking for answers in other domains.”), and 17 persuasive items (e.g., “In my team at least one member’s examples from other fields make me adopt their perspective on the issue; “In my team at least one member convinces me of his or her ideas by giving examples from other fields.”).1 Four independent researchers blind to the purpose of the study read a description of the three sub-dimensions then assigned all 54 items to one of the three categories, in line with similar scale development studies (Hinkin, Tracey, & Enz, 1997). The correlations and kappa’s inter-rater reliabilities among the dimensions proposed by the scale developers and those coded by the three researchers were very high: r ¼ 1, p ¼ .000, k ¼ 1, p ¼ .000 with coder 1, r ¼ .97, p ¼ .000, k ¼ .94, p ¼ .000 with coder 2, r ¼ .88, p ¼ .000, k ¼ .83, p ¼ .00 with coder 3 and r ¼ .91, p ¼ .000, k ¼ .91, p ¼ .000 with coder 4. This gives preliminary empirical validation that the items developed are in line with the three dimensions used in prior research on analogies.

2.1.2

Exploratory factor analysis

We distributed the 54 items to 117 students enrolled at a large Dutch university, including 62 women and 55 men with an average age of 21.34 years. Students formed 28 teams (average team size ¼ 4.18 members) and worked on a seven-week team client engagement assignment which accounted for 50 percent of their final grade. Team members did not necessarily know each other at the beginning of their team task. Respondents rated items with a 7-point Likert scale (1 ¼ strongly disagree, 7 ¼ strongly agree). The questionnaire, distributed in the fifth week of the course, asked the students to respond while thinking about the interaction they had within their teams. We analyzed the pattern of inter-items correlations and excluded six items that had few correlations with the other items (Hinkin et al., 1997). We then performed an exploratory factor analysis (principal axis factoring) on the remaining 48 items with a direct oblimin rotation. Contrary to our expectations one primary factor emerged that accounted for 32.56% of the variance. Items from all three initially theorized dimensions loaded on one single factor. Our analysis indicates that perceived analogical communication is a unidimensional rather than multi-dimensional measure. We think that there are at least three potential reasons for this finding. First, the possibility that the items developed could have been flawed should be considered (e.g., items that are not clearly stated or have too much overlap). However, we tested the adequacy of the items with three experts outside the research team and obtained excellent results. Second, it may be that the dimensions based on the three

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analogical purposes identified in the literature are not meaningfully distinct for this sample and, therefore, the statistical analysis shows one rather than three dimensions. This could be because, for instance, the purpose of that analogy (explanatory, inventive, or persuasive) might not be clear to the receiver such as when an analogy might be both inventive and explanatory. Similarly, the sender’s purpose of the analogy, specifically for persuasive analogies, is often hidden from the receiver (Pollack, 2014). As such, it makes it difficult for the receiver to distinguish purposes of analogical communication. Finally, it may be that from the perceiver’s perspective, the utility of an analogy for stimulating thinking is accomplished without any consideration for the specific type of analogy used.

2.1.3

Conclusion study 1

Considering the empirical findings and the issues discussed above, we accept the unidimensional one-factor solution as valid and theoretically meaningful. Although a unidimensional scale will not measure a specific type of analogy used, specifying too many dimensions could lead to difficulties in interpretation and replication, which would limit the generalizability of the scale (Zwick & Velicer, 1986). In line with this, we selected the highest-loading items which accurately represented our construct to develop a robust four-item, onefactor measure, of perceived analogical communication in teams (see below). A1 In my team at least one member explains new information by relating it to similar existing information. A2 In my team at least one member arrives at solutions by identifying existing solutions from related problems. A3 In my team at least one member is trying to understand concepts by showing similarities between related concepts. A4 By bringing insights from apparently unrelated fields, other team members help me to better understand the task/issue at hand.

2.2

Scale validity testing - study 2

The purpose of Study 2 was to test the validity of the perceived analogical communication scale for consistency with a separate sample. At an individual level we ran an EFA and a reliability analysis to confirm the robustness of our results obtained in Study 1. Next, at a group level we ran an inter-rater agreement analysis, a CFA as well as discriminant tests, to show that our scale is different than related scales such as team creative thinking, team communication frequency and analogical reasoning. As reliability and validity tests require large samples, we recruited 403 graduate students in 102 multi-disciplinary teams from a university course in the United Kingdom to participate in a team creativity task. The teams, averaging 3.95 members, were composed of students from different fields such as Design,

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Technology, and Business. The sample was 42% male and averaged 23.9 years in age. The task was to come up with as many good uses as possible for 5 visually represented objects (springs, ice cubes, a guillotine, foam, a barrel) for a duration of 20 min. We used a creativity task, because analogies are particularly useful in creativity (e.g., Jones & Estes, 2015). As an incentive, we offered the team with the most ideas generated a book voucher of £250. Students were asked to fill out a survey with background information and a verbal analogical reasoning test before the task, and right after the task another survey in which we measured perceived analogical communication scale, team creative thinking and team communication frequency. The respondents answered the questions with a 7-point Likert scale (1 ¼ strongly disagree, 7 ¼ strongly agree). Analogical reasoning was measured with a verbal analogy performance test (Jones & Estes, 2015). Although there are several tests available to measure analogical reasoning at the individual level, including nonverbal instruments (e.g., Ravens test), we chose a verbal analogical reasoning test as we believe that this type of analogical reasoning is closely related to analogical communication in teams. Another advantage is that the analogical reasoning test was already used in a student setting by Jones and Estes (2015). We measured team creative thinking with 3 items developed by Jiang and Zhang (2014), with items “My team members communicated and exchanged creative ideas with each other”. Cronbach’s Alpha for this scale was .93, indicating good reliability. We measured team communication frequency with 3 items by asking respondents to indicate the amount of oral, written, and non-verbal communication in their team (e.g., “My team members engaged in a lot of nonverbal communication during the exercise”). Cronbach’s Alphas for this scale was .77, indicating good reliability. Both scales used a 7-point Likert scale (1 ¼ strongly disagree, 7 ¼ strongly agree).

2.2.1

Exploratory factor analysis

Before testing for validity, we ensured that the measure maintained the single factor identified in Study 1. We performed an EFA at an individual level of analysis (principal axis factoring) on the four items with a direct oblimin rotation, showing one factor that accounted for 75.22 of the variance. The KaiserMeyer-Olkin measure verified the sample adequacy for the analysis, KMO .84, and all KMO values for individual items were higher than .80, which is well above the acceptable limit of .50. Bartlett’s test of sphericity c2 (6) ¼ 776.13, p < .001, indicated that correlations of items were sufficiently large. Reliability of items at an individual level of analysis was very high, with a Cronbach’s Alpha of .88.

2.2.2

Aggregation analysis

We assessed intragroup agreement (rwg) on the perceived analogical communication scale items to confirm that members’ responses were similar enough to

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be aggregated to a team score (George, 1990). Since our scale is designed to be used in the context of groups, this is an essential step in testing its validity (Bliese, 2000). The average rwg of the scale was .83. These results indicate that members’ responses on the scale are quite homogenous and that aggregating members’ scores at the team level of analysis is statistically justified.

2.2.3

Confirmatory factor analysis

We performed further a CFA to determine if the intended one factor solution we identified in Study 1 best fits the data. We analysed the team-level data, allowing no cross-loadings. We evaluated the fit of the model by using several indices, including chi-square, comparative fit index (CFI), goodness-of-fit index (GFI), and the root mean square error (RSMEA) (see Figure 1). The CFA of the hypothesized measurement model showed a good fit (Figure 2), c2 (2, N ¼ 101) ¼ 2.37, p ¼ .307, CFI ¼ 1, GFI ¼ .99, RSMEA ¼ .04, with all indices falling within the acceptable ranges (Hu & Bentler, 1999).

2.2.4

Discriminant validity

We tested the discriminant validity of the perceived analogical communication scale in two different ways. First, we used factor analysis to compare the items of the perceived analogical communication scale with items from other constructs. If items from other constructs are distinct from the perceived analogical communication scale items (i.e., they load on different factors), that is evidence of discriminant validity (DeVilles, 1991). As noted above, two appropriate team variables e team creative thinking and team communication frequency e served as comparison constructs. Team creative thinking is a component of team creativity that allows a team to look at problems or situations from a new perspective, thus supporting unconventional solutions. Jiang and Zhang (2014) developed a three-item subscale that measured creative thinking via idea interaction (i.e., exchange of creative ideas), idea complementation (i.e., building on each other ideas), and idea integration. Perceived analogical communication and creative thinking both involve the introduction and exchange of new ideas. However, while in creative thinking ideas may come from any source, the origin of ideas for perceived analogical communication is limited to concepts based on the use of analogies. Therefore, perceived analogical communication and creative thinking are distinct and their scale items should load on two separate factors. Table 1 shows the means, standard deviations and correlations of variables used in Study 2. We note that the three constructs are fairly highly correlated, which if differentiated in our model testing could be interpreted as a strong test of the theory, because discriminant validity of highly related constructs indicates differentiation in the mind of the participant.

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Figure 1 Results of CFA analyses with path coefficients and standardized coefficients on the team level

Figure 2 Results of CFA analyses with path coefficients and standardized coefficients at the team level

Table 1 Means, standard deviations, and correlations on the team level

1. Creative Thinking 2. Communication Frequency 3. Perceived Analogical Communication

Mean

s.d.

1

2

5.93 5.42 5.75

.69 .66 .63

.76** .81**

.74**

N ¼ 90. **p < .01.

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We compared the constructs through two CFA models. The first model specified that team creative thinking items and perceived analogical communication items loaded together on one factor, while in the second model the team creative thinking items and perceived analogical communication items loaded on two separate factors. If the fit of the second model is significantly better than the fit of the first model, then one can conclude that the comparison items are indeed distinct. All analyses were performed on team-level data. For team creative thinking, the first measurement model (i.e.,one factor) showed the following fit: c2 (14, N ¼ 90) ¼ 61.92, p ¼ 0, CFI ¼ .92, GFI ¼ .82, RSMEA ¼ .20, for the second model (i.e. 2 factors) it was c2 (13, N ¼ 90) ¼ 22.75, p ¼ .045, CFI ¼ .98, GFI ¼ .94, RSMEA ¼ .09, and the chi-square difference test was significant with c2 (1) ¼ 39.17, p < .001. Results of the CFAs and model comparison suggest that team creative thinking is indeed distinct from the perceived analogical communication scale (see Table 2). Similarly, we tested discriminant validity with team communication frequency. Although both constructs describe communicating information and knowledge within teams, perceived analogical communication focuses on relational conveyance of relatively rich meaning, while frequency of communication focuses on the quantity of explicit interactions. Analogies can enhance communication effectiveness (Graff & Clark, 2018a); however, simply communicating more frequently does not lead to more analogical communication, in part because individuals may not understand the role of analogies in improving communication (Pollack, 2014). Thus, these constructs are conceptually distinct, which we expect to be reflected in their reported ratings. We compared the constructs through two CFA models, in the same way as done previously with creative thinking. The results support communication frequency as a distinct construct from perceived analogical communication (see Table 2). For team communication frequency, the first measurement model (i.e., 2 factors) showed the following fit: c2 (13, N ¼ 90) ¼ 15.04, p ¼ .305, CFI ¼ 1, GFI ¼ .96, RSMEA ¼ .04, for the second model (i.e., 1 factor) it was c2 (14, N ¼ 90) ¼ 29.33, p ¼ .01, CFI ¼ .96, GFI ¼ .92, RMSEA ¼ .11 and the chi-square difference test was significant with c2 (1) ¼ 14.29, p < .001. Second, we tested discriminant validity of the perceived analogical communication scale by comparing it to a related scale, analogical reasoning, which has been measured by a verbal cognitive ability test of its associated reasoning ability (e.g., Jones & Estes, 2015). The analogical reasoning test attempts to capture an individual skill capacity. Analogical communication differs because, although it includes cognitive capacity, it goes beyond to encompass motivation (willingness to do so), and communication (ability to express it). This difference in use should be reflected in the perception of the receiver who reports the analogies used. Therefore, we expected a non-significant

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Table 2 Results of discriminant validity tests

Hypothesized model

c2

df

CFI

GFI

RSMEA

Perceived analogical communication and creative thinking One-factor 61.92 14 .92 .82 .20 Two-factors 22.75 13 .98 .94 .09 Perceived analogical communication and communication frequency One-factor 29.33 14 .96 .92 .11 Two-factors 15.04 13 1 .96 .04

Change of c2

Change of df

39.17***

1

14.29***

1

***p < .001

relationship between analogical reasoning and perceived analogical communication. Table 3 shows the means, standard deviations and correlations of the two variables. As mentioned in the introduction, analogical reasoning is the thought process of creating an analogy and, therefore, analogical reasoning precedes perceived analogical communication. Therefore, we tested first discriminant validity through a linear regression in which analogical reasoning is the independent variable measured by the mean team-level (N ¼ 78) and perceived analogical communication is the dependent variable measured by our newly developed scale. Participants filled out an established analogical reasoning test before the experimental study and the perceived analogical communication scale after the experiment. The result of the linear relationship was non-significant with F(1,78) ¼ 1.825, p ¼ .18 and CI [-.027; .14], with an R2 of .02. This is in line with our expectations for two reasons. First, we measured perceived analogical communication, and the receiver might not recognise all analogies used by the sender. Second, the actual use of analogies by the sender depends on his or her motivation and skills. Therefore, the non-significant results provide us with evidence that the two measures are different.

2.2.5

Conclusion of study 2

Results of Study 2 showed that the perceived analogical communication scale is a reliable scale, with good internal consistency. Results also illustrated that the perceived analogical communication items are different from unrelated constructs’ items (creative thinking and communication frequency), as well as different from a related construct (analogical reasoning). In a follow-up step, we replicated the internal consistency and predictive value of our scale while using a different sample.

2.3

Assessment of the scale in an applied setting - study 3

The purpose of Study 3 was to re-assess the scale items in an applied field setting with teams working on a design task, rather than in a laboratory. Similar to Study 2, we examined scale reliability, inter-item correlations, and

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Table 3 Means, standard deviations, and correlations on the team level

1. Analogical Reasoning 2. Perceived Analogical Communication

Mean

s.d.

1

7.05 5.73

1.53 .56

.15

N ¼ 78.

tested for discriminant validity (distinctiveness from communication competence), as well as criterion-related validity of the perceived analogical communication scale (relation to team conflict and team performance). For Study 3, we sampled 662 master students in 122 design teams, averaging 5.42 members, at a large university course in the United Kingdom. The students had backgrounds in Design, Technology, Business, or Diplomacy. There were 46% males and 54% female participants. The participants’ age averaged 24.07 years. Students worked in teams on design projects for 19 organizations. The projects they were working on related to designing new products, services, or processes for the various organizations (e.g. Foster & Partners, NHS England, or EDF Energy). The student teams worked for about two months on their project tasks, which required them to apply expertise in various functional areas. Throughout the project, the teams and the client interacted on a constant basis to support the development of the project. We collected data at 4 different timepoints. Before the start of the course, students were asked to fill out a survey with background information and the communication competence scale. This construct was measured with a 12item scale from Madlock (2008), originally developed by Monge, Backman, Dillard, and Eisenburg (1982), including items such as “I have a good command of the language,” “I am a good listener,” and “I express my ideas clearly”, which achieved good reliability with a Cronbach’s Alpha of .79. We first measured perceived analogical communication (one and a half months into the project), then at the end of the course (after two months) we used a 9-item scale developed by Jehn and Mannix (2001) to measure team conflict with items such as “How often are there disagreements about who should do what in your team?”. Reliability of the scale was good with a Cronbach’s Alpha of .91. Team performance was rated by the academic project leader after the project was over. The course had one academic project leader for each organisation and so each project leader had to assess several teams. Team performance was measured by a three-item scale developed by De Jong and Elfring (2010), rating the amount and quality of work produced and the overall team effectiveness on a 7-point Likert scale. Reliability of the scale was good with a Cronbach’s Alpha of .96.

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2.3.1

Aggregation analysis

Similarly, to Study 2, we first assessed intragroup agreement (rwg) on the perceived analogical communication scale items. The average rwg of the scale was .75, which indicates that members’ responses on the scale are homogenous and that aggregating members’ scores at a team level of analysis is statistically justified.

2.3.2

Confirmatory factor analysis

We performed a confirmatory factor analyses (CFA) to determine the fit of our four-item scale. We analysed the team-level data and no cross-loadings were allowed. We evaluated the fit of the model by using several fit indices, including chi-square, comparative fit index (CFI), goodness-of-fit index (GFI), and the root mean square error (RSMEA) (see Figure 2). The CFA of the hypothesized measurement model showed a good fit on the team-level c2 (2, N ¼ 105) ¼ 3.44, p ¼ .179, CFI ¼ 1, GFI ¼ .99, RSMEA ¼ .08, with all indices, besides RMSEA, falling within the acceptable ranges (Hu & Bentler, 1999). However, research has shown that RMSEA scores increase with low degrees of freedom and small sample sizes (Kenny, Kaniskan, & McCoach, 2015). In addition, Browne and Cudeck (1989) suggested that values in the range of .05e.08 indicate a fair fit. This provides us with confidence about the internal structure of our measure.

2.3.3

Discriminant validity

While Study 2 tested discriminant validity by comparing factor structures of communication frequency and creative thinking with perceived analogical communication, in Study 3, we test whether perceived analogical communication and its items are distinct from communication competence. Communication competence measures behaviours associate with effective communication (Madlock, 2008). Research shows that analogical communication can be a very effective method to enhance understanding in teams (Graff & Clark, 2018b). As such, we would expect analogical communication to be related to communication competence. However, communication competence is much broader and entails more facets of good communication. Table 4 shows the means, standard deviations and correlations of the two variables. We used the same methodological techniques as in Study 2 and we compared two models, a one-factor and a two-factor model. The results indicate that communication competence is distinct from perceived analogical communication. For communication competence, the first measurement model (i.e., 2 factors) fit was: c2 (103, N ¼ 68) ¼ 129.56, p ¼ .39, CFI ¼ .95, GFI ¼ .82, RSMEA ¼ .06, while the second model (i.e., 1 factor) was: c2 (104, N ¼ 68) ¼ 363.12, p ¼ 0, CFI ¼ .51, GFI ¼ .56, RSMEA ¼ .19 and the chi-square was significantly different c2 (1) ¼ 233.56, p. < .001. These findings confirm that our measure is distinct from related measures.

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Table 4 Means, standard deviations, and correlations on the team level

1. Communication Competence 2. Perceived Analogical Communication

Mean

s.d.

1

3.08 5.34

.82 .25

.31**

N ¼ 68. *p < .05, **p < .01.

2.3.4

Criterion validity

We tested criterion-related validity based on hypothesized relationships of the measurement model. As identified in the literature review, only two studies examined analogical communication (counted, not perceived) in teams and its relationship to another team variable. Paletz et al. (2013) found a complex relationship between analogies and conflict in science team. However, the study focused on micro conflicts and did not consider team performance and as noted focused on counting analogy use rather than perception of the receiver. Therefore, we examined whether perceived analogical communication has an influence on team performance via team conflict. Although we have a specific hypothesis based on the literature, that team conflict will mediate the relationship between perceived analogical communication and team performance, the primary goal of this study is to assess criterion validity rather than identifying new potential relationships. Research in analogical communication on the conversational level has been shown to improve communication and understanding (Gentner, 1998). For example, analogies can be linked to general concepts to clarify communication and improve understanding in project work (Kalogerakis, L€ uthje, & Herstatt, 2010). However, even if the analogical communication is misunderstood, it creates a goal-oriented communication which can clarify any open questions (Kalogerakis et al., 2010). This improved communication reduces misunderstandings and as a consequence can reduce conflict. The reduced conflict should improve team performance. De Dreu and Weingart (2003) found in a meta-analysis of team conflict and performance that conflict was negatively related to performance. Given the reasoning above we advance the following hypothesis: H1:Conflict mediates the relationship between perceived analogical communication and team performance. The higher the analogical communication, the lower conflict and the higher the team performance. We tested our theoretical model while using a non-parametric resampling procedure for bootstrapping (Hayes, 2012). In mediated regression modelling, bootstrapping is used to generate confidence intervals for the estimated indirect effects. Non-parametric resampling procedures have been identified as particularly powerful approaches for testing mediation effects (Williams &

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MacKinnon, 2008). Simulation research has shown that bootstrapping tends to have strong statistical power in testing such models (Williams & MacKinnon, 2008). Table 5 shows the means, standard deviations and correlations of the variables included in the mediation analysis. We tested our hypothesis through a mediation model with perceived analogical communication as an independent variable, conflict as a mediator and team performance as a dependent variable. Our results indicate a negative significant relationship between analogical communication and conflict, with a coefficient .231, p ¼ .003, CI [.384; .078]. Further, conflict had a significant and negative relationship with team performance, with a coefficient ¼ .447, p ¼ .048 and CI [.890; .004]. The direct effect of perceived analogical communication on team performance was nonsignificant, with a coefficient ¼ .116, p ¼ .525 and CI [.245; .477]. However, the indirect effect of perceived analogical communication on team performance via conflict is positive and significant, with a coefficient ¼ .103 and CI [.005; .272]. The results indicate a significant negative relationship between perceived analogical communication and conflict, which in turn has a significant negative relationship with team performance. At the same time perceived analogical communication has no direct effect on team performance. These relationships are consistent with mediation standards (Preacher & Hayes, 2004) and may provide basis for further understanding how the constructs relate. For instance, it may be that we did not find a direct relationship between perceived analogical communication and team performance because the team performance construct measured only the amount, quality, and overall performance outcome. It did not measure how innovative or creative the outcome was, which would have been closer related to perceived analogical communication. Overall, these results indicate the importance of perceived analogical communication construct on team processes (i.e., conflict) besides of its known value for problem solving and creativity.

2.3.5

Conclusion

Study 3 showed that the perceived analogical communication scale is internally consistent, unrelated to other constructs’ items (communication Table 5 Means, standard deviations, and correlations on the team level

1. Perceived Analogical Communication 2. Team Conflict 3. Team Performance

Mean

s.d.

1

2

5.38 2.48 4.29

.79 .65 1.42

.24* .06

.22*

N ¼ 81 for Perceived Analogical Communication, 121 for Communication Competence, 122 for Team Performance. *p < .05.

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Please cite this article as: Graff, D et al., Perceived analogical communication in design teams: Development and validation of a scale, Design Studies, https://doi.org/10.1016/j.destud.2019.11.004

competence), as well as related to other important team measures, such as team conflict. The results of Study 3 give confidence that perceived analogical communication is distinct from existing constructs, but important and related to other design team process and performance outcomes.

3

General discussion

This study provides initial evidence of the importance of perceived analogical communication in teams and its measure as a conceptually and statistically valid 4-item scale. It highlights the value of accounting for perceptions of the receiver because, in keeping with social information processing theory, changes in understanding or behaviors are based on receiver perceptions, rather than simply on whether analogies were used. Further, the characteristics of the scale make it appropriate for field settings because the items are taskindependent and allow comparisons between different teams and tasks. While we developed the scale for perceived analogical communication in teams allowing for consideration of three facets that may be intended by senders (explanatory, inventive, and persuasive), our EFA demonstrated that these dimensions are not distinct for perceivers in practice. Therefore, we developed the scale as one factor model and tested its convergent, discriminant, and criterion-related validity tests in two samples. Results suggested that the scale is valid and useful because it is related to similar constructs, distinct from existing constructs that it is not intended to measure, and significantly related to hypothesized causes and effects of analogical communication in design teams. The aim of this study was to develop a measure that reflects perceived analogical communication to support future research on the relationship of analogies and design team process and performance outcomes. We validated this measure with teams of graduate students, both in laboratory settings and working on design projects with real-world clients. While scale development studies such as this have justified using student samples due to the requirements for relatively large data sets (DeVilles, 1991), we also note that student teams, like practitioners in organizations, need to share, integrate, and synthesize knowledge in order to be successful (e.g. Chiu, 2002; Graff & Clark, 2018a). In fact, student teams may represent a more conservative test of our construct, considering that expert practitioners have been found to use analogies more frequently as compared to students (Novick, 1988). This would indicate that analogies potentially play a larger role rather than a smaller one, in organizational settings. Future research should use and test this scale in professional design teams.

4

Implications and future work

This study contributes to the design cognition and collaboration literature in two main ways. First, this study provides conceptual and empirical evidence

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that perceived analogical communication exists and can be measured indirectly via surveys on the individual level for design teams. The findings complement past design research on the actual use of analogies, which showed that it can enhance communication and problem solving (Christensen & Schunn, 2007). Our findings suggest that an indirect measure is effective in examining perceived analogical communication. This is important for field research in design, because measuring analogical communication by direct means through protocol studies are infeasible in many applied settings. This may be important because it may not always be possible to directly measure the instance, nor the content, of analogies used. This indirect perceptual measure also may indicate effectiveness of analogy use that is not captured through measuring the skill level of the person using the analogical communication, which has been the focus of prior research in this area. Second, the research study broadens our understanding of analogical communication in design teams as a focus on its creative function to a more holistic view of the benefits of analogical communication. In this study we showed that perceived analogical communication can reduce team conflict, and that the lower level of conflict can improve team performance. Future research should explore potential connections to other team processes and we hope this study is a first step in this direction. There are several potential uses for the perceived analogical communication scale in design research. For example, analogical communication should lead design teams to improve their information processing (Graff & Clark, 2018b). Improved information processing, such as better knowledge sharing or application, in turn can lead design teams to deliver better concept outcomes (Hinsz, Tindale, & Vollrath, 1997). This might be especially beneficial in multi-disciplinary design teams in which designers, engineers and marketers need to incorporate their knowledge to be successful. These multi-disciplinary design teams often struggle to integrate their various perspectives and expertise (Cronin & Weingart, 2007). Through analogical communication, these multi-disciplinary design teams may be able to overcome these challenges and, therefore, perceived analogical communication might partly help to explain why some diverse design teams fail while others succeed. Another potential research stream could investigate the persuasive nature of analogical communication. For example, an engineer could use persuasive analogical communication to influence decision making in multi-disciplinary teams. This could lead to suboptimal solutions proposed by the team. This is harmful if communication skills vary among design team members. Research might want to further examine this potential negative effect of analogical communication by focusing on the intend of the message (i.e. analogy).

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More broadly speaking, we encourage researchers who study themes within design collaboration, to not only to focus on the direct observations, but also on the perception of individuals within the social system. For example, rather than trying to measure multi-disciplinary diversity (e.g. Menold & Jablokow, 2019), researchers could also focus on the perceived diversity within design teams. Research in management and organizational psychology has shown that perceived diversity effects team processes and performance outcomes (Shemla, Meyer, Greer, & Jehn, 2016). This study focused solely on the recipients’ perception that an analogy was used, and we are not able to say if the recipient interpreted the message correctly. In other words, we do not know if the analogy was interpreted as the sender intended, or whether the specific content of the analogy was important. Hence, we can not assess the effectiveness of the analogy itself. Future research could distinguish, and study both, the sender’s and recipient’s perspective to examine the effectiveness of an analogy. In addition, the new scale might be beneficial for practitioners to administer the scale in their own organisation to examine design team functioning. Research in design has shown that designers and managers often use different languages, which can lead to misunderstandings (e.g. Micheli, Jaina, Goffin, Lemke, & Verganti, 2012). Analogical communication might help to overcome these misunderstandings (Christensen & Schunn, 2007). Given the success is training designers to use related communication tools such as narratives and visualisations to improve understanding (Graff & Clark, 2018a), it may be that analogical communication, both expressing and perceiving, can be learnt as well (Wormeli, 2009). In sum, the development of a perceived analogical communication scale will enable researchers and practitioners to more effectively measure the influence of analogies on team processes and outcomes.

Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Notes 1. For a full list of items, please contact the authors.

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