How to Radically Improve Communication of Innovation:
Short- and Long-term Persuasive Consumer Effects and the Role of Brand Equity
Gerjon Daniël Dol
Student number: 10631569
Master thesis, Graduate School of Communication
Specialization Persuasive Communication
Supervisor: Dr. L. R. Salome
Author Note
The current study is a master thesis, supervised by Dr. L. R. Salome, Faculty of Social and Behavioural Sciences, University of Amsterdam. Correspondence concerning this article
Abstract
Communicating innovation has been subject of debate for a long time. A plethora of innovation typologies and absence of research that differentiates between short- and long-term effects make the relationships difficult to unravel, and the role brands can have in this respect is often overlooked in prior research. In the current paper, these short- and long-term persuasive effects of communicating innovation are studied. In a 2 (innovation: radical versus incremental) x 2 (brand equity: high versus low) between-subjects experiment, participants are measured on short-term buying intention and long-term brand loyalty. The role of brand equity is hypothesized to have a moderating effect in these relationships. The results show that communicating radical innovations lead to higher short-term buying intention in consumers compared to incremental innovations, whereas brand equity positively moderates the relationship between innovativeness and brand loyalty. Managerial implications, as well as future research directions, are discussed.
How to Radically Improve Communication of Innovation:
Short- and Long-term Persuasive Consumer Effects and the Role of Brand Equity
Many companies today incorporate innovation in their core values, name innovation as one of their companies’ ‘pillars’, or even refer to concepts related to innovation in their
slogans. Honda’s ‘The power of dreams’, Boeing’s ‘Forever new frontiers’, Ericsson’s ‘Taking you forward’, Ford’s ‘Build for the road ahead’ and finally General Electric’s ‘Imagination at work’ all communicate some form of innovation. IBM has spent $6 billion dollars in the research department last year, facilitating innovation. Furthermore, IBM states that innovation is “the intersection between invention and insight”, and that it “creates value” (Quitzau, 2010, p. 3). However, communicating this innovation towards the consumer often remains a difficult task. In 1993, Apple released the ‘Newton’, the first personal digital assistant. It could recognize handwriting, exchange data with the PC, store contacts, convert notes to meetings in the agenda, and send and receive e-mail. Although innovative, sales disappointed and the Newton was discontinued, because Apple did not communicate a clear marketing vision for the product (Markoff, 1995). This example shows a number of concepts illustrative for the current paper.
First, it shows that the way innovation is communicated is crucial. Researching
efficient communication is a good contribution to any innovation, if not essential. Second, the example illustrates that at the intersection between innovation and communication, more insight is needed on how to maximize communication towards the consumer. Third, it shows that a firmly established brand cannot save an innovative, but badly communicated move, raising questions what effect a brand can have. This necessary paper thus offers insight regarding these communicative effects of company innovation, for as long as all these effects are not fully mapped, companies still face room for error regarding the communication of
innovation. As explained below, a distinction is made between short- and long-term consumer effects, as well as the role of brand equity.
Organizations are often subject to the metaphor of ‘the living organism’ (Morgan, 2011). Indeed, it is convenient to think of organizations in the light of ecology and evolution theory, because many analogies arise. For example, in order to survive, organizations strive for growth and adapt to the environment (Tushman & O’Reilly, 1996). Furthermore, efficient interaction with this environment provides organizations a competitive edge in survival (Lomi & Larsen, 1996). Most importantly, organizations show evolutionary growth, sometimes discontinued by revolutionary growth. Analogous to evolution theory, the company’s growth is sometimes offset by sudden ‘spikes’, often resulting from innovation (Greiner, 1998). This distinction between evolutionary and revolutionary innovation provides a time-frame, in which the company’s communication has room to differ. As this communication is
indistinguishable from an organizations culture, brand, and identity (Gray & Balmer, 1998), it is useful to examine the effects of evolutionary or revolutionary innovation on short- and long-term communication. In prior research, evolutionary and incremental innovation are often used as synonyms. Similarly, revolutionary and radical innovation are interchangeable (Story, Malley, & Hart, 2011). For the current study, incremental and radical innovation will be the terms used, as these are one of the most widely used dichotomous categorizations now found in literature (Garcia & Cantone, 2001).
In the current research, the consumer effects of communicating innovation on the short- and long-term are studied, and more specifically, what the communicative effect of incremental or radical innovation is on short- and long-term persuasiveness. However, prior research shows that the involved brand can have a moderating effect. For example, using innovation as a core claim can have a negative effect on long-term brand building (Ghanadan & Long, 2011), and the fact of merely branding an innovation maximizes its impact on the
consumer (Aaker, 2007). This shows that the perceived value of a brand, or ‘brand equity’, is a variable that needs to be taken into account. Brand equity is used because consumers react more favorably to high-equity brand products than to the same product without that specific brand attached to it (Keller, 1993). Concluding, the paper answers the following research question: What are the short- and long-term persuasive effects of communicating innovation and how does brand equity influence this effect?
Theoretical background Need for Innovation
Organizations today face many challenges, of which communicating innovation is one. The need for a company to innovate is explained multifold. Innovations are crucial for a company that seizes opportunities to grow, as innovations can simply create or improve the offering done by a company, or innovations can affect perception of the organization or corporate brand with respect to innovativeness (Aaker, 2007). Organizations also innovate to make use of opportunities in the fields of technology, changing marketplaces, structures, and dynamics. Moreover, organizations must simply innovate in response to changes in consumer demand (Rowley, Baragheh, & Sambrook, 2011). Hence, the adaption of innovation within organizations has received considerable attention in the past few decades (Frambach & Schilleweart, 2002). So, innovation is an absolute necessity for organizations, a conclusion which is underlined through the field of organizational ecology. The analogy of an
organization as a ‘living organism’ can be herein illustrative for its necessity to innovate (Morgan, 2011).
Organizations adapt to the environment as they need to grow (Tushman & O’Reilly, 1996), and efficient communication with this environment can provide a competitive edge which aids in survival (Lomi & Larsen, 1996). If an organization does not innovate in its offer
or underlying creation or delivery, it risks these survival and growth prospects (Bessant, Lamming, Noke, & Philip, 2005). In order to survive, organizations need to invest in different kinds of innovation, for different kinds of innovation lead to different outcomes and impacts (Siguaw, Simpson, & Enz, 2006). The current paper, however, focuses on incremental and radical innovation, which is the most widely recognized dichotomous distinction (Garcia & Cantone, 2001).
Although consensus about the constructs, the terms ‘revolutionary’, radical’, ‘really-new’, and ‘discontinuous’ innovation are often used interchangeably (Garcia & Calantone, 2002; Story, Malley, & Hart, 2011). However, evolutionary growth empirically equals incremental innovation, whereas revolutionary growth equals radical innovation (Utterback, 1996). Viewing former frameworks and models, the need to evaluate the communicative effects of incremental and radical innovation on consumers becomes evident, as most frameworks do not incorporate efficient communication of innovation.
Innovation Frameworks and the Lack of Communication
Innovation typologies are abundant, but researchers mostly have not reached a
consensus about the exact borders of constructs within innovation (Garcia & Calantone, 2002; Story, Malley, & Hart, 2011). One of the first frameworks is described by Knight (1967). Distinguishing between product-service innovation, product-process innovation,
organizational structure innovation, and people innovation, it does not take communication of these innovations into account. Illustrative, around the same time, Evan (1966) describes an administrative-technical discrepancy, in which the adoption of innovation differs for
administrative or organizational innovations, compared to technical innovations. Furthermore, many other, usually pair-wised, models have been proposed, wherein no mention of
framework where innovation is classified as either a product or a process innovation, as well as later innovation frameworks, which make a distinction between technical and technological innovations (Damanpour & Evan, 1984).
Important for the current paper, however, is that later, binary innovation models have taken the change or newness of an innovation into account and distinguished between radical and incremental innovation (Dewar & Dutton, 1986), where radical innovation is described as being a fundamental change in the broadest sense, and incremental innovation is considered an add-on without changing the essential concept (Dewar & Dutton, 1986; Rowley, Baragheh, & Sambrook, 2011). Indeed, the multidimensional innovation model by Cooper (1998)
incorporates this incremental-radical, as well as product-process and
administrative-technological dimensions of innovation. Because these more recent models still do not take the communication of these innovations into account, the aim of the current paper is to fill that research gap by focusing on how communicating different innovation types affect the consumer. As the aforementioned dimension of incremental-radical is one of the most widely used dichotomous categorizations now found in literature (Garcia & Cantone, 2001), the current paper will focus on what short- and long-term effects communication of incremental or radical innovation can have on the consumer.
Next to the lack of communication in the previous frameworks, it is evident that the different innovation typologies and models have a general concept in common. All explain that innovation results from mere product presence, despite the plethora of definitions and constructs. A more recent model, by Oke, Burke, and Myers (2007), rightly states that product innovation, in fact, automatically results in incremental or radical innovation, which can be measured on a continuum (Tidd, Bessant, & Pavitt, 2005). Although some debate exists regarding the clear definition of a radical innovation, consumers generally recognize it when they see it (Story, Malley, & Hart, 2011), but still, researchers have signified a research gap
concerning these radical innovations (Garcia & Calantone, 2001). Since radical and incremental innovation are regarded as being an attribute to any kind of innovation, like product, process, administrative, or technical (Rowley, Baragheh, & Sambrook, 2011), this signified research gap, illustrated by the lack of communicative guidelines in innovation models, makes the current research of vital importance.
At the Intersection of Communication and Innovation
Ever since the early 1990’s, the communication of corporate image and its
implications in other areas are under the continuous scope of research. Then, research already concluded that the change of corporate or brand image is paired with coordination within multiple other areas, such as vision, strategy, organizational design, organizational culture, and marketing communications (Downling, 1993). All of these factors are decisive for
innovation, which is illustrative for why innovation and communication are intertwined in the core of any organization. Ever since the rise of integrated communications, the relationship between the organizations’ culture, brand and identity have become even more interdependent (Gray & Balmer, 1998), leading to centralized corporate communication, which cannot be seen apart from other aspects of the company. In other words, this interdependent relationship has led to the synergistic ‘one spirit’, ‘one look’, or ‘one voice’-phenomenon (Kliatchko, 2009) which is also the starting point of integrated marketing communications (Luck & Mofatt, 2009). Subsequently, a lot of research has been done regarding the most effective way to communicate, for example, new products to the public (Lodato, 2008). However, the current paper differentiates by focusing on the holistic features of communicating innovation, as opposed to merely boosting sales or justifying certain marketing methods. More
specifically, the current paper aims to unravel the complex relationship between
aforementioned centralized corporate communication and intrinsic innovation, which are forcedly intertwined.
Innovation and communication can be considered as to develop within organizations in juxtaposition, as the communication is affected by type and amount of innovation and the other way around. For example, previous research has shown that patterns of technical communication have effects on the success of technological innovation (Utterback, 1984). Other researchers have pointed out what factors would stimulate or limit an organizations’ potential for innovation. Communication appears key, as the two factors are explained as the definition and communication of needs for innovation, and the existence and communication of technical innovation (Utterback, 1971). Underscored by Kelley and Littman (2006), if an organization wishes to innovate, it needs to communicate innovation not only at the level of the product, but incorporate this at every point of the company compass. If organizations succeed, it raises the question how communicating these innovations affect the consumer. If a company indeed incorporates innovation at every point of the organizational compass, the results may differ on the short- and long-term, depending on the type of innovation that is communicated.
Concluding, in order to survive, organizations need to strive for growth, as they are subject to ecology theory (Tushman & O’Reilly, 1996). To grow, a company must innovate in some manner and have some share of the market, as evolution equals revolution in terms of innovation (Greiner, 1998). Furthermore, as integrated communications have emerged, the relationship between corporate culture, corporate brand, and corporate identity are all crucial for corporate communication (Gray & Balmer, 1998). Communicating innovation not only affects how the product is perceived (Aaker, 2007), but also the corporate image (Abratt & Kleyn, 2012), is a mirror of the internal communication (Greiner, 1998), and thus is generally connected to all other aspects of an organization (Downling, 1993). The efficient interaction of an organization within its field creates a competitive edge, which in turn leads to more market share, more investors and better revenues (Lomi & Larsen, 1996). This leads to the
assumption that all companies innovate at some point in time, in some sort of way, which automatically is communicated within the entire environment in which the organization is active. The current paper furthermore aims to unravel differences concerning short- and long-term consumer effects of communicating innovation.
Short-term Effect of Communicating Innovation
As mentioned earlier, the short-term effect of communicating innovation is
operationalized as buying intention. Prior research has also measured short-term effects of innovation as buying intention of the consumer (Yoh, 2005). To understand what the short-term effects on consumers may be when organizations communicate innovation, the innovation adoption theory can be taken into account (Rogers, 2004). In this model, the concept of innovation has the following persuasive attributes: relative advantage, compatibility, complexity, observability, and trialability. Consumers generally adopt
innovations faster when these innovations are more complex, have higher compatibility, and relate to lower uncertainty (Arts, Frambach, & Bijmolt, 2011). This means when an
innovation is more complex, better suits a need, and is less ambiguous, short-term effects are more positive for consumers. More complex innovations can be considered to be more radical than incremental, as the complexity is generally higher for products which are fundamentally different. This means that short-term effects, operationalized as buying intention, tend to be more frequent when innovations are radical compared to when they are incremental.
Furthermore, higher compatibility relates to better matching consumers’ needs. In radical innovations, the innovation would logically not be brought to the consumer if the organization thinks it would not better suit the consumers’ needs. Hence, when radical innovations are communicated, this will elicit higher short-term effects, operationalized as buying intention, compared to incremental innovations. It is due to these effects the current paper hypothesizes
that when an organization communicates radical innovation, buying intention is higher compared to incremental innovation. This is summarized in the first hypothesis:
H1: When an organization communicates radical innovation, buying intention is
higher compared to when incremental innovation is communicated.
Long-term Effect of Communicating Innovation
Where previous research has stated that innovation needs to be communicated not only at the level of the product, but incorporate this in every aspect of an organization (Kelley & Littman, 2006), prior research has also shown that using innovation as a core claim can lead to negative consequences in long-term brand building (Ghanadan & Long, 2011). This raises the question whether communicating innovation has effects on the long-term, or brand loyalty. It is important to stress out that the current paper does not aim to identify the exact border between short- and long-term effects, but instead focuses on both independently. Although it is safe to logically assume that short-term effects precede long-term effects and the latter act longer, at what point in time and how they interact is currently not the focus, and instead should be subject of future research.
It is hypothesized that when organizations communicate incremental innovation, brand loyalty will be higher compared to radical innovation. Uncertainty is an important obstacle to the consumer adoption of innovations (Rogers, 2004), and the consumer might see
incremental innovations as more safe. Furthermore, prior knowledge about the product or organization plays a greater role in incremental innovations, because the consumer would perceive the innovation as less uncertain than radical innovations (Hoeffler, 2003). Finally, prior research shows that perceived product quality leads to a higher brand loyalty (Nguyen, Barett, & Miller, 2011). When incremental innovation is communicated, and the consumer already has prior knowledge about the organization or product, the current paper hypothesizes
that brand loyalty will increase when incremental innovation is communicated, compared to when radical innovation is communicated. This is summarized in the second hypothesis:
H2: When an organization communicates incremental innovation, brand loyalty will
be higher compared to when radical innovation is communicated.
Role of Brand Equity
When comparing short- and long-term consumer effects of communicating innovation, one can argue the role of brand to be of big importance. Indeed, as mentioned before,
integrated communications has led to the combination of an organization’s culture, brand, identity, and communication (Gray & Balmer, 1998). This integration has led to the ‘one-voice-phenomenon’ (Kliatchko, 2009), which is considered the synergistic starting point of integrated marketing communications (Mofatt, 2009). This means that organizations that communicate innovation, communicate more than just an innovative product. They communicate not only their brand, but all related aspects considered by the consumer. Organizations are keen on making consumers brand loyal, as this has significant impact on purchase behavior in the long term (Shukla, 2009). And indeed, branding an innovation does maximize its impact on the market (Aaker, 2007). Brand equity is chosen as the
operationalization of the role of the brand, as consumers react more favorably to products of high-equity brands than to the same product without that specific brand attached to it (Keller, 1993).
Furthermore, when consumers consider certain brands, social identification can play an important role. Social identification means that consumers identify themselves with certain brands, and that it has a positive relationship with the brand value and brand trust (Hongwei, Yan, & Lloyd, 2012). This brand trust diminishes uncertainty about a brand (Hoeffner, 2003), leading to quicker consumer adoption of an innovation (Rogers, 2004).
Concluding, previous research shows that the involved brand has an influence on the effect of communication of innovation on buying intention and brand loyalty, which raises the question to what extent this is the case. For example, in high-tech firms, innovation as a core claim can have negative effects on long-term brand building, because innovation is considered an earned attribute (Ghanadan & Long, 2011). Seeing that branding an innovation maximizes its impact on the market (Aaker, 2007), the current paper hypothesizes that brand equity moderates both the effects of radical innovation on buying intention and incremental innovation on brand loyalty. More specifically, brand equity enhances both these effects, which is summarized in the third and fourth hypothesis:
H3a: The effect of radical innovation on buying intention (H1) is stronger for high
brand equity, compared to low brand equity.
H3b: The effect of incremental innovation on brand loyalty (H2), is stronger for high
brand equity, compared to low brand equity.
Conceptual Model
The conceptual model of the current paper is shown below. The current paper studies the how communication of incremental and radical innovation affects consumers on the short- and long-term. Furthermore, the moderating role of brand equity is taken into account.
Because brand equity is manipulated in the current paper, the conceptual model features brand equity as a second independent variable. However, the hypotheses regarding brand equity assess its influence between the other independent variable and the dependent variables. Hence, brand equity is incorporated in below conceptual model as another independent variable, where its role in the model is hypothesized to be a moderating one. More specifically, the current paper hypothesizes that radical innovation leads to higher buying intention compared to incremental innovation, whereas incremental innovation leads to higher
brand loyalty, compared to radical innovation. Brand equity is hypothesized to enhance both these effects.
Methods
Design
The current paper featured a 2 (innovation: incremental versus radical) x 2 (brand equity: high versus low) between-subjects full-factorial design. The two dependent variables were ‘buying intention’ and ‘brand loyalty’.
Participants
Participants were reached by several means. First, participants were contacted through social media and e-mail. Moreover, advertisements were hung throughout a university in Amsterdam to reach more people. Lastly, flyers were spread at several locations, including a musical institute, to reach more participants. The convenience sample eventually consisted of N = 229 respondents, of which 38.9% male and 61.1% female. The average age was 29 years (M = 29.33, SD = 11.69), and education level was 4% high school (N = 10), 7.8% average
Brand Equity
Persuasive communication effects Long term (brand loyalty) Short term (buying intention) Innovation Incremental Radical H1 H2 H3a H3b High Low
professional education (N = 18), 37.5% high professional education (N = 85), and 50.7% university (N = 116). N = 221 respondents are from The Netherlands, N = 2 from Belgium, N = 2 from Germany, and N = 1 from Switzerland, France, The United States, and Japan.
Participants were volunteers and not in any way rewarded, and participants were all divided into four different groups by random trial, which was automatically done by the online survey tool Qualtrics. A restriction in the sample could be that most respondents were not above 40 and most of them highly educated (50.7% university, N = 116) students,
excluding portions of the population and creating an unrepresentative sample of the population.
Materials
All the stimuli presented were shown on a computer by Qualtrics, an online survey tool, which included 15 questions after exposure to two texts. 2 (innovation: incremental versus radical) x 2 (brand equity: high versus low) texts were shown. A fictional car brand ‘Hindushi’ was used. This way, participants were not biased by the brand because they did not know the brand, and Japan is a credible country for such statistics. Furthermore, Japan was argued to be a culturally close enough, but still geographically far enough for the cover story to be credible.
In the radical innovation condition, the text elaborated on a new car which was told to run on water. In the incremental innovation condition, the text told the new car to be
somewhat better than its predecessor. In the high brand equity condition, participants were told that 41 percent of the population in Japan owns this specific car brand, and that it has won several prizes. In the low brand equity condition, the extra text told participants that only 3 percent of the population in Japan owns the specific car brand and that it is considered as unpopular. All texts can be found in Appendix A.
Items
The survey consisted of 15 items, of which four were demographical, seven measured the dependent variables, and four measured the independent variables. All items were
measured on a five-point Likert-scale (1 = totally not agree and 5 = totally agree). Including informed consent and contact information, the total number of questions added up to 17.
Buying intention. Regarding the dependent variables, participants answered three items about buying intention. Two of these were adapted from Kim and Chung (2011), and one from Lin (2007). In prior research, buying intention is often operationalized in terms of likelihood, probability, or willingness to buy (Sinrungtam, 2013). Other research agrees that likelihood is a common construct for measuring buying intention (Son, Jin, & George, 2013). The current study will use similar operationalizations, but the items are tailored to fit this specific study context.
Brand loyalty. Brand loyalty was assessed based on the definition of Moutinho, Davies, and Curry (1996), confirmed by Wu (2011), which define car brand loyalty as switching current car brand. Furthermore, Rundle-Thiele and Bennett (2001) further argue that high risk and involvement products are better assessed by attitudinal measures to predict future behavior. This is consistent with other literature on assessing brand loyalty (Dick & Basu, 1994; Neal & Strauss, 2008; Liu, Li, Mizerski, & Soh, 2012). Thus, the four questions incorporated switching brands as well as attitudinal measures. For example, attitudinal measures such as “I like the ‘Hindushi’ brand” were used in the brand equity manipulation, which correlated with brand loyalty on a significant level (r = .273, N = 229, p < .001, two tailed). The complete survey can be found in Appendix B.
Pretest
Manipulation and reliability. A pretest was done that assessed that the dependent variable scales measured what they were supposed to measure, and no problem regarding internal consistency or multicollinearity was found. Manipulation checks were also
performed, as well as principal component analysis to assess whether the dependent variables indeed measured the meant constructs. In the pretest (N = 56), innovation type was significant with F(1, 55) = 34.99, p < .001, ηp2 = .479 and brand equity was significant with F(1, 55) =
16.47, p < .001, ηp2 = .302. Confirmed in the survey (N = 229), innovation type (F(1, 228) =
71, p < .001, ηp2 = .238) and brand equity (F(1, 228) = 21.42, p < .001, ηp2 = .086) were
successfully manipulated.
Furthermore, the scale used for measuring innovativeness (N = 2) showed a Cronbach’s Alpha of α = .849, and the scale assessing brand equity (N = 2) α = .67. The dependent variable buying intention (N = 3, α = .856) and brand loyalty (N = 4, α = .781) both seemed to have no problem regarding internal consistency. As the independent variables did not have any variance inflation factors (VIF) above 1.3, the VIF < 4 indicated no problems regarding multicollinearity.
Factor analysis. The dependent variables were further subjected to factor analysis. Regarding brand loyalty, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .74, which was above the recommended value of .6. Moreover, Bartlett’s test of sphericity was significant (χ2 (6) = 274.99, p < .001). Principal component analysis showed
communalities all above .5, and a one-component solution showed an eigen value of 2.45, which explained 61.31% of variance in brand loyalty. Finally, a scree plot confirmed a one-component solution. Buying intention showed similar results, with a KMO measure of .73, and a significant Bartlett’s sphericity test, with χ2
component analysis showed a one-component solution with an eigen value of 2.35, which explained 78.47% of variance in buying intention. The scree plot again confirmed the one-component solution. Concluding, the conditions were correctly manipulated, and the items and scales were to be justifiably used in the survey.
Procedure
The total 228 participants were provided with a hyperlink on which their response was automatically recorded within Qualtrics, an online survey tool. The respondents were first presented with the ethical guidelines of research and were asked for their informed consent. Then, their age, gender, country of residence, and education level were asked. After these questions, the participants were divided by random trial into one of four conditions: radical innovation with high brand equity, radical innovation with low brand equity, incremental innovation with high brand equity, and incremental innovation with low brand equity. In each condition, respondents were exposed to either of the two texts, which can be found in
Appendix A. Following exposure to the texts, participants were presented with 11 items, which were all measured on five-point Likert scales. Three items measured buying intention, four items measured brand loyalty, two items measured the level of innovativeness and two items measured the level of brand equity. After answering these 11 questions, respondents were asked if they would like to be notified about the results of the current study. The
respondents were finally thanked for their attention and the results recorded. The entire survey can be found in Appendix B.
Results
Main Effects of Innovation type on Buying Intention and Brand Loyalty
Regarding the first hypothesis, radical innovation was argued to have a positive effect on buying intention compared to incremental innovation. The respondents exposed to the
radical innovation condition indeed showed higher buying intention (M = 2.97, SD = 0.79) compared to the incremental innovation condition (M = 2.49, SD = 0.88). Analysis of variance (ANOVA) shows that this difference is significant (F(1, 228) = 18.73, p < .001, ηp2 = .076),
confirming H1. Furthermore, an analysis of covariance (ANCOVA) was performed in order to
identify any possible confounding variables. Controlling for age, gender, country of residence, or education level, the result remains significant (F(1, 223) = 17.90, p < .001, ηp2 = .074).
In the second hypothesis, incremental innovation was argued to elicit higher brand loyalty, compared to radical innovation. An ANOVA was performed, in which the
incremental innovation group (M = 3.19, SD = 0.68) and the radical innovation group (M = 3.24, SD = 0.71) showed no significant difference with F(1, 228) = .35, p > .56, ηp2 = .002.
With these results, the data does not support H2. Possible confounders were not identified by
ANCOVA (F(1, 223) = .37, p < .001, ηp2 = .002). The results of the ANOVA of H1 and H2 are
summarized in Table 1.
Table 1
ANOVA results of radical innovation on buying intention and incremental innovation on brand loyalty
Variable Df F ηp2 p
Radical innovation a 1 18.73* .076 .000
Incremental innovation b 1 .348 .002 .56
Note: N = 229, * significant at the p ≤ .05 level, a ANOVA on the dependent variable buying intention,
b
Interaction Effect of Brand Equity
H3a and H3b concerned a moderation effect elicited by brand equity. The third
hypothesis described brand equity to have a moderating effect on the relationship between innovation type and brand loyalty, with the high brand equity group strengthening the effect of radical innovation on buying intention. H3b was argued to show a similar effect, with brand
equity moderating the relationship between innovation type and brand loyalty. In short, high brand equity was hypothesized to elicit a higher effect between incremental innovation and brand loyalty, compared to radical innovation. Similar to H3a, H3b argued for brand equity
positively moderating the effect of H2.
An analysis of variance was performed to assess whether brand equity moderated the effect of innovation type on buying intention. Mean scores on buying intention significantly differed for the radical innovation group (M = 2.97, SD = .79) and the incremental innovation group (M = 2.49, SD = .88) with F(1, 228) = 7.38, p < .001, ηp2 = .08. Mean scores on buying
intention for the low brand equity group (M = 2.74, SD = .81) and the high brand equity group (M = 2.73, SD = .92) did not differ significantly (F(1, 228) = .03, p = .854, ηp2 = .000).
Regarding the third hypothesis, ANOVA shows that no interaction effect is present (F(1, 228) = 1.33, p = .251, ηp2 = .006). Both variables do explain a significant proportion of variance in
buying intention, R2 = .34, F(2, 227) = 58.64, p < .001. Although innovation type alone also explains a significant proportion of variance in buying intention, R2 = .26, F(1, 228) = 80.32, p < .001, significant R2 change of R2change = .08 (F(1, 228) = 27.55, p < .001) argues for
incorporating both variables in the model to explain the most variance. However, the absence of an interaction effect between innovation type and brand equity leads to the conclusion that brand equity does not influence the effect of innovation type on buying intention. Controlling for age, gender, country of residence, and education level, ANCOVA also does not show
significant interaction (F(1, 221) = 1.02, p < .314, ηp2 = .005) With these data, H3a is not
supported.
Lastly, H3b is tested by performing an ANOVA of centralized innovation type, brand
equity, and their product term on brand loyalty, to exclude any problems regarding
multicollinearity. Brand equity was found to have a significant effect on brand loyalty with F(1, 228) = 2.47, p = .014, ηp2 = .098), whereas innovation type was found to be marginally
significant (F(1, 228) = 3.64, p < .074, ηp2 = .035). Most interestingly, the interaction effect of
brand equity and innovation type was statistically significant with F(1, 228) = 3.92, p = .050, ηp2 = .052). These results partially confirm H3b, and are summarized in Table 2. Further
clarifying the direction of this interaction effect, the regression of innovation type and brand equity on brand loyalty is graphically presented as a scatterplot in Figure 1. The effect of brand equity on the relationship between innovation type and brand loyalty is higher for the high brand equity group. The high brand equity group shows higher brand loyalty as an innovation becomes more radical, compared to the low brand equity group.
Table 2
ANOVA results of innovation type, brand equity, and the product term on brand loyalty
Variable Df F ηp2 p
Innovation type 1 3.64 .035 .074
Brand equity 1 2.47* .098 .014
Innovation type * Brand equity 1 3.92* .052 .050
Figure 1. Scatterplot of brand loyalty as a function of innovativeness (centralized), split for low brand equity (R2 = .010) and high brand equity (R2 = .090).
Discussion Communicative Effects on Short- and Long-term
Regarding the hypotheses, supportive data has been provided by the current research. Support has been found regarding the first hypothesis, in which radical innovation causes higher buying intention compared to incremental innovation. The participants responded in such a way that the car that runs on water evokes more short-term effects than does the car that is merely more innovative in comparison to its predecessor. This result is not surprising, as it is a logical extension to previous literature.
To confirm that communicating radical innovations evoke higher short-term effects than long-term effects on consumers is consistent with diffusion of innovations theory (Rogers, 2004). It is often subject of discussion which of the five factors (relative advantage, compatibility, complexity, divisibility or trialability, and communicability) carries the heaviest weight. Moreover, a lot of scholars argue in favor of a sixth attribute, perceived risk (Bauer, 1960). Perceived risk is known to negatively influence buying intention, whereas the factors positively influencing buying intention are relative advantage and compatibility (Holak & Lehmann, 1990). Indeed, in the current paper, the car that runs on water has high relative advantage compared to the car that is incrementally innovative, where it is merely compared to its predecessor. On the other hand, one could argue that the perceived risk and compatibility are not in favor when discussing radical innovations regarding cars, because, for example, the effect of price on product evaluation (Dodds, Monroe, & Grewal, 1991).
However, additionally, more recent research suggests that short-term consumer effects are positively influenced when an innovation is more complex, better suits the consumers’ need, and is less ambiguous (Arts, Frambach, & Bijmolt, 2011). In this specific case, arguably, a car that runs on water may not be perceived as complex or ambiguous by the participants. Indeed, comparing radical and incremental group means, one could hesitantly say that the radical innovation may not be perceived as more complex or ambiguous at all compared to the incremental innovation, thus confirming prior literature that a radical
innovation indeed evokes higher short-term effect on consumers, compared to an incremental innovation. The current paper, where short-term effects are operationalized as buying
intention, does confirm this hypothesis. Finally, as behavioral intention is a very strong
indicator of actual behavior in car purchase intentions (Mairesse, Macharis, Lebeau, Turcksin, 2012), the current paper contributes to the understanding of communicating radical
Brand Equity
Even more so, the current paper provides evidence regarding the role of brand equity. A moderating influence is feasible, as the graphical presentation shows a heightened effect for high brand equity. If the influence of brand equity were to be mediating, for example, this effect would not be consistent with the found effect innovation type alone has on brand loyalty. With brand equity strengthening this effect, mostly when brand equity is high, a moderating influence is observed. Although not entirely hypothesized, brand equity positively influences the relationship between innovativeness and brand loyalty. In other words, when consumers are exposed to an innovative product, perceived as from a high-equity brand, they will be more loyal to the brand when the product in question is more radically innovative than when the product is more incrementally innovative. This result regarding the communication of innovation is of great value, as brand loyalty is of major impact on consumer purchase behavior in the long term (Shukla, 2009), illustrated by the maximization of impact on the market when merely branding an innovation (Aaker, 2007). Lastly, the result is financially appealing, as retaining consumers is more cost-efficient than recruiting new ones (Birgelen, Wetzels, & De Ruyter, 1997).
The current role of brand equity is an insightful one, not only for marketing purposes, but also in addition to existing literature. Prior research has shown that when customer loyalty is high, so will brand equity be (Aaker, 1991; Lee, Lee, & Wu, 2011). The current paper proves this relationship to be in both directions. Not only will brand equity be higher when consumers are more brand loyal, but the moderating role of brand equity is selective on influencing brand loyalty in terms of innovativeness. This means that there may also be other factors that influence the way brand equity and brand loyalty are intertwined. Future research has to be performed in identifying these factors and what their relationship is between types of innovation and brand loyalty.
The second and third hypotheses are, although not supported by the data, nevertheless important. Incremental innovation does not lead to higher brand loyalty, and in fact, the group means point towards a trend in the opposite direction; radical innovation evokes more brand loyalty in comparison to incremental innovation. In addition to this result, the fact that an incrementally innovative product with high brand equity leads to lower brand loyalty in comparison with a low brand equity product can have a confusing effect. Indeed, one could argue that the incremental innovation is not seen as an innovation at all, but the current research still shows differences in brand loyalty for incremental innovation, when split for brand equity. Moreover, no support was found for the influence of brand equity on the relationship between radical innovation and buying intention. This is surprising, as an effect of innovation on buying intention was found, as well as the role of brand equity in the
relationship between innovation and brand loyalty. This means brand equity, in practice, does not add towards buying intention when an innovation is communicated in general. The data point towards brand equity merely playing a role when innovativeness is already quite high, making the influence of brand equity not an important one to consider.
Concluding, the current paper aimed on answering the following research question: What are the short- and long-term persuasive effects of communicating innovation and how does brand equity influence this effect? Summarized, short-term persuasive effects,
operationalized as buying intention, are heightened when a communicated innovation is radical in comparison to incremental. Although marginally significant, radical innovations also appear to have a positive effect on brand loyalty. Regarding the role of brand equity, the current research finds that brand equity is indeed of influence, but only in the long term. When communicated innovations are radical, high-equity brands evoke higher brand loyalty, compared to low-equity brands.
Limitations
A possible pitfall in the current paper is the fact that brand loyalty is measured on a fictional brand. From multiple brand loyalty scales, the core was taken out, such as switching brands (Moutinho, Davies, & Curry, 1996; Wu, 2011), and buying brands multiple times in a row (Netemeyer, Krishnan, Balaji, Pullig, Chris, Wang, Guangping, Yagci, Mehmet, Dean, Dwane, Ricks, Joe, Wirth, Ferdinand, 2004). This apparently was not enough to evoke brand loyalty. Differentiating between perhaps four different clusters of brand loyal consumers (Knox & Walker, 2010) was not taken into account and, as such, findings regarding brand loyalty remain open for further investigation.
Furthermore, high risk and involvement and propensity towards sole brands, is where attitudinal measures better predict future behavior (Rundle-Thiele & Bennett, 2001). Other scholars also stress the importance of attitudinal as well as behavioral dimensions to measure brand loyalty (Dick & Basu, 1994; Neal & Strauss, 2008; as described in Liu, Li, Mizerski, & Soh, 2012). Attitudinal measures were used in the brand equity manipulation (such as ‘I like the ‘Hindushi’ brand’), which correlated with brand loyalty significantly. So although attitudinal measured were used to assess brand loyalty, the correlation suggests that the used scales do, in fact, predict brand loyalty.
Thirdly, assessing long-term effects without longitudinal measures is not optimal. Future research indeed could, and should, take longitudinal measures into account. Because the current paper is not longitudinal in nature, long-term brand loyalty had to be measured in a short-term fashion. Although scales were subject to thorough analysis, results could still be compromised due to this limitation. Concluding the discussion about brand loyalty, the problem seems to remain the fictional brand and lack of longitudinal measures, which makes brand loyalty hard to realistically evoke.
Lastly, the sample were mostly highly educated students (50.7% university), of which some may not yet own a car. This may have led to different results as when maybe more representative samples of the population were exposed to the survey. Moreover, prior research shows that information about environmentally relevant utilitarian product attributes affects purchase intentions (Roberts, 1996; Scholder-Ellen, 1994; as described in Hartmann, Apaolaza-Ibáñez, 2012). The environmentally relevant attributes, operationalized as innovation conditions, may have played a role in the results.
Implications
In practice, the current results lead to important implications that have to be taken into account when communicating an innovation. When the innovation itself is radical, more short-term effects will take place, resulting in more buying intention from the consumer. The question rises if innovations that are in fact more incremental than radical, but are
communicated in such a way that mostly stresses the radical factors of the innovation, will lead to the same short-term effects. Managers should take this into account when
communicating a radical innovation, because setting long-term goals in terms of brand loyalty will take more effort than the innovation alone.
Similarly, when radical innovations are communicated, managers need to realize that communicating high-equity brands will lead to higher short-term effects. In practice, this means that managers need to do thorough research in the equity their brands represent, in order to fully assess how high their short-term goals can be set. Regarding the expected but absent findings, managerial implications can also be drawn from the current paper. In communicating incremental innovations, managers should not expect to affect long-term consumer loyalty. High-equity brands also do not have a head start here; incremental
communicating innovations more radically then they really are would help in this respect, and the current paper would hint in that direction.
Future research
Future research needs to be done in order to fully assess the effects that
communicating innovations has on the consumer. As mentioned earlier, the question rises how short- and long-term communicative effects influence consumers if the innovation itself differs from the way it is communicated towards the consumer. Similarly, if brand equity can be manipulated in communication, similar effects might occur. Future research needs to be done for these effects to be fully examined. Future research should, for example, focus on the manipulation of perceived brand equity. When brand loyalty can be influenced by
manipulating perceived consumer brand equity, and similar effects are found, brand equity could no longer be a passive trait for brands.
Furthermore, the current paper uses a fictional brand in determining brand loyalty. In future research, a solid way of assessing brand loyalty on fictional brands should be
considered. Similarly, non-fictional brands could be used that are still neutral to the consumer, in order to eliminate any confounding effects of fictionality. Thorough pretests can be helpful in making these decisions, and in deciding which brands to use.
The current research provides stepping stones on which future research can be built. The aim of the current paper is to shed light onto the complex relationship between
communication, innovation, and brand equity. At the intersection of these terms, the current paper has aimed to provide insight by which future research can hopefully prove fruitful. The current paper, although maybe not radically innovative, can nevertheless be communicated just as well.
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Appendix A
Brand equity and Innovation Type stimuli (English and Dutch)
Brand equity
High brand equity:
Imagine that you are about to buy a new car. There is a new car available by the brand ‘Hindushi’. ‘Hindushi’ is a really popular and widely known car brand in Japan, where 41% of the population owns a ‘Hindushi’. In 2013, ‘Hindushi’ has won several prizes, including ‘Best car brand’ and ‘Best service’. The car has the same price as other cars in its category and will be sold in The Netherlands.
Stel je voor dat je een auto wilt kopen. Er is een nieuwe auto beschikbaar van het merk ‘Hindushi’. ‘Hindushi’ is een erg populair en bekend automerk in Japan, waar 41% van de bevolking een ‘Hindushi’ heeft. In 2013 heeft ‘Hindushi’ verscheidene prijzen gewonnen, waaronder ‘Beste automerk’ en ‘Beste service’. De auto heeft dezelfde prijs als andere auto’s in zijn categorie en zal verkrijgbaar zijn in Nederland.
Low brand equity:
Imagine that you are about to buy a new car. The picture below shows the newest car by the brand ‘Hindushi’. ‘Hindushi’ is a very unpopular and unknown car brand from Japan, where still only 3% of the population owns a ‘Hindushi’. The car has the same price as other cars in its category and will be sold in The Netherlands.
Stel je voor dat je een auto wilt kopen. Er is een nieuwe auto beschikbaar van het merk ‘Hindushi’. ‘Hindushi’ is een erg inpopulair en onbekend automerk
uit Japan, waar maar 3% van de bevolking een ‘Hindushi’ heeft. De auto heeft dezelfde prijs als andere auto’s in zijn categorie en zal verkrijgbaar zijn in Nederland
Innovation
Incremental innovation:
The new car is better than the previous car by ‘Hindushi’. It is 20% more energy efficient, and has less CO2-emission. The car is thus better for the environment and has built-in speech navigation.
De nieuwe auto is beter dan de voorganger van ‘Hindushi’. Hij is 20% meer energiezuinig en heeft minder CO2-uitstoot. De auto is dus beter voor het milieu en heeft ingebouwde spraaknavigatie.
Radical innovation:
The new car is the first car by ‘Hindushi’ that successfully manages to drive 100% on water. In the engine, water in converted into hydrogen and oxygen, which costs less energy than the combustion of those gasses.
De nieuwe auto is de eerste auto van ‘Hindushi’ die erin slaagt om 100% op water te rijden. In de motor wordt water omgezet in waterstof en zuurstof, tegen minder energie dan vrijkomt bij de verbranding van die gassen.
Appendix B
Complete Survey (English and Dutch)
Start (1):
1. Informed consent and ethical guidelines.
Demographics (4):
1. What is your age? 2. What is your sex?
3. What is your country of residence? 4. What is your education level?
Buying intention (3):
1. It is likely that I would ever consider buying a ‘Hindushi’ car. 2. If a ‘Hindushi’ car is available, I will consider buying it. 3. If this car from ‘Hindushi’ is available, I will:
o Surely not buy – might not buy – might or might not buy – might buy – definitely buy
Brand loyalty (4):
1. If the ‘Hindushi’ satisfies me, I will keep loyal to the brand Hindushi.
2. When I purchase the ‘Hindushi’ car, I would switch to another car brand less easily. 3. I would buy another ‘Hindushi’ car after this one, if this Hindushi satisfies me. 4. If I purchase this ‘Hindushi’ car, the brand will be meaningful to me.
Innovativeness (2):
1. The ‘Hindushi’ car is innovative.
2. I think the ‘Hindushi’ car is something new.
Brand equity (2):
1. I think a lot of people would like ‘Hindushi’. 2. I like the brand ‘Hindushi’.
Finish (1):
1. Would you like to be notified when the results of the study are available? If so, please provide your e-mail address.
Start (1):
1. Geïnformeerde toestemming en ethische richtlijnen.
Demografisch (4): 2. Wat is je leeftijd? 3. Wat is je geslacht? 4. Wat is je geboorteland? 5. Wat is je opleidingsniveau? Aankoopintentie (5):
1. Het is waarschijnlijk dat ik ooit zou overwegen een ‘Hindushi’-auto te kopen. 2. Als een ‘Hindushi’-auto beschikbaar is, zou ik overwegen hem te kopen. 3. Als deze auto van ‘Hindushi’ beschikbaar is, zou ik hem:
Zeker niet kopen – waarschijnlijk niet kopen – misschien wel/misschien niet kopen – waarschijnlijk wel kopen – zeker wel kopen
Merkloyalitei (5):
1. Als de ‘Hindushi’ me bevalt, zal ik trouw blijven aan het merk ‘Hindushi’. 2. Wanneer ik de ‘Hindushi’-auto koop, zou ik minder snel van merk wisselen. 3. Ik zou nog een ‘Hindushi’-auto kopen na deze, als deze ‘Hindushi’ me bevalt. 4. Als ik deze ‘Hindushi’-auto koop, is het merk betekenisvol voor me.
Innovatiefheid (2):
1. De ‘Hindushi’-auto is innovatief.
2. Ik denk dat de ‘Hindushi’-auto iets nieuws is.
1. Ik denk dat veel mensen ‘Hindushi’ leuk zouden vinden. 2. Ik vind het merk ‘Hindushi’ leuk.
Einde (1):
1. Wil je op de hoogte worden gehouden als de resultaten van dit onderzoek beschikbaar zijn? Zo ja, vul dan hieronder je e-mail adres in.
