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The influence of culture on the effects of innovation characteristics : an empirical study of the moderating affects of masculinity on the relationships between secondary and primary compatibility

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THE INFLUENCE OF CULTURE ON THE EFFECTS

OF INNOVATION CHARACTERISTICS

AN EMPIRICAL STUDY OF THE MODERATING EFFECTS OF MASCULINITY ON THE RELATIONSHIPS BETWEEN SECONDARY AND PRIMARY COMPATIBILITY

M

ASTER

T

HESIS

Maxim Inosemezw [10525831] University of Amsterdam Faculty of Economics and Business Business Studies – Marketing Track

July 07, 2014

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T

ABLE OF

C

ONTENTS

Abstract 1 1. Introduction 1 2. Conceptual Background 5 2.1 Innovation Characteristics 6 2.2 Compatibility Characteristic 11 2.3 Culture 14 2.4 Cultural Masculinity 20 2.5 Hypotheses Development 22

3. Method and Data 27

3.1 Measures 28

3.2 Data Collection Procedure 31

3.3 Obtained Sample 36 3.4 Analytical Procedure 37 4. Results 38 4.1 Reliability Analysis 38 4.2 Investigation of Sample 40 4.3 Perceptions 45

4.4 Validation of Regression Assumptions 48

4.5 Confirmation of Established Relations 51

4.6 Cultural Masculinity Moderation Tests 54

5. Conclusion and Discussion 65

6. References 73

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L

IST OF

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ABLES

Table 1: Key Differences between Individuals of Feminine and Masculine Cultures 22

Table 2: Construct Reliabilities after Treatments 40

Table 3: Differences in Means between Dutch and German Respondents 41 Table 4: Differences in Means between Early and Late Respondents 44 Table 5: Perceptions of the Surveyed Products Split by Masculinity 46 Table 6: Multicollinearity Diagnostics for Independent Variables in Model 0 49 Table 7: Inter-Item Correlation Matrix with Means, Standard Deviations and Reliabilities 50 Table 8: Effects on Innovation Adoption Intention in the Mediation Analysis 52 Table 9: Effects on Primary Compatibility in the Mediation Analysis 53

Table 10: Effects of the Control Variable PDI on CMP 55

Table 11: Effects of Independent Variables and Control Variable on CMP 56

Table 12: Regression Results of Model 1.3 57

Table 13: Correlation of Variables in the Full Model 1.3 58

Table 14: Results of the Regression of Model 1.4.1 60

Table 15: Results of the Regression of Model 1.4.2 60

Table 16: Results of the Regression of Model 1.4.3 61

Table 17: Results of the Regression of Model 1.4.4 61

Table 18: Results of the Regression of Model 2 62

Table 19: Summary of Hypothesis Tests 63

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L

IST OF

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IGURES

Figure 1: Stages in the Innovation-Decision Process, Simplified (Rogers, 2003) 8 Figure 2: First- and Second Order Innovation Characteristics, Simplified (Flight et al., 2011a) 10

Figure 3: Conceptual Model and Hypotheses 24

Figure 4: Distribution of Cultural Values in the Sample 42

Figure 5: Boxplot of the Masculinity Distribution 43

Figure 6: Scatterplot of Residuals on Predicted Values of CMP 50

Figure 7: Summary of Findings 64

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A

BSTRACT

In the consumer setting, innovation adoption is affected by both cultural dimensions and innovation characteristics. Secondary innovation characteristics form the primary characteristics which then affect innovation adoption. However, the consistent effect of cultural masculinity is yet unclear because previous research reveals mixed findings regarding its loading on innovation adoption. Thus, this research attempts to clarify the reasons due to which the consumers with distinct masculinity values adopt innovations differently. For this, the work examines how cultural masculinity moderates the socio-culturally influenced effects of secondary compatibility characteristics on the also socio-culturally influenced primary compatibility. The hypothesized logic behind this research is that the different compatibility characteristics weigh consistently differently for adopting innovations in the differing masculinity settings. Primary data was obtained with an online questionnaire from 302 students mainly from the Netherlands and from Germany. The analysis on the level of the individual reveals the following findings. Of the four secondary compatibility characteristics, personal compatibility, volition and social compatibility affect primary compatibility in the descending order of importance. Unexpectedly, social advantage was not significant and both, personal and social compatibility affected innovation adoption intention also directly. Of those two, social compatibility exhibited the considerably stronger effect. Furthermore, the masculinity moderator did not indicate that the importance of each of the secondary compatibility characteristics differs for individuals with distinct masculinity values. Implications of those findings are discussed and directions for, among others, further attempts to resolve the role of masculinity are suggested.

1.

I

NTRODUCTION

The topic of innovations has been of high interest in the marketing literature. This can be attributed to the importance of innovations for a sustainable competitive business in general and for marketing practice in particular. According to Steenkamp, Hofstede and Wedel (1999), a remarkable number of B2C companies view innovations as their major source of growth and profitability. For instance, companies introduce more than 30.000 products annually only to the US market only (Gourville, 2005). However, of these new introductions a high number fails (Rogers, 2003). Depending on the category, this number is as high as 40 to 90 percent (Griffin, 1997). Due to these statistics, in order to enhance the success of an introduced innovation, it is

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of high importance to understand how consumers adopt it. For the adoption, a high relevance can be ascribed to the attributes of an innovation – the so called innovation characteristics (Rogers, 2003). This is because innovation characteristics condition individual behavior (Moore & Benbasat, 1991) and through this, influence the individual’s adoption of an innovative product or service (Arts, Frambach & Bijmolt, 2011).

All innovations possess the same higher order innovation characteristics (Flight, D’Souza & Allaway, 2011). This is valid across different settings and kinds of innovations (Tornatzky & Klein, 1982). The innovation characteristics possess sub dimensions, which are the so called secondary innovation characteristics (Flight et al., 2011a). On behalf of the perception of the sub dimensions the individual forms his overall evaluation of the higher order innovation characteristics which then leads to shaping the intention to adopt an innovation (Flight et al., 2011a).

For the formation of the intention to adopt a special importance can be ascribed to the characteristic compatibility. Diverse studies have revealed that this characteristic, which is associated with the adopter’s personal life and with his social structure aspects (Flight et al., 2011a), is the most important out of all characteristics in the process of shaping the intent to adopt an innovation (Arts, Frambach & Bijmolt, 2011; Carter & Belanger, 2004).

Four sub dimensions can be associated with compatibility: personal compatibility, social compatibility, social advantage and volition (Flight et al., 2011a). For instance, if a new mobile computer in form of a wrist watch is perceived as fitting to the usual habits and routines of the individual’s business life and his personal lifestyle which is focused on efficiency at work, then this innovation will also be perceived higher on the personal compatibility sub-dimension. This again influences the overall primary compatibility favorably and hence, increases the intention score to adopt an innovation.

In the process of innovation adoption culture plays a significant role (Haapaniemi & Mäkinen, 2009). However, its influence on the newly introduced concept of the relationship between primary and secondary innovation characteristics has not yet been examined. It is possible to suggest that the effect weights of secondary innovation characteristics on primary characteristics systematically vary across cultures. Every culture forms its unique cultural environment due to different preconditioned developments in e.g. politics, geography and language (de Mooij & Hofstede, 2010). In consequence of different preconditions, cultures face different basic problems and regulate common elements differently for regulating human activity under the given circumstances (Schwartz, 1994). This results in different cultural values and attitudes that the individuals of a certain culture adapt and appreciate in their personal life

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and in their social structure (Schwartz, 1994). The cultural differences in social structures and personal lifestyles are likely to be reflected in distinct cultural prioritizations of the diverse attributes of innovations. Especially the compatibility characteristic which refers to the lifestyle- and social structure aspects of potential adopters is likely to be culturally influenced (Rogers, 2003).

One of the central elements that all cultures face and differently regulate in order to maintain smooth human activity (Hofstede, 1983) and that is likely to influence the effects of secondary innovation characteristics on primary compatibility is masculinity. Cultural masculinity describes mainly the social gender roles and the extent to which the roles may converge between men and women in one culture (Hofstede, 1983). While in more masculine cultures men and women tend to adapt contrasting roles and values, in cultures that score low on the masculinity dimension - also called the more feminine cultures – the roles of men and women centralize (Hofstede, 1983) and the values between those cultures centralize, too (Hofstede, 1994). These distinct value systems have been found to have implications for product adoption. For example, the nations which score high on cultural masculinity are more likely to adopt products that provide status because in those countries, achieving social status and showing-off one’s success are important (de Moij & Hofstede, 2011). This is not necessarily true for feminine cultures since, as described before, their central values are not associated with success and achievement (de Mooij & Hofstede, 2011). This knowledge can be transferred to compatibility and to innovation adoption. For instance, the secondary dimension social advantage refers to the potential adopter’s search for social status (Flight et al., 2011a). So, applying cultural needs to the importance of social advantage suggests that this dimension is more likely to meet the needs of individuals with more masculine values. Thus, those individuals will perceive this dimension as more important than individuals with more feminine values, for whom social status aspects are not of relevance. In consequence, for perceiving an innovation as compatible, social advantage will be more important to individuals with more masculine values in comparison to individuals with more feminine values. This is only one example of how masculinity is hypothesized to moderate the effects of secondary innovation characteristics of compatibility. Nevertheless, moderating influence can be expected to affect all four relationships between the sub dimensions of compatibility and primary compatibility.

In consequence, this study aims to investigate how cultural masculinity moderates the effects of the secondary compatibility characteristics on primary compatibility in the B2C context. In other words, this work examines how the importance of innovation characteristics that refer to the potential adopter’s personal life- and social structure aspects for perceiving an innovation as compatible differs for individuals with distinct masculinity values in the consumer setting.

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This has implications for both, marketing theory and practice, and beyond this, also for the design of innovations. First, the study provides insights into how important the secondary innovation characteristics of compatibility are in order to perceive an innovation as overall compatible. This knowledge is yet inexistent and it offers advice for an efficient optimization of the compatibility of innovations, which again enhances innovation adoption and so, the success of an innovation. Furthermore, a proven moderation of cultural masculinity would imply that secondary innovation characteristics vary in their importance for the primary constructs across groups of individuals with certain cultural values. This is of high practical relevance because it suggests that it is possible to increase the perception of compatibility culture-specific and/or segment-specific. I.e. when introducing e.g. a mass-market innovation to new geographic markets, it would be possible to consider the market’s masculinity score in order to adapt the design and the marketing of the innovation to the priority of the secondary compatibility characteristics in this cultural setting. Moreover, all individuals within one culture have cultural profiles which all differ from the average profile of their culture (de Mooij & Hofstede, 2011). Thus, within every culture there are individuals with different masculinity values. Consequently, it is possible to segment the market of also non-mass market innovations in regard to the cultural profiles of individuals within one culture. More precisely, this is possible by targeting different masculinity segments within this market more thoroughly in order to increase the perceived compatibility of the innovative product or service.

The examination of the cultural masculinity moderator in the prevalent context becomes even more intriguing when considering studies that have researched the influence of masculinity in the innovation adoption literature. The role of cultural masculinity has been contradicting in previous studies which dealt with the adoption of innovation as the dependent variable. The majority of these studies included masculinity as an independent variable and found either positive or negative effects or no effects at all on innovation adoption. Since there was no uniform and generally applicable effect of cultural masculinity that guides innovation adoption, investigation of this construct is required on a deeper level in the process of innovation adoption in order to better understand how and why different innovations are adopted differently in distinct masculinity settings. Hence, the research of the influence of masculinity on the relationships between secondary and primary innovation characteristics resembles the attempt to resolve the ambiguous role of masculinity in the adoption of innovations. The application of this knowledge finally offers the opportunity to improve the analysis of why certain innovations are or are not appreciated in distinct masculinity settings, which again offers advice for an adjusted (re-)design and the for the development of innovations.

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To achieve these contributions by answering the research question, this work adopts the deductive research approach. In order to obtain primary data, the study surveys students from different fields who are primarily from the Netherlands and from Germany. Both, cultural and innovation related data on the level of the individual is obtained from an empirical online questionnaire.

This work is organized as follows. The next chapter builds the conceptual background on the relevant constructs and develops the testable hypotheses. Then, in chapter three, the research method for testing the hypotheses is presented and evaluated. The subsequent chapter four pertains to the results obtained from the collected data. The last chapter concludes the findings and discusses them. Furthermore, it provides implications for theory and practice, it sheds light on the limitations of this work and it outlines suggestions for further research.

2.

C

ONCEPTUAL

B

ACKGROUND

An innovation is “an idea, practice, or object that is perceived as new by an individual or other unit of adoption” (Rogers, 2003, p. 12). The newness that is important in this definition has to be understood from a subjective point of view and may be represented by new knowledge, by persuasion or by the decision to adopt (Rogers, 2003). According to Rogers (2003), it is not of relevance, how new the innovation is objectively. Consequently, the definition of innovation applies to all products and services that are perceived as new by individuals.

The innovation characteristics play an important role for innovations. They can be described as "attributes that consumers use to evaluate an innovation" (Arts, Frambach & Bijmolt, 2011, p. 135). All innovations share the same characteristics or attributes (Rogers, 2003). They are relevant because their perceptions have an impact on the behavior of individuals (Moore & Benbasat, 1991) and so, also on the key construct innovation adoption intention, which can be defined as the “consumer's expressed desire to purchase a new product in the near future" (Arts, et al., 2011, p. 135). In turn, this predicts the actual buying behavior of innovations (Rogers, 2003). Thus, the understanding of innovation characteristics offers the possibility to improve the perceptions of innovations and hence, increase innovation adoption intention, which is the indicator for the actual adoption behavior. The concept of innovation characteristics is important for a sound comprehension of compatibility. Due to this, first the concept of innovation characteristics will be described, highlighting the innovation characteristics researched by Rogers (2003), the role of innovation characteristics in the innovation decision

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process and the innovation characteristics framework by Flight et al. (2011a). After this, the relevant innovation characteristic compatibility will be discussed in detail.

In the next sub-chapter, culture will be conceptionalized, including an introduction of cultural models with the emphasis on the model by Hofstde (2001). Culture influences how humans think and act (de Mooij & Hofstede, 2011). This way, culture also influences the perceptions of innovations and the adoption intention rates. The discussion of this concept is necessary in order to comprehend all details of the relevant cultural factor for this study, which is masculinity. This dimension will be described thereafter.

Finally, the provided insights on the relevant concepts and constructs will be merged, in order to develop the essential hypotheses for answering the research question.

2.1

I

NNOVATION

C

HARACTERISTICS

Innovation characteristics as the attributes of innovations have been extensively examined by diverse researchers for a long time. However, there is a vast variety of suggested characteristics (Arts, Frambach & Bijmolt, 2011) and there is still no absolute consensus about the finite attributes. Different researchers suggest different dimensions, which often overlap with the definitions of other studies' dimensions (Flight, D’Souza & Allaway, 2011). Often, these characteristics are not universal and not generalizable for all products and categories, limiting their theoretical importance. For instance, Meuter, Bitner, Ostrom and Brown (2005) accumulate from other studies the characteristics relative advantage, perceived risk, inertia, technology anxiety, complexity and compatibility among others. Evidently, technology anxiety is not applicable to all innovations. Flight et al. (2011a) mention that characteristics such as product risk and class risk, discontinuity, customization along with social- and personal compatibility appeared to be relevant and significant for diverse innovations. Here, product- and class risk as well as personal- and social compatibility are two pairs of overlapping dimensions. The grounding work on innovation characteristics which is of high relevance still today has been done by Rogers (1962). He found five innovation characteristics that have influence on the adoption of innovations, which is the consumer's decision to make full use of an innovation. Without going any further into detail, these attributes are relative advantage, compatibility, complexity, observability and triability. Later, risk as a sixth influential dimension had been added. These six dimensions have often been utilized in subsequent innovation characteristics studies (Flight, Allaway & D’Souza, 2011) with the result that they could have been validated and

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replicated in different settings and across diverse product categories. Studies were applied in different contexts such as in the research of information technology (Agarwal & Prasad, 1997), in the context of consumer self-service technologies (Meuter et al., 2005), in consumer durables (Flight et al., 2011a) or in the area of business context service innovations (Frambach et al., 1998). A recently conducted meta-analysis proofed again the cross-categorical and cross-setting applicability of these attributes. Consequently, the generalizability of these characteristics for innovations (Rogers, 2003) and their direct impact on innovation adoption (Flight et al., 2011a) make these characteristics worth being understood better.

In particular, these six generalizable attributes explain 36 percent of the variance of innovation adoption intention (Arts, Frambach & Bijmolt, 2011). Considering that innovation adoption is influenced by beyond at least situational factors and by consumer specific dispositions (Arts et al., 2011) this is a remarkable number. Innovation adoption intention is again correlated with 𝑟𝑟 = .53 with the actual innovation adoption behavior (Sheppard, Hartwick, & Warshaw, 1988), which is the initial (trial) buying behavior of the innovation (Rogers, 2003). Due to this, the innovation adoption intention construct can be (cautiously) used to predict the actual innovation adoption behavior. Following this argumentation chain, it is possible to recognize that innovation characteristics are among others the major drivers of overt adoption behavior of innovations (Meuter, Bitner, Ostrom & Brown, 2005) and are thus, of high importance for designing and marketing innovations.

Even though, these characteristics are well established, they are not without flaws. Two should be mentioned. First, for these characteristics, no general validated scale which could have been used in practice exists. Although a scale had been developed by Moore and Benbasat (1991), its validity was aligned to information technology research and hence, is not necessarily applicable across different settings and kinds of innovations. Additionally, the existent PCI scale measures the perceived (P) characteristics (C) of an innovation (I). However, although designed for general applicability, this is another set of dimensions and the scale suffers from poor reliability (Moore & Benbasat, 1991). Another impediment is that relative advantage and compatibility correlate with each other to a high extent (Rogers, 2003). The dependence of the two constructs can be attributed to the not clearly distinct structure of the dimensions. This is caused by status aspects that are not clearly attributed to just one construct.

According to Rogers (2003), innovation adoption is not a one-step decision. It is rather a process with distinct phases in which innovation characteristics have different importance and therefore, are perceived differently. As shown in figure one, the process comprises five phases, which are knowledge, persuasion, decision, implementation and confirmation. The process may be summarized as a route on which an individual accumulates and processes information in

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order to estimate the probability of the innovation to fail (Rogers, 2003). It is noted that the phases within the process are not timely distinct but are rather structured in this manner for a better comprehension. In the following, the, by Rogers (2003), described phases, which are widely accepted and often depicted in the literature, will be summarized, emphasizing the role of innovation characteristics.

Figure 1: Stages in the Innovation-Decision Process, Simplified (Rogers, 2003)

In the first phase the potential adopter gains first cognitive knowledge about the innovation. In the second phase, the potential adopter becomes psychologically more involved with the innovation. Here, he utilizes the information from the previous phase and actively searches for additional information for reducing uncertainty about the new product’s performance and for evaluating the advantages, disadvantages as well as the use consequences of the innovation. Both, cognitive and affective criteria are relevant. For this evaluation, the innovation characteristics are of main importance. Depending on how the innovation attributes are perceived, a favorable or an unfavorable attitude towards the innovation is formed as the final outcome in this phase. For this attitude formation, information, which can be influenced by marketing, plays a crucial role. The perception and so, the resulting attitude towards the innovation is based upon from which source the information originates, what information is processed and especially how information is interpreted. It is important to highlight that interpretation of information is determined in a sociocultural way (de Mooij & Hofstede, 2011). In the third phase, the decision is made to either adopt or to reject the innovation. Diverse physical and mental activities form the choice. Even though not explicitly pointed out by Rogers (2003), in this phase, the innovation adoption intention is formed. This is the preliminary stage to the actual adoption behavior. The decision leads to immediate implementation in the next stage, in which the potential adopter executes his choice with overt behavior. Even if an innovation already has been adopted or rejected, adopters continue seeking information in the final stage in order to confirm having made the right decision. Festinger’s (1957) dissonance theory plays an important role at this stage. However, because this is not contributing to the

1. KNOWLEDGE 2. PERSUASION 3. DECISION 4. IMPLEMENTATIO N 5. CONFIRMATION Perceived Characteristics

of the Innovation Adoption Intention Innovation

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purpose of this research it will not be discussed any further. Instead, it shall be mentioned that even though innovation characteristics play a significant role throughout the different phases of the adoption process (Arts, Frambach & Bijmolt, 2011), they are of highest importance in the persuasion phase. This is because based on the subsequent attitude formation, afterwards, the adoption intention is formed. This has a remarkable value in marketing, since innovation adoption intention, to a certain extent, predicts the actual innovation adoption behavior.

Apart from the up now discussed five innovation characteristics by Rogers (1958) and the added risk dimension, which have been well-researched and validated, there is a second important innovation characteristics framework. It builds on these discussed dimensions. Moreover, it incorporates the notion of primary and secondary innovation characteristics (Flight et al., 2011a).

More precisely, the innovation characteristic framework by Flight et al. (2011) can be viewed as the state of the art model on innovation characteristics. This is because this framework contains generally applicable innovation attributes that have been found to be valid across industries and for diverse kinds of innovations (Flight et al., 2011). Moreover, as also the previously described framework by Rogers (2003), this model clears up the interrelations of the variety of attributes, too. However, this model follows another approach to achieve this. It incorporates the notion of Downs and Mohr (1976) as well as of Holak and Lehmann (1990) and categorizes the innovation attributes into first and second order innovation characteristics, linking only the primary to innovation adoption. The secondary characteristics are linked only to the primary constructs. The secondary constructs follow the function of influencing only the primary characteristics. So, this model retains the independence of the innovation characteristics while additionally offering even more attributes than before, herewith providing a broader scope for improving innovation adoption intention even more precisely. Now, the simultaneous presence of, for instance, personal- and social compatibility is no impediment in the model, since both contribute to forming the perception of primary compatibility (Flight et al., 2011a).

Another advantage of this model is the availability of a scale for the assessment of the characteristics. A validated and uniform scale of innovation characteristics had been lacking before the development of this model (Flight et al., 2011a).

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Figure 2: First- and Second Order Innovation Characteristics, Simplified (Flight et al., 2011a)

Figure two resembles the model with the mentioned primary- and secondary innovation characteristics. Primary characteristics are the dimensions that all innovations objectively possess. They are accepted as traits and are homogeneous among industries and settings (Tornatzky & Klein, 1982). Moreover, they are independent from subjective judgment (Downs & Mohr, 1976). In contrast, secondary characteristics are judged subjectively and their perception may vary across settings, adopter groups and consumers (Downs & Mohr, 1976; Tornatzky & Klein, 1982).

Evident from the model, Rogers’ (1958) dimensions and the added risk dimension are incorporated on different levels. While observability and triability resemble secondary characteristics, compatibility, relative advantage and complexity form primary innovation attributes. Due to trait similarity, risk and complexity are combined to one primary dimension (Flight et al., 2011a). Moreover, the previously mentioned multicollinearity between relative advantage and compatibility in the framework of Rogers (1958) has been resolved due to the model reorganization in primary and secondary sub-dimensions and more precise definitions of dimensions.

As explained by Holak and Lehmann (1990), the perceptions of secondary innovation characteristics form the perception of the primary characteristics. Then, the perceptions of the primary characteristics form the overall perception of the innovation, which afterwards contributes to attitude formation towards the innovation and the decision whether to adopt or

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to reject the innovation. All this occurs within the previously introduced innovation-decision process. While information influences the perception of the relative advantage and the compatibility construct, the two latter and the risk and complexity construct are directly related to innovation adoption. Thus, in this model risk and complexity, relative advantage and compatibility are the major drivers of innovation adoption.

From this model by Flight et al. (2011) it can be concluded that this model offers a more accurate and more precise structure of independent characteristics which simultaneously has a verified influence on innovation adoption. Apart from this, the framework resolves existing unclarified issues and provides a validated scale. Due to this, this model can be viewed as the most advanced framework of innovation characteristics to the time this work had been written.

In summary, the grounding work on innovation characteristics has been presented. These are relative advantage, complexity, observability, triability and compatibility. These attributes guide innovation adoption to a remarkable extent (Meuter et al., 2005). In the innovation decision process, the innovation characteristics are to some extent influential in every phase (Arts et al., 2011) and though, most influential during the persuasion phase, in which the potential adopter forms his attitude towards the innovation (Rogers, 2003). Recent development in the innovation characteristics research has incorporated the idea of primary and secondary innovation characteristics. While the secondary sub-dimensions are subjectively perceived and are specific regarding the innovation and the situation, the primary characteristics are invariant across settings and categories of innovations. Secondary innovation characteristics drive the perception of the primary constructs, which then influence innovation adoption (Flight et al., 2011). The next subchapter deals with the innovation characteristic compatibility.

2.2

C

OMPATIBILITY

C

HARACTERISTIC

Compatibility is defined as “degree to which an innovation is perceived as being consistent with existing values, past experiences and needs of potential adopters” (Rogers, 2003, p. 240). Compatibility captures aspects, which relate to how well the innovation satisfies needs and values that relate to the potential adopter’s existing personal and social life (Flight Allaway, Kim & D’Souza, 2011b). Holak and Lehmann (1990) argue that needs and values are influenced by culture and individuals with differing cultural values, ceteris paribus, perceive this dimension differently.

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Although research on only this dimension has been scarce, diverse studies have revealed that of the researched innovation characteristics, compatibility has the highest impact on innovation adoption intention (Arts et al., 2011; Holak & Lehmann, 1990; Tornatzky & Klein, 1982; Frambach, van Herk & Agarwal, 2002). Due to this finding, this innovation characteristic plays a special role in stimulating overall favorable perceptions of innovative products and for their success in the market. In order to make the innovation compatible to the potential adopter’s personal and social life and this way increase the success, it is necessary that design of the innovation does not require too many behavioral changes in the personal and social life of the potential adopter (Gourville, 2005). Moreover, it is suggested that the innovation should be compatible to the ideas the potential adopter holds not only about his personal and social life, but also about the products, services or ideas the innovation supersedes (Gourville, 2006). The current state of knowledge comprises four researched sub-dimensions for the primary compatibility construct. These secondary compatibility characteristics are (1) personal compatibility, (2) social compatibility, (3) social advantage and (4) volition. While volition influences primary compatibility negatively, the remaining three constructs have a positive impact on primary compatibility (Flight et al, 2011a).

(1) First, an innovation is personally compatible to the extent to which it fits into the existing habits and into the lifestyle of the adopter. To be more precise, individuals are on average not open for changes (Kahneman & Tversky, 1979) and if new routines or habits would be needed for adopting the innovation then the innovation would be perceived as less compatible (Flight et al., 2011a). For instance, if an individual adopts a new office suite for his computer, which is very intuitive in use and the interface as well as the shortcuts of the software are similar to the software the individual had been using before, then the adopter will perceive this office-suite as personally compatible. In contrast, if the software requires attaining a high amount of new knowledge to use it because the user interface is organized very differently or the functionalities are distinct to the common ones then the potential adopter will perceive the software as less personally compatible.

(2) If the innovation fits into the social structure of the adopter, i.e. it meets the social expectations of the adopter and fits to the behaviors of his social class, then the innovation is socially compatible (Aggarwal, Taihoon & Wilemon, 1998). Similar activities and the participation in such as well as similar behaviors resemble the social expectations similar social classes desire of the potential adopter (Flight et al., 2011a). For instance, if the potential adopter often exchanges documents digitally with his friends and with his family and now changes his office suite that is not compatible with the formats his social surrounding is comfortable with, then the potential adopter will perceive the office-suite as

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less socially compatible. This is because the incompatibility of the document formats does not meet the social expectations of the group, which are that all documents should be easily shareable within the group. Additionally, the suite will be perceived as less compatible because the use of the with the surrounding incompatible suite separates the potential adopter from the group. It is to add that socially strong group relationships trigger higher sensitivity of what is expected from the individuals within the group (Flight et al., 2011b). For individuals with strong group bonds this results in among others a more precise estimation of social compatibility.

(3) Social advantage refers to which extent it is possible to gain status with the innovation (Fligh et al., 2011a). For diverse product groups social advantage is the sole reason for adopting innovations (Rogers, 2003). For example, although office-suites belong to a category which is not necessarily very status stimulating compared to e.g. Italian sport cars or coveted jewelry brands, diverse attempts such as certain prices strategies or rebranding campaigns can increase perceptions of social advantage also for office products.

It is to note that the status needs, to which this dimension refers, are the likely cause of the previously described multicollinearity between relative advantage and compatibility in Rogers’ (2003) framework. This is because in Rogers model status aspects are attributed to relative advantage instead of to compatibility. However, while relative advantage refers more to the objective utility of an innovation (Rogers, 2003), compatibility indicates aspects regarding the social life of the potential adopter. So, because status relates more to the social life of the potential adopter it is more convenient to sub-categorize such issues to compatibility. This might be the reason why compatibility and relative advantage are independent dimensions in the framework of Flight et al. (2011a).

(4) The final secondary construct is volition. This dimension can be seen as the degree to which the innovation is perceived to be adopted voluntarily (Moore & Benbasat, 1991). E.g. especially in work place situations, innovations are not adopted entirely in consequence of free choice (Flight et al, 2011a) because employees have to follow the decisions made on higher levels. Also in social contexts, which are independent from workplaces, volition plays a significant role. Here, expectations by peers and social pressure in general, which is the opposite of volition, contribute to the perceived degree of free choice when adopting an innovation (Flight et al., 2011a). In this context, with time, social pressure increases and volition decreases (Flight et al., 2011b). The office-suite is again an adequate example. The more people start using this innovative software, the more common and widespread it becomes. This increases social pressure and so, decreases volition which results in higher perceived primary compatibility. In this example, it is because the use of the same product

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offers benefits of objective network effects and moreover, the adoption of the already established product that the peer group uses avoids any negatively perceived exclusion from the group. So, in the social context, the more social pressure increases, i.e. the more volition decreases, the higher the overall compatibility will be perceived.

Volition is an important dimension because it creates an interrelationship among the secondary dimensions social compatibility, social advantage and volition (Flight et al., 2011). For instance, in one society, gaining status might be a central priority. This causes the peer pressured need to adopt a socially compatible innovation in order to gain social advantage with social status. Thus, all three secondary dimensions play an important role.

In short, compatibility is the innovation characteristic referring to the personal and social life of the potential adopter (Flight et al., 2011b). Of all characteristics, it has the highest impact on innovation adoption intention (Arts et al., 2011). The secondary compatibility characteristics personal compatibility, social compatibility and social advantage positively influence primary compatibility while volition influences this higher level construct negatively. This primary construct is socio-culturally influenced. Next, the concept of culture will be explained.

2.3

C

ULTURE

Culture plays a major role in business studies and in marketing. For instance, culture influences the effectiveness of both, advertising messages (Soares, Farhangmehr & Shoham, 2007) and of brand associations (de Mooij & Hofstede, 2010), it also affects service performance, innovativeness (Soares, et al., 2007), innovation adoption (van Everdingen & Waarts, 2003) and many more in marketing relevant constructs. Lenartowicz and Roth (as cited in Soares et al., 2007) provide evidence for the importance of culture in academia, stating that in the renowned journals between 1996 and 2000 more than ten percent of articles dealt with topics about culture.

Culture can be thought of as the “the collective programming of the mind that distinguishes the members of one group or category of people from another” (Hofstede, 2001, p. 9). The differences between the groups or categories can be ascribed to e.g. distinct regional historical developments in among others economy, ecology, politics, language, religion and technology (Hofstede, 1983). These distinct developments cause that humans within the groups or categories share common beliefs, attitudes, norms, roles and values, speaking the same language

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and inhabiting particular geographic regions (Triandis, 1995). All these aspects are the source of cultural differences between groups and make cultures relatively stable over time (Hofstede, 2001). Nevertheless, as shifts in e.g. climate, ecology, religion and when population migration and historical effects occur, also shifts in culture might occur (Triandis, 1995). However, although these factors influence the culture, it is important to note that economic, political, legal, religious, linguistic or educational and technological environmental factors are not the same as culture (Soares et al., 2007).

According to different researchers, culture can be linked to nations and countries (e.g., Hofstede, 2001; Steenkamp, 2001; Schwartz, 1994). This is because citizens of a nation share a long historical integration, which could have been induced by e.g. same geography, religion and economics. This causes a convergence of the collective programming among individuals within a country (Hofstede, 2001). Indeed, empirical evidence confirms that there are commonalities among individuals within countries and differences among individuals between countries, implying that nationality is an adequate proxy for culture (Steenkamp, 2001).

In order to function adequately every culture has its own priorities. The priorities are special due to every culture’s specific environment. Every environment is unique in consequence of the mix of the above stated factors such as geography, religion and economics. Exactly these distinct factors of every environment form the basic problems and issues that a culture faces for regulating human activity in its unique way (Schwartz, 1994). For a smooth and effective human activity among the individuals in the national culture they need to adapt to a certain extent to the cultural priorities (Smith & Schwartz, 1997). So, the national culture influences its individuals to develop attitudes and values that do not necessarily represent their own but rather are the result of the culture’s influence because these attitudes and values are essential for the national culture’s smooth human activity. On the other hand, culture also, to a certain extent, suppresses attitudes and values of the individuals that are counter to the cultural priorities (Schwartz, 1994). This way, culture influences the individuals from the macro-level. This adaptation to cultural priorities impacts also consumer behavior. For example, this affects the perceptions of advertising (de Mooij & Hofstede, 2011). Moreover, the effects of personal- and group-level attitudes towards purchase intentions are moderated by culture (Lee & Green, 1991) and specific consumer dispositions as well (Steenkamp et al, 1999). However, there is variation on cultural dispositions among individuals within a culture, too (Hofstede, 2001). The process of cultural influence on the individual begins in early childhood and continues throughout the individual’s whole life (Shore & Vankatachalam, 1996). Consequently, culture has a significant life-long influence on the individual’s development.

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De Mooij and Hofstede (2010) describe in more detail which areas at the level of the individual culture affects. They distinguish the influence of culture on the self of the individual and on his personality. Values and attitudes can be attributed to the individual’s self, whereas character traits to personality. Both influence the individual’s mental and social processes. Social processes are the processes that explain how humans relate to other humans. Here, e.g. motivation and emotion are important. On the other hand, mental processes are internal processes that can be associated with categorizing and processing information, with thinking and with perceiving.

In consequence, culture has the power to moderate the human mental programming (Hofstede, 2001), this way guide which needs individuals develop in general (Roth, 1995) as well as, which needs they develop regarding their social and personal life. Moreover, as also suggested by Triandis (1989), the culture influences how humans feel, think, act and perceive information. Evidently, these aspects relate to how compatibility constructs are perceived (e.g. Rogers, 2003; van Everdingen & Waarts, 2003), which then, influences innovation adoption, too.

For scientifically representing different cultures, compare them to each other and derive information for the practice research provides diverse frameworks. These frameworks explain to which extent cultures face common basic issues and problems that influence the individuals of one certain culture (de Mooij & Hofstede, 2010).

According to Sojka and Tansuhaj (1995) the available models for assessing culture can be grouped into three categories, which are assessment by language, assessment by culture’s goods and artefacts and assessment by beliefs or value systems. Operationalizing culture by value systems has become the dominating approach in marketing studies (Soares et al., 2007). This operationalization is based on measuring value structures on specific dimensions, which attempt to capture and assess the comparable invariant attributes of cultures (Soares et al., 2007). Although diverse scholars argue culture would be a too global concept to explain it on a parsimony scale of only few factors (e.g. Schwartz, 1994; Vijver & Leung, 1997) this is, though, worth an attempt, because determining certain uniform cultural values and this way capturing the concept of culture at least partially, already provides insights into basic tendencies of a culture and how cultures differ on at least these common dimensions. The differences among cultures on the basic dimensions offer valuable and constructive implications for theory and practice.

Such dimensional frameworks are for instance the GLOBE cultural dimensions (House, 2004), the Schwartz’ (1994) Cultural Dimensions of Values, the model of Trompenaars (1993) or the Cultural Dimensions researched by Hofstede (1991).

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Although, according to an assessment of Yeganeh, Zhan Su and Sauers (2009) all of the listed frameworks are parsimony and may be applied in empirical research with confidence, the model of Hofstede (1991) is the one which has been utilized most often. For scientifically describing culture in psychology, sociology, marketing and management studies, Hofstede’s cultural dimensions are the ones that have been used most often (Steenkamp, 2001). His work has been cited in more than 1.500 publications (Hofstede, 2001) and according to Sivakumar and Nakata (2001), this model is well established and broadly used in the whole area of international business research.

The dimensions have been derived from multiple research projects among students in more than 20 countries and among IBM employees in more than 60 countries (Hofstede, 1994). According to Smith et al. (1996), the collected sample data of national cultures makes this framework the most comprehensive and robust compared to alternative models. Indicating generalizability, the factors have been validated and replicated by different scholars in many subsequent studies (Sondergaard, 1994). This, again, suggests using this model when researching cultural influence on innovation related marketing variables.

Hofstede’s model describes culture on five uniform cultural value dimensions. Initially, the model comprised four dimensions, which were power distance, uncertainty avoidance and the two bipolar dimensions individualism-collectivism and masculinity-femininity. These four dimensions alone already covered more than 50 percent of the variance in the differences between countries (Hofstede, 1983). Later, long-term orientation had been added as the fifth dimension to improve the model (Hofstede, 1994).

Based on Hofstede’s (2001) argumentation, the five cultural factors can be described as follows: power distance represents the degree, to which the less powerful members of institutions and organizations accept and expect inequality of power distribution. individualism-collectivism refers to the extent to which individuals organize themselves into groups. In individualistic countries humans are integrated only into their immediate family while in collectivistic countries the group one belongs to is extended beyond the immediate family, in which protection is offered in exchange for unquestioned loyalty. Uncertainty avoidance, explains in how far people of one culture feel uncomfortable when dealing with uncertain and ambiguous situations. Long term-/short term orientation, resembles the culture's orientation towards either long-term values such as thrift and preservance or short-term values that are e.g. tradition and avoiding reputation-harming situations. Finally, masculinity/femininity reflects the extent to which the roles of sexes in a culture differ from one another.

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Hofstede (1982) researched these cultural dimensions for the application on the aggregate level. I.e. according to Hofstede, the obtained scores on dimensions are valid and reliable and hence, interpretable only if averaged scores of participants from one and the same culture are used to compare them to another culture’s similarly averaged profile. This is because the scores of individuals within the same culture differ from one another and do not resemble the aggregate profile of their culture (de Mooij, 2013). For instance, in a culture that exhibits a profile of high power distance, low uncertainty avoidance and medium individualism, the individuals may deviate from these scores. In this hypothesized culture there are also individuals with values scoring low on power distance, high on uncertainty avoidance and high/low on individualism and with different other combinations. However, taken the average scores on the dimensions of all the individuals in the relevant culture the values result in the tendency of high power distance, low uncertainty avoidance and medium Individualism. Evidently, this aggregated profile is different from the profile of certain arbitrarily chosen individuals who inhabit this cultural environment. So, the averaged cultural profile does not necessarily represent the individual cultural profile of culture’s inhabitants. Instead, it provides the tendencies for all inhabitants to adopt such value scores on each of the five dimensions separately. This inexistent possibility to conclude from the aggregate cultural profile to the individual profile is known as the ‘ecological fallacy’ (Yoo, Donthu & Lenartowicz, 2011).

Furthermore, diverse studies have revealed that Hofstede’s (2001) five dimensional value structure is equally interpreted also on the individual level. Beyond this, Yoo et al. (2011) have revealed that the Hofstede’s cultural factors are invariantly understood across different cultures and so, across different countries even despite enormous cultural differences in e.g. language or historical development. In consequence, with the right scales, it is possible to assess and compare the cultural values of also singular individuals.

The validity of the cultural values on both, the aggregate and the individual level (Fischer & Poortinga, 2012) has adjuvant benefits for marketing strategy. On the one hand, when using the cultural values on the aggregate level, it is possible to adjust the expansion strategy for products and services to specific countries based on the cultural value scores of the specific geographic markets the company has decided to enter. For instance, a Dutch company has chosen to introduce its mass market product in Germany due to the low geographical distance to this country. However, considering the cultural differences, for increasing product success in Germany, the Dutch company has to adjust the marketing strategy of the product to the significantly higher masculinity in Germany. Yoo et al. (2011) refer to this deed as the country-centered market segmentation. Furthermore, for the expansion into additional geographic markets, cultural data on the aggregate level, i.e. the averaged profile of all individuals within a

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culture, might help choosing the most profitable national cultures based on the typical buyer profile of the product/service (Chandrasekaran & Tellis, 2008). In this case, an exemplified product which targets collectivistic and very feminine buyers might become less successful in Germany than in Slovenia for example, where on average, buyers are more feminine and collectivistic than in Germany. On the other hand, using the cultural data on the individual level has advantages, too. Here, it would be possible to identify typical buyer profiles of the product and define the global buyer segments based on the cultural values for targeting these segments across countries. For this approach, Yoo et al. (2011) introduce the term global-centered market segmentation. Their study has confirmed that it is possible to use Hofstede’s (2001) cultural values on the individual level to define global buyer segments. In practice, similar segmenting approaches are used being based on the List of Values (≡LOV) (Kamakura & Novak, 1992) or on Rokeach’s (1973) Value Survey (≡RVS). Both focus on human values. Using cultural values instead of human values resembles a thorough alternative. While RVS represents 18 different values (Rockeach, 1973) and the LOV considers nine (Kahle, 1983). Hofstede’s cultural dimensions count only five. This makes the segmenting significantly easier and results in globally invariant and simpler comprehensive clusters. Moreover, as previously described, the cultural values influence also one individual’s values. Thus, they have a direct independent impact on an individual, which makes them worth studying directly. Finally, according to Yoo et al. (2011), segmenting buyers from international markets on the basis of cultural values is beneficial due to the possibility of finding equivalent consumer groups in all (national) cultures. In consequence, the global segmentation approach is an attempt to simplify a global marketing strategy. The global markets can be viewed as just one global market with segments of individuals who possess distinct cultural values.

To sum up, culture as the collective programming of the mind (Hofstede, 2001) influences mental and social processes of humans due to different environmental developments in different geographic areas (de Mooij & Hofstede, 2010). Culture is equitable with nations (e.g. Schwartz, 1994) and dimensional models offer the best possibility to as thoroughly as possible describe the difficult to capture global concept of culture (Vijver & Leung, 1997). One of these models, which has been shown to also be valid and cross-culturally invariantly understood on the national as well as on the individual level, is the five dimensional framework of Hofstede (2001). It considers the factors power distance, individualism-collectivism, uncertainty-avoidance, long-term orientation and masculinity-femininity. This model has been the most valuable in studying the influence of culture in marketing (Soares et al., 2007) and all dimensions have been shown to some extent affect important marketing variables (de Mooij & Hofstede, 2010), as also in terms of innovation adoption (e.g. van Everdingen & Waarts, 2003). Finally, Hofstede’s (2001) cultural dimensions are qualified for adjusting marketing strategy to global issues, such as in the case of

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expansion strategies and for global-centered market segmentation (Yoo et al., 2011). Of those five cultural dimensions, cultural masculinity is attributed a central role in this work. This dimension is discussed next in more detail.

2.4

C

ULTURAL

M

ASCULINITY

Masculinity is one of the value dimensions in Hofstede’s (2001) model to describe one of the basic cultural issues and priorities that affect social and mental processes of individuals. Cultural masculinity refers to the issue of how roles between men and women differ (Hofstede, 2001). The importance of masculinity as a cultural basic issue is resembled by the inclusion of this dimension in also other dimensional cultural models. Although the definitions differ among the models, at least aspects of the masculinity dimension can be found partially in other frameworks. For instance, in the GLOBE concept the issues to which Hofstede’s (2001) masculinity dimension correspond are spread upon the dimensions assertiveness and gender egalitarianism (Yeganeh et al., 2009). Trompenaar’s and Hampden-Turner’s (1993) model captures similar issues on the neutral/emotional dimension and Schwartz’ (1994) framework relates them to mastery/harmony (Soares et al., 2007). However, due to the previously described importance of Hofstede’s (2001) model for business and especially marketing, his view of masculinity will be used.

According to Hofstede (2001), the division of roles that men and women play in a culture is not necessarily biologically formed but is rather socially determined. The typical tasks of men may be different from the typical tasks of women in one society whereas in another the tasks of men and women may converge, with the consequence that both genders are accepted to take the same roles (Hofstede, 1983). On this bipolar dimension, the cultures which divide male and female roles the most score the most masculine, whereas the cultures in which human male and female roles are least distinct score the least masculine. These cultures are also known as the more feminine cultures (Hofstede, 1983). However, no one culture scores entirely masculine or solely feminine. Instead, cultures exhibit scores rather more towards more to the feminine or more towards the masculine end of the continuum and hence are either more feminine or more masculine (Hofstede, 2001).

Moreover, if gender roles are more distinct then, most often, men are the ones who tend to be more assertive and competitive while women tend to be modest, caring and tender (Hofstede, 1994). Across cultures, the roles of men vary to a significantly higher extent than the roles of women do. Nevertheless, also the roles of women vary across the cultures in the same direction as the ones of men but to a smaller extent. In particular, in comparison to a more feminine

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culture, in a more masculine culture also women are slightly more assertive and competitive. Nevertheless, men are relatively even more assertive and competitive in such a society. In a feminine culture women are modest caring and tender while men tend to be much more modest, tender and caring in comparison to the roles of women and men in a masculine setting. The roles of men in the more feminine setting differ more from their roles in the more masculine setting. But for women, the variation of roles between the two settings is less high. So, the cultures which share values that are more assertive, competitive and dominant are more masculine and the ones that share caring, modest and service-oriented values are more feminine. Between those cultures the roles of men differ to a higher extent than do the roles of women (Hofstede, 2001). Transferring this from culture to the individual, according to Yoo et al. (2011), these values are also applicable to single individuals with differing masculinity values.

Extending the explanation of more masculine cultures, for both, men and women, success and achievement are important values. Achieving visible goals, earning a higher amount of money, performing and showing-off the achievements is priority (Hofstede, 1983). Being daring, independent and capable of own undertakings are important values (Hofstede, 1998). In masculine cultures “big is beautiful” (Hofstede, 1983, p. 85) and wealth and material success are emphasized (Steenkamp et al., 1999). Therefore, the display of status and of material possessions is of higher importance in more masculine cultures (Haapaniemi & Mäkinen, 2009). Due to this, relative to the feminine cultures status displaying brands and products, such as expensive watches are bought more in more masculine societies (de Mooij, 2004). This represents the tendency to focus more on ego goals. The public hero is a “successful achiever” (Hofstede, 1983, p. 85).

In contrast, in feminine cultures the guiding values are associated with social goals (Haapaniemi & Mäkinen, 2009) and with the quality of life (de Mooij, 2011). Not showing off, emphasizing relationships instead of money and helping others are relevant values (Hofstede, 1983). Individuals from feminine countries cherish the quality of life in general as well as good work life conditions and preserve the environment (Haapaniemi & Mäkinen, 2009). Here, fuel saving cars would be more appreciated than in more masculine cultures. In comparison to the successful achiever, here, the sympathy goes to the underdog (Hofstede, 1983). It is important to note that in more feminine cultures these values are equally adopted by both, men and women (Hofstede, 1994).

Table one summarizes general differences between feminine and masculine societies.

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Table 1: Key Differences between Individuals of Feminine and Masculine Cultures

Cultural Femininity Characteristics Cultural Masculinity Characteristics

Purchase for use* Purchase for showing off*

Small gender culture gap Large gender culture gap

Work in order to live* Live in order to work*

More equal job and education opportunities Less equal job and education opportunities

Average student is norm* Best student is norm*

Larger share of women in professional and technical jobs Larger share of women in professional and technical jobs At work assertiveness is ridiculed* At work assertiveness is appreciated*

Student’s failure at school is relatively minor accident* Student’s failure at school is a disaster – may lead to suicide*

Socialization toward nontraditional gender roles Socialization toward traditional gender roles Women describe themselves as more competitive than

man do Men describe themselves as more competitive than women do Gender stereotypes rooted in universal biological

differences Gender stereotypes country specific

Characteristics freely attributed to one or the other

gender Attribution of characteristics less easily differentiated

Women describe themselves in same terms as men Women describe themselves in their own terms Men allowed to be gentle, feminine and weak Women should be gentle and feminine; nobody should

be weak

Men claim suppressing joy and sadness Men claim showing joy and sadness Womens’ liberation means that men and women should

take equal share both at home and work Womens’ liberation means that women should be admitted to positions hitherto occupied only by men All are concerned with quality of life Only women are supposed to be concerned with quality

of life

In the family resolution of conflicts by compromise* In the family resolution of conflicts by fighting them out* Unmarked points adopted from Hofstede (2001), with * marked adopted from Hofstede (1983).

In short, in Hofstede’s (2001) cultural framework the basic cultural issue called masculinity, which refers to the role distribution of sexes, influences social and mental processes of a culture’s inhabitants (de Mooij & Hofstede, 2010). Individuals who score more feminine on the masculinity dimension are characterized by more caring, modest and service-oriented values focusing on the quality of life while the more masculine cultures are focused on achievement and success, valuing assertiveness, competitiveness and dominance (Hofstede, 2001). The extent of possession of such values relates also to how individuals relate to diverse marketing constructs and to constructs from the field of innovations. The relation of cultural masculinity to innovation characteristics and especially to compatibility will be discussed in the next chapter, leading to the development of knowledge reconfirming and knowledge adding hypotheses.

2.5

H

YPOTHESES

D

EVELOPMENT

Cultural variables and in particular masculinity play a significant role for a variety of constructs in marketing (Soares et al., 2007). Similarly and more important for this work, masculinity has been found to have a contribution to innovation adoption (e.g. Steenkamp et al., 1999; Flight et

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al., 2011b). In the following, it will be discussed what has been researched in this area, stating what will be added to current knowledge by also developing the hypotheses in order to answer the research question.

Previous studies reveal inconsistent findings regarding the role of masculinity for adopting innovations. For instance, the adoption and penetration of ERP systems in the business context is negatively affected by masculinity (van Everdingen & Waarts, 2003). In contrast to this study, Png, Tan and Wee (2001) revealed a positive but insignificant effect of masculinity on IT adoption also in the business context. Similarly, Haapaniemi and Mäkinen (2009) did not find any significance for masculinity on the time to take-off of three products in the consumer context. Testing six products in the consumer context, Bagchi, Hart and Peterson (2004) find partial negative support for masculinity on IT adoption for two products. On the other hand, also examining the consumer context, Steenkamp et al. (1999) exemplify the positive effect of masculinity on innovativeness – an adopter characteristic that positively contributes to innovation adoption in large extent (Arts et al., 2011). Due to this finding, it would be logical to assume that innovations are adopted generally more by individuals with more masculine traits. However, as stated before and as evident from the study of Tellis, Yin and Bell (2009), this is not ultimately true. Furthermore, in the business context, Frambach, van Herk and Agarwal (2002) find partial negative direct effect of masculinity on innovation adoption and a positive interaction between masculinity and compatibility. Moreover, Dwyer, Mesak and Hsu (2005) manifest a significant positive effect of masculinity on the diffusion of innovations in the consumer context. Diffusion of innovations is a construct that describes the adoption of innovations by a group of individuals (Rogers, 2003).

Evident from the current state of knowledge, masculinity plays a role in innovation adoption. However, this role is from case to case either positive, negative or even insignificant and so, it is neither generalizable nor uniform. Since it is known that masculinity has a yet uncertain effect for the adoption of innovations, it is necessary to seek the source of the masculinity effects in phases earlier than in the decision stage of the adoption decision process. For this, the persuasion phase of the innovation decision process offers plausible potential. In particular, in this phase of the process the evaluation of innovation characteristics leads to an overall attitude formation about the innovation (Rogers, 2003). The characteristics are known to be the major drivers of innovation adoption (Meuter et al., 2005). Of them, compatibility is the most important characteristic for innovation adoption intention (Arts et al., 2011). The compatibility construct is socioculturally influenced (Rogers, 2003), which implicates that culture contributes to the perception of this characteristic and that masculinity is likely to have stable and uniform effects here. The relatively young research of Flight et al. (2011a) introduces the notion of

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secondary and primary innovation characteristics and offers the possibility to examine these uniform effects. According to Flight et al. (2011a) the subjective perception of secondary innovation characteristics forms the overall perception of the primary characteristic. So, it is plausible to assume that due to different values in the two different masculinity settings the secondary innovation characteristics have different importance for the formation of the overall perception of the primary compatibility, which then, influences the adoption intention of innovations. The different weights of the secondary compatibility characteristics for primary compatibility in the distinct masculinity settings equal a moderation of the effects of secondary compatibility characteristics on primary compatibility. Here, the effects of the secondary compatibility characteristics for primary compatibility are hypothesized to be different for the individuals with distinct masculinity values. This is a potential logical explanation towards the inconsistent findings regarding the role of masculinity in innovation adoption. If the truth is as hypothesized, then this line of reasoning would clarify the current understanding of how innovations are differently adopted in distinct masculinity cultures respectively by individuals with distinct masculinity values.

Subsequently, the hypotheses will be developed. They are based on the current state of knowledge on primary and secondary compatibility characteristics, which are part of the state of the art framework of Flight et al. 2011a. Regarding masculinity, they hypotheses are based on Hofstede’s (2001) definition of masculinity, which has been described as the most valuable definition of this construct in marketing studies. The conceptual model in figure three summarizes the proposed hypotheses.

Figure 3: Conceptual Model and Hypotheses

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Before the new knowledge regarding the moderation of secondary characteristics can be added, first the known relations need to be reconfirmed. As described in the literature review, Flight et al. (2011a) have researched the relations of secondary compatibility characteristics as a part of the whole innovation characteristics model presented in figure two. In the model, the secondary compatibility characteristics, personal- and social compatibility and social advantage influence primary compatibility positively. Volition affects primary compatibility negatively. This primary compatibility construct has been found to influence innovation adoption intention (e.g. Arts et al., 2011; Flight et al., 2011a; Rogers, 2003). Thus, the reconfirming hypotheses are:

𝐻𝐻1: Primary compatibility positively influences innovation adoption intention.

𝐻𝐻2: Personal compatibility positively influences primary compatibility.

𝐻𝐻3: Social compatibility positively influences primary compatibility.

𝐻𝐻4: Social advantage positively influences primary compatibility.

𝐻𝐻5: Volition negatively influences primary compatibility.

Subsequently, the hypotheses regarding the moderation of the effects of secondary compatibility characteristics on primary compatibility can be developed.

Personal Compatibility – An innovation is personally compatible if it fits into the potential

adopter’s lifestyle and to his regular routines (Flight et al., 2011a).

A typical feminine lifestyle pursues social goals focusing more on social relationships and on the quality of life. In contrast, a typical lifestyle in a more masculine culture is more assertive, competitive and is focused more on ego goals (de Mooij & Hofstede, 2010). In consequence, in the latter setting, innovations are more likely to be more compatible if they satisfy personal goals which is a priority, whereas in a feminine setting personal compatibility is likely to be secondary because there, the emphasis is put on social goals instead of on personal goals. In the more feminine cultures personal compatibility can be sacrificed for social compatibility whereas in the masculine cultures personal compatibility is of central importance.

𝐻𝐻6: Masculinity positively moderates the effect of personal compatibility on primary

compatibility.

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