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FFECT OF
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OTIVATED
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NIVERSITEIT VAN
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MSTERDAM
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ACULTY OF
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CONOMICS AND
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USINESS
Name: Onno Thomas Deumer
Student number: 5732301
Submission date: 13-06-2014
Submission version: First Draft
Qualification: MSc. Business Studies - Marketing
Institution: University of Amsterdam
Word count: 17.666 (excl. figures)
Supervisor 1: Ph.D. T. Paffen
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1 Content
2 Abstract ... 3
3 Introduction ... 4
4 Literature Review ... 7
4.1 Innovation Diffusion and Adoption ... 7
4.2 Innovation and Adopter Characteristics ... 11
4.3 Impact of Characteristics ... 14
4.4 Innovativeness and Innovation Adoption ... 17
4.5 Motivated Consumer Innovativeness ... 19
4.6 Expectations ... 25 5 Empirical Research ... 28 5.1 Objective ... 28 5.2 Design ... 29 5.3 Sample ... 32 5.4 Collection ... 34 5.5 Measures ... 36 5.6 Analysis ... 44 5.7 Methodological Limitations ... 46 5.7.1 Validity ... 46 5.7.2 Reliability ... 47 5.7.3 Generalizability ... 47 6 Results ... 49 7 Discussion ... 56 7.1 Managerial Implications ... 59 8 Conclusion... 60
8.1 Limitations and Future Research ... 62
9 References ... 64
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2
Abstract
Research Topic. The effect of motivated consumer innovativeness on the innovation
characteristics determining an innovation’s success.
Background. The success of innovative products is crucial for the survival of organizations
and measured by its rate of adoption. Whether consumers ultimately adopt an innovative product is depending on characteristics from both the innovation and the adopter. Rogers (2003) identified multiple innovation characteristics required for a successful innovation adoption, including relative advantage, compatibility, complexity, trialability and observability. The impact of these innovation characteristics on the final adoption decision making process appears to be contingent of motivated consumer innovativeness. Vandecasteele and Geuens (2010) identified four different motives to buy innovative products, being functional, hedonic, social, and cognitive. This research is examining the effect of motivated consumer innovativeness on the innovation characteristics determining an innovations success and attempts to grant an insight into the perceived importance of a predetermined set of innovation characteristics for consumers differentiated on both their global and domain-specific motivation to adopt innovative products.
Methods. A survey was conducted among more than 1000 Economics & Business students in
Amsterdam, complemented with friends, relatives, direct and indirect colleagues, and executed by means of a self-administered questionnaire spread via social media websites. Motivated consumer innovativeness and the manifestation of innovation characteristics were measured on a 5-point Likert scale generating 162 elements available for statistical analysis. Two logistic ordinal regression analysis resulted in 4x6 matrices for global and domain-specific consumer innovativeness displaying the coefficient of determination and regression coefficient indicating the effect of motivated consumer innovativeness on the impact of innovation characteristics.
Results. Both global and domain-specific motivated consumer innovativeness is significantly
related to the impact of innovation characteristics on adoption decision making processes. The impact of innovation characteristics in both circumstances is different however, demonstrating the effect of product category involvement. Multiple significant ß’s ranging from -1.019 till .860 in the global motivated consumer innovativeness matric and up to .684 in the domain-specific motivated consumer innovativeness matric indicate that the higher a consumer scores on a specific motivation to adopt innovative products, the presence of certain innovation characteristics is becoming significantly more or less important.
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3
Introduction
According to Rogers (2003), an innovation is an idea, practice, or object perceived as new by an individual or other unit of adoption, and is often believed to be a major driver for business success. Both academics and practitioners increasingly value innovation as a key component of business’s operations and innovation is therefore one of the most important issues in business research today. Innovation is perceived to be necessary for achieving many organizational goals, including but not solely; economic growth, the progression of human well-being, competitive advantage, higher business revenues, better returns and above all, business survival (Cohen, 2014). As Alan M. Kantrow, editor of Harvard Business Review, once put it, "For companies to survive a discontinuity or major innovations that change the nature of the game, they must face the rather unpalatable reality that there may have to be fundamental changes in who they are, what they do, and how they do it, as wrenching and dislocating as it may be.” (in Cohen, 2014, p. 4).
By creating such new ideas, practices or objects, organizations have the opportunity to fulfill customer needs by offering a new, effective, convenient and affordable solution to get the job done. The better an innovative product is able to help consumers fulfilling their needs, the more successful it will be. Rogers (2003) identified multiple innovation characteristics required for a successful innovation diffusion and adoption. The increasing presence of these characteristics indicate a higher success potential of innovative products. However, not product attributes but individual, specific circumstances motivate the customer to buy innovative products. The motivation to purchase innovations is created by the buyer’s recognition of an incongruity between the current situation and a desired situation. The result of this discrepancy is the need for change, which is mostly a latent need in the case for innovative products. Consumers have different reasons to adopt innovations and the purchase of new innovative
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products may stem from a need for safety and security, an addiction, or the need for replacement, identification, social recognition, or just because of its rarity or affordable price (Nederstigt & Poiesz, 2010). Consumers however might resist innovations even though they are considered necessary and desirable, due to several major barriers (Ram & Sheth, 1989). Both these motives and barriers to buying innovative products might vary for different types of consumers. Not all consumers will process innovations in the same manner and consumers will weigh innovation characteristics differently because of their individual, specific circumstances.
Although both innovation characteristics and different consumer motivations to buy or resist innovations have been identified before (Alpert, 1994; Arts, Frambach & Bijmolt, 2011; Joy, 2004; Rogers, 2003; Tornatzky & Klein, 1982; Vandecasteele & Geuens, 2011), the relation amongst both variables has never been assessed. This is remarkable, because how can one identify the innovation characteristics required for a successful innovation diffusion and adoption, if one does not know what motivates consumers to buy new products? Successful innovation rests on first understanding customer needs and then developing products that meet those needs (Hauser, Tellis & Griffin, 2006). Companies are required to know their customers and their motivations to buy because eliciting the motivation to buy is the first step in the buying process and thus a prerequisite for a successful innovation diffusion and adoption.
More recent research addressed different interactions between innovation and adopter characteristics (Herzenstein et al, 2007; Lambert-Pandraud & Laurent, 2010; Moreau et al, 2001; Steenkamp & Gielens, 2003). As these studies found important interactions between the characteristics of the consumer and the offering being evaluated, it is likely that the effect of innovation characteristics traditionally studied in adoption research varies among different types of consumers (Arts et al, 2011). Not all innovation characteristics, as proposed by Rogers’ (2003) framework, are equally important in explaining innovation adoption, because the impact of specific innovation characteristics depend on the motivation of the consumer to adopt
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innovative products. Therefore, this study will focus on the relationship between adopters’ motivation to buy innovative products and the perceived importance of a predetermined set of innovation characteristics, by attempting to give an answer to the following research question:
“What is the effect of motivated consumer innovativeness on the innovation characteristics determining an innovation’s success?”
In the first part of this study, prior literature on this topic will be addressed and discussed, foremost to get an understanding of the current knowledge of this subject and to identify the sources of motivated consumer innovativeness and innovation characteristics. In the consecutive part, the research methodology of this study will be presented and the feasibility of the research is reflected upon. Both the design and collection of the survey will be clarified, as well as he measures it contains. Following, the results of the questionnaire distributed amongst university students, friends and relatives, and both direct and indirect colleagues will be reported. Subsequently, the empirical results are discussed and compared to findings from prior literature, as debated in the literature review. Finally, a conclusion is drawn, managerial recommendations are being made and the limitations as well as possibilities for future research are addressed.
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4
Literature Review
4.1
Innovation Diffusion and Adoption
Recent literature has investigated the role of innovations in organizations and has acknowledged that innovation is vitally important for consumers, firms, and countries (Hauser, Tellis & Griffin, 2006; Paladino, 2007). There has been a noticeable increase in the number of studies directed at identifying the drivers of innovations’ success. Some of these drivers mentioned in prior studies include innovation strategy integration, team support and team communications, extensive experimentation, the use of new methods and techniques, market orientation, and resource development (Barczak, Griffon & Kahn, 2009; Paladino 2007).
However, the success of innovations ultimately depends on consumers accepting them, indicated by the innovations’ individual rate of diffusion and rate of adoption. The spread of an innovation is termed innovation diffusion, which is the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers, 2003). Understanding the spread of innovations by modelling their entire life cycles is the purpose of diffusion research. The main thread of diffusion models has been based on the framework developed by Bass (1969). The Bass model considers new adopters to join the market at each point in time as a result of two types of influences: external influences, such as advertising and other communication initiated by the organization, and internal market influences that result from interactions amongst adopters and potential adopters in the social system (Peres, Muller & Mahajan, 2010). Innovation diffusion is a process driven by social influences, which include all interdependencies among consumers that affect various market players with or without their explicit knowledge (Peres, Muller & Mahajan, 2010). Consumers today are exposed to a wide range of influences that include word-of-mouth communications,
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network externalities and social signals, which all have an influence on consumers’ perception of innovations.
A distinct aspect of diffusion is that at least some degree of heterophily is present in the communication about innovations. Heterophily is the degree to which two or more individuals who interact are different in certain attributes, such as beliefs, education, social status, and the like (Rogers, 2003). Assuming a heterogeneous population due to the existence of heterophily, consumers have different perceptions on innovations; what one likes may be disliked by someone else. Because of the newness of the idea, practice or object involved, some degree of uncertainty and perceived risk is involved in the diffusion process. People take a risk by communicating about innovations that might be disliked by others. Those who are more prone to accept this risk will communicate sooner on a particular innovation than people who are more risk averse. This degree of uncertainty and perceived risk is having a negative effect on the diffusion process as it will prevent potential adopters who a risk averse from interacting with innovations. An individual’s perception on the innovative product determines his evaluation of the innovation which in turn determines his diffusion decision. An innovations’ rate of diffusion is therefore not only determined by the innovation potential of the new idea, practice or object, but also by the perceptions on the innovation held by consumers. Innovation perceptions are initially uncertain, however these insights change over time as the potential adopter receives additional information about the innovation. An individual's timing of diffusion is thus determined by the dynamics of perceptions, given his preference structure (Chatterjee & Eliashberg, 1990).
Communicating about an innovation does not automatically lead to buying behavior with respect to the particular innovation that is communicated upon. Since the rate of diffusion only deals with the communication of innovations, it is unable to predict the success potential of innovations in terms of consumer adoption behavior. Innovation adoption is a process
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following innovation diffusion, traditionally conceptualized as a sequence of steps in which the consumer passes from initial knowledge of an innovation, to forming an attitude towards it, to reaching an adoption decision (Rogers, 2003). The rate of adoption is the relative speed with which an innovation is adopted by members of a social system and thus transfers from the diffusion stage to the adoption stage (Rogers, 2003). Figure 1 is showing the innovation adoption process for multiple innovations.
Figure 1: Innovation Adoption Process by Rogers (2003)
Consumers who are aware of an innovation and thus progressed through the innovation diffusion stage, may behave in several different ways once arrived in the innovation adoption stage. People may feel inclined to adopt the innovation because they are considered necessary, beneficial and desirable. However, according to Ram (1987), consumers may also feel disinclined to adopt the innovation, feel that the innovation is too risky and postpone the adoption decision, or may be convinced that the innovation is unsuitable. Although many consumers believe that innovations can benefit them, they resist some innovative products and services. According to Ram and Sheth (1989) innovation resistance occurs because of one of
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the following two reasons: First, an innovation may create a high degree of change in the consumers’ day-to-day existence and disrupt their established routines. Potential changes from a satisfactory status quo can cause resistance to the innovation. Second, an innovation may conflict with the consumers’ prior belief structure. Because of either of the two reasons, consumers might not intent to adopt an innovation or consumers might have innovation adoption intentions but ultimately will not buy the innovative product, therefore postponing the acquiring of the innovative product and therefor the actual innovation adoption. The final adoption decision is affected by the degree of innovation resistance experienced by the potential adopter. Innovation resistance varies in degree and exists on a continuum, increasing from passive resistance or inertia to active resistance (Ram & Sheth, 1989). Adoption begins only after the initial resistance experienced by the consumers is overcome. Any resistance to innovation adoption will hinder consumers to fully embrace an innovation. If the resistance is too high, the innovation dies and there will be no adoption (Ram, 1987). A key cause for the commercial failure of innovations thus is the resistance they experience from consumer (Ram & Sheth, 1989). Therefore, only a small fraction of the new product ideas chosen for market development is prosperous, regardless of the success potential of innovations.
Due to the existence of innovation resistance, consumers might decide not to buy an innovation and as a result, potential adopters who have progressed through the innovation diffusion stage, might not transfer through the innovation adoption stage at all. Consumers who actively talk about innovative products in a positive way do not automatically adopt the innovation communicated upon because of innovation resistance. A difference remains between an innovation communicated through a social system and the actual buying behavior of consumers, the rate of diffusion and the rate of adoption respectively. Arts, Frambach and Bijmolt (2011) conclude that consumer intentions are often poor predictors of actual adoption behavior. An important reason for the difference between consumer innovation intentions and
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consumer innovation behavior may be that the evaluative criteria which consumers use in both stages of the adoption process weigh differently (Art, Frambach & Bijmolt, 2011). Both innovation and adopter characteristics may have an impact on the overall evaluation of innovations and their diffusion and adoption as a result.
4.2
Innovation and Adopter Characteristics
Wood and Moreau (2006) suggest that adoption is rarely a neutral process and that consumers can experience strong emotions in the initial use of innovations. Positive emotions give rise to the full adoption and continues use of the innovation and new product success can be reliably predicted by an evaluation of variables determining the rate of adoption of innovative products. To identify these variables, the majority of prior literature is relying on aspects of the innovation diffusion theory by Rogers (2003). In an examination of several thousand innovation studies, Rogers (2003) identified multiple variables determining the rate of adoption of innovations, including five characteristics of innovations, the type of innovation-decision, communication channels, and nature of the social system and the extent of change agents’ promotion efforts. The five characteristics are the innovations’ attributes perceived by consumers and used to evaluate an innovative product and solely explain nearly half of the variance in the rate of innovations’ adoption. The rate of an innovation’s adoption is predicted by individuals’ perception of these five characteristics. These five individual innovation characteristics are relative advantage, compatibility, complexity, trialability and observability.
Relative advantage is the degree to which an innovation is perceived as better than the
idea it supersedes. The degree of relative advantage is often conveyed as economic profitability, social prestige, or other benefits. It is the nature of the innovation that determines what type of relative advantage is important to adopters. The relative advantage of an innovation is positively related to its rate of adoption. Compatibility is the degree to which an innovation is perceived
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as consistent with the existing values, past experiences, and needs of potential adopters. A new product that is more compatible with an adopter’s current situation is less uncertain and fits more closely with the consumer’s life situation. The compatibility of an innovation is positively related to the rate of adoption. Complexity is the degree to which an innovation is perceived as relatively difficult to understand and to use. Any innovation can be classified on a continuum of complexity versus simplicity (or ease of use). Some new products are clear in their meaning whereas others are not. The complexity of an innovation is negatively related to the rate of adoption. Trialability is the degree to which an innovation may be experimented with on a limited basis. Some new products are more difficult to divide for trial than are others. The personal trying-out of an innovation gives meaning to the new product. By finding out how an innovation works under one’s own conditions, uncertainty about the innovation is dispelled. The trialability of an innovation is positively related to the rate of adoption. Observability is the degree to which the results of an innovation are visible to others. Results of some innovations are easily observed and described to others, whereas some new products are difficult to witness and to communicate to others. The observability of an innovation is positively related to its rate of adoption. These five individual characteristics identified by Rogers (2003) have an impact on an innovations’ rate of adoption.
The innovation characteristic relative advantage is often somewhat of an omnibus category. Researchers have tended to lump together rather different referents into it (Dearing, 2007). Therefore, the item is being separated into what are often believed to be the two dominant meanings of this attribute, effectiveness and costs. Parsing out this characteristic results in six basic innovation characteristics. An overview of these innovation characteristics identified by Rogers (2003) and partially deconstructed by Dearing (2007) is shown in figure 2.
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Innovation Characteristics Description
Effectiveness The degree to which an innovation is perceived as better than the idea it supersedes.
Cost The degree to which an innovation is perceived to be low in monetary of other cost.
Compatibility The degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters.
Complexity The degree to which an innovation is perceived as relatively difficult to understand and to use.
Trialability The degree to which an innovation may be experimented with on a limited basis.
Observability The degree to which the results of an innovation are visible to others.
Figure 2: Six innovation characteristics identified by Rogers (2003) (including relative advantage being split into effectiveness and costs).
Apart from innovation characteristics, the adoption rate of innovations is also determined by adopter characteristics. Adopter characteristics capture the personal traits that describe the potential adopter of an innovative products, which can be divided into socio-demographics and psychographics. The number of different variables used to capture adopter characteristics is particularly large, as a lot of research has been devoted to finding traits of consumers that are likely to adopt an innovation (Arts, Frambach & Bijmolt, 2011). A wide range of socio-demographic characteristics have been used in research. Prior literature has focused on consumers’ age, level of education and income. Other variables frequently considered are gender, family life cycle and household size (Gatignon & Robertson, 1985; Rogers, 2003; Tornatzky & Klein, 1982). The findings from Arts, Frambach and Bijmolt (2011) suggest that the age of the potential adopter is having a negative effect on consumer innovation adoption. However, the level of education and income level of the potential adopter is having a positive
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effect on the chances of full adoption. Innovativeness, opinion leadership, media proneness, and product category involvement are the variables among the adopter psychographics most frequently used to explain adoption. Variables within this category less frequently used to explain consumer innovation adoption include price consciousness, brand familiarity, self-confidence, and dogmatism. The higher a potential adopter is scoring on each of these adopter psychographics, with the exception of price consciousness, the higher the chance on full adoption and thus continuous use of innovative products (Arts, Frambach & Bijmolt, 2011). One major stream relating personal characteristics to innovative product adoption suggests that innovative consumers tend to have higher levels of income and education, are younger, have greater social mobility and favorable attitudes towards risk, and have a greater social participation and higher opinion leadership (Im, Bayus & Mason, 2003).
4.3
Classification of Characteristics
Prior research has often used innovation characteristics as well as adopter characteristics identified in the paragraph above to group either innovations or consumers on the basis of their specific traits. Alexander, Lynch and Wang (2008) group innovations in one of two categories based on the newness of the innovation. They identify really new products and incrementally new products and reason that compared with consumers of incrementally new products, consumers of really new products are less likely to think concretely about the circumstances of buying and using the products and are more poorly calibrated in their expectations of initial product use (Alexander, Lynch & Wang, 2008). As a result, full adoption and thus the continuous use of innovations is less likely to take place in the case of really new products as opposed to incrementally new products. Another explanation for the enhanced acceptation of incrementally new products over really new products is given by Hoeffler (2003). According to Hoeffler (2003), consumers have greater uncertainty when estimating the usefulness of really
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new products than they have with incrementally new products. For really new products, respondents may not be aware of the links between innovation features and the benefits provided by those features. For incrementally new products, the experience potential adopters already have with existing products enables them to understand the link between specific attributes and the benefits provided by those attributes. This inability to identify the benefits from innovative products is hampering the continuous use of consumer innovations and thus consumer innovation adoption.
Henard and Szymanski (2001) conduct a meta-analysis of the new product performance literature to explicate the most important organizational drivers of new product success. Although many firm characteristics relating to strategy and processes are incorporated and found to be highly influential, all of the product characteristics including product advantage, product price, product innovativeness, product meeting customer needs and product technological sophistication are found to have a significant positive effect on new product success (Henard & Szymanski, 2001). Kleinschmidt and Cooper (1991) also demonstrate the relationship between product innovativeness and commercial success and according to the authors, highly innovative products are more likely to be more successful than less innovative products. This is a remarkable contrast with prior findings (Alexander, Lynch & Wang, 2008; Hoeffler, 2003). However, these different findings are the result of the incongruous understanding of exactly what product innovativeness means. Danneels and Kleinschmidt (2001) therefor present a framework to distinguish customer and firm perspectives on product innovativeness. From the customer’s perspective, innovation attributes, adoption risks, and levels of change in established behavior patterns are regarded as forms of product newness. Within the firm’s perspective, environmental familiarity and project-firm fit, and technological and marketing aspects are proposed as dimensions of product innovativeness (Danneels & Kleinschmidt, 2001). From a customers’ perspective, innovative products are associated with a
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higher risk and uncertainty, and is therefore having a negative impact on consumer innovation adoption. From a firms’ perspective, product innovativeness is paired with familiarity and fit and has a positive effect on consumer innovation adoption.
Next to innovative products being categorized based on their individualities, consumers can also be classified on behalf of their personality traits. The consumer socio-demographics and psychographics identified before form the basis for this categorization. One of such an adopter psychographics often used to classify consumer is consumer innovativeness.
Innovativeness refers to the general propensity of a consumer to adopt new products. Rogers
(2003) used consumer innovativeness to group adopters into five different categories by measuring innovativeness by the time-of-adoption method. The resulting adopter categories represent the classification of the members of a social system on the basis of innovativeness, the degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas, practices or objects than other members of a system (Rogers, 2003). The adopter categorization on the basis of innovativeness is shown below in figure 3.
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Innovators are those people who enjoy owning a product which they eventually do not need,
before others. They are eccentric, bold, confident, following trends, extravagant, willing to take risk, and very active in seeking and absorbing information provided by organization. Early
adopters are people who perceive themselves as pioneers of the innovation and who want to try
something new. They assess the risk of buying an innovation and are worried about future failures. The early majority is cautious and respective to new products. To gather information they listen to more experienced friends and relatives whom are perceived as opinion leaders and ignore the media. They are not interested in the innovation per se, but tend to follow the recommendations of those who they communicate with, trust, and convince them. The late
majority consists of skeptics who ignore the flow of information through various types of
communication channels provided by organizations. They adopt innovations as they are influenced by recommendations of peers and are subject to social pressure. Laggards are inert people who adopt innovations at the time when these are already replaced by next generation products. They are traditionalists who rely on the past and tend to use what they have until these items are completely outdated.
4.4
Innovativeness and Innovation Adoption
Recent research has addressed the different interactions between innovation characteristics and adopter characteristics (Herzenstein, Posavac & Brakus, 2007; Lambert-Pandraud & Laurent, 2010; Moreau, Lehmann & Markman, 2001; Steenkamp & Gielens; 2003; Arts, Frambach & Bijmolt, 2011). Since these studies found important interactions between adopter characteristics and the innovation being evaluated, it is expected that the effect of innovation characteristics varies among different types of consumers. In line with the research of Rogers (2003), consumers are typically grouped according to their innovativeness. The level of consumer innovativeness plays a protruding role in the diffusion and ultimate adoption of innovations. In
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relating innate consumer innovativeness and innovative product adoption behavior, there has been a debate on whether such an innovative predisposition determines innovative adoption behavior (Im, Bayus & Mason, 2003). Midgley and Dowling (1978) proposed a contingency model of innovativeness in which individual predispositions interact with personal characteristics and social communication networks (i.e. socio-demographic variables such as age, education, and social participation) to account for new-product adoption behavior, which has been tested thoroughly in consecutive empirical studies (Im, Bayus & Mason, 2003).
The findings of these studies are generally inconsistent. Results from the study by Im, Bayus and Mason (2003) indicate that the link from innate consumer innovativeness to innovative product adoption behavior in general is weak, even though it is statistically significant. The results from their study support Goldsmith, Freiden and Eastsmith (1995) argument that the relationship between innate consumer innovativeness as a generalized innovative predisposition and new-product adoption behavior is not prominent. Foxall’s (1988) empirical study on consumer innovativeness and innovative adoption behavior concludes that no significant relationship exists between consumer innovativeness and innovative product adoption behavior. These outcomes are in line with other research indicating that the relationship between personality and buyer behavior is, if significant, weak due to the general conceptual irrelevance between traits and behavior (e.g., Goldsmith & Hofacker 1991; Goldsmith, Freiden & Eastman. 1995; Kassarjian 1971; Lastovicka & Joachimsthaler 1988).
Contrary to these findings on global consumer innovativeness, previous studies examining the impact of innate innovativeness on new consumer electronic products adoption argue that the relationship is positive and significant (e.g. Dickerson & Gentry, 1983; Labay & Kinnear, 1981; Martinez, Polo & Flavian.; 1998). Goldsmith, Freiden and Eastman (1995) find that global consumer innovativeness across product categories has a weak correlation with new-product adoption behavior, while domain-specific consumer innovativeness for a specific
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product category has a strong correlation with it. Foxall (1995) concludes that the relationship between consumer innovativeness and innovation adoption behavior is contingent on the level of involvement in the product category. This argument is supported by Citrin et al. (2000) who study the adoption behavior of Internet shopping and find a direct influence of domain-specific innovativeness, and Limayem, Khalifa, and Frini (2000), who also find an influence of consumer innovativeness on Internet shopping behavior. The impact of consumer innovativeness on consumer innovation adoption therefor appears to be depending on the product category. According to Venkatraman (1991), next to product type, the innovative product adoption behavior is also depending on the influence of consumer innovativeness motivation.
4.5
Motivated Consumer Innovativeness
Last decades a lot of research has been focusing on the identification of values influencing consumer choice. These theories focus on consumption values, explaining why consumers choose to buy or not to buy a specific product, why consumers choose one product type over another product type, and why consumers choose one brand over another brand. According to Sheth, Newman and Gross (1991) consumer choice is a function of multiple consumption values. These are functional value, social value, emotional value, epistemic value, and conditional value. Any brand, product type, or “buy or not buy” decision may be driven by completely different consumption values (Sheth, Newman & Gross, 1991). Every consumer is experiencing different motivations for the consumption of products. Alpert (1994) summarizes a new typology of innovator motivation, since it will help to understand innovation fascination and clarify its difference from chasing the advances. It represents an adaptation of the conventional buyer motivation typology from Sheth, Newman and Gross (1991) to the context of innovator motivation toward innovations. Essentially, it is a benefits-sought segmentation,
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where the benefits also include those that come from the product being innovative now, as opposed to intrinsic benefits that will always be available from the product (Alpert, 1994).
According to Alpert (1994), chasing the advances is primarily driven by utilitarian motivation. Each innovative new product delivers a higher performance than prior products. Innovators with a utilitarian motive to buy new products, focus on tangible relative advantage. These consumers are not interested in the innovation per se, but in the improved performance. However, innovation fascination might also be driven by one of three non-utilitarian motives, or a combination of these motivations at one time. Though intellectual fascination from novel stimuli is clearly cognitive, it is not the usual price/performance evaluation thinking of the average consumer. Also, there is an emotional exhilaration to buying and using innovations. Consumers with intellectual motives focus on understanding how the new benefits will be delivered and the comprehension and mastery of the product class. These people habitually have a high need for cognition. Not extreme enough to make one laugh or cry, but novelty can deliver an emotional payoff as well. Buying decisions based on emotional motives are focused around the excitement of innovative products: “I just got to have this!”. Lastly, some consumers may be motivated by having the latest version of any product rather as much as by using it, so that others may see how trendy or fashionable they are, which is referred to as social motivation (Alpert, 1994). Innovators with social motivations want others to see that he or she has the latest products and are mainly other directed.
Existing, mostly uni-dimensional consumer innovativeness scales ignore the multitude of motivation sources of buying innovations as proposed by Alpert (1994). The adopter categorization by Rogers (2003) is an example of such a consumer innovativeness scale disregarding consumers’ motives to buy innovative products. An innovativeness scale that is more balanced in addressing potential purchase motivations goes beyond existing scales of this original type, addressing the difference between consumers in terms of not only their level of
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innovativeness but also their type of innovativeness (Vandecasteele & Geuens, 2010). Prior literature has acknowledged the importance of different sources of innovativeness or motivations (Alpert, 1994; Daghfous, Petrof & Pons, 1999). However, the consumer innovativeness scales used by these researchers take into account two different motivations at most (e.g. Roehrich, 1994; Venkatraman & Price, 1990). Based on the research by Rogers (2003, p. 115), who states that “we should increase our understanding of the motivations for adopting an innovation. Such ‘why’ questions about adoption have seldom been probed effectively.” an extensive literature review was performed by Vandecasteele and Geuens (2010). By including a wider spectrum of motivations, the authors have been able to develop and validate a multi-motivational consumer innovativeness scale based on general motivation and value taxonomies that performs better in terms of both content validity and predictive validity. By conducting five studies, they indicate that four types of motivation underlie consumer innovativeness: functional, hedonic, social, and cognitive. Each of these consumer innovativeness motivations are clarified below.
Functional motivation refers to self-reported consumer innovativeness motivated by the
functional performance of innovative products and focuses on task management and accomplishment improvement (Vandecasteele & Geuens, 2010). Consumers with a functional motivation to innovation adoption behavior will buy new products to reach certain task goals. These goals can be defined in terms of mastery and management including dimensions like improving performance, being productive, organizing, and avoiding threats. Innovation attributes important for functional motivated consumers are usefulness, compatibility, efficiency, handiness, quality, ease, comfort and reliability. Functional motivation is comparable with the utilitarian motivation identified by Alpert (1994). Hedonic motivation is the self-reported consumer innovativeness motivated by affective or sensory stimulation and gratification (Vandecasteele & Geuens, 2010). Consumer adoption behavior grounded in
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hedonic motives serves to reach specific affective goals like arousal and happiness. Adopters with a hedonic motivation attempt to experience feelings of excitement, joy and satisfaction by buying new products. Examples of these motivates include, but not solely: pleasure, sensation, tension, fun, desire, excitement, enjoyment and the need to escape from the daily round. Hedonic motivation has a resemblance with the emotional motivation addressed by Alpert (1994). Social motivation reflects the self-reported consumer innovativeness motivated by the self-assertive social need for differentiation (Vandecasteele & Geuens, 2010). Motives of a social nature to consumer innovation adoption behavior result from a drive to accomplish social relationship goals. Consumers buying new products with social motives aim to reach a sense of individuality, status, success, superiority, freedom, and uniqueness. An attempt to reach these goals might result in adopting innovations motived by the desire to be different and unique, or to have prestige, opinion leadership, social rewards, and a sense of belonging. A social motivation to buy innovative produce was already identified by Alpert (1994). Cognitive motivation is indicated by the self-reported consumer innovativeness motivated by the need for mental stimulation (Vandecasteele & Geuens, 2010). This type of motivation underlying consumer innovativeness refers to the need to reach consumer specific cognitive goals primarily by expanding cognitive limits through knowledge and thought through means like exploration, understanding, and intellectual creativity. Examples of cognitive motivation include knowledge, logical thinking, mental stimulation, insight and understanding, information, brainpower, wisdom, intelligence, reason and an eagerness to learn. Cognitive motivation is comparable with innovators’ intellectual motivation to buy as elaborated upon by Alpert (1994). The multi-dimensional Motivated Consumer Innovativeness scale developed by Vandecasteele and Geuens (2010) and that takes into account the different motivations of innovative consumers is summarized in figure 4.
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Motivated Consumer Innovativeness Scale Functionally Motivated
Consumer Innovativeness
Self-reported consumer innovativeness motivated by the functional performance of innovations and focuses on task management and accomplishment improvement.
Hedonically Motivated Consumer Innovativeness
Self-reported consumer innovativeness motivated by affective or sensory stimulation and gratification.
Socially Motivated
Consumer Innovativeness
Self-reported consumer innovativeness motivated by the self-assertive social need for differentiation.
Cognitively Motivated Consumer Innovativeness
Self-reported consumer innovativeness motivated by mental stimulation.
Figure 4: Motivated Consumer Innovativeness Scale (Vandecasteele & Geuens, 2010).
This consumer innovativeness scale including functional, hedonic, social and cognitive motivations, maintains the middle ground between existing domain-specific innovativeness scales focusing on a specific product category, and global innovativeness scales treating motivated consumer innovativeness as a generalized innovative predisposition. The scale performs better in predicting innovative buying behavior because it takes into account a more complete range of motivations for innovativeness (Vandecasteele & Geuens, 2010). By using this motivated consumer innovativeness scale it is not necessary to identify particular innovations prior to researching the effect of innovation characteristics, because the impact of the attributes identified by Rogers (2003) is no longer depending on the product category but on the consumer motivation instead. No distinction has to be made between really new products and incrementally new products either. As a result, the identification of four adopter categories based on motivation allows studying the differential effect of innovation characteristics for different types of consumers, based on the different types of motivations for innovation adoption behavior each individual experiences. Unfortunately, this has not been examined before. The aim of this study is to address this research gap and examine the effect of motivated consumer innovativeness on the importance of a predefined set of innovation characteristics
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Research Area
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that innovative products are expected to possess in order to become successful through means of full adoption and continuous use. This framework is presented in figure 5.
Figure 5: Conceptual framework showing the effect of motivated consumer innovativeness on the impact of innovation characteristics on innovation adoption.
Based on prior literature, it is expected that the motivated consumer innovativeness, i.e. consumers’ reason for innovative product adoption, is having an effect on the perceived importance of the innovation characteristics identified before. The size, strength and significance of this effect is currently unknown. The main objective of the current research is to clarify this issue by trying to answer the following research question:
“What is the effect of motivated consumer innovativeness on the innovation characteristics determining an innovations success?”
By answering this question, contributions to both theory and practice can be made. The results of this study will highlight the importance of different innovation characteristics for different types of consumers. Although this has already been addressed in prior research, the use of a new innovativeness scale based on motivation will give academics a better understanding of
Innovation Adoption Innovation Characteristics: Effectiveness Costs Compatibility Complexity Trialability Observability Motivated Consumer Innovativeness: Functional Hedonic Social Cognitive
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the motives for weighing the evaluative criteria consumers use in the adoption process differently. It is necessary for researchers to understand the factors that influence innovation adoption and its variance among multiple consumer categories. This paper contributes to that understanding. The results of this study are also highly relevant for marketers, since it sheds light on the importance of certain innovation characteristics when targeting a specific consumer base and thus gives companies an idea which innovation characteristics to prime. It may also help managers to identify and reach motivated innovative consumers, realizing interest in an innovative product or service more efficiently and effectively.
4.6
Expectations
Prior research on shopping motivation has examined the role of different motivations for internet shopping (Arnold & Reynolds, 2003; Childers, Carr & Carson, 2001; To, Liao & Lin, 2007). The findings from these studies shed light on the drivers for buying decisions at different retailers, differentiated for multiple types of consumer motives. Although these inquiries have taken place in a different research environment serving a different purpose, the outcomes can help to create expectations for the moderating role of motivated consumer innovativeness on the relationship between innovations characteristics and innovation adoption, which is the aim of this study.
Motivations to engage in retail shopping include both utilitarian and hedonic dimensions (Childers, Carr & Carson, 2001). To, Liao and Lin (2007) conducted a study based on utilitarian and hedonic values to investigate shopping motivations on internet. The study finds that utilitarian motivation, which is comparable with the functional motivation derived from the paper by Vandecasteele and Geuens (2010) is a determinant of consumer intention to search and intention to purchase. Hedonic motivation has a direct impact on intention to search and indirect impact on intention to purchase. While these dual motivations have significant effects,
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utilitarian motivation is the strongest predictor of intention to search and intention to purchase. According to To, Liao and Lin (2007), utilitarian motivation is influenced by values, ranked by their relative importance, such as convenience, cost saving, information availability, and selection. Factors such as sociality and customized product or service would not influence the utilitarian motivation of Internet shopping. When translated to the current research, it is expected that consumers with a functional motivation to adopt innovations, so functional motivated consumer innovativeness, would assess comparable values to be the most important. The innovation characteristics identified by Rogers (2003) show some resemblance with the values mentioned in the research by To, Liao and Lin (2007). Convenience for instance is comparable with relative advantage, i.e. the convenience caused by improved performance, and a low complexity. Costs savings automatically relates to the innovation characteristic costs, which describes the negative relationship costs has with innovation adoption. Therefore, it is expected that the innovation characteristics relative advantage, complexity and costs are the most important to consumers with a functional motivation to adopt innovations.
The same study also proves that hedonic values influence hedonic motivation of Internet shopping. The hedonic values, ranked by their relative importance, are: adventure/explore, authority and status (To, Liao & Lin, 2007). These are the drivers that led consumers to engage in Internet shopping behavior based on their hedonic motivation. Arnold and Reynolds (2003) confirm these findings and even construct a six-factor scale including adventure, gratification, role, value, social and idea shopping motivations. These findings are in line with the concept of hedonically motivated consumer innovativeness given by Vandecasteele and Geuens (2010), who define hedonic shopping behavior as being motivated by affective or sensory stimulation and gratification. However, on first sight none of these constructs is closely related to the innovation characteristics described. In addition, the relation between the two measures has never been examined before. Therefor it is not possible to present a reliable estimation of the
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effect of hedonic motives to innovation adoption on the perceived importance of innovation characteristics.
The majority of research on consumer innovativeness has only identified utilitarian and hedonic motivations to innovation adoption. Several other authors acknowledge the importance of different motivations or sources of innovativeness but take into account these two different types of motivations at most. Vandecasteele and Geuens (2010) are one of the few who identified four consumer categories based on motivation. However, the additional consumer categories identified have never been linked to innovation characteristics before. As a result, the relationship between the remaining two categories, social and cognitive motivation, and other variables has not been tested and the influence of social and cognitive motivation on the perceived importance of innovation characteristics is not grounded in theory. However, it is possible to make some estimates based on common sense. As Vandecasteele and Geuens (2010) describe socially motivated consumer innovativeness as the self-reported consumer innovativeness motivated by the self-assertive social need for differentiation, an increased perceived importance of innovation characteristics like observability, communicability and social approval is expected. Cognitively motivated consumer innovativeness refers to the self-reported consumer innovativeness motivated by mental stimulation. Consumer who adopt innovation because of this specific motivation have a desire for new products which are able to stimulate thoughts and beliefs. No specific innovation characteristics are obviously linked to cognition so any outspoken expectations are not present.
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5
Empirical Research
5.1
Objective
One conclusion of the literature review is that so many findings can be deducted from prior research on the innovation adoption process. What all authors agree on is that innovations and their successful diffusion and adoption are essential to business performance. For decades academics have been focusing on the determinants for innovation success, ranging from product attributes to organizational qualities and consumer characteristics, all of them having a part in innovation success to a certain degree. Rogers (2003) has been a pioneer on the subject of innovation diffusion and adoption, and his diffusion theory serves as a guiding principle for fellow researchers. The identification of five innovation characteristics describing the success potential of an innovation has ever since been used by many academics to predict the rate of an innovation’s adoption. Consumer attitudes towards innovative products assessed by the perceived importance of innovation characteristics and the resulting adoption rates have been tested thoroughly for different kinds of innovations in markets like banking (Ndubisi and Sinti, 2006), information systems (Moore and Benbasat, 1991), health education (Atkinson, 2007), information communication technology (Richardson, 2011), and farm practices (Fliegel and Kivlin, 1966). However, the adoption rate of innovative products is not only determined by the presence of innovation characteristics, but also by adopter characteristics. One such a personality trait is a person’s overall motivation to adopt innovations, measured with the motivated consumer innovativeness scale by Vandecasteele and Geuens (2010).
Each of the aforementioned studies focus on one specific product for one specific consumer group and take a homogeneous market for granted. The consumers’ attitude towards the innovation and the motivation for buying the new product is therefore generalized. For these studies this assumption is appropriate, because the products investigated were designed to meet
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a consistent and uniform need held by the consumer. More generally however, consumers have differing motivations to buy innovative products (Alpert, 1994; Joy, 2004; Vandecasteele & Geuens, 2010). Since consumers buy innovative products for different reasons, their perceptions of innovations might differ which will influence the final adoption decision. The success of innovative products, reflected by the adoption rate, is thus depending on the consumers’ motivation to buy. Since the adoption rate is determined by the consumers’ collective assessment of innovation characteristics it is expected that consumer motivation will also have an impact on the perceived importance of innovation characteristics.
The main objective of this study is to research this impact and examine how consumers’ motivations to buy innovative products, measured by the motivated consumer innovativeness scale from Vandecasteele and Geuens (2010), can alter the perceived importance of a predetermined set of innovation characteristics, as identified by Rogers (2003). Not much attention has been paid to relating differences between consumers’ type of motivation and their preference for specific innovation characteristics in currently existing literature. The results must give an insight into what different consumer segments, grouped by their innovation buying motivation, perceive as important innovation characteristics.
5.2
Design
This research has a deductive nature. The approach involves the testing of a theoretical proposition by the employment of a research strategy specifically designed for the purpose of its testing. The nature of the research strategy will be multifold. First, the study will examine the moderating role of motivated consumer innovativeness on the impact of innovation characteristics on the innovation adoption decision, and will have an explanatory character which is defined as a focus on studying a situation or a problem in order to explain the relationships between variables (Saunders et al., 2007, p. 134). Second, the research will have
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a descriptive nature. The objective of descriptive research is to ‘portray and accurate profile of persons, events or situations’ (Robson, 2002, p. 59). The study will continue by giving four different adopter profiles based on consumers’ motivation to buy innovative products and the relative perceived importance of a predefined set of innovation characteristics. Any liaison between the adopter categories and innovation characteristics may serve as a precursor to more pieces of explanatory research.
A survey will be conducted to give an answer to the main research question. Conducting a survey is considered to be the best approach for this research, because it allows the collection of a large amount of data from a large amount of people, in a highly economical way. The survey strategy is perceived as authoritative by people in general and is both comparatively easy to explain and to understand (Saunders et al., 2007, p. 138). More specifically, a questionnaire will be used to collect the required data. Although questionnaires are usually not particularly good when requiring large numbers of open-ended questions, they work best with standardised questions that you can be confident will be interpreted the same way by all respondents (Robson, 2002). The questionnaire is also used to guarantee standardized and consistent questions, so that every person gets the same questions, to compare the answers of different respondents easily and to make sure this comparison is reliable (Saunders et al., 2007, p. 139). The collected data can then be analysed quantitatively using descriptive and inferential statistics, and can be used to suggest possible reasons for particular relationships between the variables examined. Furthermore, a lot of prior studies on innovation characteristics and to a lesser extent on motivated consumer innovativeness used self-administered questionnaires to gauge the importance of innovation characteristics or motivations to buy innovative products. The use of a questionnaire will allow the examination and explanation of relationships between two variables, in particular cause-and-effect relationships like the moderating role of innovation adoption motivation, and enable the opportunity to identify and describe the variability in
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different phenomena, in this case the perceived importance of different innovation characteristics for multiple consumer categories (Saunders et al, 2007, p. 356). Questionnaires can therefore best be used for descriptive or explanatory research, or a combination of both as is the case with the current research.
The survey design and in particular the use of questionnaires also has drawbacks. One limitation of the use of questionnaires is the number of questions that can be included, since generally people are not interested in filling in a large questionnaire (Saunders et al., 2007, p.364). To reduce the apparent length without reducing the legibility of the research, it is recommended to record answers to questions with the same set of possible responses as a table. To prevent having to ask more questions than necessary and avoid the risk of respondents not participating in the research because of the apparent length of the questionnaire, as well as to increase both the internal and content validity, scales designed and tested by Vandecasteele and Geuens (2010) were used to assess the motivated consumer innovativeness and a measure developed by Dearing (2007) was used to gauge innovation characteristics. Another major disadvantage of questionnaires especially when self-administered via Internet, is the low response rate. Fan and Yan (2010) identified many factors in the stage of survey development, survey delivery, survey completion and survey return affecting response rates of web surveys. To increase the response rate attention was paid not only to general factors involved but more importantly to specific factors uniquely related to a web survey. The techniques used to enhance the response rate are discussed in the section about survey collection.
The questionnaire consists of three independent parts. The first part of the questionnaire consists of common questions about gender, nationality, and age, to be able to create a profile of the respondents. The second part of the questionnaire consisted of two scales used to measure a consumer’s motivation to buy new products. Because the motivated consumer innovativeness scale is a personality scale, the concepts measured should be stable over time. The innovation
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in question or the product category should therefore not have an influence on consumers’ motivation to buy the new product. Moreover, the respondents should not respond to the scale items in a socially desirable manner. Therefore, the first scale was used to gauge global motivated consumer innovativeness, treating motivated consumer innovativeness as a generalized innovative predisposition. Next, respondents were asked to rate the perceived importance of a set of predefined innovation characteristics. However, an innovativeness scale must also predict innovativeness consumer behavior in everyday life. Consequently, a second scale measured domain specific consumer innovativeness for a specific product category. This scale assumed motivated consumer innovativeness to be dependent on the consumers’ involvement in the product category. In both motivated consumer innovativeness scales, there is a unique relationship between each motivation dimension and the buying intentions or buying behavior of consumers seeking innovations that satisfy their specific functional, hedonic, social, or cognitive needs (Vandecasteele & Geuens, 2010). The results of this second scale designed to measure motivated consumer innovativeness in relation to a specific product category can be compared to the results of the first scale measuring consumers’ motivation to buy innovative products as a personality trait, and permits to research whether motivation is really stable over time, or indeed depends on the product category involved. The third part of the questionnaire was designed to measure consumer’s perception towards the five innovation characteristics that, once gauged by consumers, determine the success of the innovation in terms of its adoption rate. This was done using a scale designed and validated by Dearing (2007). Both scales are discussed in more detail in the section about measures.
5.3
Sample
Consumer are confronted with innovations in consumer products on a daily basis and some people are triggered more often into buying behavior than others. Rogers (2003) defined
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different types of consumers based on the degree to which an individual is relatively earlier in adopting new ideas, practices or objects than other members of a social system. Every member of the society can be classified in the categories innovators, early adopters, early majority, late majority or laggards and all have their personal motivation to adopt new products, making every consumer a viable target to research. The population examined in this research and from whom a sample frame will be selected are consumers in The Netherlands.
Due to budget and time constraints it would be impractical to survey the entire population and a non-probability sampling technique was used to select a sample from the sample frame. Although the probability of each case being selected from the total population is not known, by using non-probability sampling a generalization about the population can still be made. However, not on statistical ground (Saunders et al, 2004). Because of the limited time and budget available as well as for convenience reasons, students in Amsterdam are the best possible sample available and were selected to be the sampling frame for this research. Convenience sampling is prone to bias and influences that are beyond control as the cases appear in the sample only because they are easy to obtain. However, since this research involves consumers and their motivation for buying innovative products it is not expected to differ much in relation to education and age. To improve the reliability of the research and to be able to generalize the results, a sample size as large as possible was aimed for because samples of larger absolute size are more likely to be representative of the population from which they are drawn. To further increase the generalizability of the result and nullify any bias as a result of a too specific sample, friends and family as well as both direct and indirect colleagues who are not in the initial sampling frame were requested to participate in the research. The final sample was selected from the sampling frame by using a self-selection method.
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5.4
Collection
Because the sample consists of as many respondents as possible, the survey method chosen was a self-administered questionnaire published and spread via Internet. This type of questionnaire and method of distribution was chosen for several reasons. The use of a self-administered questionnaire allowed each respondent to read and answer the same set of questions in a predetermined order without an interviewer being present. The questions could be completed most quickly without the interference of an interviewer, since all of them required scaling to answer. Furthermore, self-administration saved a lot of time and it guaranteed anonymity. This reduced the subject or participant bias and therefore improved the reliability of the data (Saunders et al., 2007, p. 359). The Internet was used to distribute the questionnaire because of the opportunity to reach a lot of potential respondents, in contrary to a postal or telephone questionnaire. Although a delivery and collection questionnaire has a higher response rate than any other kind of self-administered questionnaire, much fewer people can be reached. Other advantages of using the Internet to spread the questionnaire included that the costs involved were low, it was efficient and no data entry was required.
Internet-mediated questionnaires are administered in one of two ways: via email or via a website. The first of these uses email to post and receive questionnaires in a more personal way and is dependent on having a list of addresses. Although it might have been possible to retrieve many potential respondents their email addresses either via the directory of the universities in Amsterdam or by searching on the Internet, it is not recommended to obtain them this way because of privacy concerns (Saunders et al, 2007). Therefore, potential respondents were invited to access a website to fill in an online questionnaire using Qualtrics, a renowned online survey software provider. Adopting this web-based approach meant that respondents can remain anonymous. Using this survey tool allowed to explain the purpose of the research and how to complete the questionnaire in advance, taking the place of the cover letter. A direct link
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from the website containing the questionnaire was advertised widely using a range of social media likely to be looked at by the target sample. By these means a total of approximately 1000 unique students from the Faculty of Economics and Business of the University of Amsterdam were reached. When the respondent completed the questionnaire, the data file was generated and saved automatically and Qualtrics averted multiple responses from one respondent. Next to social media groups containing a lot of impending participants, friends, family, and colleagues were contacted by email to personally request them to fill in the questionnaire. All recipients were emailed one week after the initial email thanking early respondents and reminding others to respond. The email was reworded to emphasize further the importance of completing the questionnaire. However, response rates from such an approach are likely to be very low, and there are considerable problems of non-response bias as the respondent has to take extra steps to locate and complete the questionnaire (Coomber, 1997).
Hence, and in reaction to the research on response rates of web surveys by Fan and Yan (2010), several techniques were used to increase the response rate. The survey’s layout was designed to be attractive to make the questionnaire easy to process for participants. A short introduction which explained the purpose of the research and thanked the participant in advance preceded the actual questionnaire. It also stated an instruction to fill in the questionnaire and that the responses are processed strictly anonymous and confidential. Because of the high variety of nationalities studying in Amsterdam, the questionnaire was written in both English and Dutch. This allowed domestic and foreign students to participate in the survey by giving them the opportunity to select their preferred language at the start of the questionnaire. However, translating questionnaires and measures into another language requires a lot of care when the translated questionnaire is to be decoded and answered by participants in the way intended (Saunders et al., 2007, p.375). To increase the validity and decrease the change on translation bias, the translated measures were presented to two independent relatives who were
