“Impact of consumer innovativeness on risk and new product adoption: a moderating role of Indonesia’s demographic factors”

Consumer innovativeness is an important driver of economic progress and a country’s position in global competition. This study aims to examine the moderating effect of demographic factors of Indonesian consumers on the impact of consumer innovative- ness on perceived risk and new product adoption. The type of research chosen is a causal comparative study by using online and offline survey methods. Data were ob- tained from a sample of 1,000 consumers from 31 provinces. The results showed that the demographic variable became a moderating variable for the impact of consumer innovativeness on new product adoption, but did not play a role in the influence of consumer innovativeness on credit-purchase risk perception. With regard to the influ- ence of consumer innovativeness on credit-purchase risk perception, only social class has a significant effect as a moderating variable. As for the effect of consumer innova- tiveness on a new product adoption, the variables of marital status, occupation, income, and social class have significant effects. The social class variable consistently becomes a moderating one in both equations. The results of this study are useful for marketers to focus more specifically on their target markets, especially on the diffusion of new product innovations based on demographic characteristics. class variable acts as a moderating variable for the effect of consumer innovativeness on the perception of credit-purchase risk. The next test results show that the demographic variables that have a significant direct effect on new product adoption before moderating interactions are age, education, ethnicity, and social class. After the interaction, the variables of marital status, occupation, income, and social class have a significant effect.


INTRODUCTION
Development of the global market and rapid application of technology encourage marketers to continue to innovate and pay more attention to consumer linkages with new product acceptance (Jain & Dalal, 2015). Companies need to understand how the diffusion of new product innovations can successfully penetrate specific population segments (Hussain et al., 2014).
Recent studies tend to link consumer innovativeness with demographic factors (Dobre et al., 2009). The impact of demographic factors on consumer innovativeness, especially risk and new product adoption, has been debated (Bartels & Reinders, 2011). Demographic variables and attitude toward technology complement each other as predictors of the intention to embrace and use technology-based products and services (Rojas-Méndez & Parasuraman, 2015).
Demographic factors are considered to be the causes of this diversity. In several studies, demographic factors are directly associated with saving behavior and credit constraints (Blanc et al., 2015), credit card objects In Indonesia, consumers can choose to buy consumer products for cash or on credit. Some examples of products commonly purchased on credit include investment products and even other consumer goods. SOFIA (Survey on Financial Inclusion and Access) research in 2017 showed that more than 60% of respondents borrowed money and/or are currently having loans in the last 12 months, with 71% borrowed from outside the financial system. The consumer credit market in Indonesia tripled by 1,115,092 billion rupiah in the last 10 years, from 2010-2020 (Global Economy, 2020). Financial risk is an important factor that affects perceived risk (Putritama, 2019), and Indonesian consumers who are interested in buying products on credit have a risk taker characteristic (Adiyanto et al., 2017). However, not many link the Indonesian consumer credit market with the adoption of new products and consumer innovativeness.
Several Indonesia researchers examined the impact of demographic factors on the risk tolerance in the context of investor decisions as stated by Nosita et al. (2020), and Leon and Angie (2019). In addition, Firmansyah (2016) has shown that consumer innovativeness and financial risk tolerance significantly influence consumer's intention to adopt a payment card. However, they did not examine the effect of consumer innovativeness on perception on credit-purchase risk and new product adoption and did not relate it to the role of demographic factors. Here it is important to examine the relationship between consumer innovativeness and perceived risk of credit purchase because the willingness to take risks is a characteristic of consumer innovativeness.
It is important for companies to rely on the success of new product diffusion and survival in a fiercely competitive environment (Jain & Dalal, 2015). For business people, it is very important to know how consumers have innovative behavior; knowing about innovations, accepting an innovation, buying innovations, and finding new areas of use for a product are the different levels of innovative behavior (Karaarslan & Akdoğan, 2015). Innovators have an influence on the success and failure of new products related to the diffusion level of their innovation (Dobre et al., 2009).

LITERATURE REVIEW AND HYPOTHESES
Consumer innovativeness is a personal characteristic as reflected in human behavior (Dobre et al., 2009). The definition of consumer innovativeness among researchers leads to a predisposition of consumers to new products, earlier than other consumers. Midgley and Dowling (1978) believe that the level of acceptance toward innovativeness is the way individuals take new viewpoints and make innovative decisions without referring to other people's experience.
Consumer innovativeness is behavior that is present from birth and is constant (Hynes & Lo, 2006). Roehrich (2004) (Filová, 2015). These explanations show that consumer innovativeness is a behavior and is reflected in consumer behavior.

Consumer innovativenessrisk perception of credit purchase
In some situations, retailers offer products that can be purchased on credit. To encourage transactions, the seller creates a marketing strategy in the form of installment credit (Holmes & Shore, 1982). Decision making carries the effects of risk. Thus, the risk perception of credit purchase is actually a risk that consumers realize in relation to credit purchases. However, consumers want to manage these risks (Koparal & Çalık, 2014) because they cannot foresee the impact of these decisions (Goyal, 2008).
Perceived risk in purchasing decisions is defined as uncertainty in decision making and the consequences of these decisions. Perceived risk refers to the degree of risk that consumers perceive and their own tolerance for risk taking, which are factors that influence their purchase strategies (Goyal, 2008). Maciejewski (2011) states that consumer risk is a possible consequence of decision making and this is an important aspect in the level of consumer perception.
Many aspects of consumers' budget limitations are related to consumer preferences for high-risk products and high-risk loans (Jorgensen, 2011). In particular, financial risk in purchasing on credit shows the probability of financial loss that consumers must manage (Okeke, 2013). The higher the level of perceived risk, the weaker the desire to use or choose credit purchase decisions and use credit cards (Chahal et al., 2014).
Consumer innovativeness also correlates to risk-taking behaviors; high-level innovators are also risk takers (Chih, 2018

Consumer innovativenessnew product adoption
Consumer innovativeness is an innate tendency to be attracted to the unique qualities of inherent propensity to desire to adopt innovations (Morton et al., 2016). New product adoption is the process of a mental set of consumers going through, beginning with first becoming aware of the new product's existence and ending with the decision to adopt the product for continued and regular use (Ngirwa, 2014). Consumer adoption behavior itself is influenced by perceived group size moderated by need for assimilation and need for distinctiveness (Timmor & Katz-Navon, 2008

Demographic aspects as a moderating variable
In several studies, consumer innovativeness is related to consumer demographics, but these studies are still debatable. The research aims to examine the moderating effect of demographic factors on the impact of consumer innovativeness on the perceived risk of credit purchase and new product adoption of Indonesian consumers.
Based on these arguments, the hypotheses are: Ha1: Consumer innovativeness affects risk perception of credit purchase.
Ha2: Consumer innovativeness affects new product adoption.
Ha3: Demographic variables (gender, age, marital status, the role in the family, income, level of education, types of work, social class, and ethnicity) affect the influence of consumer innovativeness on risk perception of credit purchase.
Ha4: Demographic variables (gender, age, marital status, the role in the family, income, level of education, types of work, social class, and ethnicity) affect the influence of consumer innovativeness on new product adoption.

METHOD
The type of research used in this study is a survey to look for causal relationships between variables. The variables in this study were consumer innovativeness, perceived risk of credit purchase, and new product adoption. Indicators of the three variables are developed by researchers themselves because indicator measurement of the three variables has many versions and lacks consensus (

RESULTS
Before the analysis, the data was transformed into centered data on the independent and moderating variables to equalize the scale between the variables. Classical assumption tests were then conducted, namely the normality, multicollinearity, and heteroscedasticity tests. The autocorrelation test was not carried out because the data used were time series. All the prerequisites for the assumption of the normality test, multicollinearity, and heteroscedasticity are fulfilled.
Validity and reliability tests were carried out to ensure that the instruments used are valid and reliable. The validity test of the instrument was the Spearman Brown Correlation, which correlates the items with the total per variable. Validity and reliability tests show that all items are significant at the level of α = 0.05. The Alpha Cronbach reliability test showed that all items were reliable at α = 0.05 level.  Based on the results of the three equations (before and after the moderating variable interaction), consumer innovativeness has a significant effect on perceived risk of credit purchase. Thus, hypothesis Ha1 is accepted. Based on the results of the Fit model, it is known that before the interaction (1a), after adding the demographic variables (1b), and after the demographic variables interact with consumer innovativeness as a moderating variable (1c), the existence of demographic variables slightly increases the values of R, R2 and F. It can be said that the demographic variable is a slightly moderating variable for the effect of consumer innovativeness on perceived risk of credit purchase. Thus, hypothesis Ha3 is not accepted. Based on the partial test results, the variables that have a significant direct effect are consumer innovativeness, gender, occupation, education, ethnicity, and social class. After the demographic variable is included as a moderating variable, only the social class variable has a significant effect.

DISCUSSION
Based on the initial test results, it can be explained that the variables that directly and significantly affect the influence of consumer innovativeness on perceived risk of credit purchase are consumer innovativeness, gender, occupation, education, ethnicity, and social class. Consumer innovativeness has a positive and significant direct effect, so this means that the higher the consumer innovativeness level, the higher the perception on credit-purchase risk. This result is in line with Dobre et al. Furthermore, of the consumer innovativeness, gender, occupation, education, ethnicity, and social class variables that directly affect perceived risk in credit-purchase, only gender has a negative and significant effect. This means that male consumers have a higher perception on credit-purchase risk than women. These results are in line with Chavali and Mohanraj (2016), although on a different object, which is investment. Kiarie et al. (2013) state that women are more risk averse. Frank et al. (2015) state that male consumers tend to have more innate willingness to pay for innovation compared to female consumers.
Besides, the marital status variable plays a negative and significant moderating role; and the 'unmarried' status has a greater influence on the effect of consumer innovativeness on the new product adoption. In Savas (2017) and Morton et al. (2016), marital status is not a variable that influences new product adoption and there is no difference in innovation based on marital status.
The three components of social class show interesting results. The occupation variable becomes a moderating variable that significantly affects the influence of consumer innovativeness on the new product adoption. This means that non-managerial work affects the influence of consumer innovativeness on the new product adoption. The education variable has a positive and significant direct effect on new product adoption, but it is not significant as a moderating variable. This means that the lower the education, the higher the preference for new product adoption. Rojas-Méndez and Parasuraman (2015) stated that less educated people prefer the adoption of new products more because of the company's interpersonal way of communication. The income variable becomes a moderating variable, which is positive and significant. This means that the lower the income, the higher the influence of consumer innovativeness on the new product adoption. Savas (2017) shows the same thing, while Lee and Son's (2017) research shows that income is not related to consumer innovativeness.
Parker and Sarvary (1996) and Tellis et al. (2009) also state that differences in nationality and cultural differences will lead to varying levels of consumer innovativeness. In this study, the differenc-es between the Javanese and non-Javanese have a positive and significant direct effect on new product adoption. The non-Javanese tend to have a more level of new product adoption. However, the difference in ethnicity is not important as a moderating variable.
In general, the results of this study indicate that the demographic variable becomes a moderating variable of the effect of consumer innovativeness on new product adoption, but does not play a role  (2015), which state that innovation is more inclined towards individuals who adopt new products earlier.
Academics and practitioners have paid a lot of attention to consumers' adoption of new products (Kim, 2008). In practical terms, this research implies that identifying innovators is essential for proper segmentation and market analysis to make it more competitive in the market (Hussain et al., 2014). For example, there is a large gap between millennial and non-millennial generations of Indonesia related to consumer innovativeness in adopting new products due to perceived risk aspects. Currently in Indonesia, the millennial market is the locomotive of the market, and female consumers are the first locomotive for technology-affiliated products (IPSOS Flair Collection, 2019). Tellis et al. (2009) stated that the relationship between demographics and consumer innovativeness can help marketers focus more on their target market.
Apart from individual consumer reasons, company success is also determined by consumer response to products, which is motivated by con-sumer adoption (Tomaseti et al., 2004). Racela (2015) states that consumer decision making will become increasingly complex when consumers are faced with innovative products. Marketers need to implement the right strategy based on the product life cycle that is on target in the innovator segment, offering discounts to early adopters at product launch, adequate information, and quality products (Al-Jundi et al., 2019).
Research on consumer innovativeness and new product adoption has several implications for further studies. One of the emerging topics is the differences between individuals and categorization of people's responses to new things (Absari & Joudaki, 2018) and psychographic (Savas, 2017). Dobre et al. (2009) suggest that consumer innovativeness research can be linked to the product life cycle at the introduction and innovation levels.
Consumer innovativeness also needs to be linked to differences in culture and nationality, for example with Hofstede's nationality (Jain & Dalal, 2015).
To expand research in Indonesia, consumer innovativeness can be explored more deeply in various ethnic groups in Indonesia in order to describe the diversity of characteristics of Indonesian consumers. The difference between the three variables with many ethnicities requires further study.
This study has several limitations. Indonesia is a very large and heterogeneous multicultural country. The study portrays only consumers in general and to a lesser extent reflects the demographic aspects of all consumers from hundreds of ethnic groups and regions in Indonesia, not just Javanese versus non-Javanese. This research is also part of a large multi-year study related to social class segmentation, culture, and consumer decision making style, so the focus on variables needs to be further explored. Future research, especially in Indonesia, is suggested to fill the limitations of this research.

CONCLUSION
Innovative consumers become companies' capital valuable for introducing new products, as they can spread innovation (Cowart et al., 2007;Figueroa & De Meneses, 2013). When testing the direct effect, consumer innovativeness, occupation, education, ethnicity, and social class have a positive and significant effect, while gender has a negative effect on perception on credit-purchase risk. Among all these variables, only the social class variable acts as a moderating variable for the effect of consumer innovativeness on the perception of credit-purchase risk. The next test results show that the demographic variables that have a significant direct effect on new product adoption before moderating interactions are age, education, ethnicity, and social class. After the interaction, the variables of marital status, occupation, income, and social class have a significant effect.
In general, the results of this study indicate that the demographic variable becomes a moderating variable in relation to the effect of consumer innovativeness on new product adoption compared to the perception of credit-purchase risk. These are new findings for consumer studies in which demographic differences contribute to the level of innovativeness of Indonesian consumers. This leads to a willingness to adopt new products compared to perceived risk. This is the basis that the diffusion of new product innovations has great potential.
Based on testing the moderating role, only the social class variable has a significant effect, as a moderating variable, on the influence of consumer innovativeness on perception of credit-purchase risk and new product adoption. Differences in social class of consumers and their components, namely education, income, and work, should be of concern to marketers, as it relates to the characteristics of consumer innovativeness, adoption of new products and risks.  Note: ** significant at α = 0.05; * significant at α = 0.10.