EVALUATING THE IMPACTS OF SOCIAL MEDIA USAGE ON MOTIVATED CONSUMER INNOVATIVENESS ABSTRACT

This study was conducted to investigate the effects of social media usage on motivated consumer innovativeness. For the related purpose, the Onikişubat district of Kahramanmaraş province of Turkey was chosen as the research universe. A field study was carried out on a sample selected by the convenience sampling method. An electronic questionnaire was filled by individuals who lives in the specified place. Statistical analyzes were carried out and interpreted on the data obtained from the 520 available questionnaires. According to one of the results, the social media usage rates, frequencies and competencies of the participants positively affect their motivated consumer innovativeness levels. In addition, it has been determined that the perceptions of the mentioned variables positively affect socially motivated consumer innovativeness levels. However, unlike other social media variables, social media usage competencies of individuals affect functionally motivated consumer innovativeness in a significant and positive way.


INTRODUCTION
Along with changing life conditions, people's lifestyles and consumption behaviors are also affected. In this context, innovation is considered as one strategic driver towards the consumption of products of services (Pauwels et al., 2018). However, despite the development of product-related technologies (design, method, marketing, etc.), new products or services of organizations may not find a positive response in the market (Srinivasan et al., 2009). Therefore, consumer and innovation-oriented studies attract the attention of many researchers and practitioners (Hauser et al., 2006). In the literature, it is observed that the adoption and diffusion of innovations are generally emphasized (Greenhalgh et al., 2004;Rogers, 2010;Wejnert, 2002). However, there is a limited number of studies that focus on consumer needs and innovations together.
Within this direction, we investigated the relationship between social media usage and consumer innovativeness in this study. Firstly, a detailed literature review and theoretical investigation were conducted to evaluate the relationship between the variables. Then, the instruments to be used in the field study were selected. The necessary data were obtained by using these tools from the individuals who live in the Onikişubat district of Kahramanmaraş province in Turkey. The findings obtained as a result of the analysis of the relevant data were evaluated and interpreted.

THEORETICAL FRAMEWORK
In this part of the research, we provide general theoretical information on study variables. We explain what kind of conceptual framework the relevant variables have in the literature and how the information about these variables progresses.

Social Media Usage
The reasons such as the widespread use of the internet, the emergence of user-friendly browsers, and the fact that individuals and organizations are more active in the online environment have increased the importance of the social network. Therefore, the concept of social media stands out, which includes people who create online content and interact with other people in developing social networks (McConnell & Huba, 2007).
According to the marketing framework, social media refers to a network where consumers obtain information about their purchases and follow innovations in products and services (Kaplan & Haenlein, 2010). In social media platforms, users can create content (Boyd & Ellison, 2007) and communicate with other users (Bauman & Lucy, 2020) through internet-based applications.
However, under the name of social media platform, there are many dimensions such as networking sites, blogs, discussion forums, content sharing sites (Hansen et al., 2010). Regarding this complexity, Charlesworth (2014) states that five types of websites constitute social media. These websites could be focusing on the news (Reddit, Digg, etc.), bookmarking (Delicious, StumbleUpon, etc.), networking (Facebook, LinkedIn, etc.), knowledge (Yahoo Answers, Wikipedia, etc.), and sharing (Instagram, YouTube, etc.).
Social Media Usage (SMU) rates of individuals may vary according to variables such as their demographic characteristics and social environments (Bauman & Lucy, 2020). In this context, social media usage has attracted the attention of researchers and various scales have been developed on the relevant subject.
As one of these studies, Deniz and Tutgun-Ünal (2019) developed a scale for the SMU variable that includes two factors. These dimensions are Social Media Usage Competence (SMUC) and the Social Media Usage Frequency (SMUF). SMUC focuses on the user's ability to use social media applications effectively. On the other hand, SMUF concentrates upon how often individuals use social media platforms.

Consumer Innovativeness
Consumer innovativeness is generally seen as a personality trait that reflects the desire to change (Hurt et al., 1977). Innovative consumers are an important market segment for marketers. It is known that the income from new products adopted by innovative consumers plays an important role for many companies (Cowart et al., 2008). Therefore, the successful launch and marketing of new products to innovative consumers are critical for firms. Within this direction, a good understanding of innovative consumers' decision-making styles is a necessity for marketing research activities.
Consumer innovativeness has been historically discussed in the marketing and innovation literature since the 1970s. Since these years, it has been seen that there have been reviews and discussions on the behavior of consumers to adopt new products (Pan et al., 2021). In addition, there is no generally accepted definition in the academic community about consumer innovativeness. Some researchers approach the subject as the earliest degree of adoption of new ideas within the social system (Rogers & Shoemaker, 1971), the tendency to buy new products (G. R. Foxall et al., 1998), an inner desire that brings out creativity (Hirschman, 1980), a generalized unobservable trend towards innovations (Midgley & Dowling, 1993), the inclination to buy new and different products or brands (Steenkamp et al., 1999) or the aptitude to willingly embrace change and try new things (Cotte & Wood, 2004).
As we can see from the related literature, the consumer innovativeness concept includes the aptitude to embrace innovations (Tellis et al., 2009), the inclination to buy new products more often and faster than other people (Deniz & Erciş, 2016;Midgley & Dowling, 1978;Roehrich, 2004), an inner desire towards creativity (Hirschman, 1980) or change (Cotte & Wood, 2004). Within this context, the concept has been handled and examined in different dimensions by researchers (Akdoğan & Karaarslan, 2013).
Innate innovativeness is considered a personality trait (Pan et al., 2021). It is thought that consumers' willingness to follow and accept new products and new things is due to their personality features (Midgley & Dowling, 1978). In this context, unlike previous choices or consumer patterns, their tendency to try new products and brands is discussed (Steenkamp et al., 1999).
However, there are some factors that affect innate innovativeness (Pan et al., 2021) Innovativeness levels of individuals vary depending on their demographic characteristics or social environment. In this context, consumers can approach innovation from an emotional or cognitive perspective (Zuckerman, 1979). Consumers with cognitive innovativeness are motivated to stimulate the mind by seeking new experiences or making decisions (Hirschman, 1984). On the other hand, users with emotional innovativeness prefer new experiences that stimulate the senses (Venkatraman & MacInnis, 1985).
Unlike innate innovativeness, special fields innovativeness states that the tendency of individuals to adopt new products varies according to product categories (Pan et al., 2021). For instance, a consumer with more innovative perceptions in the field of electronic products may show less interest in other product categories. Within this direction, researchers (Citrin et al., 2000;Clark & Goldsmith, 2006;Flynn & Goldsmith, 1993; state that perception towards special fields innovativeness changes according to product knowledge, brand attitude, purchase intention and related product use variables. On the other hand, actualized innovativeness refers to the degree to which consumers seek attention and purchase new products (G. R. Foxall, 1988). There are dimensions such as the purchase of new products, the number of new products owned, the use of new products and the realization of innovation demand under actualized innovativeness (Cotte & Wood, 2004). In this context, consumers can discover and adopt new products or obtain information by using advertising (Steenkamp & Baumgartner, 1992).
Despite the fact that product-related approaches are common, the subject of product types and services that individuals have not experienced before is also discussed in the literature. One of the important examples of classifications in the literature was carried out by Vandecasteele and Geuens (2010). Motivated Consumer Innovativeness (MCI) focuses on different goals, values and motivations towards consumer innovativeness. According to this classification, there are four dimensions: cognitive, functional, hedonic and social.
Cognitive Motivated Consumer Innovativeness (CMCI) is related to the need for mental stimulation. CMCI refers to reaching cognitive goals such as intellectual creativity in line with epistemic value according to intrinsic motivations (Venkatraman & Price, 1990). In this dimension, individuals seek ways to widen their cognitive limits by choosing the right consumption innovation (Vandecasteele & Geuens, 2010).
Conversely, Hedonic Motivated Consumer Innovativeness (HMCI) is related to affective stimulation (Venkatraman & MacInnis, 1985). HMCI focuses on the exploratory acquisition of products towards emotional value, hedonism and stimulation. The fact that individuals are happy and satisfied by adopting the right consumption innovation is handled under this dimension (Baumgartner & Steenkamp, 1996).
In contrast to HMCI, Social Motivated Consumer Innovativeness (SMCI) is related to social innovativeness (Roehrich, 2004). SMCI states that reaching social relationship goals such as selfdetermination in line with social values is possible with selecting the suitable consumption innovation (Vandecasteele & Geuens, 2010).
Lastly, Functional Motivated Consumer Innovativeness (FMCI) focuses on the functionality of motivated consumer innovativeness. Under this dimension, aims such as increasing performance and being better organized are evaluated (Venkatraman & Price, 1990). In other words, motivations towards consumer innovativeness such as comfort, quality and reliability are critical under the FMCI factor (Vandecasteele & Geuens, 2010).
In the literature, consumer innovativeness is discussed with different variables. For example, Limayem et al. (2000) state that innate innovativeness has a positive effect on online shopping intentions. Similarly, Jin and Suh (2005) evaluate that innovativeness has a positive effect on purchase intention. On the other hand, Okazaki (2007) states that innovativeness directly affects the intention to use wireless services.
Many researchers recognize the importance of different motivations or sources of innovativeness (Daghfous et al., 1999). However, there is a limited number of field studies in the area of motivating consumer innovativeness (Percy & Rossiter, 1997).
As one of these studies, Shin et al. (2020) stand out. In this research, they investigated the effect of consumer characteristics like consumer innovativeness on social media usage in Korea. By using the panel data, they estimated social media usage. According to their findings, users with HMCI are likely to use social media. But users with FMCI are not likely to use social media platforms.
Additionally, Aldahdouh et al. (2020) did research on the relationship between social media usage and individual innovativeness. They found out that there is a positive relationship between actualized innovativeness and using non-academic social media networks.
Within this context, the hypotheses that were formed in accordance with the literature information are given below.

EMPIRICAL STUDY
This study aims to investigate the impacts of social media usage on consumer innovativeness. To do that, firstly, the methods of previous studies were examined. Accordingly, it was determined that the majority of them used the survey method. In this direction, it was decided to conduct survey research by selecting the appropriate instruments and using the survey and data collection method.
Thus, the related scales were adopted from former studies and a questionnaire was formed. This questionnaire contains three parts. A 5-point Likert rating was used for the scales under the first two sections. In the last section, demographic questions are included.
In  In order to determine the understandability and validity of the questionnaire, a preliminary study was conducted on 60 people. Also, a questionnaire was sent to three expert researchers from the relevant field, and they were asked to examine it. In line with the evaluations from these two processes, the problematic or incomprehensible parts were corrected.
The study's universe contains the individuals who live in the Onikişubat district of Kahramanmaraş province in Turkey and are registered in the Address Based Population Registration System (ADNKS). As of 2020, Onikişubat's population consists of 441,681 people (TUİK, 2020). İnce et al. (2019) recommend choosing a sample in cases where the research universe is very large. Within this direction, the appropriate sample size needs to be higher than 384 people (Baştürk & Taştepe, 2013). An online survey was constituted and delivered through social media channels. The data collection process was based on voluntary participation. However, participation was encouraged on social media (Eren, 2016). The convenience sampling method was used, and sample adequacy was ensured with the data obtained from 594 individuals. On the other hand, 74 observations that were missing, incorrect, or did not comply with the Mahalanobis limit value criteria were removed (Esen & Timor, 2019). Analyzes were carried out on 520 available observations.
Descriptive Statistics Analysis was conducted to examine the demographic profiles of the participants. The answers to the open-ended questions about the age of the participants were grouped according to the results of the analysis. The findings are shown in Table 1. With the Kolmogorov -Smirnov Test, it was determined that the data were normally distributed. Homogeneous responses were obtained from the sample. Then, the reliability values of the research variables and sub-dimensions were examined. The results are given in Table 2. According to Table 2, the reliability statistics (α) of all dimensions are above 0.70. As Kalaycı (2008) stated, this indicates that the reliability of the data belonging to the dimensions is appropriate. Then, a Multiple Correlation Analysis was performed to re-evaluate the relationships between dimensions. The results obtained are given in Table 3. As can be seen from Table 3, there are significant relationships between some dimensions. Overall, there are positive correlations between MCI and all social media-related variables (SMU, SMUC and SMUF). Similarly, CMCI and SMCI have significant positive correlations with social media-related variables. However, this significance is not valid for the relationship between HMCI and SMUC. On the other hand, correlations with FMCI include unusual results. FMCI has negative relationships with SMU (r= -.357; p< .05) and SMUF (r= -.332; p< .01), but a positive relationship with SMUC (r= .165; p< .05).
Multiple Linear Regression Analysis was used to determine the extent of the observed effects. Dimensions were selected according to the hypotheses of the research, and their effects on each other were analyzed. The relevant results are given in Table 4. The results of Multiple Linear Regression Analysis vary widely as can be seen in Table 4. In addition, R2 levels of regressions appear to be quite low in general. However, Model 1, Model 3, Model 5, Model 6, Model 8 and Model 10 are significant. These statements are proven by p statistics.
Surprisingly, SMUF has no significant effect (sig. > .05) on MCI. Conversely, SMUF has a significant and positive effect (β= .223; sig. < .05) on SMCI. But SMUF has a significant and negative effect on FMCI. When there is an increase of 100 in SMUF of participants, their FMCI decreases by 19.3.

CONCLUSION and DISCUSSION
There are a limited number of studies in the literature that deal with the variables of consumer innovativeness and social media usage together. Based on this insufficiency, the findings of the studies in the literature were evaluated. After the investigation and creation of a theoretical framework, it was decided to conduct a field study.
In the field study, the questionnaire technique was chosen as the data collection method and the scales to be used were determined. The data obtained from 520 participants living in the Onikişubat district of Kahramanmaraş province were evaluated with various statistical methods. It was observed that some of the findings are similar to other studies in the literature, while some of them differentiate.
As one of the main results of the study, the social media usage levels of the participants are positively related to motivated consumer innovativeness. SMUs of the participants positively affect their MCIs and SMCIs. The high rate of social media usage of the participants indicates that the level of following the innovations for consumption will be better. These findings are similar to Shin et al. (2020).
However, there is no significant effect of SMUs of the participants on their CMCIs, FMCIs, and HMCIs. Besides, these results are similar to the effects of social media usage frequencies of the participants on related variables. This one is considered as an expected result that people's social media usage rates have a positive effect on improving their social relations and acting in accordance with social values.
Conversely, an additional result emerges in the effects of social media usage competencies of the participants. SMUCs of the participants affect functionally motivated consumer innovativeness of theirs positively. It is interpreted that people who can use social media applications and tools effectively evaluate the usefulness of innovations in general. Eventually, this result agrees with the relevant literature.
In summary, following a positive attitude towards social media usage of individuals increase their consumer innovativeness. For this reason, it is recommended to make new policies and practices that will enable people to use social media at appropriate duration and purposes in societies and organizations. Therefore, it is necessary to explain to people the importance of using social media correctly and effectively, also the benefits and harms of using social media. Within this direction, it is thought that individuals will be more knowledgeable consumers and more moderate towards the changes brought by innovations.
The limitations of the research are that the convenience sampling method is used, and the research is conducted only in one place. We recommend conducting a larger sample field research and using multidisciplinary methods for researchers of the relevant field.