Youth Social Networking Service (SNS) Behavior in Indonesian Culinary Activity

Abstract

Purpose: In this paper, we provide an illustration of Indonesian youth Social Networking Service (SNS) behavior and its relation to their culinary activity. Specifically, their behavior of culinary activity preferences and also the factors affecting their action of spending their money. Data and methodology: We gathered primary data from stratified random questionnaire survey (406 youth). The gathered data was analyzed using text data mining and statistics using R statistical computing language. Results: 1) We found out why our respondents are interested in following the accounts of SNS food influencers: i.e. visually attracted to the posts, as their reference to find places to dine out, as their reference to try new food menu and to get nostalgic feeling about the food. 2) The respondents decide to actually go to the recommended culinary places because of several factors, specifically, its description (visual and text), location, word of mouth (WoM), the experience of being to that place and price. 3) Important factors affecting culinary spent are income, number of following food influencer account, SNS usage time and their interest when looking at WoM. Conclusions: SNS behavior influences Indonesian youth culinary activity preferences and spent.

1. Introduction

Culinary activity is a big part of Indonesian culture. Culinary activity in Indonesia has become an important culture in which imperative records can be traced since several centuries ago. China, India and European countries, especially Netherland, had important roles in Indonesian culinary activity (Rahman, 2011). Those countries influenced the culinary activity to be evolving from the beginning of the 16th century to the middle of the 20th century. Even today, culinary activity is still evolving from time to time (Febriani, 2015; Pamungkas, 2016).

Culinary itself is generally defined as related to food, from the preparation, cooking, presentation of food and dining activity. In Indonesia, the term culinary firstly started to gain people‘s attention since 2005, specifically when a TV show called ―culinary tour‖ aired (Lazuardi & Triady, 2015). The TV show covered unique eating places and also places which were popular to local Indonesians. The same source also reported that since then, the word culinary has become increasingly popular in Indonesia and has transformed into something synonymous with the activity of tasting various types of food and drinks.

According to Febriani (2015) and Pamungkas (2016) even though Indonesian culinary is said as having a great potential for national economy, it has never been paid enough attention until very recently. In the end of 2012 Indonesia‘s Ministry of Culture and Tourism was restructured into Ministry of Tourism and Creative Economy and during the restructure, culinary finally made its way under the ―special interest tourism‖ strategy. The working group‘s main task was to inventory Indonesian unique cuisines that represent regions in Indonesia as well as to develop its promotional strategy. One result that came out of the working group is that for the first time, the government officially introduced ―the 30 culinary icons of Indonesia‖ in 2013 (Lazuardi & Triady, 2015; Serenami & Palit, 2017).

On the other hand, as the ICT (information and communication technology) evolve, it has been causing radical changes in the markets around the world. Almost everything is digitalized including economy where electronic commerce (e-commerce) takes place (Foster et.al., 2010). The same source also reported that almost two-thirds of marketers and agency managers believe that strong customer relationships can be established through the strategic use of Internet technology. Moreover, the motivation for this shift is the increasing penetration of the Internet into households across the globe.

Since the introduction of SNS (social networking service) in the late 1990s, millions of people have become active users who have integrated these services into their daily practices (Boyd & Ellison, 2007), especially youth (Greenwood et al., 2016). SNS itself was generally first defined as ―social network site‖, referring to a web-based service that allows users to construct a public or semipublic profile within a bounded system, articulate a list of other users with whom they share a connection and view their list of connections within the system. Yet, according to Zhang & Leung (2015), SNS can nowadays be defined as ―social networking service‖ in a broader sense because SNS is not limited to only web-based platform anymore.

The rise of SNS has not only changed the internet as we know it, but has also dramatically changed the way people communicate, interact and do business (Anderson, 2008; Hung & Li, 2007; Petrescu & Korgaonkar, 2011). SNS has become a crucial tool to increase productivity from a business viewpoint (Park & Kang, 2013). It is because SNS connects people who share interests and activities across geographic borders and have become a social commerce platform for businesses in recent years (Huang et al., 2014). SNS itself can potentially be an effective marketing tool to better serve, attract and retain customers (Gironda & Korgaonkar, 2014) because it has a huge amount of personal information online (Ahmed, 2013).

Since the last couple of years, the enthusiasm of Indonesian SNS users toward culinary activity has grown immensely. As an example, in Instagram, there are numerous accounts that provide culinary information in various cities in Indonesia such as @jktfoodbang of Jakarta, @kulinerbandung of Bandung, @kulinersby of Surabaya, @kulinermedan of Medan, @kulineryogya of Yogyakarta and many more. Beside culinary information in specific cities in Indonesia, there are also many culinary information without city limitation and cover national levels culinary information such as @dietmulaibesok, @laperbaper or @indozonefood. As on November 5th, 2019, each of those accounts has at least 300 thousand people who follow the accounts for culinary information (so-called followers). In SNS world, a popular account with thousands of followers is generally called an influencer (Willers & Schmidt, 2017). In this report, an account that mainly post about culinary information is called a food influencer.

In Indonesia, the youth dominate the use of mobile device, SNS and the internet (Agustina et al., 2019). Moreover, the enthusiasm toward culinary activity in SNS world is very high in Indonesia as there are hundreds of thousand food influencer followers in each different city. The followers of those food influencers are mostly youth (BPS, 2018). The same source also reported that Indonesian youth account for 33% of the entire population. Besides, the youth in Indonesia is reported as consumptive, yet, due their consumptive behavior they are also reported to contribute significantly to the national economy (BPS, 2018; Agustina et al., 2019). Those three elements, youth consumption, SNS and culinary activity, are undeniably very important for Indonesia as those three elements are three of several focuses of the ministry of Ministry of Tourism and Creative Economy of Indonesia since 2013 (Serenami & Palit, 2017, BPS, 2018). Therefore, we would like to clarify the relationship and causality between those three.

Despite the fact that culinary activity has a big potential for the national economy and high enthusiasm of Indonesian SNS users, the study of youth consumer behavior in regards to culinary activity information from SNS is still insufficient and unclear. Several previous studies focused on purchase intention from an SNS accounts of specific restaurant or a specific city (Siswanto & Junaedi, 2017; Syahbani & Widodo, 2017; Handika et al., 2018). However, in the previous several studies, we found only SNS and its relationship with purchase intention not the action of food purchasing. Yet, purchase intention is barely an intention, there is no guarantee they will take action to actually buy the product. There is still unclear study about the action of purchasing itself, what factors make them to actually take action to do culinary activity, what prevent them not to, how much money do they spent, what factors drive them to actually spent the money. Other study focused on an Indonesian city or province promotion that uses influencers‘ service (Nurrahman & Yulianti, 2019). Moreover, we do not find a specific academic report about youth culinary activity and its relation to SNS usage. These issues are particularly important for culinary business owner and Indonesian government, therefore, this study is necessary.

Specifically, the objectives of this study are: (i) to clarify how culinary information from food influencer affects Indonesian youth culinary activity; (ii) to identify what factors trigger youth to be interested in a culinary information and actually go to the informed culinary places including their behavior in the culinary place; and (iii) to investigate the money spent of Indonesian youth during culinary activity. This paper provides an illustration on consumer behavior of Indonesian youth culinary activity (from purchase intention, buying decision process until the money spent) which are driven by SNS usage behavior.

2. Literature Review

2.1. ICT Usage in Indonesia

The ICT development brings a marvelous impact on the way Indonesian people communicate, especially throughout the mobile phones or smartphones. In 2018, the number of mobile phone active users in Indonesia reached 371 million which represents 142% of the total 262 million Indonesia population (Sutarsih et al., 2019). This means some mobile phone users in Indonesia owns an average of 2 or 3 mobile phones. Furthermore, number of smartphone active users in Indonesia has also increased rapidly since the last decade (Sutarsih et al., 2019; Hootsuite, 2018). Number of active users of smartphone in Indonesia were 55 million people in 2015 (Robinson & Sivakumaran, 2018). Yet, based on a survey conducted in last January 2018, active users of smartphone in Indonesia have increased to be 133 million people which represents more than double the amount of users that were reported in 2015 (Hootsuite, 2018). In 2018 Indonesia even became the fourth largest country of smartphone active users after China, India and the United States of America (Sutarsih et al., 2019).

2.2. SNS Usage in Indonesia

In Indonesia, the SNS active users reached almost 60% of the population in 2018 (Hootsuite, 2018; Sutarsih et al., 2019). The same source stated that the highest SNS users in Indonesia are Facebook and Instagram, with 130 million (54% of the population) and 61 million (25% of the population) accounts, respectively. Sutarsih et al. (2019) stated that most of Indonesians access the SNS through mobile devices, using both smartphones or mobile phones which have internet connection. It is because using SNS in mobile device is very convenient, one can check SNS during commuting, break or in other free time.

Indonesian SNS users are mostly dominated by youth (Agustina et al., 2019), ages 15 to 35 (Robinson & Sivakumaran, 2018). Likewise, youth is defined as someone who is between the age of 15 to 35 years old in Indonesia (Agustina et al., 2019). This situation is in line with the previous study by Greenwood et al. (2016) who stated that almost 90% of active SNS users are youth. This kind of situation is unsurprising because youth are more comfortable with online communication than adults (Thayer & Ray, 2006). SNS platforms are also attracting many young users in emerging nations, and the number of SNS users in such countries is increasing rapidly (Boyd, 2007; Bennett et al., 2012).

As stated in the previous chapter, to date, we only found very few academic reports about youth culinary activity and its relation to SNS usage in Indonesia. Several previous studies focused on the purchase intention from an SNS accounts of specific restaurant or a specific city (Siswanto & Junaedi, 2017; Syahbani & Widodo, 2017; Handika et al., 2018). Siswanto and Junaedi (2017) analyzed the relationship between WoM (word of mouth) for branding and for consumer purchase intention of a restaurant called ―Warunk Upnormal‖ in Yogyakarta, a city in middle southern part of Java Island, Indonesia. They investigated the relationship of WoM to branding and purchase intention by simple regression. Yet, the coefficient of determination results for WoM to branding and WoM to purchase intention were only 0.18 and 0.15, respectively. On the other hand, Syahbani and Widodo (2017) reported the use of Instagram as a platform to promote food and its relation with purchase intensity in Bandung, with the respondents of only college students. They reported that there are four factors which influenced purchase intensity, i.e. context, communication, collaboration and connection. From the business‘ side, Handika et al. (2018) evaluated the marketing strategy of a restaurant called ―The Night Market Café & Co-working Space‖ through Instagram in Denpasar, a city in southern part of Bali Island. They reported the merit of conversion from non-digital marketing to digital marketing.

Another study of SNS utilization focused on an Indonesian city promotion that uses influencer‘s service (Nurrahman & Yulianti, 2019). While the influencers on the reports sometimes did promote about culinary places located in the area, culinary was not the main focus of the Instagram posts. Nurrahman & Yulianti (2019) evaluated the influence of posts from an influencer that mainly promote a city called Bengkulu, located in western part of Sumatra Island, to followers‘ travel intention. The research used a simple regression analysis and yet, it showed that the coefficient of determination was only 0.29.

3. Methodology

This study was conducted using primary and secondary data. We collected primary data from stratified random questionnaire survey (Kish, 1965) for youth age 15 to 35, made using google form to target youth in Indonesia. The questionnaire consisted of a demographic part and assessment of consumer behavior toward culinary activity through the information from SNS. We spread the questionnaire out through SNS. As for the number of respondents, we would like to have a margin of error to be no more than ±5% at the 95% confidence level, so the number of samples must be at least 384 respondents (Anderson et al., 2008). Yet, to anticipate invalid sample data, we added an extra 5% of 384 people to be at least 403 respondents. The primary data gathering was conducted from July to October 2018. On the other hand, we gathered secondary data from government or related-organization official reports, books and journals. The data gathered were then analyzed using text data mining and statistics, e.g., frequencies, percentages, mean scores, analysis of variance (ANOVA) as well as its post hoc test and multiple regression analysis. We utilized R statistical computing language to conduct the analysis for this study.

4. Results and Discussion

4.1. Respondents Characteristics

After distributing the questionnaire survey, we gathered valid 421 respondents. However, 15 respondents were cut because of sampling error, mainly the answers far exceed margin of error (Kish, 1965). The respondent demographic characteristics gathered for this study is summarized in Table 1. The respondents represent the four biggest and most populous islands in Indonesia, Java, Sumatra, Borneo, and Celebes. As shown in table 1, the majority of the respondents are student, while their educational backgrounds vary from junior high school to PhD graduates. The respondents‘ monthly income also varies from less than 100 thousand IDR to more than 15 million IDR. The average income of our respondents is 4.1 million IDR. Note that currently, one USD is roughly equal to 15 thousand IDR. According to the latest data in 2016 (BPS, 2018), Indonesian average monthly income was 3.9 million IDR (roughly 260 USD). We conducted t-test in order to determine if there is a statistically significant difference between two groups (Anderson et al., 2008), i.e. income of our respondents and Indonesian national income. The t-value was 0.9245 and p-value was 0.1778. This result indicates that there is no significance difference between respondents‘ income and Indonesian national income. As for monthly culinary activity spent, the respondents spent vary from less than 25 thousand IDR to more than 10 million IDR. We are going to discuss in more detail about culinary spent in chapter 4.4.

Table 1: Respondents demographic characteristics (N = 406)

In terms of SNS usage, Instagram is the most popular SNS for respondents as 92.8% of them are Instagram active users, followed by LINE (77.8%), YouTube (61.2%), Facebook (58.6%), Twitter (41.6%), Google+ (25.2%), LinkedIn (24.8%), Pinterest (16.2%), Path (14%), and others (10.6%). While, the daily use of SNS varies from less than 10 minutes (1.2%), more than 10 to 30 minutes (13.5%), more than 30 minutes to 1 hour (13%), more than 1 to 2 hours (16%), more than 2 to 3 hours (14.2%), more than 3 to 5 hours (20%), more than 5 to 8 hours (13.5) and even more than 8 hours (8.7%). Moreover, 64.5% of the respondents follow 1 to 3 food influencer accounts, 24.6% of them follow 4 to 7, 4.7% of them follow 8 to 10 and 6.2% of them follow more than 10 accounts.

4.2. The Reason of Using SNS to Get Culinary Information

As written above, currently the enthusiasm of Indonesian SNS users toward culinary is very high. Therefore, we would like to examine the reasons behind this phenomenon in order to understand the consumer behavior of the respondents. We asked the respondents why they use SNS to automatically get culinary information after following a food influencer. Specifically, our question was "why do you follow account that provide culinary information?". We provided several possible answers and one free writing option in case the respondents cannot find suitable answers with a checkboxes format, in which the respondents can select multiple answers.

We conducted text data mining to cluster the reason for respondents. For this study we utilized qdap R package library for qualitative data analysis and text data mining (Rinker et al., 2019). Firstly, we extracted frequent terms from the answer we gathered from the respondents. We then conducted keyword clustering as shown in Table 2. We clustered the frequent term toward this issue into four clusters. Firstly, visually attracted which is related with pictures and video. Secondly, the term related to place reference for their activities. Next is the food menu reference word cluster. Lastly, the nostalgic feeling word cluster.

Table 2: Keyword cluster reasons to follow food influencer

Figure 1 shows the reasons for respondents to follow culinary information account in decreasing order of occurrence. 88.7% of the respondents stated that they follow because they are visually attracted to watch video or picture of food. Several of them stated that the visual descriptions of food are satisfying and tempting. This circumstance is expected because sharing picture of food is a popular category to be posted and to be searched in social media (Abbott et al., 2013; Ranteallo & Andilolo, 2016). Next, 77.6% of the respondents use culinary information accounts as their reference to find a places to do their activities while enjoying the food. Particularly, the respondents use SNS to find places to spend time with their closest people, to work or just to kill time. This phenomenon is closely related to the characteristics of many Indonesians, i.e. who like to gather while enjoying food (Mufidah, 2006). Moreover, Indonesians, especially youth recently tend to go to cafés such as coffee shops to hangout, to work or just to kill time (Said, 2017). Then 59.9% of respondents follow culinary information accounts because they use it to get reference for new food to dine out or ideas to cook the food by themselves. Lastly, 21.2% of the respondents stated that by following culinary information accounts, the respondents can watch food videos or look at pictures of food they used to consume when they were younger or in their hometown, especially when the respondents are migrants. Several respondents even said that the nostalgic feeling when watching the videos or pictures is priceless and they are very happy with that kind of feeling.

Figure 1: Reasons to follow food influencers

4.3. Culinary Activity After Obtaining Information from SNS

We then asked about the respondents‘ interest when their following accounts provide new culinary information. Respondents used a five-point Likert scales, 1 defines not interested at all to 5 that defines 'very interested‘, to answer this question. The result showed that 73.6% of the respondents are interested or very interested to get new culinary information (mode = 4, median = 4, IQR = 1). Besides, we also conducted t-test to check the significance of the distance of the average from the mid-point of the Likert scale (Anderson et al., 2008). The t-value was 24.6 and p-value was 2.2×10-16. This result indicates that they tend to be interested when new culinary information is posted by food influencers.

Moving forward, after getting new culinary information we are interested to know how often they actually go to places suggested by the food influencers for culinary activity. Therefore, we also asked their frequency of going to the culinary places that were introduced by food influencers that they follow. 3% of the respondents stated that they go to the places that were introduced every day. 17.5% answered once a week, 15.3% once in two weeks, 31.9% once a month, 16.8% once in three months, 8.6% twice in a year and 6.9% answered once a year.

We also asked the reasons why they decided to go or not to go to the informed culinary places. We provided several possible answers and one free writing option in case the respondents cannot find a suitable answer, in which the respondents can select multiple answers. We then conducted text data mining, with the same manner to the previous section, to cluster the reason for respondents. Figure 2 shows the factor affecting respondents to actually go to the culinary place. We found out that 92% of the respondents decide to actually go to the informed culinary places because of the influencers‘ interesting description, either visual description, both videos and pictures or text description. In other word, Indonesian youth are descriptive oriented consumers. This result supports a study conducted by Resti and Purwanegara (2013) who stated that psychologically, consumers‘ intention to dine out tend to appear after looking at posted food pictures on SNS. Next, 76.8% of the respondents answered the location as one of the factors, specifically the respondents stated that they decided to go to culinary places when the location is strategic and easy to reach. This is an unsurprising phenomenon because location is known as one of the most important factors in marketing sector (Tödtling, 1992).

Figure 2: Factors affecting respondents to actually go to the informed culinary places

The third highest factor is positive word of mouth (WoM) with a percentage of 73.5%. The respondents stated that they can easily find WoM in the comment section of a new post, showing the review of culinary information or recommendation from a friend. WoM is known as an influential factor for culinary activity (Smith et al., 2010; Dougherty & Green, 2011; Kim et al., 2019). WoM is also acknowledged as one of the methods of integrated marketing communication that is not only used to promote and increase products awareness, but also to create customer loyalty (Satria, 2018) to voluntarily review and recommend the culinary place. Then, the next important factor is experience. 65.4% of the respondents said that they have been to the informed culinary places, they do like the places and would like to go to those places again as repeat customers. The last factor is price, specifically, 42.6% of the respondents decided to go to the informed culinary places because of their fair price.

However, after looking at new culinary information, the respondents do not always go to the informed culinary place. For that reason, we also conducted text data mining in order to investigate what factors affecting respondents not to go to the culinary place. Figure 3 shows the factors affecting respondents not to go to the culinary place. We noticed that location is the most important factor which made respondents decided not to go to the informed culinary places, specifically 95.6% of them mentioned about bad location. When the culinary place‘s location is not strategic and not easy to reach, the respondents tend not to go there even though they are interested with the description or they found positive WoM. Continuing on, 73.5% of the respondents stated that they are not going to go to the location of the culinary places when they are not interested with the description, either visual or text description. As we found in the previous result that the respondents are descriptive oriented youth, this situation is unsurprising. Next, 69.6% of respondents answered that they decided not to go because of negative WoM. Because WoM is one of the most important factors for our respondents to go to culinary places, when they find negative WoM such as complaints in the comment section in SNS they avoid to visit the places. Lastly, 45.6% of the respondents answered that they have been to the informed culinary places but did not like them, so they are simply not willing to go back there.

Figure 3: Factors affecting respondents not to go to the informed culinary places

Now we are also interested with whom the respondents usually go to the informed culinary place. For this question, we also provided several possible answers and one free writing option in case the respondents cannot find the suitable answer, in which the respondents can select multiple answers. We then conducted text data mining to cluster the reason for respondents. 76.6% of the respondents tend to go with someone else when visiting culinary activity place. Specifically, 77.8% of the respondents go with friends, 53.2% go with family or relatives, 44.8% go with a partner (spouse or date) and 12.8% go with colleagues from work. While, 23.4% of the respondents answered that they usually go to the informed culinary places alone. It means the respondents tend to invite someone else or more when they want to visit culinary places. And again, it is one of the characteristics of many Indonesians, who like to gather while enjoying food (Mufidah, 2006). An interpretation of the facts indicated that when culinary business owner via food influencer succeeds to convince Indonesian youth to go to their place, the sales would probably be higher because the youth tend to go with someone else.

We also conducted text data mining of types of food that the respondents particularly interested in and decided to go. The most popular category is Indonesian traditional food (88.4%) both at restaurants or street food. This result is in line with a study conducted by Alamsyah (2008) that stated the popularity of Indonesian traditional food has been growing in the last several years. The second most popular food is fast food category with 51% of the respondents answered so. Next is oriental food (49.8%) such as Japanese, Chinese or Korean food. The fourth is western food (42.6%) such as European or American food. The last category is Middle East and African food (12.3%).

4.4. Culinary Spent

4.4.1. Culinary Spent Based on Respondents Groups Characteristics

In order to examine the characteristics of culinary spent, we divided the respondent into several groups based on gender and occupation. Originally the groups are female and male students, female and male worker, housewife and also unemployed male. Yet, after conducting cluster analysis of the respondents‘ characteristics, we found that housewife cluster is similar to the female student cluster while unemployed male cluster is similar to male student cluster. Therefore, we classified housewife as female student and unemployed male as male students, resulting in four groups, i.e. female student (n = 186), working female (n = 98), male student (n = 63) and working male (n = 59). After that, we conducted ANOVA to inspect whether there is any significant difference in those four groups (Anderson et al., 2008). As a result, the p-value was 2.8×10-8 which means that there is a significant difference between those four groups.

However, ANOVA does not show specific differences between groups. Therefore, to inspect how a specific group differs from each other we conducted Tukey-Kramer post-hoc test. The Tukey-Kramer post-hoc test is known as a conservative post hoc test (controls Type I Error rate) and is used when the sample sizes for each level are unequal which is suitable for this case (Anderson et al., 2008). Table 3 shows the summary of the Tukey-Kramer post-hoc test which shows that there are six comparisons between each group. The results show that there are no significant differences between female and male student as well as working female and male group. On the other hand, we can see that significantly different judgements are found during the comparison in regards to occupation, namely, between student and worker.

Table 3: Summary of Tukey-Kramer post-hoc test

The reason for that is obviously the income of the working group is simply higher than student group, hence their purchasing power is also higher. The average income of the students is 1.8 million IDR whereas the workers is 8 million IDR. Meanwhile, culinary spent of students and workers are 0.4 million IDR and 1 million IDR, respectively. We also conducted t-test of worker and student income to confirm whether the income is statistically significant. The p-value is 2.1×10-32 which means it can be confirmed that income of the working group and student group are statistically different.

4.4.2. Factors Affecting Culinary Spent

As stated above, the culinary spent varies from less than 25 thousand IDR to more than 10 million IDR. Therefore, we would like to investigate what factors affect respondents to spend their money. We conducted multiple regression analysis of culinary spent with several variables from the questionnaire. The regression is conducted to examine influential factors of culinary spent of respondents (Anderson et al., 2008). The regression model in this paper is determined in Eq. (1)

\(\mathrm{Y}=\beta_{0}+\sum_{\mathrm{i}=0}^{\mathrm{n}} \beta_{\mathrm{i}} \mathrm{x}_{\mathrm{i}}\)     (1)

Where Y indicates the culinary spent in IDR, 𝑛 is number of independent variables, β₀ is intercept, β_i is i-th estimate coefficient and x_i is i-th independents variable.

The summary result of multiple regression analysis of culinary spent is shown in Table 3. The adjusted multiple R-squared is 0.7409 which means independent variables in this model can explain approximately 74% variability of the response data around its mean. In other word, nine independent variables in Table 4 can explain 74% of the money spent for culinary activity in this study.

Table 4: Summary result of multiple regression analysis of culinary spent

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1;

Residual standard error: 603500 on 396 degrees of freedom; Multiple R-squared: 0.7512, Adjusted R-squared: 0.7409. 32; F-statistic: 53.37 on 9 and 396 DF, p-value:< 2.2e-16.

As shown in Table 4, we used nine different independent variables for multiple regression analysis. The variables for this analysis are income of respondents in IDR; number of following food influencer accounts; daily SNS time usage in hour; distant of the respondents' hometown to the city where they currently live in km; educational background in level, i.e. 1 that indicates an elementary school graduate until 7 that indicates a PhD graduate; age in years; gender as a dummy variable; interest when looking at the new culinary posted by food influencers that they follow in five point likert scale; finaly, interest when looking at the comments in the post as WoM in five point likert scale.

From the result of multiple regression analysis of culinary spent, we can see that there are four most important factors of consumers to spend their money for culinary activity. Specifically, the significance level (α) of income was below 0.001, number of following food influencer account was 0.001, daily SNS usage time was 0.01 and interest when looking at WoM was 0.001. It points out that income was one of the most important factors of culinary spent. It means the higher the income, the probability of the respondents to spend their money for culinary activity is higher as well. Moreover, income factor was also discussed in the previous section as occupation factor was statistically significant for culinary spent. Next, number of following food influencer account and SNS time usage were also dominant factors of culinary spent in this study. The more one follows culinary account and using SNS, the more probability of that person to get more culinary information.

Lastly, youth consumers in Indonesia are most likely to spend more money for culinary activity when they see positive WoM or review in influencers' post.

The results from this study support the previous studies (Kwok & Yu, 2013; Kim et al., 2014; Sukhu et al., 2015) which reported that SNS has become a significant force for decision-making behaviors in our lives, i.e. in shaping consumers' information-sharing and purchase intention. All the more, SNS does not only contribute up to purchase intention, but also beyond that which is the action to purchase, especially in culinary activity area. Particularly, consumers who have higher SNS usage are more likely to spend their money.

5. Concluding Remarks

This paper presents an illustration of SNS on consumer behavior of Indonesian youth culinary activity. The study showed that the respondents are interested in obtaining culinary information from food influencers because they are visually attracted to the pictures or videos of culinary activity, as a reference to find a places to eat, as a reference to try new food menu and the nostalgic feeling they get from the food posts. The respondents decided to actually go to a particular culinary place after getting new information because of its description, location, word of mouth, the experience of being to that place and price. Moreover, income, number of following food influencer accounts, SNS usage time and interest when looking at WoM are important factors in culinary spent. However, it should be evident that we need to develop a model of buying decision process of Indonesian youth toward culinary activity based on SNS usage and marketing strategy for culinary business side in the future study.

We wish to thank Mrs. Raisa Nursaputri and Professor Etty Riani for the help and fruitful discussion about this study.