Factor Analysis of investment intention: Millennials and Gen Z perspective

This study aims to determine what factors influence the investment interest of millennials (Y) and Z generations in North Sumatra. This research was conducted by survey method, and the number of respondents in this study was 280. The results indicate that two main factors determine millennials and generation z in investing intention: first, knowledge, self-motivation, social environment that has investment experience, and initial capital; and second, variables include information, transparency, social media influencers, and financial literacy.


Introduction
Many changes and new habits range from studying, working, and consumer behavior to investing during the pandemic. According to several sources, the number of young investors investing in financial products, particularly stocks in the capital market, has increased significantly during the worldwide pandemic.
The digitization trend during the Covid-19 pandemic has provided a blessing for an increase in the number of investors in the Indonesian capital market. During the pandemic, it can be seen that many investment players have turned to the capital market. One of the reasons behind this condition is the existence of funds that were previously engaged in the real sector; in fact, they did not run effectively during this new average period. This is in line with the Community Restrictions policy to be considered a case of Covid-19, which has caused many business sectors to carry out activities under this policy.
Throughout 2021, the number of investors in the Indonesian capital market recorded the highest growth record in the 44-year history of the Indonesian capital market. Based on data from the Indonesian Central Securities Depository (KSEI), the number of capital market investors has reached 6.43 million investors as of the end of September 2021. This figure recorded an increase compared to the position at the end of 2020 of 6.10 million. Based on KSEI data as of September 30, 2021, the number of Indonesian capital market investors has reached more than 6,287,350 SID, including 2.9 million SID shares. On the other hand, as of September 30, 2021, there are currently 750 companies listed on the IDX with 38 new additions. 2 Research by Moore (2003) found that knowledge affects investment interest. In contrast, less knowledgeable households tend to take out mortgage loans on unfavorable terms (Gerardi, Goette, & Meier, 2010;Miles, 2004). In addition to literacy, we also summarize several factors that may influence investment interest. The first is motivation; Darmawan et al. (2019) suggest that cause partially has a significant effect on investment interest. This motivation is also likely to be influenced by the environment (Basura et al., 2021). Before making an initial investment, the minimum capital is required. Although many instruments offer small purchases, the availability of this initial capital may still influence individual investment interests. Furthermore, Lai (2017) states that perceived ease of use or access is essential in a person's decision to purchase, including investing online.
In the midst of some of the variables that have been mentioned, we also pay attention to the influence of social media influencers which are currently rife not only in Indonesia but also in the world. Our part of the study sample is that Millennials and Gen Z, as a digital generation, are very likely to influence their investment behavior by influencers (Safitri, 2021; Wibisono 2019). Not all these influencers have a qualified educational background or experience, so they need to be careful. Understanding how Millennials and Gen Z respond to this phenomenon is one of the goals of this study.
This study expands the literature on investment interest, especially from a generational perspective. The rest of this paper discusses the methods, results, and conclusions.

Method
This study spreads a total of 645 questionnaires, and 248 are fully completed questionnaires, and we declare that they are feasible to be used as research data. This study uses the purposive sampling method in determining the sample to be studied, namely with the following criteria: 1) has made transactions in stocks, bonds, and mutual funds; 2) have a simulation of bond stock transactions and mutual funds; 3) interested in investing in stocks, bonds, and mutual funds; 4) follow social media about investing in stocks, bonds, and mutual funds and the capital market.
Factor analysis is used to see the dimensions that arise from the tested attributes of the 49. The number of components in the factor analysis is determined based on the eigen values and scree plot tests. Factor analysis seeks to group several attributes, so there must be a strong enough correlation between attributes so that that grouping will occur. If an attribute is weakly correlated with other attributes, then the attribute will be excluded from the factor analysis. The methods used are Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO MSA) and Bartlett's Test with an alpha value greater than 0.5. MSA is used to determine the combination of variables.

Empirical Result
Of the 49 attributes tested in this study, it turned out that all variables had a KMO MSA value above 0.5, which was between 0.678 to 0.916; this explains that all variables can be analyzed further. Bartlett's test score expressed in Chi-Square also shows a significant number (0.000), supporting the KMO MSA conclusion (Table 1).  Table 2 shows the extraction value of 49 attributes, which can explain the strength of the relationship between the factors formed in the rotated component matrix. In the Knowledge attribute, knowledge of the rate of return on investment has an extraction value of 0.845. The formed factors can explain around 84.5% of the variance of knowledge about the capital market. The motivation attribute, namely, the family's motivation, has the largest extraction value of 0.978, which means that the attribute has a strong relationship with the factors to be formed. In the social environment attribute, Friends who are successful after investing have the most excellent extraction value among other attributes, 0.23. Minimum capital attribute, small capital to invest the extraction value is 0.731. Minimum modal variance has a strong relationship with the factors to be formed. The attribute of perceived ease, information that is easily accessible from the application, has an extraction value of 0.978. The trust attribute has an extraction value of 0.846. Attribute Social Media Influencer extraction value is 0.727 and financial literacy is 0.971. 49 attributes are included in the factor analysis resulting in 2 factors (Table 3). These two factors can explain 78.84% of the variability of the 49 attributes. It is also seen that all of the eigenvalues are above one for these two factors, so the two factors result from the reduction of 49 attributes as optimal results. Table 4 shows that eight attributes are divided into two factors after the rotation and loading results. The two factors identified from the table are dimensions derived from 49 characteristics of interest in investing in the capital market. The attributes included in each size are referred to as the underlying construct. After obtaining two factors resulting from the reduction of 49 attributes, the next step is to give names to the two factors that have been formed. The terms of these factors are expected to reflect each component's characteristics that have been obtained. The names of these factors are: 1. Factor A The basic constructions contained in this dimension are: having knowledge of the capital market, being self-motivated, an environment that has investment experience, and investing with minimal capital.

Factor B
The basic constructions contained in this dimension are: investment information is straightforward to obtain, investment applications prioritize transparency, capital market investment social media has many followers, and compare product prices before buying.

Fig 1. Scree Plot
The scree plot explains the primary number of factors obtained in graphical form, as shown in Figure 1. It can be seen that from factor 1 to 2, the direction of the line decreases very sharply, then from number 2 to 3 the line is still reducing, from number 3 to 4 and to 5 the line still decreasing with the boundary of eigenvalues on the Y-axis still not being crossed. However, when moving from the number 4 to 5, the factor of 5 is already below the number 1 on the Y-axis (Eigenvalue). This shows that these two factors are sufficient to summarize 49 attributes The implication of the factor analysis above is that to understand Millennials and Gen Z investment intention, it is not necessary to measure all attributes but only pay attention to two factors that have been formed. This finding also indicates that social media influencers are one of the factors driving Generation Z's investment interest.

Conclusions
Based on the analysis of the factors that determine the interest of the millennial generation and generation z in investing in the capital market, it can be concluded that after a factor analysis of the 49 existing attributes, two factors are extracted. First, factors with basic construction include knowledge of the capital market, self-motivation, environment with investment experience, and minimal capital. The second is information, transparency, the influence of social media influencers, and financial literacy.