INNOVATION APPROACH IN INDONESIA
4. RESULT AND DISCUSSION Result
Two Step Cluster analysis used in this research data form three groups or clusters automatically, 46.7% in the first cluster with 420 respondents, 35% in the second cluster with 315 respondents and 18.3% in the third cluster with 165 respondents (see Table 1.1).
Table 1.1 Cluster Distribution
N % of Combined % of Total
Cluster 1 420 46.7% 46.7%
2 315 35.0% 35.0%
3 165 18.3% 18.3%
Combined 900 100.0% 100.0%
Total 900 100.0%
The grouping was carried out on categorical and continuous variables which resulted in the formation of three clusters, then a profile was made of each group that was formed so that analysis and interpretation could be carried out. Profiling of categorical variables was carried out using SPSS 17 using the chi-square test with one
critical line (Critical Value). The variable is considered significant to differentiate a cluster from other clusters if the test results of these variables exceed the critical value. Meanwhile, the formation of profiles on continuous variables was carried out using SPSS 17 with Student’s t test with two critical lines. Variables that are considered significant if the test results of these variables exceed the critical line. If the statistical test line is pointing to the right it means the variable made a positive contribution, and if the statistical test line is pointing to the left it means that the variable made a negative contribution. Variables that exceed the critical line then these variables contribute to cluster formation. Chi-square graphs forming the profile of the first cluster or group based on categorical variables (Figure 1.1)
The first cluster consisted of 420 respondents with the most dominating educational status in this cluster are the undergraduate graduates, most of them are private employees with range of age 21 to 30 years old, as many as 193 respondents aged 31 to 40 years as many as 176 respondents, the average income in this group was 2,000,000 to 5,000,000 rupiah, using the internet per month around 100,000 to 300,000, using internet for more than 5 years, daily uses the internet more than 9 hours a day, more than 5 times a week and interested in using internet banking more often.
Figure 1.1 Chi-square and Student’s t Cluster 1
The first cluster assumed that internet banking was easy to use, not complicated to use, the service was fast, and how to use it was clear and easy to understand, and did not mind if internet banking services required periodic PIN changes. They also think that internet banking is economical and can assist in managing financial matters. The risk in using internet banking is not felt by this first cluster because they are not worried about the disconnection of their internet connection when using the service, there is no concern about losing their internet banking PIN code. They did not like to visit banks and meet tellers to transact in person, they thought that internet banking services were better than customer service and other bank services. They hold a positive view of internet banking services and consider them easy to use, they think that new technology is not complicated to use.
The profile of the results of clusters formed by chi-square and student’s t from the second cluster in Figure 1.2, the second cluster consisted of 315 respondents, most of them are Senior High Schools - students from 21 to 30 years old and 17 to 20 years old. The income of this cluster is less than 2,000,000, with average use of the internet is more than 5 years, frequency of using internet more than 5 times a week, more than 9 hours per day, they are interested in using internet banking but don’t know when. Respondents in this cluster have a significant variable focusing on the risk of using internet banking they are worried when using internet banking services, the connection will disappear or disconnect which is considered to be detrimental as well as concerns about the risk of losing the internet banking PIN code and fear of being misused by people who not responsible.
Figure 1.2 Chi-square and Student’s t Cluster 2
The profile of the cluster results was formed by the chi-square and student’s t of the third cluster see Figure 1.3, the third cluster consisted of 165 respondents - 18.3% of the total data. Most of them are the undergraduate graduates who work as entrepreneurs with dominant age range at the age of 41 to 50 years old. The income rate in cluster three is around 5,000,000 to 10,000,000 rupiah with an average monthly internet cost of less than 100,000 rupiah. Most of the respondents use the internet for less than 1 year, use the internet less than 1 hour a day, with 2 to 5 times a week, they are interested in using internet banking more often
Figure 1.3 Chi-square and student’s Cluster 3
Respondents in the third cluster stated that using internet banking is difficult and complicated, the service is slow, cluster three objected if the internet banking service required changing PIN periodically because it was a hassle.
Respondents in cluster three thought that internet banking was uneconomical and useless in managing financial matters.
There is minimal risk for cluster three in using internet banking because they are not worried about the internet connection being cut off when using the service, they do not believe the receipt from internet banking services can be used as valid proof of payment, and they are not worried about losing the internet banking PIN code.
Discussion
Based on the explanation, it can be seen from the knowledge of cluster one on internet banking, cluster one consists of young adults of productive age who have very broad knowledge of new technology or know the latest technology even though they have not used it but know its function. This cluster already intends to use this service soon or less than 1 year, this group seems delay the decision to adopt the innovation (Laukkanen at al., 2008) and won’t adopt it to soon (Szmigin & Foxall 1998 as cited in Yao & Lee, 2016) they postpone adoption even though they find the innovation is acceptable (Gatignon & Robertson, 1989 as cited in Chen, 2019), therefore this group will be named Postponers.
The second cluster consists of adolescents to young adults who are still cautious about the risks of using new technologies that they don’t know in depth about, they have an interest in using internet banking but don’t know when and for sure not in the near future, this group intends to use innovation but do not know when to use it (Kleijnen et al., 2009) This group will be named as an Opponent (Opponent) cluster where in nature they still do not want to use service because they are still looking for the service.
The third cluster consists of adults to the elderly who do not use technology in their daily lives, their internet usage is less than one hour per day, they don’t like new technology because they find it difficult to adapt to using new technology, they prefer transactions that interact directly with tellers and customers services, and have no intention of using internet banking at all. This group do not interest on innovations after evaluating the innovations (Rogers 1983, as cited in Yao & Lee, 2016), they not adopt at all (Lian & Yen, 2013). This third cluster is called the rejector according to its nature this group rejects the interest in using new technology.
Limitation
In this study, segmentation of consumer has not been done specifically, it is necessary to improve the segmentation analysis by comparing the urban and regional areas by examining each province in order to improve the accuracy of data on grouping non user of internet banking customer in every province in Indonesia. This will provide a lot of insight into the right marketing of internet banking for each region, this study just looking at the grouping of non-user internet banking generally in Indonesia using non-probability techniques, further research can use probability sampling for more accurate overview of the group of non-user of internet banking customer in Indonesia.
5. CONCLUSION
This study results is found that non-user of internet banking consumer in Indonesia are divided into three cluster with different characteristics, the first cluster consist of people who know internet banking technology but have not used it and will use it in the near future. The second cluster consist of customers who think about the risks of using internet banking but will still use internet banking because they are still studying internet banking innovation and the third cluster consist of people who have a negative view of internet banking technology because they prefer conventional services.
The first cluster is a potential user for internet banking services, this is insight for banking companies for conducting the marketing strategy based on cluster profile, the preference for internet banking clear and recognizable.
Educate about the advantage of internet banking need to be done if we want to target the second cluster, this cluster consist of teenagers and young adults that being the potential user of internet banking, more advertising and introduce the product knowledge will reduce barriers to this cluster in using internet banking services. The third cluster, which consists of many adults to the elderly who do not understand technology, should be focused on being given an approach through the service demonstration so that they can learn, non-users are yet to identify the true benefits of these service innovations or banks have not demonstrated them well enough (Laukkanen, 2016). Banks can either “pull” customers by actively marketing the benefits of the service innovation, or “push”
consumers towards online channels by increasing service fees in branch offices (Laukkanen, 2016). Laukkanen and Kiviniemi (2010) demonstrate that the value barrier falls significantly if banks offer sufficient information and guidance.
For future research this study suggest to be more specifically in segmenting, using variables that have not been studied, such as psychographic comparisons between cities and regions by examining each province in order to improve the accuracy of data on bank customer grouping who have not used internet banking in every city in Indonesia.
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