FACTORS INFLUENCING CONSUMERâS WILLINGNESS TO PAY FOR INTERNET OF THINGS (IOT) PRODUCTS IN INDONESIA: ANALYSIS OF TAM AND TRI FACTORS
The development of technology has grown rapidly in these past years and Information Technology (IT) has become one of the potential sectors to have positive development. One of the trends of IT to look out for in 2020 is the Internet of Things (IoT). Globally, IoT has been a trend. The number of IoT...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/49002 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The development of technology has grown rapidly in these past years and Information Technology (IT) has become one of the potential sectors to have positive development. One of the trends of IT to look out for in 2020 is the Internet of Things (IoT). Globally, IoT has been a trend. The number of IoT connected devices in the world will be 38.5 billion used in 2020, and the market for IoT in Indonesia is expected to grow to 444 Trillion Rupiah in 2022.
However, IoT is considered as a new kind of technology in Indonesia. In some conditions, even though the product has a breakthrough innovative value, but if the consumer is not ready to accept the product, it has a high opportunity to lose its sales. Using the smart garden as the IoT product example to gather the willingness to pay data from the market, this research wants to find out further about the factors that could affect the consumer’s willingness to pay (WTP) for IoT products.
To identify the relationship between the readiness and acceptance of IoT products to the willingness to pay, the Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) were used in this research. An external variable (Subjective Norm) is added in this research to test the social influence on people's decisions to use IoT products. Researchers used quantitative methods using purposive sampling to get respondents aged 20-55 years who are in the upper-middle to elite economic class. 353 samples of respondents were obtained through online questionnaires. The analysis used is PLS-SEM analysis to test the hypotheses and measure the relationship between one variable to another. Contingent Valuation Method is also used to find out the price of IoT products that suits what market desires. The results of this study indicate that people’s acceptance of IoT products can influence their willingness to pay. TAM factors can be the mediator of optimism variable to the willingness to pay. This indicates that the market’s readiness for new technology can indirectly impact their willingness to pay for IoT products through their optimism towards that technology. |
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