Consumer Acceptance for Using Personal Data

Abstract: Research backgroundDigitalization has been accelerating by the COVID-19 pandemic. Some service fields are offered only via the face-to-face selling channel before starting using the remote channel. The proper use of customers' data, such as their lifestyles, preferences, and behavior history, makes these services more valuable for both customers and companies. However, currently the data utilization infrastructure, law and consumers’ knowledge is not established enough.HypothesesThis study aims to clarify the structure of consumer acceptance for their data usage by a survey in the medical fields. We verified the three hypotheses by using the conjoint analysis. H1. If people have a high knowledge and involvement in personal data, they use the Central route for no PD disclosure from their own devices. H2. If people have a high knowledge and involvement in medical care, they use the Central route for the benefits of personal data usage. It means better recommendations of clinics or hospitals.H3. If people have a high knowledge and involvement in PD or Medical Care, they use the central route for the trustworthiness of an AI application’s developer. It is related to both risk and benefit, which means No PD disclosure and recommendations. For conjoint analysis, we put the 3 attributes and the two levels. Level 1 represents the central route, and level 2 represents the peripheral route. Attribute1’s level1 explains the technology limiting PD use just inside their smartphones. Attribute1’s level2 explains that large companies highly evaluate and use this technology. Result of analysis and discussionWe made segments by PD and Medical knowledge and involvement into four segments. Segment 1 is high PD and high Medical Care, segment 2 is high PD - low medical care, segment 3 is low-high, segment 4 is low-low. All 4 segments place the highest emphasis on attribute 1, no personal data disclosure from their own devices. Look at the graph, the blue bar shows it. As for the direction of the preference, the central route is preferred by All 4 settlements, but it is more strongly preferred by HH and HL, those are the segments more interested in PD. There is no difference in the other two attributes.Regarding to the understanding of the explanation of attributes, no PD disclosure and recommendation, the segments that were more interested in medical care segments show a higher understanding. The segment HL, which is the most sensitive to the PD, shows the highest level of understanding of the trustworthiness of the AI application’s developer. Since many such application developers are small start-ups, it is difficult to determine their trustworthiness. That’s why this segment, which is sensitive and more skeptical to AI applications, has a higher understanding of this aspect. FindingsAll segments are weighted toward no PD disclosure, and prefer the central route for this attribute. The higher the knowledge and involvement in PD, the more the central route is preferred. The benefit concern segment understands the no PD discloser and recommendation. The PD sensitive segment understands the trustworthiness of companies.

Keywords: Personal Data, Conjoint analysis, Elaboration Likelihood Model

DOI: 10.54941/ahfe1002283

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