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Thesis (Master's)

Reykjavík University > Samfélagssvið / School of Social Sciences > MSc Viðskiptadeild (og Klínísk sálfræði -2019) / Department of Business Administration >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1946/46211

  • Decision intelligence : transformational developments in skin cancer screening using mobile applications
  • Master's
  • Background: Despite the advancement of mobile health applications (mHealth apps), customer acceptance has influenced the success of implementing and managing these mHealth apps, and in achieving a strategic position, skin cancer mobile app developers should structure their business models, embedding primary determinants of customer acceptance.
    Objective: To identify differentiation opportunities in developing a viable and sustainable business model in the skin cancer mobile app development context by integrating a technology acceptance-based survey (modified Technology Acceptance Model (TAM)) with business model innovation concerning the existing companies in the market.
    Methods: People aged 18 years and above were invited to participate in an online survey on acceptance of skin cancer mobile apps, and statistical analysis was conducted using descriptive analysis and statistical tests. A qualitative analysis was conducted with five skin cancer mobile apps to understand in-use business models developed by software developers for skin cancer detection. A comparative analysis was performed to understand differentiation opportunities by integrating modified TAM benchmarking with business model innovation.
    Results: Most participants expressed a positive attitude towards using skin cancer apps, and they significantly valued perceived ease of use, usefulness, accuracy and facilitator determinants. Analysis of business models provided insights into three key differentiation building blocks: unique value propositions, key partners and revenue streams. Companies
    should focus on strategic partnerships to invest in AI-based technology designs and prioritize unique value propositions addressing attributes in perceived ease of use, usefulness, and facilitator determinants. The accuracy of the application needs to be improved by investing in anonymous data processing research. Strategies to improve revenue include providing B2B and B2C services and sharing data anonymously for dermatology research purposes.
    Conclusion: Services offerings in the context of skin cancer detection are similar. Consequently, successful business model innovation should focus on understanding differentiation opportunities and offering similar services following unique approaches by incorporating key determinants significantly valued by customers in strategically investing in key three differentiation building blocks.
    Key Words: Artificial Intelligence, Skin Cancer, Skin Cancer Screening, Customer Acceptance, Business Models, Virtual Health Care

  • Jan 15, 2024
  • http://hdl.handle.net/1946/46211

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