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UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP

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  • Chi-Yo Huang
  • Yu-Sheng Kao

Abstract

The smart mobile devices have emerged during the past decade and have become one of the most dominant consumer electronic products. Therefore, exploring and understanding the factors which can influence the acceptance of novel mobile technology have become the essential task for the vendors and distributors of mobile devices. The Phablets, integrated smart devices combining the functionality and characteristics of both tablet PCs and smart phones, have gradually become possible alternatives for smart phones. Therefore, predicting factors which can influence the acceptance of Phablets have become indispensable for designing, manufacturing, and marketing of such mobile devices. However, such predictions are not easy. Meanwhile, very few researches tried to study related issues. Consequently, the authors aim to explore and predict the intentions to use and use behaviors of Phablets. The second generation of the Unified Theory of Acceptance and Use of Technology (UTAUT2) is introduced as a theoretic basis. The Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (DNP) will be used to construct the analytic framework. In light of the analytic results, the causal relationships being derived by the DEMATEL demonstrate the direct influence of the habit on other dimensions. Also, based on the influence weights being derived, the use intention, hedonic motivation, and performance expectancy are the most important dimensions. The analytic results can serve as a basis for concept developments, marketing strategy definitions, and new product designs of the future Phablets. The proposed analytic framework can also be used for predicting and analyzing consumers’ preferences toward future mobile devices.

Suggested Citation

  • Chi-Yo Huang & Yu-Sheng Kao, 2015. "UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-23, August.
  • Handle: RePEc:hin:jnlmpe:603747
    DOI: 10.1155/2015/603747
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    Cited by:

    1. Kristoffer Francisco & David Swanson, 2018. "The Supply Chain Has No Clothes: Technology Adoption of Blockchain for Supply Chain Transparency," Logistics, MDPI, vol. 2(1), pages 1-13, January.
    2. Adam Malešević & Dušan Barać & Dragan Soleša & Ema Aleksić & Marijana Despotović-Zrakić, 2021. "Adopting xRM in Higher Education: E-Services Outside the Classroom," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    3. Kum Fai Yuen & Do Thi Khanh Huyen & Xueqin Wang & Guanqiu Qi, 2020. "Factors Influencing the Adoption of Shared Autonomous Vehicles," IJERPH, MDPI, vol. 17(13), pages 1-17, July.
    4. A. A. I. N. Marhaeni & Kittisak Jermsittiparsert & Sudarmo & Lucia Rita Indrawati & Andjar Prasetyo & Noviati Fuada & Arnis Rachmadhani & Tri Weda Raharjo & Heri Wahyudianto & Bekti Putri Harwijayanti, 2023. "Adoption of the Green Economy through Branchless Rural Credit Banks during the COVID-19 Pandemic in Indonesia," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    5. Syed Imran Zaman & Sharfuddin Ahmed Khan & Sahar Qabool & Himanshu Gupta, 2023. "How digitalization in banking improve service supply chain resilience of e-commerce sector? a technological adoption model approach," Operations Management Research, Springer, vol. 16(2), pages 904-930, June.
    6. Xinlu Wen & Marios Sotiriadis & Shiwei Shen, 2023. "Determining the Key Drivers for the Acceptance and Usage of AR and VR in Cultural Heritage Monuments," Sustainability, MDPI, vol. 15(5), pages 1-24, February.
    7. Yuan Li & Jiaqi Liang & Jingxiong Huang & Mengsheng Yang & Runyan Li & Huanxia Bai, 2022. "Would You Accept Virtual Tourism? The Impact of COVID-19 Risk Perception on Technology Acceptance from a Comparative Perspective," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    8. Wu, Min & Wang, Nanxi & Yuen, Kum Fai, 2023. "Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    9. Tsai, Pei-Hsuan & Kao, Ya-Ling & Tang, Jia-Wei, 2023. "Key factors influencing mass willingness to use CESPs under green concept: ECOCO smart recyclers as a case study," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    10. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers," IJERPH, MDPI, vol. 16(18), pages 1-31, September.
    11. Khan, Ali Nawaz & Jabeen, Fauzia & Mehmood, Khalid & Ali Soomro, Mohsin & Bresciani, Stefano, 2023. "Paving the way for technological innovation through adoption of artificial intelligence in conservative industries," Journal of Business Research, Elsevier, vol. 165(C).
    12. Kalisri Logeswaran Aravindan & Ramayah Thurasamy & Murali Raman & Narinasamy Ilhavenil & Sanmugam Annamalah & Arul Selvam Rathidevi, 2022. "Modeling Awareness as the Crux in Solar Energy Adoption Intention through Unified Theory of Acceptance and Use of Technology," Mathematics, MDPI, vol. 10(12), pages 1-14, June.
    13. Ahlam Mohammed Al-Abdullatif & Merfat Ayesh Alsubaie, 2022. "Using Digital Learning Platforms for Teaching Arabic Literacy: A Post-Pandemic Mobile Learning Scenario in Saudi Arabia," Sustainability, MDPI, vol. 14(19), pages 1-20, September.

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