METICOS Deliverable D5.1 Smart Border Technology Experience Research State of the Art
Creators: name: Schatz, Raimund
name: Sackl, Andreas
Publisher: name: Zenodo
Year: 2022

description: Deliverable D5.1 provides an overview of the of the state of art (SOTA) that is relevant for the technology acceptance modeling (TAM) activities of work package WP5 of the METICOS project and related activities in work packages WP6 and WP7. Beyond discussing the foundations of technology acceptance assessment and modeling itself, a broader, user-centric perspective is given by providing an overview of relevant experience factors and phenomena related to interaction with border- and access control technologies, including the experience of biometric sensing and authentication technologies. Furthermore, SOTA in METICOS-relevant TAM application contexts (border control, big data analytics, and machine learning) is discussed. <br> This deliverable consists of two core parts: the first part (Section 2) provides a more general overview of the SOTA addressing human user experience of smart border technology. It gives an overview of the different groups of experience factors in the context of border control, with a focus on those aspects that are relevant to the METICOS project: access control, authentication as well as cross-cultural aspects and user diversity. The second part (Section 3) then focuses on TAM, which is also the key topic and activity of the project work package WP5. To this end, it provides a general introduction to TAM, followed by a survey of work addressing more specific aspects and challenges related to the project: application of TAM to the context of border control as well as the fusion of TAM with big data analytics and machine learning approaches. <br> Finally, a number of conclusions and findings from the surveyed SOTA are derived, particularly as regards upcoming activities in work packages WP5 to WP7. Among those, key findings and recommendations are:<br> Travelers and border guards constitute two very different border control user groups with very different requirements and perspectives on BC and related technologies. Thus, it is important to clearly distinguish between these two user groups when technology acceptance models are developed. One of the major influence factors on SBC system acceptability is malfunction and high error rate in document and biometrics scanning. It is important to capture such failures and consider them in TAM modeling. In general, many factors/parameters related to the operational environment cannot be considered when modeling technology acceptance on behalf of empirical ex-ante questionnaire data. Some of this information can be retrieved ex-post, e.g., via traveler questionnaires after the actual border control process or by analyzing responses on social networks. Gender-based differences in technology adoption should be investigated in the METICOS project as they help to achieve a fuller understanding of the participation and power structures between genders in society and the nature of their interaction in big data analytics. In METICOS, cultural dimensions should be investigated for each SBC technology of interest in order to better understand modulators in technology experience across different countries and national origins. There is no single universal technology acceptance model that covers every possible scenario. TAMs must be adapted to the specific contexts, technologies, user groups, research questions, etc. addressed. The integration of machine-learning and big data approaches in TAM represents a major research opportunity for the METICOS project. However, the project needs to ensure that selected modeling approaches also match the requirements of the use cases targeted.