Internet of Things technology skills enhancement in the digital era
: absorptive capacity driven solutions

Student thesis: Doctoral Thesis


Purpose: This research embeds the role of absorptive capacity that is defined as ability to integrate new knowledge to enhance and retain the organisation’s existing knowledge base to create required skills for the Internet of Things technology implementation. Utilisation of absorptive capacity for this research is mainly focused to address the pro-people approach with the dawn of Industry 5.0.  Most of the pre-existing research that involves IoT technology has not addressed the methods that can be used to create an enhanced skill development pathway. This research investigates and answers the major aspects of skill transfer and skill development - both individually and as an organisation - through the absorptive capacity lens. This study will be critical for employees and employers. This will help in planning for the future implementation of the new, emerging technologies.

Methodology: The methodology for this research is a mixed method. Three data sources have been used. Two secondary data sources and one primary data have been used. This mixed-method approach helped triangulate accurate findings and provide the results required to conclude the research.

Findings: This research finds that a widening skills-gap exists as IoT technology is being implemented. This research also finds the factors and the matrix that can help bridge this skills-gap with the help of the absorptive capacity. This research also evaluates critically the skills that are required for IoT job roles. The findings from the semi-structured interviews are particularly helpful as they provide insights, such as how the individual and organisational absorptive capacity can be utilised to bridge the widening skills-gap for IoT technology. One interesting finding in this research is that both individual and organisational absorptive capacity can be utilised to bridge the skills-gap.

Contribution: The two focused areas of contributions are the utilisation of the absorptive capacity-based skill amplifier matrix, which identifies and describes the key factors that can create a skill amplification - especially for emerging technologies like: IoT, AI, robotics and similar technologies that are undergoing rapid implementation. These factors are derived from the quantitative and qualitative data that are collected. The second contribution comprises of the key success factors that support the creation of the skill amplifier matrix. Together, the two contributions create the dynamics of skill upgradation. Skill upgradation is a blend of both individual and organisational features. This cognitive approach can aid the implementation of Internet of Things technology with the right skills.
Date of AwardApr 2024
Original languageEnglish
Awarding Institution
  • University of Brighton
SupervisorKamila Walters (Supervisor), Jose Christian (Supervisor) & Karen Cham (Supervisor)

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