The digital maturity levels of African airports: a departure point for the digital transformation journey
Date
2020
Authors
Mosehlane, Tshegofatso
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Abstract
Background: The study aims to investigate Digital Maturity levels within the African airport industry. The correlation between Digital Maturity and the following airport performance indicators; total revenue growth, total departing passenger growth and Airport Service Quality (ASQ), was investigated to establish whether any such relationships exist.
Objectives: To determine the as-is Digital Maturity levels as input into Digital Transformation Strategy development and to understand whether there exists a relationship between high Digital Maturity levels and an increase in company performance.
Method: A literature study of fourteen Digital Maturity models was performed to determine the qualitative dimensions of the Digital Maturity Model used in this study. An online survey set up in a Likert scale format (1 = strongly disagree to 5 = strongly agree), was subsequently developed. Frameworks by De Bruin, Rosemann, Freeze, and Kulkarni (2005) and Maier, Moultrie, and Clarkson (2012), were used for the development of the Digital Maturity Model. The reliability of the Digital Maturity model was tested using Cronbach’s alpha (α) test (Gilem & Gilem, 2003). The survey was sent to African airport employees via email. Responses were quantitatively measured by allocating weightings (1 to 5) to Digital Maturity sub-dimensions, enabling the calculation of maturity levels per Digital Maturity dimension for each airport. Descriptive studies were further conducted to understand the distribution of the collected data. The second part of the study investigated the correlation between Digital Maturity levels and company performance indicators (Remane, Hanelt, Wiesboeck, & Kolbe, 2017).
Results: The study found that African airports display low maturity levels, ranging between 1.39 and 2.96. With South African and Ghanaian airports being on the higher end and Nigerian airports being on the lower end of the Digital Maturity scale. Most of the airports fall on the higher end of the scale, above Digital Maturity level 2.7. Furthermore, all the airports experienced a decline in total revenue and an increase in total departing passenger numbers over 3 years. The airports with the higher Digital
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Maturity levels experienced lower total revenue declines and higher total departing passenger growth, compared to the airport with the lowest Digital Maturity level. Additionally, the airport with the highest Digital Maturity level, experienced the most considerable decline in ASQ. Whereas the airport with the lowest Digital Maturity level, experienced an improvement in ASQ over the 3 years.
Conclusion: Digital Maturity levels at African airports are low and to remain competitive, airports need to define strategies to assist them in progressing to higher levels of Digital Maturity. The features and outputs of the Digital Maturity Model survey should be used to inform the Digital Transformation Strategies. The study found a positive relationship between Digital Maturity and growth in total revenue and total departing passengers, and a negative relationship between Digital Maturity and ASQ. Organisations should decide on the Digital Maturity dimensions that will be a priority for them to remain competitive. These priority dimensions should be used to offer a differentiated experience to passengers and customers per the organisations’ refreshed Digital Transformation Strategy.
Description
A research report submitted in partial fulfilment of the requirements for the degree of Master of Management in the field of Digital Business to the Faculty of Commerce, Law and Management, University of the Witwatersrand, Johannesburg, 2020
Keywords
Digital Maturity, Digital Transformation, Maturity Model, Fourth Industrial Revolution, 4IR, Industry 4.0, African Airport, Airport 4.0