Influence of Constant Returns to Scale and Variable Returns to Scale Data Envelopment Analysis Models in ICT Infrastructure Efficiency Utilization

Influence of Constant Returns to Scale and Variable Returns to Scale Data Envelopment Analysis Models in ICT Infrastructure Efficiency Utilization

Yinka Oyerinde (University of South Africa, South Africa) and Felix Bankole (University of South Africa, South Africa)
DOI: 10.4018/978-1-5225-8229-8.ch007
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A lot of research has been done using Data Envelopment Analysis (DEA) to measure efficiency in Education. DEA has also been used in the field of Information and Communication Technology for Development (ICT4D) to investigate and measure the efficiency of Information and Communication Technology (ICT) investments on Human Development. Education is one of the major components of the Human Development Index (HDI) which affects the core of Human Development. This research investigates the relative efficiency of ICT Infrastructure Utilization on the educational component of the HDI in order to determine the viability of Learning Analytics using DEA for policy direction and decision making. A conceptual model taking the form of a Linear Equation was used and the Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models of the Data Envelopment Analysis were employed to measure the relative efficiency of the components of ICT Infrastructure (Inputs) and the components of Education (Outputs). Results show a generally high relative efficiency of ICT Infrastructure utilization on Educational Attainment and Adult Literacy rates, a strong correlation between this Infrastructure and Literacy rates as well, provide an empirical support for the argument of increasing ICT infrastructure to provide an increase in Human Development, especially within the educational context. The research concludes that DEA as a methodology can be used for macroeconomic decision making and policy direction within developmental research.
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The growth of Information and Communication Technology (ICT) in recent years has been remarkable in all countries and sectors throughout the world because of it’s transformational power that favours productivity and efficiency (Kayisire & Wei, 2016). Many governments have heeded the call for increased investments in ICT with the aim to improve national development with respect to the Human Development Index (HDI) (Oyerinde & Bankole, 2019a). Over the last three decades, the literature on national development research has grown to encompass certain intervening variables and social factors such as education and some other aspects of human welfare. (Desai, 1991; Anand & Ravallion, 1993; Bankole & Mimbi, 2017). This is ever more evident considering that countries have defined policies that show an emphasis on creating support mechanisms for the use of ICT (Hinostroza, 2018), however, the opinions on the bearings of ICT Infrastructure for development are in two perspectives vis a vis national development: The adoption of ICTs has the potential to empower communities and countries while secondly, the ICT revolution can lead to imbalances and inequalities through lack of ICT adoption, access and usage (Bankole, 2015).

In the on-going discourse on international human development within the Information and Communication for Development (ICT4D) context, the concept of national development has been said to encapsulate the notion of human development as the means of enlarging people’s choices to acquire knowledge, amongst others, in order to have access to the resources needed for a decent standard of living (UNDP, 2006; Bankole & Mimbi, 2017). When considering the importance of educational attainment, itself being one of the core indices for measuring development with respect to the Human Development Index (HDI) (UNDP, 2006; Bankole et al., 2011a; Bankole et al., 2015), in the national development discourse, coupled with the considerable successes of data analytics in business for decision making, it is not surprising that data analytics implementations have found their way into main stream ICT4D research. Data analytics in education, otherwise known as Learning Analytics (LA), and other research investigating the constituent components of the HDI are therefore relevant and applicable for ICT4D research as well as for national policy/decision making and implementation.

Data Envelopment Analysis (DEA) is a well-known and established non-parametric linear programming methodology that has been widely used for data analysis within the Information Systems discipline and in quantitative research within the ICT4D context. DEA is used for the assessment and measurement of relative efficiency and performance of organizations (Cooper et al., 2006; Thanassoulis et al., 2008, 2011; Bankole et al., 2011c) and has also been used for understanding the impacts of IT investments on performance and productivity (Hatami-Marbini et al., 2010). It has long been recognized that DEA by its use of mathematical programming is particularly adept at estimating inefficiencies in multiple input and multiple output production correspondences (Banker et al., 2004). In Enterprise Business Architecture, DEA serves as a purposive tool for creating composite indicators according to multiple outputs articulated in different measurement units so as to enable enterprise specific weighting of different objectives (Staessens et al., 2019). For Instance, DEA has been applied for the assessment of efficiency of the school provision at different levels (Färe et al., 2006; Portela et al., 2012), universities and their departments (Avkiran, 2001; Thanassoulis et al., 2011), and the impact of education policies and, as well as welfare and profit oriented decision making (Bradley et al., 2001; Grosskopf & Moutray, 2001).

Key Terms in this Chapter

Learning Analytics: Data Analytics on data from the education sector referred to as educational data.

Decision Making Unit: A business or organizational entity which is responsible for collectively making decisions.

Human Development Index: An index/tool for measuring a country’s key dimensions of human development.

Educational Attainment: The highest level of education that an individual has completed.

ICT Infrastructure: Key Information and Communication Technology hardware and software physical stock previously invested in and now available for utilization.

Adult Literacy Rates: Percentage of population aged 15 years and over who can both read and write with understanding a short simple statement on his/her everyday life.

Human Development: The process of enlarging people's freedoms and opportunities and improving their well-being.

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