Exploratory Study of Societal Contexts and Industry Performance

Exploratory Study of Societal Contexts and Industry Performance

Delvin Grant, Benjamin Yeo
Copyright: © 2022 |Pages: 22
DOI: 10.4018/IJEBR.309387
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Abstract

There is inconclusive evidence on the effectiveness of information and communication technologies (ICT) at the industry level. Using the influence-impact model as a theoretical framework, the authors apply data mining techniques to identify ICT, financial, and geographical predictors of industry performance. The authors find that ICT are necessary but insufficient, and a mix of technical advancement, financial factors, and geography affect industry performance at different stages of development. These findings are used to discuss ICT for development (ICT4D) research, and abduct hypotheses for theory development with implications for future research.
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Introduction

ICT are synonymous with information systems (IS) and information technology (IT) (Schryen, 2013). They spur growth and development in developed and developing countries (Appiah-Otoo & Song, 2021) toward digital economies by improving performance, competitiveness (Koivunen et al., 2008), welfare, and network externalities (Torero & Von Braun, 2006). However, studies find their ability to improve productivity, growth, and other performance indicators (Bloom et al., 2010; Botello & Pedraza Avella, 2014), inconsistent (Piget & Kossaï, 2013). Firm-level ICT impact is mostly positive (Chipidza & Leidner, 2019) but inconsistent at the industry level (Devaraj & Kohli, 2000; Schryen, 2013), warranting more industry research (Chae et al., 2018; Crowston & Myers, 2004). This is because technologies are tied to their contexts (Cutrell, 2011; Pacey, 1983), causing ICT to have different impact under different conditions. Contexts add rigor to research findings, and their absence diminishes our understanding of ICT impact (Ko & Osei‐Bryson, 2004; Yeo & Grant, 2019b). ICT4D research is also insufficiently grounded in theory (Heffernan et al., 2016; Sein et al., 2019), and Karanasios (2014) recommends rigorous theoretical approaches to interpret and unify ICT4D research.

Despite a need for ICT4D researchers to develop hypotheses and analytical directions (Avgerou, 2017), researchers face challenges developing new, rigorous, and relevant knowledge on existing and emerging problems (Osei‐Bryson & Ngwenyama, 2011) to expand theories, identify alternate explanations (Popper, 1957), new hypotheses (Popper, 1959), and advance theoretical contributions (Popper, 2014). Osei-Bryson and Ngwenyama (2014) acknowledge generating hypotheses for empirical testing is a persistent IS challenge of emerging technologies and dynamic organizations. This is compounded by the lack of technical aids and can be overcome by abducting hypotheses using data mining (Osei‐Bryson & Ngwenyama, 2011).

Motivated by these challenges, the objectives of this exploratory study are 1. to use a contextual theory to investigate how societal contexts and ICT influence industry performance, and 2. to abduct testable propositions and hypotheses for future ICT4D research. We use the Influence-Impact Framework (IIF) to develop a hybrid data mining method for this exploratory research (Osei‐Bryson & Ngwenyama, 2011) on ICT impact. The findings inform technology-driven development in developing countries and illustrate how IIF can be used to study ICT4D. We use three overarching research questions for this investigation:

  • Research Question One (RQ1): How does infrastructure affect manufacturing industries sales growth?

  • Research Question One (RQ2): How does economy affect manufacturing industries sales growth?

  • Research Question One (RQ3): How does culture affect manufacturing industries sales growth?

The results are used to generate propositions (Xue et al., 2008) and hypotheses (Fann, 2012; Osei‐Bryson & Ngwenyama, 2011) for future ICT4D research. This process of abduction departs from traditional deductive and inductive approaches (Osei‐Bryson & Ngwenyama, 2011). We hope the new hypotheses lead to new knowledge that supports ICT industry growth and business decisions.

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