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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.