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European Journal of Information Systems
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Information infrastructure, governance, and socio- economic development in developing countries
Peter Meso, Philip Musa, Detmar Straub & Victor Mbarika
To cite this article: Peter Meso, Philip Musa, Detmar Straub & Victor Mbarika (2009) Information infrastructure, governance, and socio-economic development in developing countries, European Journal of Information Systems, 18:1, 52-65, DOI: 10.1057/ejis.2008.56
To link to this article: https://doi.org/10.1057/ejis.2008.56
Published online: 19 Dec 2017.
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Information infrastructure, governance,
and socio-economic development in
Peter Meso1, Philip Musa2, Detmar Straub1, and Victor Mbarika3
1J. Mack Robinson College of Business, Georgia State University, Atlanta, GA, U.S.A.; 2School of
Business, The University of Alabama at
Birmingham, USA; 3College of Business, Southern
University, Baton Rouge, LA, U.S.A.
Correspondence: Philip Musa, School of Business, The University of Alabama at Birmingham, U.S.A. Tel: þ1 205 934 8844 Fax: þ1 205 989 6688 E-mail: firstname.lastname@example.org
Received: 27 August 2008 Revised: 28 September 2008 Accepted: 13 October 2008
Abstract There is growing interest in the role and contribution of national information
infrastructure (NII) to the quality of governance and the socio-economic
development of nation states. In this paper, we use publicly available archival data to explore the relationships among NII, governance, and socio-economic
development in developing countries. Results substantiate a significant
relationship between NII and governance, and NII and socio-economic
development. The findings suggest that NII have the capacity to contribute to country development, both directly (via impacts on socio-economic
development) and indirectly (via its impacts on governance, which in turn
influences socio-economic development). European Journal of Information Systems (2009) 18, 52–65. doi:10.1057/ejis.2008.56
Keywords: national information infrastructure (NII); governance; developing countries; socio-economic development; partial least squares analysis
Introduction While a great deal of research has been conducted in recent years on how nations create information infrastructures, the influence of such infrastructures on country governance and socio-economic development remains – except for a few recent studies – at best anecdotal and conjectural (Meso et al., 2006). The key question is: can such infrastruc- tures demonstrate tangible benefits to those who deploy them in the national arena? Emerging research provides contradicting responses. One group of research points to the positive impact of select groups of information infrastructures on socio-economic development and/or governance. Examples include Dutta (2001), Gatica (1994), Mbarika et al. (2001, 2002a, 2005), Meso & Duncan (2000), Nidumolu & Goodman (1993), Nidumolu et al. (1996), Organization for Economic Co-operation and Development (OECD) (1997), Rose & Straub (1998), Sheffield & Gallupe (1995, 1996), Straub & Watson (2001), Straub (1994), and Meso et al. (2006), among others. However, others argue that governance and socio-economic development are complex phenomena which cannot be direclty improved by the effects of technology alone (Walsham & Sahay, 1999; Casely, 2004; Avgerou et al., 2005). Still, there are those who indicate that technology’s impact on governance and socio-economic development is heavily dependent on the context and environment in which the technology is implemented. A good example is Ciborra & Navarra (2005) who show that implementing information infrastructure solutions aimed at improving governance is not an easy task, is fraught with a number of
European Journal of Information Systems (2009) 18, 52–65 & 2009 Operational Research Society Ltd. All rights reserved 0960-085X/09
risks, and may not necessarily be conducive to enhancing country development. We also observe that most of the investigations into the influence of information infra- structure on governance and socio-economic develop- ment have been undertaken via a qualitative, usually case-study, approach. In this paper, we seek to identify if indeed there is quantitative merit in the relationships among information inftrastructure, the quality of coun- try governance, and the levels of socio-economic devel- opment when the entire collection of developing countries is examined as a block. While the insights we obtain do not replace the deep insights obtained from a qualitative assessment of the impacts of information infrastructure implementations within the narrow con- fines of a single case-study or a handfull of comparative case studies, we feel that they illuminate our under- standing of the contributions of national information infrastructure (NII) at the national level by providing a macro-perspective of its impacts on key national-level development parameters. Using archival data, the current research analyzes the
relationship between NII and governance quality in 144 developing countries. The rest of the paper is organized as follows: in the ensuing section we present the research model and hypotheses. This is followed by the section on research design. The section after that presents the analysis and results of the study. We then discuss the results and the implications for future research. The final section provides concluding remarks with a restatement of the value of the work.
Research model and hypotheses There is evidence that NII solutions, when effectively implemented, facilitate and support good governance. For example, Sheffield & Gallupe (1995, 1996) report on the positive contributions of electronic-meeting infra- structure on policy development in New Zealand. Study- ing information technology (IT)-based government initiatives in Gujarat, India, Madon (2005) identifies ‘that IT-based initiatives can yield positive and effective governance reform, particularly where appropriate in- stitutional support and activities couch the implementa- tion of such IT-based solutions.’ Madon et al. (2007) also reveal that effective implementation of government- based health information systems for the provision of services is impacted by the macro-level policy-making organs, thereby shaping the type of system that even- tually gets developed. However, once such systems are in place they impact the efficacy of policy-making at those same macro-levels. As such, governance quality is influenced by the nature and type of IT-based solutions in place, but also influences the kinds of IT systems that get developed. Madon et al. (2007) thus posit that ‘evaluation does help to understand the disjuncture between policy at the macro-level and implementation at the micro-level and to identify linkages between the two (p. 327).’ In a twist of the general directionality used to examine the relationship between IT-based initiatives
and country governance, Andersen et al. (2003) examine the impacts of governance on the diffusion of electronic commerce (e-commerce) initiatives in Denmark. They identify knowledge diffusion, economic incentives, elec- tronic government, and regulation and control, as the four governance initiatives that foster development and diffusion of e-commerce within a country. In studying the impacts of culture on IT diffusion in developing countries in the Arab world, Straub, Loch and co-workers (Loch et al., 2000, 2003; Straub et al., 2001b) identify governance as a viable explanation for differences in the ways countries exploit information infrastructures. OECD (1997) proposes that extensive information
infrastructure may readily enhance government effec- tiveness and facilitate greater participation in the govern- ance process by a nation’s citizens. While studying teledensity in developing countries, Mbarika et al. (2002b) concluded that the level of teledensity correlates positively to governance quality. Most of the developing countries have been cited as having governance problems that in turn affect their progress toward economic prosperity and socio-economic development (Odedra et al., 1993; Odedra-Straub, 1993; Leftwich, 1995; Easterly & Levine, 1997; ECA, 1998; Meso & Duncan, 2000; LeBlanc et al., 2004). These countries, especially those categorized as least developed, are subject to significant internal unrest and civil strife (Easterly & Levine, 1997; LeBlanc et al., 2004). It is critical that we learn more about the ways that
information infrastructures contribute toward improving the quality of governance in these countries. These mechanisms include, among others:
(a) allowing greater access by the population to govern- ment services – especially via interactive on-line access;
(b) facilitating participation in the governance processes
by a more diverse and larger segment of the population; (c) dissolving the state’s monopoly over news, informa-
tion, and propaganda; (d) rapidly disseminating news and information to the
larger population; (e) enhancing transparency and accountability of gov-
ernment officials via readily accessible information
on governmental transactions; (f) eliminating or minimizing barriers to participation in
the country’s economic markets; and (g) promoting the rule of law.
Most of the past studies on information infrastructure have limited the scope of NII to the telecommunications infrastructure that made the Internet a reality (Philip, 1988; Dutta, 1992, 2001; Mbarika et al., 2001, 2002b). While these studies provide an initial understanding of the role of information infrastructure in economic advancement, studies by Sadowsky (1993, 1996), Byrd et al. (1995), Byrd & Turner (2000), Byrd (2001), Meso & Duncan (2000), Nidumolu et al. (1996), Tapscott (1996), and Miller et al. (1993) argue that a NII is more extensive
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European Journal of Information Systems
than just the Internet and its associated telecommunica- tions backbone. Selwyn & Brown (2000) note that most industrialized
countries have witnessed the development of advanced information networks, usually under the rubric of creating a ‘national information infrastructure.’ They state that, in an organizational sense, such NII was envisioned as encompassing ‘all computerized networks, applications and services that citizens can use to access, create, disseminate and utilize digital information (p. 662).’ Therefore, the development of the NII in practice has
encompassed technologies as diverse as POTS (plain old telephone service), digital broadcasting, the Internet and other multimedia, in both the private and public sectors. In proposing a more-encompassing construct for NII, Meso & Duncan (2000) state:
It is important to recognize that NII does not necessarily
mean the Internet. Until this decade, NII throughout the
world meant radio, newspapers, postal services, etc. These
are still vital components of information infrastructure
throughout the world y (p. 34).
Therefore, preceding research provides support for the inclusion of the Internet, personal computers, teleden- sity, radio density, television density, and newspaper circulation as technological constructs of the level of development of a nation’s NII. For this reason, we employ this more-encompassing view of NII. We posit that NII impacts governance and socio-
economic development. The diagrammatic representa- tion of the research model with hypotheses indicated is presented in Figure 1. We next derive and explain each hypothesis.
Relating NII to governance Although the concept of governance has been exten- sively examined at the organizational level in published information and communication technology (ICT) re- search, it remains relatively recent where it concerns national-level or country-based ICT studies. In the international setting, governance refers to the manner in which power is exercised in the management of a country’s economic and social resources for development (IBRD, 1998; Meso et al., 2006). The concept is gaining increasing focus as a national-level construct owing to the rapidly growing domain of e-government within the ICT research. Unfortunately, the definition of national- level governance remains increasingly limited to the narrow confines of e-government. For example, e-govern- ment may be perceived as a solution for ‘jump-starting’
dysfunctional and inefficient government operations, thereby yielding better governance (Goldsmith, 2005). In other words, the e-government systems implement governance. Chadwick & May (2003) posit that there are three models of governance observable in contemporary e-government implementations: managerial, consulta- tive, and participatory. The managerial model of e-government has its focus on the dissemination of information to the citizens. In this context, effective governance is seen as providing the citizenry with pertinent information services in an open, transparent, and timely fashion. In the consultative model, effective governance is perceived as successfully obtaining feed- back and opinions from the general public. The opinions may then be used in the policy-making process to inform and/or influence future government actions. As such, the role of e-government systems becomes that of soliciting and obtaining citizens’ inputs. In the participatory model, governance is seen as open communications – the ‘voicing of one’s concerns’ – where the opinions are not necessarily directed only to government but to all players within the governance communications space. Therefore, according to Chadwick & May (2003), e-government implementations in this realm foster the ‘collaboration and information sharing among disparate stake holders.’ However, governance is a broader construct than is
perceived within e-government. According to Larmour (1995) governance connotes either of two things. The first is ‘effective government.’ This refers to the perfor- mance of a government as judged by conventional economic parameters such as fast rate of economic growth, low rates of poverty, high living standards, high GDP, etc. The second connotation of governance relates to the ‘freedoms’ accruing to a country’s citizens owing to their government’s actions. In this context, governance is seen as fostering democracy, legitimacy of public offices and institutions, limits to state power, and transparency in government operations. This second perception of governance is also evident in
Peters & Pierre (1998) who posit that governance is not the exclusive preserve of national governments. Rather, it entails multiple disparate players – citizenry, non-govern- mental organizations (NGOs), special-interest groups, etc., each seeking to satisfy their own interests. Therefore, governance is perceived as the dynamic interactions between and within public and private sectors, not relying simply on authority and sanctions of government (Stoker, 1998). As such, governance involves a coalition of diverse stakeholders from business, government, and NGOs working together to achieve mutually agreed-upon goals (King et al., 1994; King & Kraemer, 1995; Leftwich, 1995; Kazancigil, 1998; Stoker, 1998). Therefore, govern- ance is related to the concept of autonomous self- governing networks of institutions. However, while drawing from this intellectual base, the concept of governance transcends government. Definitions of gov- ernance generally thrive on this blurring of boundaries
Governance Social-Economic Development
Figure 1 Research model and hypotheses.
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European Journal of Information Systems
and focus attention more on end actions (Finkelstein, 1995). Concepts of governance invoke responsibilities for
tackling social and economic issues, and suggest the need for power dependence between all relevant institu- tions in order to precipitate collective actions. Therefore, as a concept, governance recognizes the capacity to get things done while not resting solely and simply on the power of government to command or flex its authority. The NII in a country is expected to impact quality of
governance. It can be argued that the nature of a country’s information infrastructure can lead to increased levels of transparency and accountability (Park, 2002). Transparency refers to the degree of awareness by local citizens about all the key issues affecting the survival, performance, and well-being of the nation. When the larger majority of citizens are fully informed about these key issues and how they impact country’s future, there is a higher probability that the actions and/or decisions of public institutions will be brought to scrutiny by various disparate stakeholders thereby leveraging the account- ability of public socio-economic and government institu- tions within the economy (ECA, 1998). A transparent and accountable governance system clearly and publicly identifies parties responsible for particular decisions and actions, generating requisite pressure for high integrity and judicious execution of responsibility by civil servants and public agencies. In so doing, it discourages stake- holders and decision-makers from engaging in such vices as corruption (IBRD, 2001; Musa et al., 2005a). Given that easy and adequate access to information is made possible by a well-developed NII, the extent of development of this infrastructure plays a significant role in optimizing the governance system within a given nation. Therefore, we posit that information infrastructure impacts the quality of governance. Advanced information infrastructure enhances the
number of participants in all sectors of a country’s economic, social, and political systems and the power– position of each participant (Alcantara, 1998; Jessop, 1998; Senarclens, 1998). In the advanced economies, key e-commerce market places such as E-Bay and Amazon.- Com have allowed a myriad of small businesses to gain access to geographically distant clients. In this example, the NII solution has contributed to an enhancement in the economic productivity for these countries by opening up new multi-billion economic sectors (Kraemer et al., 2005; Lin et al., 2007). In the lesser developed nations, the meteoric diffusion of cellular telephony and Internet technologies is beginning to impact economic produc- tivity, by enhancing the density of economic networks and allowing many more individuals to participate in the formal economy (Meso et al, 2005; Musa et al., 2005b). The dynamic interaction between participants within and without each sector, the power-dependence of these participants, and the conflicting goals of each create an intricate governance network. Thus, the developments and the direction charted by each sector, as well as by the
entire economy, will depend on consensus and colla- borative efforts between all participants. In so doing, the governance of all sectors is enhanced (Jessop, 1998; Stoker, 1998). The above discussion points to the proposition that the
quality of country governance clearly depends on the information and collaborative networks made possible by the requisite information infrastructures. Therefore, we posit that information infrastructure is expected to impact the quality of a country’s governance much like it has shaped and transformed the management of business enterprises. This line of thinking leads to our first hypothesis:
H1: NII influences the quality of governance in developing countries.
Relating NII to socio-economic development The dissemination of NII in developing countries has continued to lag behind that of the industrialized world. Goodman (1991), Odedra et al. (1993), and Mbarika et al. (2002b), among others, report that the perceived value of information infrastructures in under-developed countries is far below that in industrialized nations. Reinforcing this point of view, Rose & Straub (1998) further identify government-based bottlenecks, specifi- cally inept government policies, as key impediments to the development of information infrastructures in these countries. Nonetheless, all these researchers are unan- imous in asserting that information infrastructures may have beneficial impacts on the socio-economic develop- ment of nations. Literature on IT and development proposes that high
levels of ICTs impact the standards of living, access to socio-economic development variables such as education and healthcare, and good governance (Meso & Duncan, 2000; IBRD, 2001; UNDP, 2006). As noted in UNCTAD’s 2001 report on E-commerce and Development (UNCTAD, 2001):
The introduction of wireless communications has not only
expanded telephony in many developing countries, but also
introduced wireless data services y For many people in developing countries, mobile handsets may be the first
and main access route to information and communication
technologies (ICTs), the Internet and e-commerce technol-
ogies (p. 89).
Published national development research points to the relevance and significance of technology in accelerating a nation’s development, of which socio-economic devel- opment is only a part. Kraemer et al. (2005) and McCallum (1989), among others, indicate that technolo- gical progress positively influences the sustainable devel- opment of nations. In light of this, NII solutions are expected to contribute to socio-economic development. Hayami & Ogasawara (1999) reinforce this perception by stating that growth of national product depends pre- dominantly on improved efficiencies (or technological
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European Journal of Information Systems
progress broadly defined) rather than on capital accumu- lation. Mowery et al. (1996, 1998) also acknowledge that the influence of international technology transfer on national development has rapidly increased, especially in the post-World War II era, and that this importation of technology has been the predominant cause of the meteoric development evidenced in most of the newly industrialized countries. Studies on ICT diffusion in the Middle East (Goodman,
1991; Goodman & Green, 1992; Danowitz et al., 1995; Nidumolu et al., 1996; Rose & Straub, 1998; Loch et al., 2000, 2003; Straub et al., 2001b), Asia Pacific (Nidumolu & Goodman, 1993; Goodman et al., 1994; Dedrick & Kraemer, 1995; Goodman & Press, 1995; Thajchayapong et al., 1997; Walsham & Sahay, 1999; Barrett et al., 2001), South and Central America (Correa, 1992; Montealegre & Applegate, 1994; Mahmood et al., 1995; Montealegre, 1996, 1998, 1999; Ward, 2000; Tigre, 2001), and Sub-Saharan Africa (Odedra et al., 1993; Odedra-Straub, 1993; Goodman, 1994; Amoako, 1996; Damsgaard & Scheepers, 1999; Meso & Duncan, 2000; Mbarika et al., 2001, 2002a, b) have shown that there has been a very rapid growth in the diffusion of ICTs. Likewise, owing to the advent of the digital revolution, conventional broad- cast technologies have also experienced such exponential growth (Kuhlen et al., 1996; Keyes, 1997; Lam, 1998; Mifflin, 1998; Paterson, 1998; Wresch, 1998, 2001; O’Sullivan, 1999; Weissman, 1999; Djerdjour & Patel, 2000; Fandy, 2000; Kayany & Yelsma, 2000; Phelps, 2000; Simha, 2000; Neuendorf et al., 2001). As the intensity of this diffusion increases, the use of NII for socio-economic development in less developed countries continues to receive much attention (Bhatnagar & Bjorn-Andersen, 1990; Wolcott et al., 1996; Goodman et al., 1998; Ein-Dor et al., 1999; Goodman, 2001; United Nations Conference on Trade and Development, 2001). Dutta (2001) performed a granger causality analysis of telecommunications infra- structure on economic development for 30 countries and found that the evidence for a causal link from levels of telecommunications infrastructure to economic activity is stronger than that for causality in the opposite direction. Further, this pattern of causality is evidenced by both developing and developed countries despite low indices of telecommunications infrastructure within developing countries. Dutta’s findings provide impetus for examining the causal nature of the relationship between NII (not just telecommunications infrastructure) and socio-economic development, which normally goes hand in hand with economic development as a metric for national development. In studying the ‘digital divide,’ Warschauer (2003)
provides examples of practical interventions with respect to information infrastructure development affecting enhanced socio-economic development at the grassroots level in India. He reports:
The Gyandoot (which translates to ‘purveyor of knowl-
edge’) project in India was inexpensive to launchy and it is
partly self-sustaining y In the nine months beginning in October 2001, the Gyandoot kiosks had some 21,300 users,
80 percent of whom had annual incomes of less than $300.
The number of users is a small percentage of the population,
but the benefits of the project, such as improved govern-
ment services, eventually ripple outward to friends, families
and co-workers. The magnitude of the Gyandoot success
story remains to be determined. But the underlying
approach – a combination of well-planned and low-cost
infusions of technology with content development and
educational campaigns targeted to social development – is
surely a healthy alternative to projects that rely on planting
computers and waiting for something to grow (p. 42).
Arguing that, as yet, very little is known about the long-term impact that ICTs may have on a country’s social and cultural systems, Morales-Gomez & Melesse (1998) go on to assess the contribution of these technologies to economic and socio-economic develop- ment. They conclude that one of the greatest socio- economic development benefits derivable from the effective use of ICT is leveraging the reach, scope and quality of education and training to the citizens of a nation. Thus ICTs, they argue, have direct impacts on the socio-economic development of nation states in the long term. Based on the above arguments, we expect this increase
in NII technologies in those regions where all developing countries are found to correspond with increases in national development, particularly so with socio-eco- nomic development. Should this be the case, these infrastructures may be assisting in the progress of these countries toward socio-economic development. There- fore, we hypothesize that:
H2: NII influences the level of socio-economic development in developing counties.
Relating governance to socio-economic development The review of literature also indicates that governance has an impact on sustainable socio-economic develop- ment. Kaufmann et al. (1999a, b) establish that there is a positive causal relationship between governance and economic development. Kaufmann et al. (1999a), Jessop (1998), Dutta (2001), and Kazancigil (1998) indicate that the quality of governance affects the rate of economic development. Prior research has established that the quality of
governance impacts the rate of a nation’s socio-economic development (Leftwich, 1995; Jessop, 1998; Kazancigil, 1998; Kaufmann et al., 1999a; IBRD, 2002). As in the management of a firm, it is assumed that information is a valid resource that enables organizations and individuals to improve their effectiveness, efficiency, productivity, and overall competitiveness. For example, one of the key measures of good governance is political stability (defined as the measure of the degree of turbulence in a country). Literature on economic development and
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European Journal of Information Systems
international finance indicates that a particular country’s level of political stability directly influences the risk associated with investing in a given country. The greater the degree of turbulence, the more risky it is to invest in the country (Sadowsky, 1993, 1996; Kaufmann et al., 1999a). Political stability also influences the level of engagement by local citizens in productive socio- economic activity (Kaufmann et al., 1999a). In situations of high political instability, citizens retire their produc- tive resources, transfer these resources to more stable political environments, or covert these resources into assets that will protect them against possible loss of life and wealth. The net result is a drop in socio-economic development. Therefore, it is logical to presume that as the quality of governance rises, so does the level of socio-economic development. The hypothesis that follows logically is:
H3: The quality of governance influences the level of socio- economic development in the developing countries.
Research design To empirically test the hypotheses in this study, we gathered archival data for each of the main constructs. This approach has the advantage of independent genera- tion of variable values, and is thus more robust to the threat of common methods bias (Woszczynski & Whitman, 2004). Archival data also has limitations, one being that it is dependent on the assumptions that underlay the original data collection, as reported in Jarvenpaa (1990, 1991). We examine the threat of some of these assumptions later. Hypotheses were tested via a cross-sectional analysis of
144 countries classified as middle- and low-income countries by the World Bank (IBRD, 2002) and as developing countries by the United Nations Develop- ment Program (UNDP) (UNDP, 2006). The primary sources of data were the International Telecommunica- tion Union World Indices (ITU, 2007), the UNDP Human Development Report (UNDP, 2006) and the dataset for governance indices created by Kaufmann et al. (2007).
Operationalization of constructs NII was operationalized as a formative construct mea- sured by the density of ICTs within a country. The key ICT indicators that we included were telephone density, density of personal computers, Internet density, radio density, newspaper circulation density, and television density. The density is measured as the number of peripherals per 1000 population. These measures were adopted from the ITU (2007). Governance was operationalized as a single formative
construct comprising six indicators of governance origin- ally presented in Kaufmann et al. (1999a). These measures are: Voice and Accountability, Political Instability and Violence, Government Effectiveness, Regulatory Burden, Graft, and Rule of Law. These measures have since been
adopted by the World Bank and employed as indices of governance quality in the world development reports (IBRD, 2002). In a separate paper published in the same year, Kaufmann et al. (1999b) show that aggregated variables are richer and better predictors of governance than the individual governance measures that are currently used by a wide group of organizations. Further, they demonstrate that aggregating individual variables allows for the coverage of many more countries and for the standardization of the resulting measures, thereby facilitating cross-country comparative research. Socio-economic development was operationalized
using one formative latent variable comprising three indicators that make up the human development index. The indicators were life expectancy, education index, and per capita GDP calculated using the purchasing power parity (PPP) method. PPP calculates each country’s GDP relative a selected standard, usually the U.S. dollar (UNDP, 2006). Table 1 presents the descriptive statistics for the
indicators to each latent variable used in the study. The table indicates that while the diffusion of personal computers remained relatively low at 3.23 computers per 1000 population, there was a relatively large diffusion of mobile phones – 25 per 1000 persons on average across the developing countries. This is consistent with the reports from ITU and other sources that have shown a meteoric rise in mobile phone ownership and usage in these countries. On average, there were 7.847 Internet access points per 1000 population and 3.8 land-line telephones per 1000 persons. When contrasted to the advanced nations, it is evident that the scope and extent of NII in the developing nations remains modest. The data show that governance was also of moderate
quality on average, with the mean scores on all the governance indicators being below 1.0. Socio-economic development measures were, on average, good. The mean scores of education, life expectancy and per capita GDP when adjusted for PPP were 0.753, 0.667, and 0.632, respectively. The best score a nation can attain on these indices is 1.0. Thus, these nations tended to register slightly above average performance when taken as a group. We note that these descriptive statistics provide an overall summary. There are nations that perform quite well on these indices while others report abysmal scores.
Analysis and results The archival data for the 144 countries was analyzed using SPSS statistical software and the partial least squares (PLS) statistical analysis method as supported by the PLS software. All analysis was conducted on a personal computer. SPSS was used to run the descriptive statistics, assess construct validity and also to assess the reliability of the indicators. The hypotheses articulated by the research model were tested using PLS. PLS is a structural equation modeling technique that is well suited for highly complex predictive models (Fornell & Larcker, 1981; Joreskog & Wold, 1982; Chin & Todd, 1995;
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European Journal of Information Systems
Diamantopoulos & Winklhofer, 2001; Wixom & Watson, 2001; Gefen et al., 2003). PLS has several strengths that make it appropriate for
this study, including its ability to handle formative constructs, reputed robustness in handling small sample sizes, and missing values (Straub et al., 2002). As documented in Wixom & Watson (2001), the technique concurrently tests the psychometric properties of scales used to measure the variables in the model (i.e., the measurement model), and analyzes the strengths and directions of the relationships among the variables (i.e., the structural model). The path coefficients established by evaluating the research model in PLS allow u’s to assess if there are relationships among the constructs represent- ing NII, governance, and socio-economic development.
Assessment of the measurement model The measurement model articulates the psychometric properties of scales used to measure the variables in the model. The specific tests used to assess this model include test for the research model’s reliability, as well as tests for construct validity. The research model’s reliability was tested by assessing the multicollinearity of the indicators for each construct. As summarized in Table 2, all the VIF values were below 3.3 which is the acceptable cut-off point (Nunnally, 1978; Diamantopoulos & Winklhofer, 2001; Jarvis et al., 2003; Petter et al., 2007). Construct validity was assessed by examining the item
weightings for the constructs (Jarvis et al., 2003). These results are presented in Table 3. It is worth noting that the indicators we selected to use have been accepted as standard measures for information infrastructure, gov- ernance, and social development, respectively. They have been in use for several years and are published annually by established global organizations (Kaufmann et al., 1999a; UNDP, 2006; ITU, 2007). Additionally,
Diamantopoulos & Winklhofer (2001) establish that the elements of a construct cannot be dropped if the content is valid. Petter et al. (2007) recommend that indicators
Table 1 Descriptive statistics of indicators for the constructs
Construct Indicator N Minimum Maximum Mean SD
National information infrastructure Telephone density (TL_DNST) 144 �1.751 20.680 3.816 4.833 Internet density (INT_DNST) 144 0.000 55.343 7.847 11.041
Personal computer density (PC_DNST) 144 0.000 31.911 3.232 5.573
Television density (TV_DNST) 144 0 9285 206.15 1030.80
Radio density (RADIO) 144 0 32.0 2.537 5.253
Newspaper circulation density (NEWS) 144 0 88.4 15.904 19.759
Governance Effectiveness of central government (GOV_EFF) 144 �1.427 1.442 0.030 0.481 Regulatory quality (REG_QLT) 144 �2.398 1.567 �0.090 0.623 Rule of law (RULE_LAW) 144 �1.181 1.769 �0.062 0.426 Corruption control (CRP_CTRL) 144 �1.690 0.921 �0.014 0.425 Voice and accountability (VOA) 144 �1.285 1.166 0.013 0.424 Political stability (POL_STAB) 144 �2.514 2.078 �0.054 0.675
Socio-economic development Purchasing power parity index (GDP_PPP) 144 0.317 0.941 0.632 0.159
Life expectancy index (L_EXPNDX) 144 0.259 0.901 0.667 0.174
Education index (ED_INDX) 144 0.255 0.973 0.753 0.177
Table 2 VIF scores for indicators in research model
Construct Indicator VIF statistic
Personal computer density
Radio density (RADIO) 1.569
Governance Effectiveness of central
Rule of law (RULE_LAW) 1.507
Voice and accountability
Purchasing power parity
Life expectancy index
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should be preserved even when they reflect non-signifi- cant weightings to their respective constructs where theorization of constructs affirms their content validity and dropping of such indicators would lead to a conceptual dilution the resultant construct. The theori- zation performed in the early parts of this paper reflects that the indicators used are adequately grounded in theory and are a core constituent of their respective constructors. Because of these reasons, we decided not to drop any of the indicators that were statistically insignif- icant in their contribution to each construct, since doing so would dilute the constructs so measured and threaten their content validity.
Assessment of the structural model In PLS, the structural model tests the path coefficients and the R2 values. Path coefficients represent the relationship between dependent and independent con- structs. Results of the assessment of the structural model are indicated in Figure 2. The results for hypothesis testing are presented in Table 4. Our criteria for ‘supported’ is that the path coefficients should be strictly greater or equal to 0.20 and that the P-value for the path coefficient should be less than or equal to 0.05 (in other words, the t-value for the path coefficient should be greater than 1.96). Based on this criterion, two of the three hypotheses – H1 and H2 – were supported. However, hypothesis H3 was not. Probable reasons for lack of support ofH3 are presented
in the discussion section. Power calculations are particu- larly relevant whenever the null is rejected (Baroudi & Orlikowski, 1989) and so we performed a power analysis for H3, the hypothesis that were not supported. The objective of this analysis was to determine the accuracy of
this conclusion that the hypotheses are truly insignif- icant at the 0.05 alpha level. Power is the likelihood of a Type II error, and it requires parameters for sample size, alpha level and desired effect size. According to Cohen (1977), an effect size (d) of 0.2 or less is considered small, that of 0.5 is deemed moderate, while an effect size greater than 0.8 is deemed to be strong. Using the Gpower statistical program, the calculated power for the hypothesis was 0.8192, with a sample size of 144 and an effect size of 0.5. This, according to Cohen’s threshold of 0.80 (1977), allows us to conclude that there is no Type II error and the lack of significance can be believed. The structural model also allows us to assess the degree
to which each dependent variable is explained by its respective independent variables. The measure used to capture this is the R2. R2 values represent the amount of variance explained by independent variables. There were two dependent variables in this study – socio-economic development and governance. Figure 2 presents the R2
results for these variables. Both R2 values were statistically significant (Po0.050) within the context of this study.
Table 3 Item weightings for model’s constructs
Construct Indicator Original sample Sample mean SD SE T-statistics
Telephone density (TL_DNST) 0.240383 0.26119 0.157073 0.157073 1.530389
Internet density (INT_DNST) 0.583559 0.58185 0.154336 0.154336 3.781094
Personal computer density (PC_DNST) 0.368961 0.334576 0.193698 0.193698 1.904825
Television density (TV_DNST) �0.124268 �0.13751 0.090055 0.090055 1.379916 Radio density (RADIO) �0.303982 �0.28064 0.15568 0.15568 1.952611 Newspaper circulation density (NEWS) 0.30866 0.269878 0.138794 0.138794 2.223874
Governance Effectiveness of central government (GOV_EFF) 0.79072 0.641402 0.318159 0.318159 2.485298
Regulatory quality (REG_QLT) 0.144831 0.279882 0.214394 0.214394 0.675537
Rule of law (RULE_LAW) 0.071725 0.281735 0.196019 0.196019 0.365909
Corruption control (CRP_CTRL) 0.249914 0.334356 0.220848 0.220848 1.13161
Voice and accountability (VOA) �0.128397 �0.22318 0.155598 0.155598 0.825186 Political stability (POL_STAB) �0.002318 �0.21299 0.166938 0.166938 0.013883
Purchasing power parity index (GDP_PPP) 0.808691 0.809745 0.255248 0.255248 3.168255
Life expectancy index (L_EXPNDX) 0.089281 0.21695 0.157408 0.157408 0.567197
Education index (ED_INDX) 0.161254 0.215133 0.151896 0.151896 1.06161
Legend: * Item is significant at the p<0.05 level (T >1.661) ** Item is significant at the p<0.01 level (T > 2.367) *** Item is significant at the p<0.001 level (T >3.396)
Governance (R2 = 0.1566)
Social Development (R2 = 0.5777)
Figure 2 Results of the PLS analysis.
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Discussion of results The results of this study reveal that NII has an influence on both governance and socio-economic development in the developing countries. The results also indicate that governance in and of itself has little direct impact on socio-economic development within the context of developing nations. This observation is refreshing as it is informative. Most of the past studies (Easterly & Levine, 1997; Dutta, 2001) indicate that there has been modest to no impact of governance on the improvement of the human development conditions in many devel- oping nations. This is one reason why governance and the strengthening of governance institutions has become one of the key millennium development goals for the international development agencies (IBRD, 2002). However, it is interesting to note that NII influences governance. There has been an increase in concerted efforts to implement e-government systems with the view to easing and enhancing governmental service delivery to citizens, as well as enhancing access to information by citizens. Our research model indicates that if these initiatives are done well, then they stand to leverage the socio-economic development of member nations. It is also interesting to note that NII has direct bearing
on the socio-economic development of member nations. Also supporting the point of view that IT infrastructure influences socio-economic development are Tapscott (1996), Mbarika et al. (2002a), and Meso et al. (2006), among others. Past empirical information systems research points to the fact that information infrastructure has positive effects on socio-economic development – both directly, and through its effects on governance (Finkelstein, 1995; Dyer, 1996; Jessop, 1998; Farazmand, 1999; Kaufmann et al., 1999a; Durant, 2000; Hart, 2001; Islam 2001; Musa et al., 2005a; Meso et al., 2006). Therefore, the results of this study are in keeping with previous studies. This may be a reflection of the contributory effects of NII in providing ‘new’ informa- tion and opportunities to the citizens of these nations. In allowing for freer and easier communication and collaboration with other parties, technologies such as mobile cell-phones and Internet cyber-cafes are empow- ering citizens of these nations. In providing them with access to hitherto unreachable markets and ‘new’ market information, these technologies are shrinking
the distance between suppliers and consumers and squeezing out the inefficiencies attributed to middle- men and other trade intermediaries. The very nature of NII may also be contributing to increases in literacy levels, and a change in hygienic behavior, owing to educational information, that contributes to a reduction in infectious diseases. We must point out that this study was structured as a
quantitative analysis of the impacts of NII on governance and socio-economic development. While we acknowl- edge that there may be unintended consequences of NII, or that the impacts of misusing NII on both governance and socio-economic development may indeed by deleter- ious, we were not able to measure these using the constructs and methods employed in this study. This study’s scope did not allow us to examine the specific ways that NII is being used. We view the study of actual usage of NII as an interesting and necessary extension of this study. An examination of the precise usage is best conducted in in-depth field studies that we propose need to be undertaken to provide further verification of the results observed in this study. In summary, the study’s results provide strong empiri-
cal support for the research model in this study. The tests confirmed the model’s rigor and relevance in all its antecedents. The results also provide grounding for in- depth studies in the specific usage of NII within various countries and how such usage impacts both governance and socio-economic development. In this regard, the results provide empirically validated information on the value (perhaps potential value) of NII solutions within the context of developing nations. What is important about the results from this study is that they provide empirical support for the impacts of NII in the advance- ment of developing nations. The results indicate that the development of information infrastructures should impact the quality of governance and socio-economic development in the developing countries. Therefore, developing countries stand to benefit by leveraging their NII. Although several past studies such as Durant (2000),
Dyer (1996), Farazmand (1999), Finkelstein (1995), Hart (2001), Jessop (1998), and Kaufmann et al. (1999a) have suggested that governance is a significant determinant and contributor to socio-economic development in
Table 4 Results of hypothesis testing with PLS
Hypothesis Original sample Sample mean SD SE T-statistics Result
H1: NII influences the quality of governance
in developing countries.
0.335 0.439 0.086 0.086 3.923 Supported
H2: NII influences the level of socio-economic
development in developing counties.
0.682 0.653 0.056 0.056 12.135 Supported
H3: The quality of governance influences the
level of socio-economic development in the
0.144 0.175 0.089 0.089 1.616 Not supported
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developing countries, our study results did not elicit a similar result. However, the relationship between govern- ance and the socio-economic development construct was in the expected direction (i.e., governance influences socio-economic development). Several reasons can ex- plain this, but these remain to be empirically validated. First, the strength of this relationship may have been weakened by the fact that this study limited itself to developing countries. It may be that because the vast majority of low-scoring countries on the governance scale are developing nations, the linear association between governance quality and socio-economic devel- opment is suppressed. We note that published research examining the effects of good governance on socio- economic development has either included a balanced sample of both the developed and the developing nations (Dyer, 1996; Finkelstein, 1995; Jessop, 1998; Farazmand, 1999; Kaufmann et al., 1999a; Durant, 2000; Hart, 2001; Islam, 2001), or has taken the format of a single-nation case-study (Islam, 2001). This limitation in our study may have caused the insignificant governance to socio- economic development linkage. Second, archival developmental data for underdeve-
loped countries still suffers from missing data values. Our dataset reveals that most of missing data were in variables that were used to operationalize socio-economic devel- opment. While the statistical tool PLS graph is capable of handling cases that have missing data, it is likely that more significant results would have been observed had these cases been fewer in number. It is gratifying, though to observe that despite these limitations, the direction- ality of the relationship was consistent with previous research. Therefore, while our study did not come to the
expected conclusions with respect to the impacts of governance on socio-economic development, we can state that our findings are in the same direction as past studies where this relationship was found to be signifi- cant. This allows us to infer that adequate investments in information infrastructure not only enhance quality of governance, but also contribute to the enhancement of governance’s effects on socio-economic development. In this light, our finding concurs with Dutta’s study (2001).
Conclusion This research examined the nature of the relationship between NII and governance within developing coun- tries. The results partially confirm that the NII matters. It is significantly related to governance. Moreover, higher levels of NII dissemination relate to significantly better performance in governance. The findings in this paper confirm the belief that concerted efforts to increase the levels of NII in developing countries is a step in the right direction. Through the direct impacts of NII on govern- ance, enhancing NII levels in these countries should also contribute to the eventual improvement in the quality of governance. Enhancement of the NII also leads to improvements in
the levels of socio-economic development. Therefore, enhancing the information infrastructure in these coun- tries is bound to contribute significantly toward the acceleration of sustainable socio-economic development and the consequent integration of these countries into the global economy. However, much transformation is needed in the information infrastructures of these countries to foster the benefits that can be reaped from extensive NII. Historically, poor governance (coupled with dictatorial
regimes) has been a major characteristic of developing countries. Most of these countries have traditionally turned to the ‘West’ (Europe or North America) for a ‘hand-out’ to address problems of poor governance through loans as a step to imperfectly resolve these problems. Our study sets forth the proposition that the broad diffusion of NII may be a starting point, or perhaps a necessary but not sufficient condition, toward sustainable improvement of governance in developing countries. We neither claim that NII will amount to successful govern- ance, nor that it will instantly transform poorly governed nations into role models of exceptional governance. What we do posit is that capabilities (such as electronic voting, web-based reporting of government spending, etc.) made possible by information infrastructures present a possible avenue for the effective delivery of government services, operationalization of functional and sustainable govern- ance frameworks, and the implementation of efficient government operations and for the sustainable socio- economic development of developing nations.
About the authors
Peter Meso is a member of faculty in the Computer Information Systems Department of Georgia State Uni- versity’s J. Mack Robinson College of Business, located in Atlanta, GA, U.S.A. He is also the Co-Editor-in-Chief of the African Journal of Information Systems and a member of the Editorial Review Boards of the Journal of Global Information Management and the Electronic Journal of Information Systems in Developing Countries, respectively.
He earned his Ph.D. degree in Information Systems from Kent State University, and holds a Bachelor of Science degree (Information Systems) and a Master of Business Administration (MBA) degree from the United States International University – Africa. He conducts research in the areas of information systems development and global information technology with a key interest in researching information technology in the developing economies.
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His research appears in a number of journals such as Communications of the ACM, Information Systems Research, Information Systems Journal, Journal of Systems and Software, Information Systems Management, Journal of Global Informa- tion Management, IEEE Transactions on Information Systems in Biomedicine, Electronic Journal of Information Systems in Developing Countries, and the Journal of the Association for Information Systems. He teaches courses in the areas of information systems analysis design, web applications development, and computer programming languages. He is a member of the Association for Information Systems and the International Federation for Information Processing Working Group 9.4.
Philip F. Musa is an Associate Professor of Management and Information Systems in the School of Business at the University of Alabama at Birmingham. He teaches various courses such as project management, supply chain management, quality management, strategic informa- tion systems, electrical engineering, operations manage- ment, etc. He holds a B.S.E.E., M.S.E.E., M.B.A., and Ph.D., all from Texas Tech University. He has published research in various prestigious journals such as Commu- nications of the ACM, Information Systems Journal, Commu- nications of AIS, Journal of Global Information Technology Management, Journal of Global Information Management, Journal of Information Systems Education, etc. He has served on special assignments related to Ph.D. programs to other universities around the world. In addition to serving on the editorial boards of several academic and practi- tioner journals, he has presented at and published in dozens of proceedings of national and international Information Systems conferences such as Americas Con- ference on Information Systems, the International Fed- eration for Information Processing, Information Resource Management Association, Global Information Technol- ogy Management, Decision Sciences Institute, among others. He has also served as chair or on program committees of many of the professional conferences. He is an academic professional member of APICS, senior member of the Institute of Electrical and Electronics Engineers (IEEE), member of the Association of Informa- tion Systems (AIS), and a lifetime member of Phi Kappa Phi. He is a licensed professional engineer (P.E.) with backgrounds in electrical engineering and semiconductor industry. He is also a certified supply chain professional (CSCP).
Detmar Straub is the J. Mack Robinson Distinguished Professor of Information Systems at Georgia State University. He has conducted research in the areas of net-enhanced organizations (e-commerce), information security, technological innovation, IS methodological issues, and international IT studies. He holds a D.B.A. (Doctor of Business Administration) in MIS from Indiana and a Ph.D. in English from Penn State. He has published 140 papers in journals such as MIS Quarterly, Management Science, Information Systems Research, Organization Science, Journal of MIS, Journal of AIS, Information & Management, Communications of the AIS, IEEE Transactions on Engineering Management, Communications of the ACM, OMEGA, Acad- emy of Management Executive, and Sloan Management Review. He is the Editor-in-Chief of MIS Quarterly, with a term starting in January of 2008. Previously he has served as Senior Editor for MIS Quarterly, Information Systems Research, Journal of the AIS (JAIS), and DATA BASE. He was also Co-Editor of DATA BASE for Advances in Information Systems. Previously, he was Associate Editor for Manage- ment Science as well as an editorial board member on a host of other journals. His consultancies with industry have been in the areas of information security, e-commerce, and technological innovation. He teaches masters level courses at Georgia State University in: E-commerce Strategy, IT Strategies for Management, Systems Integration and IT Outsourcing, International IT Policies and Issues, and Computer Security Manage- ment, and doctoral seminars in Quantitative Methods in IS Research, and Experimental Design. He serves as Director of Research and Doctoral Programs in the Robinson College of Business. He is former VP of Publications for the Association for Information Systems. He was appointed AIS Fellow in 2005.
Victor W. Mbarika is on faculty in the College of Business at Southern University and A&M College. He holds a Ph.D. in Information Systems from Auburn University. His research on information and communica- tions technology (ICT) diffusion in developing countries and his research on multimedia learning has been published (or are forthcoming) in 100 academic outlets in the form of books, refereed journals, conferences, and book chapters. He is a member of the Association of Information Systems (AIS), the Institute of Electrical and Electronics Engineers (IEEE), and the Information Re- sources Management Association (IRMA).
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- Information infrastructure, governance, and socio-economic development in developing countries
- Research model and hypotheses
- Relating NII to governance
- Relating NII to socio-economic development
- Relating governance to socio-economic development
- Research design
- Operationalization of constructs
- Analysis and results
- Assessment of the measurement model
- Assessment of the structural model
- Discussion of results