Association for Information Systems AIS Electronic Library (AISeL) GlobDev 2014 Proceedings Annual Workshop of the AIS Special Interest Group for ICT in Global Development 12-14-2014 A Cluster Analysis of Research in Information Technology for Global Development: Where to from here？ Jie Xiong University of Nebraska at Omaha, jxiong@unomaha.edu Sajda Qureshi University of Nebraska at Omaha, squreshi@unomaha.edu Lotfollah Najjar University of Nebraska at Omaha, lnajjar@unomaha.edu Follow this and additional works at: htp://aisel.aisnet.org/globdev2014 Recommended Citation Xiong, Jie; Qureshi, Sajda; and Najjar, Lotfollah, "A Cluster Analysis of Research in Information Technology for Global Development: Where to from here？" (2014). GlobDev 2014. Paper 1. htp://aisel.aisnet.org/globdev2014/1 his material is brought to you by the Proceedings Annual Workshop of the AIS Special Interest Group for ICT in Global Development at AIS Electronic Library (AISeL). It has been accepted for inclusion in GlobDev 2014 by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org. Xiong et al. Cluster Analysis of Research in ICT4D A Cluster Analysis of Research in Information Technology for Global Development: Where to from here？ Research-in-progress Paper Jie Xiong Sajda Qureshi University of Nebraska at Omaha 6001 Dodge Street, Omaha, NE 68182 jxiong@unomaha.edu University of Nebraska at Omaha 6001 Dodge Street, Omaha, NE 68182 squreshi@unomaha.edu Lotfollah Najjar University of Nebraska at Omaha 6001 Dodge Street, Omaha, NE 68182 lnajjar@unomaha.edu ABSTRACT While research in Information Systems recognizes the importance of Information Technology in a global context, it continues to focus on a narrow view of IT adoption. In recognizing that the majority of innovations in IT are taking place in developing countries, it is important to find out what research is being undertaken to understand the effects of the different technologies on development outcomes. This paper conducts a cluster analysis of 214 papers from the SigGlobDev Workshop, the Information Technology for Development Journal and other Information Systems Journals and conferences which have published papers in Information Systems and Global Development. This analysis throws light on the ways in which research is being undertaken in this area. The contribution of this paper lies in identifying the key areas in which Information Systems research is addressing the ways that development outcomes are or are not being addressed, and it highlights areas that still need to be investigated. Keywords: IT for Development, Economic Development, Social Development, Human Development, Cluster Analysis Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014. Xiong et al. Cluster Analysis of Research in ICT4D INTRODUCTION It appears that current research in Information Systems (IS) focusses on how Information Technology (IT) can be adopted by users. Yet the majority of people in organizations adopt technology on a regular basis, and gains from the adoption of IT have only been assessed in a rudimentary fashion such as return on investment, net present value or transaction cost analysis. The bottom line of a business, community or society relating to its survival and growth has not been connected to its use of IT. Limited research has been conducted in IS into studying the outcomes of IT Adoption beyond variables affecting the user perceptions of technology. One way of assessing the ways in which technology can improve the lives of people is by assessing the ways in which the majority of businesses in the world that are micro-enterprises adopt the technology. There is evidence to suggest that when these businesses use IT in innovative ways, they grow by a factor of 3.8 (Qiang et al. 2003). Although innovations in Information Systems have had an impact on multiple aspects of the way organizations do business, and how communities and regions grow, little is known about how this impact takes place. Questions arise, such as, Why do we need to know about how IT brings about Development? Why does it matter? While the majority of innovations in Information Systems appear to be taking place in the developing world, little research in Information Systems has attempted to understand why this is the case? And, how are these innovations affecting the lives of people? Cell phones are being used to make payments at street markets and to drive agriculture supply chains in African and Asian countries. Mobile technologies also support the transfer of funds between people in Asia, Africa and the Middle East. The world’s largest numbers of users of mobile payments reside in Kenya. Fishermen and farmers are able to find new markets by using simple text messaging; new businesses are developing which support the increased demand fueled by the liquidity and income generated by new markets. The Economist reported that for every 100 cell phones in a typical developing country, gross domestic income rises by almost a percentage point. This suggests that there is growth in incomes through the use of mobile technologies (Economist, 2009). Recent events in the world have shown that Information and Communication Technologies (ICTs) can bring about significant changes in the lives of people. For example, the use of social Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D media and mobile communications have brought about changes in the way people interact with their governments - as can be seen in the Arab Spring – and the way they do business and interact in their communities. However, what research is being undertaken to understand the effects of technology on development outcomes? And how is this research contributing to what we already know? Are there any connections between levels of analysis, research methods and contributions development outcomes? Because there are many different ways of adopting IT, this paper provides a theoretical and empirical basis of understanding the outcomes of using IT. It appears that the innovative ways in which Information Systems are used in different regions enable these regions to develop. The purpose of this paper is to find out what is known about the effects of Information Technologies on how development takes place. We review key papers in leading journals and workshops that report on these innovations. Our analysis samples 214 papers from the SigGlobDev Workshop, the Information Technology for Development Journal and other Information Systems Journals and conferences that have published papers in Information Systems and Global Development. We hypothesize that the different development outcomes, including social development, economic development, and human development, are associated with the research methods scholars choose, as well as different levels of analysis. We follow a cluster analysis method to see how these papers are grouped with each other. This analysis throws light on the ways in which research is being undertaken in this area. The contribution of this paper is in identifying the key areas in which Information Systems research is addressing the ways in which development outcomes may or may not be addressed and highlights areas that still need to be investigated. THEORETICAL BACKGROUND The concept of development has its roots in innovation of the firm. Development is defined as “changes in the system that arise from within the system” (Schumpeter, 1934, p.63). Development is often used to describe growth in organizations and in the regions in which they reside. ICTs and development can be viewed as socioeconomic improvements through transfer and diffusion (Avgerou, 2010). Economic development can entail political, opportunity, and economic freedom (Sen, 1999). As ICT development entails increasing diversity of research topics, research methods, and research implications, we surveyed the literature in the Information Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D System Research areas to understand the role of ICT as an artifact in development (Sein and Harindranath, 2004, Taylor et al., 2010; Orlikowski and Iacono, 2001). We hope to derive a common body of knowledge that can be shared in the IS area (Hirschheim and Klein, 2012). Traditionally, IS research has been driven by areas such as adoption and diffusion of IT (Davis 1989, Harrison et al. 1997, Venkatesh, et al. 2003, Gefen, et al. 2003) for developing methods and approaches for implementing IS globally and for managing dispersed collaborative environments in a variety of contexts including off-shore outsourcing (Carmel and Nicholson, 1993; Tractinsky and Jarvenpaa 1995, Willcocks et al. 2004, Sahay et al. 2003, La Rovere & Pereira, 2000, Watson et al 1997). Since IS research is both a science and a profession, generalizability is a major concern in IS research (Lee and Baskerville, 2003). Similarly, research in the field of Information Technology for Development (ITD) has grown to provide specific insight and approaches through which Information Systems can be implemented and adopted in a variety of cultural contexts. It is the study of how innovative applications of IT bring about improvements in the lives of people. These improvements are assessed in terms of economic, social and human outcomes. ITD research has made contributions in providing equitable access to information and knowledge in areas such as education (Rodrigues and Govinda 2003; Rodrigo 2003, Scheepers and de Villiers 2000), healthcare (Braa et al 2004; Mosse and Sahay 2005; Kimaro and Nhampossa, 2005), software development (Chudnovsky and Lopez 2005; Tan and Leewongcharoen, 2005; Han, 2000), reduction in poverty (Cecchini and Scott 2003; Kenny, 2000; Qureshi et al 2009), better government (Tan and Leewongcharoen, 2005; Walsham and Sahay, 1999; Qureshi, 1998), and off-shore outsourcing (Sahay et al., 2003; Preis-Heje et al., 2005; Hawk and McHenry, 2005). Now that the effects of globalization permeate many parts of life, organization, and society, the relevance of ITD research for the MIS community is evident. Although ICT has been conceptualized as a tool to achieve social, economic, and human development, little is known about how this tool may actually enable development. Brown and Grant (2010) argue that the existing research in ICT for Development can be categorized into “For Development” and “In Developing” countries by reviewing 184 journal and conference articles from 1982-2007. ICT for Development research focuses on the link between ICTs and development, and empowering marginalized populations, while the research of ICT in Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Development focuses on cultural implications and local adaptation (Brown and Grant, 2010). It is argued that increased research attention should be placed on research in developing contexts, that is, “For Development.” Avgerou (2008) suggested that IS research in development should engage with the study of IS innovation with particular social-economic rationales, especially in development countries. Sein and Harindranath (2004) also proposed ICT use, ICT views, and ICT impact as key ICT artifacts, to understand the role of ICT in national development. Some suggest that in a set of emerging economies, IT investments achieved consistently higher growth rates of GDP and productivity (Kraemer and Dedrick, 1994; Samoilenko and OseiBryson, 2011). However, Bollou and Ngwenyama (2008) investigated the total factor productivity of ICT sectors in six West African countries from 1995 to 2002. They determined that total factor productivity of those countries did not benefit from the investment, because “Using ICT as an engine of economic growth is complex” (Bollou and Ngwenyama, 2008, p303). Heeks (2002) pointed out that the accessibility of IS failure in developing countries is not as easily identified, compared to the industrialized countries. Pick and Azari (2008) conducted research on the influence factors on ICT from 71 developing and developed countries. They identified technology attributes that are strongly associated with foreign direct investment (FDI), government prioritization of IT, and education. These authors suggested that there was a lack of case study research from developing countries about how ICT could leverage economic, social, and human development. The definition of development remains controversial; the majority of definitions of ‘development’ carry implicit value assumptions (Summer and Tribe, 2008). Willis (2011) placed development theories within a historical context. Escobar (1995) conducted a discussion of alternative visions for a post-development era, suggesting that current views on development prevent people in developing countries from coming out of poverty. The various applications of ICT have been seen to fuel globalization. A number of theories have been developed on the nature and impact of the process of globalization (Castells 2001, Held et al 1999, Hirst and Thompson 1996, Robertson 1992, Scholte 1993, Wallerstein 1974, Giddens 2003). Castells (2000) was notable in his description of globalization fueled by IT; he suggested that what characterizes the current technological revolution is the application of knowledge and information within knowledge generating and information processing devices. The following sections describe what is known about the three aspects of development: economic, social and human. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Economic Development The most discusses aspect of development, Economic Development, can be viewed as quantitative and qualitative improvement in the economy. Economic development as a concept entails a broad view of economic growth. Malecki (1997) distinguished between economic growth and economic development. Economic growth “increases in the quantity or the value of the goods and services” (Malecki, 1997, p1) and economic development “leads to qualitative improvements in life” (Malecki, 1997, p1). As Sen (1973, p748) pointed out, “economic growth is one aspect of the process of economic development.” Economic development involves the growth and improvement of factors such as literacy rates, poverty rates, employment rates, GDP per capita, access to healthcare, and government investment. On the other hand, care must be taken to understand ICT investment and strategies towards development countries. Ewusi-Mensah (2012) provided analysis associated with IT diffusion in sub-Saharan Africa. He identified inadequate IT resources, hindered levels of IT assimilation, and the inadequate human resources as the main reasons the impact of IT on the economy is problematic. Essentially, as a country level indicator, economic development is highly related to human development in education, health, and income. Economic growth and development are often observed simultaneously. For example, Kamal et al. (2008) investigated ICT capacity and skills, and their effect on economic development in 183 countries of the United Nations. The authors showed that increase in skill development and ICT capacity development would ultimately lead to economic development. Jiménez et al. (2013) investigated the Cobb-Douglas relationship, between GDP per capita, info-density, tertiary and secondary education, and labor from 72 countries. They pointed out that there is an imbalance between developed and developing countries in the ICTs’ effect on GDP per capita. As a key determinant of a nation’s development of production, technology can be explained as an exogenous factor which could interact with other determinants, such as capital and labor, and lead to economic growth (Mankiw, 2012). Mankiw et al. (1992) provide an augmented Solow Growth Model and analyze the data of 121 countries from 1960-1985. It has been observed that there are not substantial externalities to the accumulation of physical capital, which provides the foundation for emerging economies in the world, such as Brazil, Russia, India, and China Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D (BRIC) to catch up and to achieve “leapfrogging”( Brezis et al., 1993). That is, new technology enables developing countries to use lower wages to achieve new leadership (Brezis, 1993; Lee and Lim, 2001; Steinmueller, 2001). Samoilenko and Osei-Bryson (2011) used the Solow Growth Model to show that IT can have an effect on productivity in certain types of countries under certain conditions. Disparities occur in all societies, including those considered to be developed. Chakraborty and Bosman (2005) measured the inequalities in home PC ownership in the United States by applying the Lorenz Curve and the Gini coefficient. Based on the data gathered in 2011, the authors found that inequalities in PC ownership are substantially smaller among white households than among African American households in the United States. It is important to bridge those gaps because the use of IT appears in both developed and developing areas. There are several international organizations, for example, International Telecommunication Union (ITU), United Nations Conference on Trade and Development (UNCTAD), UNESCO Institute for Statistics (UIS), Organization for Economic Co-operation and Development (OECD), UN Department of Economic and Social Affairs (UNDESA), and World Bank, have been focused on the measurement of and access to ICT infrastructure. The core indicators for measuring access to ICT are radio, telephone, television, and computer (ITU, 2014). Social Development Social development is governed by many factors such as capital, technology, and government support. Social development tends to focus on ‘putting the people first’ in the development process (World Bank, 2014). Warschauer (2004) introduced the idea of interaction between ICT and social inclusion. Social relations shape access to ICT, as well as human and social development (Coleman, 1988). The concept of social capital is also introduced; social capital is defined as “aspect of social structures, and the facilitation certain actions of actors within the structure” (Coleman, 1988, p.98). The benefit of ICT can be shared through social development, which will increase social capital (Warchauer, 2004). Midgley et al. (1986) pointed out the importance of community participation in social development. Although those changes, especially from the Internet (Castells, 2001) will provide challenges, opportunities, and risks for emerging areas (Mansell and Wehn, 1998; MoralesGomez and Melesse, 1998), it is important to understand how those changes could lead to Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D sustainable development (Credé and Mansell, 1998). Byrne and Sahay (2007) conducted a participatory design for social development in South Africa. They showed that community plays a crucial role in social development. On the other hand, it is important to understand the issue of cost and wealth distribution, access, ownership and control, and culture when ICT contributes to social development (Morales-Gomez & Melesse, 1998). Government has an effect on social development. E-government, defined as “The employment of the Internet and the world-wide-web for delivering government information and services to the citizens,” e-learning - the application in education - and e-Health, healthcare practice using the Internet (United Nations, 2006), play a critical role which could lead to social development, especially for marginalized people in developing countries (Unwin, 2009). Human Development The idea of human development began a revolution of its own in the 1950s and early 1960s with the research of Schultz (1961), Mincer (1958), and Becker and Chiswick (1966). Economists current place much greater emphasis than in the past on the importance of knowledge and information to development of countries and of individuals (Becker and Woessmann, 2011). Human Capital has a role in lowering economic costs or in elevating customers’ willingness to pay (Porter, 1985, p. 394). Human capital is defined and created by changes in individuals which increase skills and capabilities, enabling people to behave in new ways (Coleman, 1988). Human capital also can be described as all the competencies and commitments of the people within an organization (Ceridian, 2007). Human capital may be assessed in terms of education and social embeddedness. Social embeddedness is defined as the degree to which individuals or firms are enmeshed in a social network (Granovetter, 1985). Boyer-Wright and Kottemann (2008) compared e-government issues in emerging parts of the world, including Eastern European and Asian countries, and in advanced countries. They also noted that education and on-the-job training of individuals plays an important role in ICT use in the three domains. Ngwenyama and Morawczynski (2009) determined that economic factors, human capital, geography, and civil infrastructure factors should be considered during analysis. Baliamoune-Lutz (2003) argued that ICT diffusion is not associated with education, a conclusion based on cross-sectional data from the World Economic Forum’s (WEF) Government Information Technology Report (GITR). Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Education and training expenditures are the key variables used to assess human capital. Education in its broadest sense is the means through which aims and habits of a group of people are sustained from one generation to the next. Training is the acquisition of knowledge, skills, and competencies as a result of learning vocational or practical skills, and increasing knowledge that relate to specific useful competencies. Training has the specific goals of improving an individual’s capability, capacity, and performance. Training forms the core of apprenticeships and provides the backbone of content at institutes of technology (also known as technical colleges or polytechnics). As a socioeconomic improvement, it is critical to understand how ICT could lead to social, economic, and ultimately human development (Avgerou, 2010). In sum, economic development, social development, and human development are not independent systems. Although human development is closely associated with social development and economic development, economic development outcomes are also associated with them. This relationship can be cyclical in some cases, bringing negative growth cycles as well as positive growth cycles (Qureshi 2005, Qureshi et al 2009). CONCEPTUAL RESEARCH MODEL Although development outcomes can be assessed in multiple ways through economic, social and human development lenses, research methods and levels of analysis also vary. Based on the discussion of the literature above, we hypothesized that the different development outcomes social development, economic development, and human development - are associated with the research methods scholars choose as well as different levels of analysis. Figure 1 describes the conceptual research model we propose. Research methods that can be identified in the IS field range from qualitative action research and case studies to quantitative methods, which range from experiments to statistical analysis methods. There are also a range of theoretical papers that report literature reviews and develop models or frameworks. IT for Development research tends to go beyond the conceptual, individual, group and organizational levels of analysis to the country level of analysis. In this analysis these three aspects of research, research method, level of analysis and development outcomes, are used as the basis of coding the articles collected. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Figure 1. Conceptual Research Model Level of Analysis Conceptual, Individual, Group, Organizational, Country Research Method Action Research, Case study, Experiment-Statistical Analysis, Literature, Frameworks-Model development Development Outcome Social, Economic and Human RESEARCH METHODOLOGY Cluster Analysis was conducted in this research to identify the key themes. Cluster Analysis has been widely applied in the IS research field to help researchers classify and unravel entities in a given context (Balijepally, Mangalaraj, & Iyengar 2011). Particularly, two-step cluster was adopted, because the relocation and hierarchical clustering methods did not directly address the issue of determining the number of clusters (Bacher, Wenzig, & Vogler, 2004). The two-step cluster could sufficiently contain both continuous and categorical variables, which provided opportunities to extend this research in the future. Two-step cluster analysis in SPSS involves two steps: the pre-cluster data stage, which adopts a sequential clustering approach (Theodoridis and Koutroumbas, 1999), and grouping data into sub-clusters, using agglomerative hierarchical clustering methods (Bacher, Wenzig, & Vogler, 2004). Cluster analysis is considered to be a powerful tool in IS research, because it permits researchers to examine the socio-technical phenomenon through interaction with organization, technology, and people (Balijepally et al., 2011). Lowry et al. (2013) conducted cluster analysis on top IS journals; they identified MISQ, ISR, and JMIS as Tier 1 clusters, and EJIS, ISJ, JAIS, and JSIS as Tier 2 clusters. Because of the exploratory setting of the proposed research hypothesis, twostep cluster analysis in SPSS was selected. Data was collected from recent journals, conferences, and workshop publications. In order to triangulate the cluster analysis, we conducted a test of independence. This was conducted to find out if there was any correlation between the variables to triangulate the findings from the exploratory cluster analysis. Pearson's chi-squared (χ2) test for independence Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D was conducted to further explore if the three dimensions/categories: research methods, level of analysis, and development outcomes. DATA COLLECTION This study carried out content analyses of publications in IS research as they related to how ICT related to Development outcomes. Since the majority of ITD has been reported since 2008, this research was focused on publications from 2008-2014. However, other important and representative IS journals and conferences from 2002-2014 were also included in the research. The major journals in MIS that are highly cited were scanned for the terms “Information Technology for Development.” The journals that produced the most papers in this area are: the Information Technology for Development Journal, Senior Scholars' Basket of Journals 1 : European Journal of Information Systems, Information Systems Journal, Information Systems Research, Journal of AIS, Journal of Information Technology, Journal of MIS, Journal of Strategic Information Systems, MIS Quarterly, and Annual SIG GlobDev Pre-ICIS Workshop. We selected these journals and workshops because they represent the frontier of research in IS, especially from IT for development. The combination of journals and conferences provided upto-date research trends and insightful research analysis. Particularly, our sample contained comprehensive collections of all SIG GlobDev Pre-ICIS Workshop publications from 20082013. Table 1. Description of Data Paper Resources Annual SIG GlobDev Pre-ICIS Workshop The Journal of Information Technology for Development (ITD) Other Important and Representative IS journal and conference publications Total 1 Time Frames 2008-2013 2008-2014 Number of Paper 118 74 2002-2014 22 http://aisnet.org/general/custom.asp?page=SeniorScholarBasket Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 214 Xiong et al. Cluster Analysis of Research in ICT4D Through the above selection and searches by using keywords “development” and “Information Technology,” 217 publications were gathered for this study. Following Zhang et al.’s (2011) approach, each paper was examined and coded using the concepts discussed in the conceptual development section. Step one in the research involved examining, coding and validating the results. Step two involved the revalidation of a random sample of the results. Table 1 provides the description and distribution of the data. MODE OF ANALYSIS Each paper gathered was further coded using the concepts discussed in the conceptual development section. There are nine variables that needed to be coded into the spreadsheet: publication year, publication type, key words, research methods, demographics, findings, development outcomes, theory base, and level of analysis. At the first stage of exploratory research, research methods, development outcomes, and level of analysis were selected and identified as important variables. Table 2 provides an overview of the coded variables from the paper. Publication Year Publication Type Key Words Research Methods Demographics Findings Development Outcomes Theory base Level of analysis Table 2. Variables from the Paper The Year of Publication Paper can be either journal, workshop, or conference publications. Keys words from the publication Action Research, Case Study, Literature Review, Model Development, and Statistical Analysis The location where the study was studied Findings of the paper Economic Development, Human Development, Social Development Different theories that authors adopt, e.g., UTAUT, Sen’s Capability Framework. Conceptual, Country, Group, Individual, and Organizational Research methods in the sample of papers we identified are classical research methods that can be observed from IS research, including Action Research, Case Study, Literature Review, Model Development, and Statistical Analysis. Development outcomes contained the three types of development which were discussed in the theoretical background, including economic development, social development, and human development. The third variable we identified was the level of analysis, which contained Conceptual, Country, Group, Individual, and Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Organizational levels of analysis. The other variables we gathered and coded will provide the opportunity to further explore the data in future research. RESULTS AND ANALYSIS Cluster analysis enables us to discover structures in data without explaining why they exist. There are certain determining factors affecting development outcomes: research method, theory base, level of analysis, and location of the study. The cluster analysis (Hair et al., 2006) using SPSS version 21 was conducted on the coded 214 papers. Seven papers were excluded due to incomplete data. Two-way cluster analysis was conducted, and three clusters were generated. Table 3 provides information about the cluster distributions. Table 3. Cluster Distributions N % of Combined % of Total 1 85 41.06% 39.7% 2 48 23.19% 22.4% Cluster 3 74 35.75% 34.6% Combined 207 100.0% 96.7% Excluded Cases 7 3.3% Total 214 100.0% The three clusters that were identified contain 85 (41.06%), 48 (23.19%), and 74 (35.75%) publications, respectively. Table 4 below provides the summary of the sample data findings. Table 4. Summary of the Sample Data Findings Type Number Action Research 7 Case Study 86 Literature Review 17 Research Methods Model Development 50 Statistical Analysis 47 Total 207 Conceptual 21 Country 77 Group 4 Level of Analysis Individual 35 Organizational 70 Total 207 Economic Development 86 Human Development 40 Development Outcomes Social Development 81 Total 207 Dimension Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Percentage 3.38% 41.55% 8.21% 24.15% 22.71% 100% 10.14% 37.20% 1.93% 16.9% 33.8% 100% 41.55% 19.32% 39.13% 100% Xiong et al. Cluster Analysis of Research in ICT4D There are 86 papers that used case study as the main research method, which represented 41.55% of all research method chosen from the sample. The second and third most frequently used methods are model development and statistical analysis. Only seven papers from the sample selected action research as the research method. In terms of level of analysis, the majority of the papers focused on country, organizational, or individual level analysis. Very few research papers focus on group level analysis. The most-studied level of analysis in the sample of papers studied was the country level of analysis. As is illustrated in Figure 2, studies in global development were not limited to developing countries but also included developed countries such as the United States, Australia and the Netherlands. It is interesting to note that the majority of country-level studies in the development outcomes of IS are in India and the USA. The countries studied in the 207 papers analyzed in this sample are distributed as follows: Figure 2. Main Countries Of the total number of papers analyzed, the papers appeared to cluster around social and economic development, human development with case study, model development and statistical analysis methods being the most used. The following figure 3 illustrates the distribution of papers: Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Figure 3. Distribution of total Papers In terms of development outcomes, a combination of economic and social development were found and social and human development papers appeared to stand in their own cluster. As stated above, three clusters were identified from the 207 publications. The following sections provide a specific description of each cluster. Cluster 1- Economic and Social Development at the Country level The first cluster contains the largest number of papers, 85 across 207 publications, which covers 41.06% of the data. As data presented in Table 5 indicates, 75.29% of the papers in this cluster comprise country-level analysis. Among the groups, development outcomes arrive at either economic development (50.59%) or social development (49.91%). In terms of research methods, a mixture of case study (24.71%), literature review (14.12%), model development (30.59%), and statistical analysis (30.59%) were observed. This distribution is illustrated in figure 4. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Figure 4. Economic and Social Development Country Level The clustering of papers at the level of analysis indicates that economic and social development outcomes are most studied. Although there is a significant correlation between level of analysis and development outcomes (see appendix 1), it appears from a review of the papers in this cluster that the main contributions in this cluster relate to the digital divide, mobile penetration and payments, tele-centers, telecommunications, and on cyber-crime and corruption. Models and frameworks used were primarily Sen’s capability approach and statistical analysis at the macro level. Cluster 2-Human Development at the Group Level Members from cluster 2 represented 48 (23.19%) of the sample. This was the smallest of the three clusters. More than half (54.17%) of the papers in this cluster comprised research at the group level. We also observed that there was a mixture of research methods. 81.25% of the papers in this group studied human development, and the rest of the papers (18.75%) studied social development. Economic development was not observed in this cluster. This cluster is illustrated in Figure 5. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Figure 5. Human Development at the Group Level In addition to the types of papers observed in cluster 1 on the digital divide, mobile phones and the digital divide mostly using the Sen Capability model, this cluster was also comprised of papers on crowdsourcing, Massive Open Source On-Line Communities, eLearning and education. The key characteristic of this cluster is that human development outcomes are studied at the group level. The group level is also seen to encompass communities that use ICTs to achieve better livelihoods. Cluster 3- Economic and Social development of Organizational Case Studies The third cluster was comprised of 74 papers, or 35.75% of the papers from this sample. In this group, more than half of the research methods used in these papers were case studies (56.76%). In terms of level of analysis, 85.14% of the papers focused on organizational level analysis. In development outcomes, 98.65% of the papers in this cluster focused either on economic development (58.11%) or social development (40.54%). This cluster is depicted as follows: Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Figure 6. Economic and Social development of Organizational Case Studies Papers in this cluster were comprised of ethnographic studies, ICT intermediaries, participation, mobile and telecenter usage, health information systems and small business entrepreneurship through ICTs. It appeared from the papers in this cluster that case studies in organizations relate primarily to how people may achieve better economic livelihoods for themselves, and how social capital and social embeddedness may enable social development outcomes. These papers showed that it is possible to arrive at conclusions based on case studies of economic and social development outcomes. We know from the above literature review that social and economic development outcomes are interconnected. The results of our analysis confirm these connections and show that contributions are being made through both qualitative and quantitative methods. The following Table 5 provides a summary of the key content of each cluster described above. Triangulating this analysis with a test of independence between the three sets of variables (see appendix 2), we found that there is a significant correlation between: 1) levels of analysis and development outcomes and 2) levels of analysis and research methods. However there was no significant connection between development outcomes and research methods. These findings suggest that it is the level of analysis that is most important in helping researchers in our field arrive at contributions to development. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D Table 5. The Cluster Content Research Methods Cluster 1: Country level economic development (n=85) Cluster 2: Group level analysis on human development (n=48) Model Development and Statistical Analysis Case Study, Model Development, and Statistical Analysis Cluster 3-Organizational level case studies on economic and social development (n=74) Case Study Level of Analysis Country Development Outcomes Economic and Social Group Human and Social Organizational Economic and Social The lack of clustering of conceptual and individual levels of analysis, and action research and literature review research methods suggest that these may be ways in which contributions to development need to be made. An area that still needs to be investigated in more depth are human development outcomes at the individual level. Given that the majority of IS research is at the individual and organizational level, it is surprising to see that limited research on development outcomes particularly at the individual and conceptual level is being undertaken. While conceptual papers abound in both IS literature and in ITD literature, it is interesting to note that conceptual papers and literature reviews that are currently published in our field rarely offer insights into development outcomes. CONCLUSIONS, LIMITATIONS, AND FUTURE RESEARCH The authors of this paper conducted a cluster analysis of a sample of papers from the SigGlobDev Workshop, the Information Technology for Development Journal and other Information Systems Journals and conferences which have published papers in Information Systems and Global Development. This analysis throws light into the ways in which research has been undertaken in this area. Three clusters, Economic and Social Development at the Country level, Human Development at the Group Level, and Economic and Social development of Organizational Case Studies have been are identified. Our research indicates that there is limited research on development outcomes particularly at the individual and conceptual level. The contribution of this paper is in identifying the key areas in which Information Systems research has addressed how development outcomes may or may not be addressed, and the authors highlight areas that still need to be investigated. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D The study has several limitations that need to be addressed. First, as Ketchen and Shook (1996) point out, due to the limitations of cluster analysis, cluster analysis should be used in combination with other research methods, such as determination the number of clusters, validating clusters, and multicollinearity among variables, in order to maximize the development of knowledge. Second, due to the sample size limitation, we a larger sample size is needed to further investigate the research. Finally, as illustrated in Appendix 3, we provided a test of independence. This was conducted to determine whether there was any correlation between the variables to triangulate the findings from the exploratory cluster analysis. Pearson's chi-squared (χ2) test for independence was conducted to further explore if the three dimensions/categories, i.e. research methods, level of analysis, and development outcomes. 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Cluster 1-Country level, economic and social development Cluster 1 (n=85) Dimension Type Number Percentage Action Research 0 0.00% Case Study 21 24.71% Literature Review 12 14.12% Research Methods Model Development 26 30.59% Statistical Analysis 26 30.59% Total 85 100% Conceptual 19 22.35% Country 64 75.29% Group 2 2.35% Level of Analysis Individual 0 0.00% Organizational 0 0.00% Total 85 100% Economic Development 43 50.59% Human Development 0 0.00% Development Outcomes Social Development 42 49.41% Total 85 100% Table 7. Cluster 2-Group level, human development Cluster 2 (n=48) Dimension Type Number Action Research 3 Case Study 23 Literature Review 1 Research Methods Model Development 10 Statistical Analysis 11 Total 48 Conceptual 2 Country 13 Group 26 Level of Analysis Individual 0 Organizational 7 Total 48 Economic Development 0 Human Development 39 Development Outcomes Social Development 9 Total 48 Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Percentage 6.25% 47.92% 2.08% 20.83% 22.92% 100% 4.17% 27.08% 54.17% 0.00% 14.58% 100% 0.00% 81.25% 18.75% 100% Xiong et al. Cluster Analysis of Research in ICT4D Table 8. Cluster 3-Organizational level case study on economic and social development Cluster 3 (n=74) Dimension Type Number Percentage Action Research 4 5.41% Case Study 42 56.76% Literature Review 4 5.41% Research Methods Model Development 14 18.92% Statistical Analysis 10 13.51% Total 74 100% Conceptual 0 0.00% Country 0 0.00% Group 2 2.70% Level of Analysis Individual 9 12.16% Organizational 63 85.14% Total 74 100% Economic Development 43 58.11% Human Development 1 1.35% Development Outcomes Social Development 30 40.54% Total 74 100% APPENDIX 2: MAIN COUNTRIES STUDIED Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D APPENDIX 3: TEST OF INDEPENDENCE This was conducted to find out if there is any correlation between the variables to triangulate the findings from the exploratory cluster analysis. Pearson's chi-squared (χ2) test for independence was conducted to further explore if the three dimensions/categories, i.e. research methods, level of analysis, and development outcomes. Chi-square Test of Independence for Level of Analysis and Development Outcomes H0=Level of Analysis and Development Outcomes are independent with each other. Ha= Level of Analysis and Development Outcomes are dependent with each other. Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 26.146a 8 .001 Likelihood Ratio 23.396 8 .003 Linear-by-Linear Association .776 1 .378 N of Valid Cases 208 a. 4 cells (26.7%) have expected count less than 5. The minimum expected count is .75. Symmetric Measures Value Nominal by Nominal Contingency Coefficient Approx. Sig. .334 .001 208 N of Valid Cases Since p value is .001, so the null hypothesis is rejected. Level of Analysis is dependent with Development Outcomes. Chi-square Test of Independence for Level of Analysis and Research Methods H0=Level of Analysis and Research Methods are independent with each other. Ha= Level of Analysis and Research Methods are dependent with each other. Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 54.404a 16 .000 Likelihood Ratio 56.324 16 .000 Linear-by-Linear Association 17.459 1 .000 N of Valid Cases 209 Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014 Xiong et al. Cluster Analysis of Research in ICT4D a. 12 cells (48.0%) have expected count less than 5. The minimum expected count is .13. Symmetric Measures Value Nominal by Nominal Contingency Coefficient Approx. Sig. .454 .000 209 N of Valid Cases Since p value is 0, so the null hypothesis is rejected. Level of Analysis is dependent with Research Methods. Chi-square Test of Independence for Development Outcomes and Research Methods H0=Development Outcomes and Research Methods are independent with each other. Ha= Development Outcomes and Research Methods are dependent with each other. Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 9.548a 8 .298 Likelihood Ratio 10.236 8 .249 4.165 1 .041 Linear-by-Linear Association 208 N of Valid Cases a. 4 cells (26.7%) have expected count less than 5. The minimum expected count is 1.31. Symmetric Measures Value Nominal by Nominal Contingency Coefficient N of Valid Cases Approx. Sig. .209 .298 208 Since p value is .298, null hypothesis cannot be rejected. Based on the initial test of independence, it appears that level of analysis and development outcomes, level of analysis and research methods are dependent with each other, while development outcomes and research methods are independent with each other. As the research is continuing, the test of independence will be conducted once data collection is completed. Proceedings of the SIG GlobDev Seventh Annual Workshop, Auckland, New Zealand. December 14, 2014