Electronic Business: Concepts, Methodologies, Tools, and Applications (4-Volumes) P133 ppt

1254 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 4.17 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa: An Exploratory Study from Nigeria 3ULQFHO\,¿QHGR University of Jyväskylä, Finland ABSTRACT The use of information communication technolo- gies (ICT) especially the Internet by small- and medium-sized enterprises (SMEs) is on the in- crease in many regions of the world, including Africa. Nevertheless, empirical evidence from Sub-Saharan Africa (SSA) regarding the factors that affect the adoption of e-business is scarce. In that regard, the main objective of this chapter LV WR ¿OO WKH UHVHDUFK JDS ZLWK DQ H[SORUDWRU\ study that is aimed at eliciting views from SMEs in Nigeria. This article made use of a theoretical framework encompassing organizational, external and technological contexts to deliberate the issue. A survey is conducted in three Nigerian cities DQGWKH¿QGLQJVRIWKHVWXG\DUHSUHVHQWHG7KH implication of the study is discussed and future research directions also given. INTRODUCTION The use of information communication technolo- gies (ICT) by small- and medium-sized enterprises (SMEs) is already an established way of life in the developed countries (Beck, Koenig, & Wigand, 2003; Bunker & MacGregor, 2002; Lockett & Brown, 2003) and has been extensively studied in extant information systems (IS) literature (see, for example; Beck et al., 2003; DeLone, 1988; Kalakota & Robinson, 2001; Montazemi, 1988; Pigni, Faverio, Moro, & Buonanno, 2004; Poon, 2002; Scupola, 2003). In contrast, only a few research have surfaced wherein e-business in the developing countries including Sub-Saharan Af- rica (SSA) are discussed (Chifwepa, 1998; Heeks & Duncombe, 2001; Masten & Kandoole, 2000; Okoli, 2003; Okoli & Mbarika, 2003; Travica, 2002). We want to add to these few available 1255 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa studies by looking at the possibility of e-business adoption by SMEs in Nigeria. In this chapter, a business with up to 250 employees is categorized as an SME according to the European Parliament’s GH¿QLWLRQ2(&'2QWKHZKROH60(VDUH characterized by informal and inadequate plan- QLQJVWURQJRZQHU¶VLQÀXHQFHODFNRIVSHFLDO- ists, small management team, heavy reliance on few customers, limited knowledge and so forth (Bunker & MacGregor, 2002, Reynolds et al., 1994; Yap, Soh, & Raman, 1992). Further, the term e-commerce is often used interchangeably with e-business by many, though some experts have pointed out a difference. For example, Tur- ban, Lee, King, and Chung (2000) assert that the former refers to buying and selling electronically and it is a subset of the latter, which is broader and includes the servicing of customers, collabo- rating with entities both within an organization DQGRXWVLGHLW=ZDVVGH¿QHGHEXVLQHVVDV ³ W KH VK DU L Q JRI EX VL Q HV VL Q IRU P DW L R Q P DL QW D L QL Q J  business relationships, and conducting business transactions by means of the telecommunication networks” (p. 3). Here, both concepts are referred to as e-business. The adoption of ICT by SMEs reported widely is literature tend to focus attention on the developed West (see Beck et al., 2003; Bunker & MacGregor, 2002; Poon & Strom, 1997; Scupola, 2003). Examples of countries in the West include the US, Australia, and Italy. On the whole, these studies pertaining to ICT and SMEs or e-busi- ness in general have deliberated ICT deploy- ment, organizational and environmental factors concerning ICT use in business, success issues and so on (Abell & Lim, 1996; DeLone, 1998; Lockett & Brown, 2003; Poon & Strom, 1997; Walczuch, den Braven, & Lundgren, 2000; Yap et al., 1992). This chapter will attempt to look at some of those factors from the perspective of SSA. Importantly, many development research and reports have noted how ICT usage and adoption in the developing countries (and their by SMEs) could redress some of the inequalities resulting from WKHHPHUJLQJ³GLJLWDOGLYLGH´FXUUHQWO\H[LVWLQJ between the developed North and the developing South (Avgerou, 1998, 2003; Baliamoune-Kutz, 2003; Castells, 1999; Mbarika, Jensen, & Meso, 2002; Molla, 2000; Okoli, 2003; Singh, 2000; Travica, 2002; WSIS, 2004). Moreover, it is important to have some under- standing regarding the diffusion of e-business (if any) in SSA in light of the fact that some aspects of that society may impact the adoption of ICT in general and e-business, in particular. Further, among the few studies on e-business adoption in SSA, the work of Okoli (2003) has discussed the LPSDFWRIFXOWXUDOIDFWRUV+HDVVHUWVWKDW³$IUL- cans do not have the culture of buying a product without tactile contact … where the consumer can feel and examine the product before haggling…” (Ibid, p. 16). Thus, a research study of e-business in the SSA region may be useful for both theory and practice. Thus, the objective of this chapter is to present WKHSUHOLPLQDU\¿QGLQJVUHODWLQJWRWKHSHUFHS- tion and adoption e-business by SMEs in Nigeria. Primarily, this study is exploratory in nature and uses a survey. It is hoped that this article would contribute to knowledge as it seeks to assess e- business and/or the use of the Internet/IT by SMEs in Nigeria, and perhaps serve a base for further discussions and studies on the issue. Answers to the following questions will be provided in the chapter. Firstly, what are the state of preparedness and/or readiness of Nigerian SMEs for e-busi- QHVV"6HFRQGO\LQZKLFKVSHFL¿FZD\VGR60(V FXUUHQWO\XVHWKH,QWHUQHW"7KLUGO\ZKDWEHQH¿WV do SMEs in Nigeria seek as they contemplate using—or currently use—the Internet in their business operations? And, in generic terms, what are the main barriers to e-business adoption in Nigeria? 1256 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa Background Information about Nigeria and Sub-Saharan Africa Nigeria is the most populous country in Africa and has a population of about 140 million (World Bank Group, 2004). It is one of the fastest grow- ing economies in SSA, and has a large number of small businesses complementing its oil-run economy. According to Ojukwu and Georgiadou (2004), 97% of all businesses in Nigeria employ less than 100 employees. This fact is similar to other SSA countries, where SMEs also form the bedrock of their economies (Matambalya & Wolf, 2001; Mead & Liedholm, 1998). Unarguably, SMEs are viewed as the economy growth engine o f m a n y n a t i o n s — b e t he y d e v e l o p i n g o r d e v e l o p e d (Brouthers, Andriessen, & Nicolaes, 1998). Sadly, the use of ICT by SMEs in Nigeria does not appear to be pervasive; however, events on the ground in Nigeria such as the on-going liber- alization policy in the telecommunication sector are creating opportunities for the emergence of HEXVLQHVV $MD\L  ,¿QHGR  $OVR Nigeria is one of the best-performing nations in terms of ICT products use and diffusion in SSA (Hamilton, Jensen, & Southwood, 2004; Mbarika, Jensen, & Meso, 2002; Mbarika, Kah, & Keita, 2004; NITDA, 2001). Relatedly, the spread of cyber cafés in the country may be helping to popu- larize the Internet, which in turn could enhance e-business adoption (Ajakaye & Kanu, 2004). The teledensity (number of telephones lines per one hundred inhabitants) for Nigeria has been improv- ing; for example, it rose from 0.5 in 1999 to 2.0 in 2002 (Ajayi, 2003). The present teledensity rate is even better following the deregulation of telecoms industry with licenses being granted to several operators. The sector also received foreign direct investment (FDI) of U.S. $4 billion. Hitherto, the Nigerian government has been the sole provider of telephony to Nigerians (Ajayi, 2003; Hamilton HWDO,¿QHGR,QWKHVDPHYHLQWKH current Nigerian government is promoting e-busi- ness among SMEs in its National IT Policy, which ZDVLQDXJXUDWHGLQ$MD\L,¿QHGR 2004). All the aforementioned facts informed the choice of Nigeria as an intriguing county in SSA to investigate e-business adoption. Moreover, many parts of SSA have far less infrastructural and political support for IT-related initiatives or any e-business engagement (Mbarika et al., 2002, 2004; Odedra, Lawrie, Bennett, & Goodman, 1993; Woherem, 1996). Furthermore, the region of Sub-Saharan Africa (SSA) is home to 32 of the 48 least devel- oped countries in the world, it has a population of about 860 million people, and it is associated with poverty, high illiteracy rate, and chronic underdevelopment characterized by inadequate and poor telecommunications infrastructure, low teledensities, low level of technical skills and poor energy supply (Dutta, Lanvin, & Paua, 2003; ITU, 2004; Mbarika, et al., 2004). Usually, the republic of South Africa is excluded from SSA due to its superior indicators, so are countries in the northern part of Africa. Thus, the overview of the region in which this study is set, is highlighted. The rest of the chapter is organized as follows: The following section presents a review of litera- ture on e-business adoption and the theoretical framework of the study. After the Literature Re- view, the research method and context is discussed. 7KH¿QGLQJVDUHSUHVHQWHGLQWKHUHVXOWVVHFWLRQ The implications and discussions are dealt with in the Discussions and Implications section. The concluding part of the chapter is presented in the Conclusion section. LITERATURE REVIEW: E-BUSINESS ADOPTION BY SMES In the IS domain, Rogers’(1995) diffusion of in- novations theory has been used by researchers 1257 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa in studying the adoption of new innovations and technologies and that theory forms the bedrock for the theoretical model used in this chapter. With respect to e-business adoption by SMEs, Scupola (2003) provides a summary of literature on such studies. Among the studies she discussed are those b y I a c o vo u , B e n b a s a a t , a n d D e x t e r (19 9 5 ) w h e r e i n organizational readiness, external pressure and the SHUFHLYHGEHQH¿WVRIWKHWHFKQRORJ\DUHYLHZHG as factors affecting the adoption of ICT by SMEs. Also, Thong and Yap (1995) studies the impact of organizational and environmental factors on e-business adoption with emphasis on the role of &(2VFKLHIH[HFXWLYHVRI¿FHUV,QDVLPLODUYHLQ Walczuch et al. (2000) compiled a list of barriers to Internet commerce adoption by small business in Holland, by citing previous literature; includ- ing those by Abell and Lim (1996) among others. Some of the barriers discussed include unfamiliar- ity with the Web and lack of guidance about it, security issues and so on. Furthermore, Walczuch et al. (2000) also deliberated reasons why SMEs fail to adopt the Internet in their business; some of the reasons they mentioned include high costs, attitude, and so on. Also, Scupola (2003) highlights WKHEHQH¿WVRI,QWHUQHWFRPPHUFHHEXVLQHVVWKDW are similar with those in Walczuch et al. (2000). Examples include reduced costs, more customer satisfaction, distance barrier disappearance, and FRPPXQLFDWLRQHI¿FLHQF\ Of note, a majority of the literature review men- tioned above originates from the developed West DQGRIWHQWHQGWRIRFXVRQWKHVSHFL¿FFRQFHUQV of that society. This chapter is not suggesting, in any way, that some of the factors discussed in such literature do not apply in developing countries (including SSA). What we are attempting to point out in this chapter is that due to socioeconomic and cultural differences between the regions, other factors may in fact exist taken for granted, at least in the developed world. An example cited above relates to the prevailing attitude or culture towards commerce in general (see, Okoli, 2003); or even electric power generation, which is a seri- RXVSUREOHPLQ1LJHULD,¿QHGR2MXNZX Georgiadou, 2004) and may not be seen as a threat to e-business in the developed West. Additionally, in contrast to many research on e-business/e-com- merce adoption and diffusion in the West, where organizations that have actually implemented e-business (or in the process of implementing) DUHVWXGLHGDQG¿QGLQJVRIVXFKUHVHDUFKGLVVHPL- nated; this study is not avail of that opportunity. The number of SMEs, for example in Nigeria HQJDJLQJLQ UHDOHEXVLQHVV²E\GH¿QLWLRQ²LV limited; and, obtaining information about such companies is not an easy task. As such, the thrust of this article may appear dissimilar with those from the West, in what it sets out to investigate and how it approaches such issues. However, it is worth noting that the situation regarding e-busi- ness adoption and diffusion may be somewhat different in multinationals, banks and other large entities in Nigeria (and in the region) due to the availability of resources—human, technical and ¿QDQFLDO7LDPL\X Notwithstanding, empirical studies are begin- ning to emerge with focus on the adoption, use, and diffusion of ICT by African SMEs. Prominent amongst such work include those by Heeks and 'XQFRPEHZKHUH¿QGLQJVDERXW,&7XVH by SMEs in Botswana is deliberated. Likewise, Okoli (2003) assesses e-business outcomes and values in SSA and concludes that the availability of ICT infrastructure amongst other factors af- fect e-business capabilities in the region. Other studies have investigated the impact of ICT on the performance and growth of SMEs in SSA and found positive relationships (Matambalya & Wolf, 2001; Ojukwu & Georgiadou, 2004). This present chapter adds to these few studies. The Research Framework The research model used for this study is modi- ¿HGIURPWKHZRUNRI7RUQDW]N\DQG)OHLVFKHU (1990) and Chau and Tam (1997), which is shown in Figure 1. The model has featured in research 1258 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa on e-commerce adoption elsewhere (see, for example, Lertwongsatien & Wongpinunwatana, 2003; Scupola, 2003). Tornatzky and Fleischer’s (1990) model has three components impacting the adoption and implementation of innovations; namely, factors or items from the technological, organizational and external environments. In this chapter, we are not dealing with the implementa- tion of e-business in SMEs, per se; rather we are interested in how some of the factors from the three mentioned contexts affect the adoption of e-business by SMEs in Nigeria. Importantly, the model is applicable to any organization, unit of analysis and region (Lertwongsatien & Wongpi- nunwatana, 2003; Scupola, 2003; Tornatzky and Fleischer, 1990). External Environment In Tornatzky and Fleischer’s (1990) model, the external environment in which organizations carry out their business is noted as being crucial. Factors such as customer-supplier relations, gov- ernment regulations and the attitude or the culture amongst others do impact the adoption of e-busi- ness. With regard to Nigeria, a vast majority of the population would, usually, buy its wares from sellers after having tactile contacts and haggling (Okoli, 2003). E-business adoption may face an uphill task here. In addition, there is no strong IT culture in the country (Ojo, 1996) as the country LV\HWWREHIXOO\LQWHJUDWHGLQWRWKH³QHWZRUNHG world” (Dutta et al. 2003; ITU, 2004). The role of the Nigerian government in setting policies for e-society (including e-government and e-busi- ness) is only emerging after the inauguration of the national IT policy in March, 2001 (Ajayi, 2003; NITDA, 2001). This effort, though belated, is nonetheless welcoming. Research has shown that government policies are vital in the diffusion of e-business (Damsgaard & Lyytinen, 1996). Moreover, Nigerians expect those in authority Figure 1. Theoretical framework of the research (adapted from Chau & Tam, 1997; Scupola, 2003; Tornatzky & Fleischer, 1990) External Environment: Culture, role of government, infrastructural su pp ort Organizational Context: Employee IT skills, company size, financial and technolo g ical resources Technological Context: E-business Barriers, E-business Benefits E-business adoption and growth 1259 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa to champion causes or issues including those relating to IT innovations (Anandarajan, Igbaria, & Anakwe, 2002). The telecommunication infra- structure that is a sine caveat non for e-business development is in a sorry state in Nigeria (ITU, 2004). Also, electric power generation is poor in Nigeria. Power generation is taken for granted in the developed West and perhaps never mentioned in IS literature as having any impact on e-busi- ness adoption. Organizational Context This is manifest in the overall quality of the human resources such as the level of education, training and so on available to the enterprise. Iacovou et al. (1995) contend that the level of IT sophistication affects e-business adoption. Likewise, employee IT skills or knowledge, the size of the organiza- WLRQDQGWKHDYDLODELOLW\RI¿QDQFLDOUHVRXUFHV DUHRWKHUIDFWRUVWKDWPD\LQÀXHQFHHEXVLQHVV adoption and diffusion. Regarding SMEs orga- nizations in Nigeria, the level of sophistication that is required to enhance the adoption of e- business is lacking in the county; such skills are most likely to be found in larger and well-funded organizations in the country (Anandarajan et al. 2002; Tiamiyu, 2000). Lack of general IT skills and illiteracy among the population is rife and could affect e-business adoption (Ajayi, 2003; Dutta et al. 2003; Ojukwu & Georgiadou, 2000; World Bank Group; 2004). Technological Context In this chapter, the technological context is used to highlight the impact that an innovation such as e-business would have on the SMEs adopting—or planning to adopt it—against the backdrop of their X QGHU VW DQGL QJRI W KHE HQH¿WVD QGED UU LH U VRIVXFK an innovation. Importantly, several studies in the GHYHORSHG:HVWKDYHLQYHVWLJDWHGWKHEHQH¿WVRI ICT for SMEs (Beck et al., 2003; Poon, 2002; Poon & Swatman, 1997), the satisfaction derived by SMEs from the use of IT in their organizations (see, Beck et al., 2003; Poon & Strom, 1997) and the barriers to adopting e-business. Some of the EDUULHUVDQGEHQH¿WVWKDWDUHXVHGLQWKLVFKDSWHU come from the work of Walczuch et al. (2000). 6HH7DEOHVDQGIRUGHWDLOV,QWKH³WHFKQRORJL- cal dessert” of Africa (Odedra et al., 1993) a few exploratory studies and developmental reports have attempted to present perspectives of the EHQH¿WV DQGEDUULHUV ZLWK UHJDUG WRWKH XVH RI ICT by SMEs on the continent. Some of those are discussed below: Barriers to E-Business Adoption in SSA Generally speaking, some of the barriers to the adoption e-business (or, the use of ICT by SMEs) that are mentioned in literature focusing on or- ganizations in the developed world also resonate in SSA. Such factors amongst others include inadequate awareness or lack of knowledge, HTXLSPHQWFRVWVDQGODFNRI¿QDQFH,QSDUWLFX- lar, some researchers including Duncombe and Heeks (1999, 2001); Henten, Falch, and Anyimadu (2004); Mead and Liedholm, (1998); Matambalya and Wolf (2001); Oyelaran-Oyeyinka and Adeya, (2004); and Ojukwu and Georgiadou (2000) have provided relevant insights. For example, Dun- FRPEHDQG+HHNVFODVVL¿HGEDUULHUVRI,&7 use by African SMEs under two main categories; namely, the macro and the micro factors (see also, Iyer, Taube, & Raquet, 2002). The former deals with overall socioeconomic and technological hin- drances and the latter revolves around the limiting factors facing SMEs in the context of SSA. The barriers that Duncombe and Heeks (1999) found as to why SMEs in Botswana do not adopt the Internet in their business include: • Lack of money • Lack of skills or knowledge • Lack of technological infrastructure, e.g. telecommunications, electricity supply 1260 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa • Lack of awareness of the business environ- ment and how to take advantage of it.  /DFNRI³FULWLFDOPDVV´)HZORFDOSHRSOH organizations use computers/e-mail and are unable to engage in meaningful e-busi- ness 3RYH U W \ L VSH UKD S VW K H¿ U VWE DU U LH UWR WKH D GRS - tion and diffusion of ICT by SMEs in SSA. The World Bank (2001, p. 38) report provides the dire VWDWHRIDIIDLUVZKHUHLWVWDWHV³,Q$IULFDVORZ growth increased both the share and the number of the poor over the 1990s; Africa is now the region with the largest share of people living on less than U.S. $1 per day.” As such, many SMEs in the region cannot afford telephones or procure connectivity for their business and the use of the Internet for business is marginal (Henten et al., 2004; Oyelaran-Oyeyinka & Adeya, 2004). The ongoing campaign for funds for African SMEs from international sources is commendable (Anonymous, 2004; ADF, 2004; Nweke, 2004). Unfortunately, the priority of many developing nations tends to be on other socioeconomic matters rather than with the diffusion and applicability of ICT by SMEs (Castells, 1999); thus, it remains to be seen if such funds would actually assist e- business initiatives, in particular. The low levels of technical expertise that the educational institutions in SSA turn out may not be amenable to the adoption and implementation of e-business (Odedra et al., 1993; Woherem, 1996). Relatedly, the telecommunication infrastructure in SSA is appalling. Sadly, the communication systems in SSA are built to focus on the external rather than internal communications. This is the legacy of colonialism, which is perhaps to blame for such unpleasant facts (see, Korpela, 1996). For example, it is somewhat easier to place a call to a European city, say London or Paris than for calls to go through two SSA cities, say Dakar and Lagos (Henten et al., 2004). By the same token, the technical abilities of SMEs in many SSA countries, including Nigeria is inadequate or LQVXI¿FLHQWWRIDFLOLWDWHVPRRWKHEXVLQHVVDGRS- tion or sustenance (Odedra et al., 1993; Ojo, 1996; Udo & Edoho, 2000). A recent research pointed RXWWKDW³WKHUHLV DVWURQJDVVRFLDWLRQEHWZHHQ WKHFRPSOH[LW\RIWKH¿UPOHYHOHWHFKQRORJLHV and the level of national technological capability” (Oyelaran-Oyeyinka & Lal, 2004). The techno- logical capacity in SSA is abysmally poor; hence the discouraging statistic regarding ICT use in SSA—and for its SMEs—(Dutta et al., 2003; WSIS, 2004). Realistically, the prevailing situation OLPLWVWKH³FULWLFDOPDVV´QHHGHGIRULQQRYDWLRQV such as e-business to thrive in the region. 3RWHQWLDO%HQH¿WVRIE-Business to SMEs in SSA 7KHEHQH¿WVRI,&7IRU60(VDQGWKHDGRSWLRQ of e-business reported in the developed world LQFOXGHLQFUHDVHGHI¿FLHQF\LPSURYHGFXVWRPHU relationships and service, lower costs, and higher information quality to mention but a few (Abell & Lim, 1999; Chaffey, 2002; Iacovou et al., 1995; Kalakota & Whinston, 1998; Poon & Strom, 1997; Poon & Swatman, 1997; Premkumar, Ramamur- thy, & Crum, 1997; Walczuch et al., 2000). With respect to Nigeria and other SSA countries, the IROORZLQJEHQH¿WVPD\EHDFFUXDEOH • Improved knowledge and better supply chain management: The commonest problem to SMEs in SSA relates to lack of information and knowledge about the market, poor com- munication, uncertainties in supply, poor quality and seasonal impacts of caused by excessive stocks (Singh, 2000). By the same token, the issue of information asymmetry, which may lead to high transaction costs and even market failure, is insidious (Mat- ambalya & Wolf, 2001). E-business engage- ment could alleviate some of these problems. Recently, some ICT-related initiatives have been developed to help improve the provision of demand information for businesses and 1261 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa entrepreneurs in the developing countries (see, Duncombe & Heeks, 1999). It is hoped that such initiatives could help provide an enabling environment for better manage- ment of knowledge that enhances better management of the demand-supply chains of SMEs in the region. • The ability to adopt ICT (including the In - ter net) by SMEs in Nigeria (and SSA) could have a catalytic effect on improving the IT sector in the region. This could generate the critical mass discussed to be lagging in the region. Fortunately, many SSA governments have commissioned bodies and agencies to help small businesses with the deployment of ICT (and the Internet) in their operations. In Nigeria, NITDA (National Information Technology Development Agency) does that IXQFWLRQ,¿QHGR1,7'$ • Innovations through e-business: The innova - tive mind that saw the birth of the Yahoos, Dells, and eBays of this world could be cop- ied in Nigeria (and in other SSA countries). The generated opportunities in employment, revenues and so on could hasten the socio- economic development of the region. Of note, some cooperatives in East Africa have already started getting themselves organized for using the Internet for commerce. See for example: http://www.giftofafrica.com/. • The opportunity for B2G (Business-to- Government) in Nigeria may emerge as more SMEs adopt ICT (and the Internet) in their operations. The cost advantages and transparency that electronic activi- ties can engender is enormous to both the government and SMEs in the region. For example, access to government information LV HQ KD Q FHG  WD [DW LR QS URFH GX UHV VL PSOL ¿H G and so on. This may be revolutionary in a region noted for its endemic corruption (World Bank Group, 2004). For instance, the avenue for bribes—given to corrupt func- tionaries—may be blocked as e-business opens up electronic transactions between SMEs and governments. The government of Mauritius has already implemented a successful online taxation system for busi- ness in that country (Duncombe & Heeks, ,¿QHGR • Improved internal operations: The adoption of e-business at the micro level could help ¿UPVLPSURYHWKHTXDOLW\RIWKHLULQWHUQDO services. In the developed world, such ben- H¿WVIRU60(VKDYHEHHQZLGHO\UHSRUWHG (see for example, Lockett & Brown, 2003; Premkumar et al., 1997; Thong & Yap, 1995). • The world at your feet! This is the greatest E HQ H¿ W W KD WH  E X VL QH VV FD Q RI IH U6 0( VL Q W K H developing countries (Travica, 2002). In light of the less favorable prospects for SSA in the world trade (World Bank, 2001); SMEs adopting e-business may help bridge the gap as greater international trade is enhanced with the outside world. Such exposures could bring about new skills and standards that could help African SMEs integrate within the global networked economy. Research Method and Context The main data for the study was collected through two contact persons in Nigeria. Previously, these contact persons acting as research assistants had worked with the author on a similar project. Therefore, their experience in data collection is not in doubt; moreover, they are postgraduate students. Contact person has been used by other researcher(s) for data collection, including in Nigeria (see for example, Anakwe, Anandarajan, & Igbaria, 1999). The contacts were instructed to collect data for this study by distributing 100 questionnaires to randomly selected SMEs—ac- FRUGLQJWR60(GH¿QLWLRQXVHGLQWKLVFKDSWHU²LQ three Nigerian cities; namely, Lagos, Ibadan, and Port-Harcourt. The selected cities are among the large commercial cities in the country; therefore, 1262 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa it is more likely that SMEs in these cities may have some exposure to some ICT usage in their businesses; or at least, in the process of adopting some e-business initiatives. There is no prefer- ence given to any particular industry. As this is an exploratory study we are hoping to elicit the views of proprietors and supervisory/managerial employees of SMEs in the country, on certain issues operationalized on a two-page question- naire. It is worthy to point out that in Nigeria; WKHUHLV³XUEDQUXUDOGLYLGH´ZLWKUHJDUGWRWKH use of ICT facilities (Ajayi, 2003). ICT facilities are almost nonexistent in the rural parts of the country. This informed our choice of only SMEs in large cities. Further, the author sent out 15 questionnaires, as a Microsoft Word attachment, to similar entities involved in SME in Lagos and Ibadan; all these are commercial cities in Southern Nigeria. The author decided to collect the additional data personally for the purpose of data triangulation. To ensure YDOLGLW\RIWKH¿QGLQJVWKHDXWKRUFRQGXFWHGIRO- low-on interviews with some of the respondents. On the whole, in the both instances—through contacts on the ground and e-mail collection—63 u s a b l e q u e s t i o n e d w e r e o b t a i n e d . N o t a bl y, 5 4 w e r e received on the ground and 9 through e-mail at- tachments. This represents an effective response rate of 54.8%, which is good for a study such as this. Of note, judgmental sampling process is used in selecting respondents. This approach involves the researcher(s) handpicking his respondents due to his/her judgment. In this study, requests were made to key informants in the participating SMEs, and such include the proprietors and other knowledgeable employees holding supervisory and managerial positions within their organiza- tions. Key informant technique has been used in IS literature to collect data from key personnel in functional areas such as marketing, accounting and so on (see Bradford & Florin, 2003). This study got responses from such personnel—one for each SME. The maximum number of employees in the SMEs sampled in this survey is 186 and minimum is 1. The breakdown is in Table 1. Overall, the viewpoint of 22 (35%) proprietors and 41(65%) supervisory/managerial employees is used. Each participant was given or sent the questionnaire developed with inputs or items from previous studies relating to Internet commerce or e- business adoption (Duncombe & Heeks, 1999; Matambalya & Wolf, 2001; Oyelaran-Oyeyinka & Adeya, 2004, 2000; Walczuch et al., 2000). The questionnaire also has a part for open-ended feedback. Participation was voluntary with a SURPLVHWRVKDUH¿QGLQJVZLWKSDUWLFLSDQWV0RUH importantly, non response bias was assessed by using a method similar to those recommended by (Armstrong & Overton, 1997) where means scores of response are compared. In this instance, the responses received by e-mail attachments are compared with those received on the ground (see DOVR'H/RQH1RVLJQL¿FDQWGLIIHUHQFHVLQ means between the two sets of data collection are observed; thus indicating there is no evidence to suggest bias attributable to non-responses. There were no noticeable outliers in the data, assessed IURPKRZWKHUHVSRQGHQWV¿OOHGLQLWHPVRQ the questionnaire. Basically, the questionnaire requires each participant to indicate appropriate choices on relevant statements about the extent to which they agree/disagree with items anchored on a Likert-type scale. Demographic information is also collected. See Tables 4 and 5 below for the detail. The questions anchored on the Lik- ert-type scale got analyzed using mean analysis and percentages on statistical software; namely, SPSS 10.0 and the qualitative feedback from the open-ended part of questionnaire and interviews DUHDOVRXVHGWRLOOXVWUDWHWKH¿QGLQJV Nonetheless, there are limitations to this study; ¿UVWO\WKHVDPSOHVL]HXVHGLVVPDOODQGPD\QRW be representative. More so, all the SMEs in this study came from a region of the country—the South. The viewpoints from other parts of the 1263 Factors Affecting E-Business Adoption by SMEs in Sub-Saharan Africa country may differ. Secondly, the diversity of the participating SMEs; namely, operations and VL]HRIWKHUHVSRQGLQJ¿UPVPLJKWKDYHLPSDFWHG WKH¿QGLQJV,WLVSRVVLEOHWKDWWKHUHPD\EHVRPH industries where the use of ICT or the adoption e-business may not be crucially important; at least, in the present day Nigeria with low IT skills, resources and awareness. Yet, this exploratory study did not seem to make any distinctions in VRIDUDVDQ60(PHHWVWKHGH¿QLWLRQFULWHULRQ Thirdly, response bias may exist; for example, in relation to age, educational level, gender and 7DEOH'HPRJUDSKLFSUR¿OHRIWKHUHVSRQGHQWV Type of organization Frequency Percent Retail / Sales Light Engineering (Metal) Business Centre Agro-related business Education Confectionary / Bakery Import / Export business Constructions Oil Support Services Pharmacy Marketing / PR company Computer/IT training school IT consultancy Others 5 3 7 2 3 4 3 1 3 5 7 6 3 11 7.9 4.8 11.1 3.2 4.8 6.4 4.8 1.6 4.8 7.9 11.1 9.6 4.8 17.2 Total 63 100.0 Age: Less than 25 26 – 39 40 – 55 56 - 67 8 30 14 11 12.7 47.6 22.2 17.5 Gender: Female Male 16 47 25.4 74.6 Education: Primary / Secondary University Graduate Others 7 36 20 11.1 57.1 31.7 Organization Size: 1 -10 employees 11 – 49 employees 50 – 250 employees 32 19 12 50.8 30.2 19.0 . including Duncombe and Heeks (1999, 2001); Henten, Falch, and Anyimadu (2004); Mead and Liedholm, (1998); Matambalya and Wolf (2001); Oyelaran-Oyeyinka and Adeya, (2004); and Ojukwu and Georgiadou. example, Tur- ban, Lee, King, and Chung (2000) assert that the former refers to buying and selling electronically and it is a subset of the latter, which is broader and includes the servicing. found in larger and well-funded organizations in the country (Anandarajan et al. 2002; Tiamiyu, 2000). Lack of general IT skills and illiteracy among the population is rife and could affect