Research Paper
Information Technology Adoption in Small Business: Confirmation of a Proposed Framework by ThuyUyen H. Nguyen, Michael Newby, and Michael J. Macaulay
This paper investigates which drivers affect information technology (IT) adoption and which factors relate to a successful IT implementation in small businesses, where the adoption rate is traditionally low and the failure rate is high. The findings from this study suggest that customers are the main driving force of IT adoption. When it comes to IT implementation, our results suggest that managers/owner–managers must engage with five factors: organization, internal IT resources, external IT consultants, supplier relations, and customer relations. These findings give further insight into IT adoption in small businesses and highlight the importance of customer relations in the adoption process.
Introduction Information technology (IT) adoption is
the stage at which a decision is made about adopting particular hardware and/or soft- ware technology (Thong 1999) and involves various activities, including managerial and professional/technical staff decision-making in both the internal and external environment of the organization, which must occur before the given technology can have a physical presence in the organization (Grover and Goslar 1993; Preece 1995). There have been a number of research studies on the determinants of IT adop- tion in small businesses such as those by Bharadwaj and Soni (2007), Fuller (1996), Irvine and Anderson (2008), Lee and Runge (2001), Riemenschneider, Harrison, and Mykytyn (2003), and Thong (1999), all of which focus on searching for factors that affect the decision and intention to adopt IT. These factors include cost
benefits, management innovativeness, percep- tion, knowledge and skills, employee attitudes, acceptances and contributions (the Theory of Planned Behavior and the Technology Accep- tance Model), IT skills and knowledge of man- agement and employees, and IT infrastructure. The decision to adopt is also influenced by external factors such as consultants, business partners, suppliers, and customers.
However, it is not always clear whether small businesses see new IT as an opportunity or a threat. Evidence suggests that IT adoption rates in small business are low, and that failure rates are high: the question is why. Some com- mentators have suggested that using IT is not always going to be beneficial to such firms (Bull 2003; Oakey and Cooper 1991), while others have argued that IT is not appropriate for every small firm (Macpherson et al. 2003; Morgan, Colebourne, and Thomas 2006). Levy, Powell, and Yetton (2001) suggest that IT
ThuyUyen H. Nguyen is Senior Lecturer in Business Analysis, Systems, and Supply Change Management at Northumbria University, UK.
Michael Newby is Professor of Information Systems and Decision Sciences at California State University, Fullerton.
Michael J. Macaulay is Associate Professor of Public Management at School of Government, Victoria University, New Zealand.
Address correspondence to: ThuyUyen H. Nguyen, Newcastle Business School, Northumbria University, Newcastle upon Tyne NE1 8ST, UK. E-mail: thuyuyen.nguyen@northumbria.ac.uk.
Journal of Small Business Management 2015 53(1), pp. 207–227
doi: 10.1111/jsbm.12058
NGUYEN, NEWBY, AND MACAULAY 207
adoption in small businesses often happens without any proper planning, resulting in a low percentage of successful implementations. According to Carson and Gilmore (2000), small businesses, especially new ones, often experi- ence ambiguity and uncertainty regarding IT adoption. Bhagwat and Sharma (2007) point out that many difficulties are due to the lack of resources (financial, technical, and managerial) available to small businesses.
This paper extends these debates and sug- gests that there is no one single factor that accounts for the low adoption rate or the high failure rate of IT adoption in small businesses. Indeed, this paper will demonstrate, through an empirical study of the IT adoption process in small businesses, that there are five intercon- nected factors that influence the success or failure of IT adoption: organization, internal IT resources, external IT consultants; supplier relations, and customer relations. In so doing, this paper offers a twofold approach: first, it investigates drivers to or reasons for IT adop- tion in small businesses; second, it determines factors relating to a successful implementation in the specific context of three industries (retail, financial services, and manufacturing) in Los Angeles County and Orange County in South- ern California.
The remainder of this paper is structured as follows: the next section presents a review of key aspects of the cognate literature in this area and an outline of the components of the study research framework. This is followed by the research methodology, the results analysis, and a discussion of the findings and implications. Limitations of the study are also discussed with some suggestions for future research.
Background and Theoretical Framework IT Adoption in Small Businesses
By changing the way staff capture and dis- tribute information (Claessen 2005; Currie 2004), IT provides organizations with a number of benefits—sustainable competitive advantage (Bruque and Moyano 2007; Carbonara 2005; Hung and Tang 2008; Lee and Runge 2001), lower production and labor costs, added value to products and services (Corso et al. 2003; Nguyen, Sherif, and Newby 2007; Premkumar 2003)—while generally improving business pro- cesses (Búrca, Fynes, and Marshall 2005; Levy, Powell, and Yetton 2001). Despite these poten- tial benefits, there have been numerous cases of
unsuccessful IT implementations in this sector (Acar et al. 2005; Mole et al. 2004; Ruiz- Mercader, Meroño-Cerdan, and Sabater-Sánchez 2006), and the adoption rate can be very slow (Peltier, Schibrowsky, and Zhao 2009; Thong 1999). A survey conducted by the research and advisory firm Gartner, for example, found that more than half of the organizations that had implemented IT encountered difficulties after implementation (Baumeister 2002).
The key to this lack of success appears to be a disconnection between vision and execution: organizations do not do enough research and planning before implementing the new tech- nology, often because management is unclear about how and why their firms are adopting IT in the first place (Bull 2003; Mazurencu- Marinescu, Mihaescu, and Niculescu-Aron 2007). Added to this are other barriers to adop- tion. Some firms do not have the capabilities to expand their IT resources (Acar et al. 2005; Bharadwaj and Soni 2007; Claessen 2005) as they lack business and IT strategies. Others have only limited access to capital resources and also have limited IT/Information Systems skills (Ballantine, Levy, and Powell 1998; Bruque and Moyano 2007). There are, inevita- bly, financial barriers (Lema and Duréndez 2007; Shin 2006). In addition, project execution often failed or suffered from a lack of senior management support, poor project manage- ment, or insufficient skills to complete the project (Bull 2003; Näslund and Newby 2005). At the same time, there is a significant influence from major customers (Bhagwat and Sharma 2007) who are becoming more demanding and expect rising standards of IT excellence. If cus- tomer influence goes unrecognized, and orga- nizations rush into implementing IT, they will experience problems (Mazurencu-Marinescu, Mihaescu, and Niculescu-Aron 2007).
The present paper investigates the tendency to adopt IT in small businesses using the Nguyen (2009) IT adoption framework (Figure 1). Here, it is suggested that small firms adopt IT for reasons that come from either the internal or external pressures or forces. These reasons are known as drivers to adoption as they are ultimately the cause of adoption of IT in a business. In addition, the framework inte- grates four main aspects of small business when it comes to IT adoption, and these are (1) organizational, which includes management, staff, culture, and knowledge; (2) network orientation (or networking, as illustrated in
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Figure 1) that includes the relationship to the suppliers, business partners, and customers; (3) external IT consultants; and (4) internal IT resources, which include the IT abilities, capacities, and capabilities of the firm. These aspects will be referred to as factors, as they are predicated to affect the success of IT adoption and will be explored and expanded upon after- ward. In the context of this study, IT to be adopted can range from the Microsoft Office Suite (Microsoft, Redmond, WA, USA) to an enterprise resources planning system or point of sales (POS) system and is used to manage
resources and communications in daily busi- ness operations.
Drivers to Adoption The report by the National Federation of
Independent Business (2005) on the state of technology in small business indicates that the most common reason for technology to be upgraded in this sector is simply the desire to upgrade it, but it is not clear what drives this. Studies suggest that for many firms, the most common objectives for IT adoption are to enhance organizational survival and/or growth
Figure 1 Conceptualized Framework for Small and Medium-Sized Enterprises
(SME) Information Technology Adoption
- Abilities - Capacities
- Capabilities
- Experience - Recommendations
- Network relationship
- Knowledge and learning
- Management - People & culture - Absorptive capacity of the firm
Information technology adoption
Organizational Networking
External expertise
Information technology resources
Life cycle/ Maturity
Growth stages
Market-pull/ Innovative
Technology- push/
Competitive
Internal force
External force
Factor(s)
Driver(s)
Source: Adapted from Nguyen, T. H. (2009). “Information Technology Adoption in SMEs:
An Integrated Framework,” International Journal of Entrepreneurial Behaviour and
Research 15(2), 164.
NGUYEN, NEWBY, AND MACAULAY 209
and to remain competitive and/or enhance inno- vative capacity (Bridge and Peel 1999; Bruque and Moyano 2007; Búrca, Fynes, and Marshall 2005). These can be the result of pressure from both the internal and external environment (Andries and Debackere 2006; Morel and Ramanujam 1999; Winter et al. 2003), from either an emphasis on improving efficiency and business expansion or a pressure to meet certain requirements from customers and industry stan- dards (Ballantine, Levy, and Powell 1998; Corso et al. 2003). Rogers (2003) refers to these drivers as part of an innovation decision process, where management and organizations assess the advantage and disadvantage of the adoption. This is an important aspect of small and medium-sized enterprises (SMEs), especially in small businesses, where it has been noted that insufficient finance is one of the sector’s weak- nesses when it comes to investment (Eden, Levitas, and Martinez 1997; Lema and Duréndez 2007). Most small businesses do not have sufficient financial resources and often, they mortgage their own personal possessions as collateral (Fuller-Love 2006). As a result, these organizations search for positive potential ben- efits from any investment. They have to see or at least believe that new IT will bring advantages to their firms (Eden, Levitas, and Martinez 1997; Riemenschneider, Harrison, and Mykytyn 2003). Hence, drivers to adoption can be viewed not only as reasons for, but also as catalysts, triggers, or prerequisites for IT adoption in small busi- nesses (Nguyen 2009). The decision to adopt IT is the result of these drivers. However, it is not part of the adoption process. The next section details our research model and study hypoth- eses on the IT adoption process.
Research Model and Study Hypotheses IT Success Implementation
The dependent variable measured here is the IT success implementation. As suggested by Bruque and Moyano (2007), success can be measured in terms of rapid and effective use of the new technology, where the objective of the adoption is to reach a desired outcome. The objective of a successful implementation can range from the return on investment (ROI), increase in revenue, increase in sales, or improvement in quality of products and services (Anderson and Huang 2006; Payne and Frow 2005; Raymond 2005; Roberts, Liu,
and Hazard 2005). Thong (1999) suggests that success in implementation is directly influ- enced by organizational factors, particularly the top management, and by IS external expertise. Levy, Loebbecke, and Powell (2003) suggest that SMEs benefit from their external environment when it comes to knowledge generated for the firms, whereas Caldeira and Ward (2002) contend that the internal IT resources contribute to the success of the implementation.
In this study, the measure for the dependent variable is on the five-point Likert scale (strongly agree to strongly disagree). This measure indicates the degree to which the respondents rate their IT adoption to be suc- cessful. Five items were used to measure the IT success implementation scale. The first and second items assess the ROI and increase in revenue, the third item concerns the increase in sales and services volumes, and the fourth and fifth items relate to the improvement in quality of products and services.
The dependent variable was hypothesized to be dependent on four factors: organizational, network orientation, external IT consultants, and internal IT resources. These four factors construct an adoption environment, which measures the overall preparedness (in terms of attitude, resources, requirements, abilities, capacities, and capabilities) of the business to adopt new IT. The factors of the environment are interrelated, and it is hypothesized that all contribute to the success (or otherwise) of the implementation.
Figure 2 summarizes the stages of the adop- tion process. The drivers to adoption lead to a decision to adopt IT. This decision affects the adoption environment within the business, and the environment, in turn, affects whether the implementation is successful or not, so the success of the implementation is viewed as an outcome of the adoption environment. Figure 3 gives details of our primary research model. The methodology used here follows that of Baker and Sinkula (2009), which involves developing a survey instrument, then measur- ing and confirming the proposed research model (see Figure 3).
The Relationship between Organizational Factor and Successful Implementation
Previous studies have identified a number of organizational factors that influence the IT adoption process, including the size of the firm,
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its goals, the knowledge, skills and experience of staff, and the organizational culture and structure. It is suggested that a culture that is flexible to change is more innovative than one that is resistant to change (Denison, Lief, and Ward 2004). Hence, in a flexible culture, the adoption of IT is more likely to happen and is more likely to succeed (Minguzzi and Passaro 2001; Ruiz-Mercader, Meroño-Cerdan, and Sabater-Sánchez 2006). Organizational culture in small business is seen as being strongly influenced by the owner–manager’s attitude, personality, and values (Dibrell, Davis, and Craig 2008; Gudmundson, Tower, and Hartman 2003; Riemenschneider and McKinney 2001/ 2002). In small organizations, management or owner–managers make most, if not all, of the key decisions (Fuller-Love 2006; Stanworth and Gray 1992), and these decisions are based on their existing knowledge, personal judgment, and communication skills (Carson and Gilmore
2000). It is not only their decisions that affect the adoption of IT, but also their commitment to the adoption process as well (Näslund and Newby 2005). At the same time, the employees’ knowledge, and degree and form of involve- ment contribute to the success of the IT adop- tion (Anderson and Huang 2006; Igbaria et al. 1997; Kotey and Folker 2007). In addition, employees should understand the purpose behind the adoption, their role within the adoption, and their contribution to it. Hence, communication between the management and employees regarding the change is essential. Failure to communication can lead to doubt in employees about the usefulness of the new technology, resulting in a negative attitude towards the change, fear about job security, and a low level of support. Finally, small busi- nesses are viewed as knowledge generators and knowledge dispersion enterprises (Dew, Velamuri, and Venkataraman 2004; Levy, Loebbecke, and Powell 2003). Their ability to absorb existing knowledge, transform it, use it, and generate new knowledge affects the IT adoption process (Gray 2006; Macpherson and Holt 2007; Zahra, Neubaum, and Larrañeta 2007). Management should ensure that there is efficient knowledge sharing among individuals within the firm, as the IT adoption process requires teamwork and acceptance across all functions within a firm (Phelps, Adams, and Bessant 2007; Smith 2007). Moreover, techno- logical learning and IT can promote entrepre- neurial development and growth (Carayannis et al. 2006). The discussion earlier leads us to the following hypothesis:
H1: The organizational factor is directly and positively related to a successful implementation.
The Relationship between Network Orientation Factor and Successful Implementation
A core characteristic of small businesses is their relationship networks (Fletcher 2002; Lema and Duréndez 2007). These networks emerge through the numerous interactions, which take place between firms, business partners, vendors, suppliers, and customers. They can be personal networks (Lema and Duréndez 2007) or business networks (and on occasions, it can be difficult, if not impossible, to differentiate between the two), and they are not restricted by organizational boundaries
Figure 2 Information Technology (IT)
Adoption Stages
Drivers to Adoption -Internal forces
- External forces
IT Adoption
Adoption Environment - Factors affecting
successful implementation
IT Success
Implementation
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(Taylor and Pandza 2003). Through these net- works, firms exchange, collaborate, and share knowledge, information, and communication (Pittaway et al. 2004; Taylor and Pandza 2003). Collaboration with customers or suppliers can facilitate the development and improvement of products and/or services (Levy, Loebbecke, and Powell 2003; Rosenfeld 1996). According to Rosenfeld (1996), this is where knowledge is created, transferred, and transformed. Collaboration with these external networks brings learning opportunities (Rothwell 1991), knowledge creation (Dew, Velamuri, and
Venkataraman 2004), and competitive advan- tage (Taylor and Pandza 2003). Because they often lack IT resources and skills (Carbonara 2005; Chan and Chung 2002), small businesses can benefit from network membership when it comes to IT adoption (Au and Enderwick 2000), as networking can provide SMEs with necessary resources (Fletcher 2002). Conse- quently, our second hypothesis is
H2: Network orientation is directly and positively related to a successful implementation.
Figure 3 Information Technology (IT) Adoption Research Model
Networking Orientation - Network relationship - Collaboration - Knowledge management
External IT Consultant - Experience - Recommendations
Internal IT Resources - Abilities - Capacities - Capabilities
Organizational - Management - People and culture - Knowledge management
IT Success
Implementation
H1
H2
H4
H3
Adoption Environment
Drivers to Adoption -Internal forces
- External forces
IT Adoption
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The Relationship between External IT Consultants and Successful Implementation
Because small businesses generally lack IT expertise and skills (Izushi 2005), firms often seek professional consultants when it comes to IT adoption (Fuller 1996; Shin 2006). It has been suggested that advice from professional consultants or IT vendors can be useful for small business management or owner– managers, especially when they do not have sufficient experience or understanding of IT themselves (Hjalmarsson and Johansson 2003). Research by Thong, Yap, and Raman (1996) suggests that external IT expertise plays an important role in the IT implemen- tation process. Turban, Aronson, and Liang (2005) claim that consulting firms have acquired and absorbed knowledge from assist- ing their clients, and therefore can offer this knowledge to firms that seek their help. Although IT expertise has been perceived to have benefit for small business when it comes to IT adoption, not all small businesses utilize these resources as the knowledge comes at a cost, and some firms are not in a financial position to accommodate such expenses (Bull 2003; Izushi 2005). Therefore, we propose the following hypothesis:
H3: External IT consultants are directly and positively related to a successful implementation.
The Relationship between Internal IT Resources and Successful Implementation
The IT resources factor focuses on the IT abilities, capabilities, and capacities of a firm. The former refers to the skills, the second to the resources and strategies, and the latter the ability of firms to absorb, process, and present the information the firm holds (Carbonara 2005; Guan et al. 2006; Premkumar 2003). According to Caldeira and Ward (2003), orga- nizational competencies; organizational and technical processes; technical, managerial, and business skills; and the allocation of resources within firms are the key ingredients for under- standing IT adoption in the small enterprise sector. Other studies suggest that IT managers should not only understand the reasons why IT needs to be implemented in their businesses, but also the importance of taking into account the needs of their suppliers and customers
(Guan et al. 2006; Mata, Fuerst, and Barney 1995). As mentioned earlier, IT can assist firms in enhancing their business practices, so a clear purpose for pursuing new IT should be identi- fied before any key decision on IT adoption is made. Guan and Ma (2003) argue that the IT innovation capability of a firm cannot be mea- sured by a single dimension alone, as it is comprised of technology infrastructure, pro- duction, process, knowledge, experiences, and organization. It involves an articulation between internal experience and experimental acquisition and includes a wide variety of assets and resources. Hence, the IT abilities, capabilities, and capacities of the organization play a key role in the IT adoption process (Búrca, Fynes, and Marshall 2005), and we hypothesize that
H4: Internal IT resources are directly and positively related to a successful implementation.
Research Methodology Sample and Data Collection
The sample was taken from owners and managers of small businesses that are dealing or participating in any IT adoption process in the retail, financial services, and manufacturing sectors in Southern California. With the help of an employment agency, 437 employers were contacted, and 284 agreed to participate in the survey. The survey questionnaires were mailed, and there were 117 responses. Five more com- pleted questionnaires were received after follow-up telephone calls, which gave a response rate of 43 percent. Of the 122 responses, 17 were excluded because there were too much incomplete data. This resulted in 105 usable sets of data, which give an overall response rate of 37 percent. This sample size is not unusual for this type of study or for the method used. It is similar in size to those used by Baker and Sinkula (2009), Brouthers and Nakos (2005), and Werbel and Danes (2010).
Of the firms that responded to the survey, the industry breakdown is as follows: 36.6 percent were from retail, 45.8 percent from financial services, and 20.5 percent in manufac- turing. In terms of size, 19.6 percent have 10 employees or fewer, 30.8 percent between 11 and 25 employees, 38.3 percent between 26 and 50, and 11.2 percent more than 50 employ- ees. Of the respondents, 58 percent were male and 42 percent female. The age distribution
NGUYEN, NEWBY, AND MACAULAY 213
was 9.8 percent under the age of 25, 40.0 percent between 25 and 34, 38.1 percent between 35 and 44, and 12.4 percent over 45 years of age. All respondents had more than three years experience. The data were tested for potential effects associated with the specific industry sector (retail, financial services, and manufacturing). The results suggest that there are no significant differences in the responses due to industry sector.
Research Instrument and Measuring Scale
The survey questionnaire was developed and structured on four scales that correspond to the factors of the IT adoption environment (see Figure 3). These scales are organizational, network orientation, external IT consultants, and internal IT resources. Although this is the first time this particular model has been tested, scales and items from existing instruments were used as much as possible. Organizational and external IT consultant scales were taken from the IS effectiveness instrument of Thong, Yap, and Raman (1996). This instrument was derived from Kirton (1976)’s Adaption– Innovation Inventory. An additional two items in these two scales were taken from Özgener and İraz (2006) and Payton and Zahay (2005). The network orientation scale measures the orientations of the organization and its suppli- ers and customers. It was adapted from the REMARKOR (Clarkson 1998). This instrument is an extension of the MARKOR instrument by Kohli, Jaworski, and Kumar (1993), which measures the relationship orientation. The REMARKOR instrument has seven scales. These scales have between two and 17 items per scale with a total of 44 items. Only items that are relevant to the context of this study were used. The internal IT resource scale was derived from Caldeira and Ward (2002) and Özgener and İraz (2006).
All items are on a five-point Likert scale (strongly agree, agree, neutral, disagree, or strongly disagree). Table 1 gives descriptive information for each constructed scale. As the number of items in each scale was different, the mean score of each scale was calculated for each individual response, so that for each scale, the respondent had a score between 1 and 5.
Questions for possible reasons/drivers to IT adoption for small businesses were derived from Caldeira and Ward (2002), Payton and Zahay (2005). They include customer require-
ment, business expansion, quality improve- ment, industry requirement, investment, and cost control. These questions are not part of the instrument because the drivers to adoption are separate from the adoption environment (see Figure 3). Questions on demographic informa- tion were also included.
Results Instrument Validation
Exploratory factor analysis using principal component analysis with varimax rotation was performed on the 105 cases to extract the factors that were hypothesized. According to a number of authors, a sample size of 105 is more than enough for four scales (Hair et al. 2005; Kline 1994; Lawley and Maxwell 1971). The Kaiser–Meyer–Olkin sampling adequacy mea- surement (Kaiser 1958, 1974) was 0.823. This is classed as meritorious (Norusis 1990) and indi- cates that the matrix is factorable, and so, the assumptions for carrying out factor analysis were met. Using eigenvalues greater than 1.5 as the criterion, five factors were extracted. Three of the factors were as postulated: these were internal IT resources, organizational, and exter- nal IT consultants; the other two both came from network orientation. After examining the items in the extracted components, it was observed that most items in internal IT resources, organizational, and external IT con- sultants load onto their a priori scale with the exception of two, “management involvement” and “management commitment.” These two items were originally hypothesized to be part of the organizational factor but load onto the internal IT resources factor (see Table 2). Four items originally hypothesized under the network orientation factor were extracted together composing a new factor (see Table 3). Examining this new factor, all items were seen to be related to customers and the authors named it customer relations. The remaining items within the original network orientation factor were all related to suppliers, and so, it was renamed as supplier relations. Table 2 gives a summary of results of factor loadings, and Table 3 gives details of the new extracted component.
The findings indicate that there are five factors that contribute to the IT adoption envi- ronment in small businesses, and these five factors are hypothesized to be directly and positively related to a successful implementa- tion outcome. The extracted five factors explain
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54.75 percent of the variance, which, according to Kline (1994), is satisfactory for social sci- ences studies as it is 60 percent or less. Table 4 gives details of the new measurements, and Figure 4 reflects the revised research model.
As the items from this instrument were derived from previous instruments, it was nec- essary to test and evaluate the reliability of the scales and examine the proposed factors. The reliability of each factor was evaluated by assessing the internal consistency of the items within each factor using Cronbach’s alpha. The results show the reliability values (see Table 5) range between 0.70 and 0.87, which indicate their internal consistency is reliable within each scale (Cronbach 1951; Nunnally 1978). The test for common method variance was conducted
on the five extracted factors using Pearson cor- relation matrix. The results indicated that mul- ticollinearity did not seem to be present in the sample, as all correlation coefficient values are less than 0.7 (Hair et al. 2005).
Model Validation and Hypothesis Tests Figure 4 illustrates a revised conceptual
model based on the factor analysis results (see Table 2). Structural equation modeling was employed to test the hypotheses, and Table 6 reports its results. The goodness of fit indices for the revised model (model 2) are robust. The chi-square value is 6.16 with a significance of p = .162. The chi-square degrees of freedom ratio value of less than 2 (χ2/df = 1.23) is con- sidered to show a very good fit (Marcoulides and
Table 1 Descriptive Information of the Developed Instrument
Scale No. of Items
Measure Reference
Organizational 8 Extent to which knowledge and information are exchanged within and throughout the organization. Management and staff training, development, and contribution
Özgener and İraz (2006); Payton and Zahay (2005); Thong, Yap, and Raman (1996) derived from Kirton (1976)
Network Orientation
9 Extent to which the relationships to the suppliers, business partners, and customers are developed from trust, shared benefits, and investment
Clarkson (1998) derived from Kohli, Jaworski, and Kumar (1993)
External IT Consultants
6 Extent to which external expertise and software vendors are used and encouraged in terms of ease of access and usefulness to the organization
Thong, Yap, and Raman (1996)
Internal IT Resources
10 Extent to which the IT group is knowledgeable with respect to the technical application and business functions within the organization, as well as the IT investment and acquisition
Caldeira and Ward (2002) Özgener and İraz (2006)
Outcome IT Success
Implementation 5 Extent to which the IT application
acquired is successfully implemented in terms of satisfying the requirements of the stakeholders
Caldeira and Ward (2002); Payton and Zahay (2005)
IT, information technology.
NGUYEN, NEWBY, AND MACAULAY 215
Hershberger 1997). This is supported by other strong fit indices (comparative fit index = 0.984, Tucker Lewis Index = 0.935, normal fit index = 0.972, root mean square error of approximation [RMSEA] = 0.047), signifying a good-fitting model (Tabachnick and Fidell 2007).
In Table 6, the original model (model 1) also shows a reasonable fit with chi-square value of 10.52 but it is significant (p = .006), indicating the fit is not as good. The indices also show a strong fit but not as good as the revised model. In addition, the value of the RMSEA is too high
Table 2 Factor Loadings of Rotated Component Matrixa
Item Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
Ext_ITC01 0.742 Ext_ITC02 0.770 Ext_ITC03 0.648 Ext_ITC04 0.811 Ext_ITC05 0.673 Ext_ITC06 0.760 Int_ ITR01 0.634 Int_ ITR02 0.679 Int_ ITR03 0.634 Int_ ITR04 0.653 Int_ ITR05 0.696 Int_ ITR06 0.794 Int_ ITR07 0.662 Int_ ITR08 0.746 Int_ ITR09 0.809 Int_ ITR10 0.724 NR02 0.671 NR06 0.769 NR07 0.727 NR08 0.678 NR09 0.684 OR01 0.725 OR02 0.649 OR03 0.806 OR04 0.724 OR05 0.715 OR06 0.802 OR07 0.763 OR08 0.682 NR01 0.850 NR03 0.778 NR04 0.786 NR05 0.621 VEb 27.42 9.95 8.02 5.21 4.68 Eigen 9.05 3.28 2.65 1.72 1.55
Extraction method: principal component analysis. Rotation method: varimax with Kaiser normalization. aRotation converged in eight iterations. bVariable explained in percentage.
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Table 3 Items of New Extracted Factor—Customer Relations
Customer Relations Sharing Commercial Information with Our Customers Sharing Technical Information with Our Customers Customers’ Feedback Contributes to the IT Development Customer’s Feedback Contributes to the Improvement Business Process
IT, information technology.
Table 4 Variables in IT Adoption in Small Businesses
Independent Variable Measure
External IT Consultants • Seek opinion before acquiring new IT application • Benefit from consultants’ experience • Contribution of knowledge to IT implementation • Decision confirmation on IT application • Usefulness of consultants
Internal IT Resources • Planning of IT • IT investment (infrastructure and resources) • IT investment (training and skill development) • IT resources (skills) • IT resources (infrastructure) • Management involvementa
• Management commitmenta
Supplier Relationsb • Collaboration with suppliers • Knowledge sharing among suppliers (commercial information) • Knowledge sharing among suppliers (technical information) • Benefit from suppliers’ feedback
Organizational • Knowledge sharing among employees • Management support and involvement (overall business process) • Employees involvement and contribution • Management and employees awareness of changes • Management and employees awareness of overall business
process Customer Relationsb • Collaboration with customers
• Benefit from customers’ feedback • Knowledge sharing among customers (both commercial and
technical information) • Response to customers’ needs
aOriginally hypothesized under the Organizational factor. bOriginally hypothesized under Network Orientation factor. IT, information technology.
NGUYEN, NEWBY, AND MACAULAY 217
(RMSEA = 0.103). This indicates that the revised IT adoption model (model 2) is a better fit.
H1 predicted a significant and positive rela- tionship between the organizational factor and a successful implementation. This hypothesis was supported with a t-value of 5.07 (p < .001). H2 predicted a significant and positive relationship between network orientation and a successful implementation. The outcomes of the factor analysis differentiated orientations between cus- tomers and suppliers, which constructed two factors, one for customers and the other for suppliers, both hypothesized to be directly and positively related to successful implementation.
Both factors are significantly related to a suc- cessful outcome with a t-value of 5.86 (p < .001) for supplier relations and a t-value of 9.44 (p < .001) for customers relations. H3 predicted a significant and positive relationship between external IT consultants and a successful imple- mentation. This hypothesis was supported with a t-value of 6.72 (p < .001). Finally, H4 predicted a significant and positive relationship between internal IT resources and a successful imple- mentation. This too was supported with a t-value of 9.40 (p < .001).
In summary, all hypotheses (H1, H2, H3, and H4) are supported, which suggest that a
Figure 4 Revised Information Technology (IT) Adoption Research Model
Supplier Relations - Network relationship - Collaboration - Knowledge & information
External IT Consultant - Experience - Recommendations
Internal IT Resources - Abilities - Capacities - Capabilities
Organizational - Management - People and culture - Knowledge management
IT Success
Implementation
H1
H4
H3
H2
Customer Relations - Network relationship - Collaboration - Knowledge and information
H2
Original factor(s)
New extracted factor(s)
Adoption Environment
Drivers to Adoption -Internal forces
- External forces
IT Adoption
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Table 5 Descriptive and Correlation Matrix
Variable Meana S.D.b (1) (2) (3) (4) Cronbach’s alpha
(1) External IT Consultants 3.28 0.89 0.85 (2) Internal IT Resources 3.50 0.69 0.60** 0.87 (3) Supplier Relations 3.28 0.78 0.51** 0.46** 0.81 (4) Organizational 3.78 0.74 0.33** 0.32** 0.38** 0.80 (5) Customer Relations 3.50 0.74 0.35** 0.35** 0.37** 0.51** 0.70
aCalculated by summation and then divided by the number of items for each respective measure. bStandard deviation. **Correlation is significant at p < .01. IT, information technology.
Table 6 Parameter Estimate Goodness of Fit for IT Adoption Model
Parameters Standardized Estimate
t-Value (p)
Original Model (Model 1) H1: Organizational → Success Implementation 0.106 5.27 (p < .001) H2: Network Orientation → Success Implementation 0.119 8.25 (p < .001) H3: External IT Consultants → Success Implementation 0.110 5.97 (p < .001) H4: Internal IT Resources → Success Implementation 0.143 6.70 (p < .001) Revised Model (Model 2) H1: Organizational → Success Implementation 0.114 5.07 (p < .001) H2: Supplier Relations → Success Implementation 0.138 5.86 (p < .001) H2: Customer Relations→ Success Implementation 0.151 9.44 (p < .001) H3: External IT Consultants → Success Implementation 0.156 6.72 (p < .001) H4: Internal IT Resources → Success Implementation 0.124 9.40 (p < .001)
Goodness of Fit Indicators
Model 1 Model 2
χ2 10.520 6.160 p < 0.006 0.162 χ2/df 2.104 1.232 CFI 0.939 0.984 TLI 0.877 0.935 NFI 0.916 0.972 RMSEA 0.103 0.047
IT, information technology; CFI, comparative fit index; TLI, Tucker Lewis Index; NFI, normed fit index; RMSEA, root mean square error of approximation.
NGUYEN, NEWBY, AND MACAULAY 219
successful implementation of IT in small busi- nesses depends upon the organization, its cus- tomers and suppliers, and both internal and external IT resources. However, as shown in Table 6, according to the results from the revised model, the factor that contributes the most is external IT consultants (standardized estimate [SE] = 0.156). This is followed by cus- tomer relations (SE = 0.151).
Reasons to Adopt IT The results from drivers to adoption show
the different rationale between the firms in terms of IT adoption orientation (see Table 7). The majority of firms are likely to adopt IT to improve the quality of their products and ser- vices or to meet their customer requirements. Business expansion is another driver to IT adoption in small businesses, followed by quality improvement, industry requirement, and investment. Cost control is last on the list of the drivers with only 34.9 percent saying “yes,” but 35.9 percent remaining “neutral.”
Discussions and Implications Drivers/Reasons to Adopt IT
Previous research showed that small busi- nesses are risk adverse (Nguyen 2009); hence, IT adoption occurs for a reason, or reasons, not just for the desire to change. This could be to satisfy customer requirements, industry stan- dards, quality improvement, cost reduction, or efficiency (Andries and Debackere 2006; Bhagwat and Sharma 2007; Corso et al. 2003). Bull (2003) contends that firms should have a
clear indication of why they adopted IT in the first place, as failure to do so could result in disconnection between IT adoption and imple- mentation. The results for drivers/reasons to adopt IT adoption (Table 7) indicate that the top reason that the respondents’ firms adopted IT was to meet customers’ requirements (61.9 percent). This suggests that customers are a driving force that many organizations are beginning to recognize. Mazurencu-Marinescu, Mihaescu, and Niculescu-Aron (2007) contend that customers are becoming more demanding (e.g., for the convenience of IT for purchasing, ordering, checking status, and ease of returning items), so even a small company has to be able to meet or exceed these expectations to be able to compete or survive in the market. This sup- ports Reinartz, Krafft, and Hoyer (2004) who suggest that the current competitive market has forced firms to move closer to their customers. The second most cited reason to adopt IT is growth (61.6 percent). Many researchers have indicated the positive relationships between IT and innovation and growth (Bruque and Moyano 2007; Devaraj and Kohli 2003). As sug- gested by Atherton (2003), one of the necessary resources to invest in growth and innovation is technology. This is in line with Dibrell, Davis, and Craig’s (2008) study, which suggests that there is a strong correlation between IT adop- tion and business growth. Quality improvement of products and services came third (52 percent), followed by industry requirement (46.7 percent), and IT investment (42.9 percent). Surprisingly, cost control came last on the list with only 34.9 percent say “yes” for this reason. The findings suggest that adopting IT is not necessarily to control the cost of running their businesses, but it is an investment as a means to improve the quality of products and services, to expand businesses and, more importantly, to meet and/or exceed their cus- tomer’s expectation, which is a requirement that small enterprises must meet in the current competitive market.
Factors Affecting IT Adoption Environment and Related to a Successful Implementation
From the SEM analysis of the revised model, it can be seen that all five factors, organiza- tional, internal IT resources, external IT exper- tise, supplier relations, and customer relations, make a positive contribution to the success of the IT implementation. Examination of the
Table 7 IT Adoptiona
Drivers/Reasons Yes No Neutral
Customer Requirement
61.9 14.3 23.8
Business Expansion 61.6 13.4 25.0 Quality Improvement 52.0 26.0 22.1 Industry Requirement 46.7 21.9 31.4 Investment (Every
Two to Five Years) 42.9 24.8 32.4
Cost Control 34.9 29.1 35.9
aMeasured in percentage. IT, information technology.
JOURNAL OF SMALL BUSINESS MANAGEMENT220
regression coefficients (standardized estimates in Table 6) for the revised model shows that these factors all have a similar influence in terms of significance. There would seem to be underlying reasons for the significance of the contribution of each of these factors.
The organizational factor is directly and positively related to a successful implementa- tion of IT. It would appear that once the system is implemented, the organizational relation- ships can affect its success. This means that for an IT implementation to be successful, it must be supported by both management and employees; in addition, their involvements and contributions to the change through knowledge sharing among themselves contribute to a suc- cessful implementation. This factor goes hand in hand with the internal IT resources of the firm. These resources represent the firm’s IT capabilities, abilities, and capacities; hence, they need to be adequate, appropriate, helped by employees’ knowledge, and attitude and more so by a positive attitude from owners or top management. The distinguishing character- istic of management does not simply lie on the owner/manager’s characteristics, but it is their commitment and support of the new IT adop- tion and implementation. Hence, this finding does not support Thong (1999), which suggests that owner/manager’s characteristics do not have a direct effect on the extent of IT adop- tion. However, it is in line with Anderson and Huang (2006), Näslund and Newby (2005), and Igbaria et al. (1997) that the involvement and commitment of both management and employ- ees contribute to the success of an IT adoption. As shown in Table 3, “management commit- ment” and “management involvement” were extracted to be part of the internal IT resources, and this factor, representing the IT capabilities, abilities, and capacities of the firm, is directly and positively related to the successful imple- mentation. Hence, it is essential to be aware of the role of the project champion leading the IT adoption project (Näslund and Newby 2005), what resources are available (Acar et al. 2005), teamwork and acceptance (Phelps, Adams, and Bessant 2007), and knowledge sharing and training (Zahra, Neubaum, and Larrañeta 2007).
In addition to the internal IT resources, the use of external IT consultants is very common in small businesses (Bull 2003; Shin 2006). This is because many small enterprises initially do not have expertise; therefore, seeking external IT skills and knowledge is one of the first steps
in IT adoption. Our findings show that this factor is directly and positively related to a successful outcome of an implementation and is highly correlated to the internal IT resources (see Table 5). This could be because consul- tants are independent from the business, and besides possessing knowledge and experience, they can provide unbiased recommendations (Izushi 2005). They often stay on even after business has enough expertise of its own. Moreover, the owners/managers feel more comfortable with consultants as people who know their system, and they trust them.
New IT that is to be adopted within an organization should be integrated with suppli- ers IT, not only for the compatibility of the technology, but also for the knowledge and learning opportunities, which could lead to greater efficiency (Rosenfeld 1996). Small firms can get assistance from their suppliers, as they are usually larger and have more resources—if they can cooperate more efficiently, then it will improve their own profitability (Au and Enderwick 2000).
Results from the factor analysis identified customers as another factor that contributes positively to the IT adoption environment, which in turn relates directly to the success of the implementation. SEM results show that separating customers and suppliers within the relationship orientation results in a model with a better fit. This suggests that the respondents see relationships with customers differently than relationships with business partners or suppliers. The distinctive characteristics of cus- tomer relationships in the adoption environ- ment signify the crucially important role of customers in these small businesses. This means that small firms should take their cus- tomers into consideration when it comes to changes in IT communication in their daily business operation, quite apart from their sup- plier requirements. This finding is in line with Levy, Loebbecke, and Powell’s (2003) study, which argued that collaborating with customers can facilitate the improvement/enhancement of the products and/or services. Results from the drivers to adoption (see Table 7) indicate that the top driver or reason for an organization to adopt IT is their customers. This result rein- forces other views that many small businesses have become more customer oriented (Bhagwat and Sharma 2007; Özgener and İraz 2006; Reinartz, Krafft, and Hoyer 2004). Firms should be able to meet and/or exceed their
NGUYEN, NEWBY, AND MACAULAY 221
customers’ expectation by understanding their customers’ needs (Gummesson 2004; Homburg, Wieseke, and Bornemann 2009). Hence, including the customers as part of the adoption process would subsequently lead to a greater chance of a successful implementation outcome.
This research agrees with studies that have suggested that IT can provide a wide range of benefits to small businesses. More importantly, it suggests a framework (see Figure 5), which firms can use to assess and evaluate their IT
environment, which contributes to a successful IT adoption outcome. The revised framework builds on the Nguyen (2009) IT adoption framework and manifests the important role of customers within the adoption process. The results of this study have implications for IT adoption in small business: first, the study high- lights the importance of drivers/reasons for IT to be adopted. Small business owners/ managers must understand the purpose of the IT to be adopted; the goals, aims, and objec- tives must be clear. Second, firms must be
Figure 5 Revised Framework for Small and Medium-Sized Enterprises (SME)
Information Technology Adoption
Growth stages
Life cycle/ Maturity
Technology- push/
Competitive
Market-pull Innovative
- Abilities - Capacities
- Capabilities
- Experience - Recommendations
- Management - People and culture - Absorptive capacity of firm
Information technology adoption
Internal force
Organizational
External force
External IT
consultants
Internal IT
resources
- Network relationship - Knowledge and
information
Customer relations
Original factor(s)
New extracted factor(s)
Drivers IT success
implementation
- Network relationship - Collaboration
- Knowledge and information
Supplier relations
Outcome
Adoption environment
JOURNAL OF SMALL BUSINESS MANAGEMENT222
able to assess the factors that are directly related to the adoption environment, which can, in turn, contribute to a successful imple- mentation. These factors are (1) the organiza- tion, which includes the management, staff, their knowledge, acceptance, commitment, and contribution; (2) the internal IT resources, which are the firm’s IT abilities, capabilities, and capacities; (3) the external IT consultants, who can contribute their knowledge and exper- tise to develop strong IT; (4) the suppliers, who can provide their assistance for greater effi- ciency; and (5) the customers, who are the driving force of the firm. Hence, firms must engage with each of these factors or risk failure.
Further Research and Limitations
The findings from this study extend the understanding of IT adoption in small business and help in building a greater understanding of the factors surrounding the adoption of IT, but like most empirical research, this study has limitations. First, the sample size was relatively small (only 105), although it is within the range 100–150 subjects agreed to be the minimum satisfactory sample size (Ding, Velicer, and Harlow 1995 cited in Schumacker and Lomax 2004). Replication of this study using a random national sample would be of interest: a larger sample size study would have stronger statisti- cal power, which could be generalized to the entire population of small enterprises with greater confidence. Second, the industries focused on were in manufacturing, retail, and financial services and were geographically spe- cific to Los Angeles County and Orange County in Southern California. Finally, only one respondent was surveyed from each firm. As this study was specific to Los Angeles County and Orange County in Southern California, future research should now be undertaken to test the model by applying it in other small business contexts (e.g., different location and industry), particularly as different countries (e.g., the United States and United Kingdom) define small businesses in slightly different terms.
Despite these relatively minor limitations, the study discussed in this paper has a number of important implications. Far from IT adoption being inappropriate for small businesses, as suggested by a range of authors previously identified here, this study suggests that IT
adoption can be extremely beneficial as long as firms take a broad view of what is needed for success. This study clearly demonstrates that there is no single explanatory factor for the adoption and failure rates of IT in small busi- nesses. Indeed, there are a number of intercon- nected factors that can clearly be identified as predictors of success (organization, internal IT resources, external IT consultants, supplier relations, and customer relations). These factors are particularly important in addressing the tension at the heart of IT adoption in small businesses: the necessity of improving customer relations from within a (well docu- mented) culture of risk adversity. Understand- ing the factors identified in this study can enable small businesses to minimize the risks inherent in IT adoption by utilizing planned strategies for adoption.
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