Document(s) 5 of 17

Factors promoting or hampering the adoption of IT applications are numerous and have been a prime concern for many researchers and practitioners (see the bibliography). In this rich variety of literature, adoption factors were sometimes examined in the specific context of SMEs but can be more broadly considered as originating from inside or outside the organization. Figure 11 presents these two different levels of determinants, but both internal and external factors must be taken into account when trying to understand a firm's criteria for deciding about technology. The best case, obviously, is one in which it is possible to ultimately find congruence, or fit, between the factors internal to and those external to the firm.

Figure 11. Levels of determinants of technology adoption.

Adoption factors are usually considered for specific IT applications (for example, spreadsheet software, database-management systems, MRP I and MRP II systems, and expert systems), as illustrated in Table 13, but can be generalized to other IT applications. Some factors listed in Table 13, such as individual characteristics, attitudes, or influences, also pertain to the decision-making process, which will be examined in Chapter 3.

Table 13. Some examples of empirical studies of the adoption–diffusion IT applications.
Authors	Adoption–diffusion phenomenon	Source of data	Adoption–diffusion factors	Major results
Ball et al. (1987): Data Base	Adoption of database-management systems by industrial firms	Questionnaires from 24 members of the Boston Chapter of the Society for Information Management	Organizational characteristics (communication effectiveness, number of engineers and scientists in management, etc.) IT group characteristics (stage in Nolan's life cycle) Information sources (journals, advertisements, salespersons, technical staff, etc.)	Organizations with high R&D commitments and a large number of engineers and scientists in management are more likely to be early adopters
Leonard-Barton (1987): Interfaces	Adoption of SSA by individual system developers	Survey of 145 programmers, analysts, and supervisors in three sites in a natural-resource firm	Perceived innovation characteristics (value, feasibility of use) Organizational influences (reward systems, support systems, client preferences) Personal characteristics (demography, skills, years of experience)	Client preferences, adopter attitudes, training in SSA strongly discriminate adopters from nonadopters Years of experience, perceived accessibility of consulting, supervisor desires, and acquaintance with an advocate are moderately discriminating
Raho et al. (1987): MIS Quarterly	Diffusion of PCs in industrial firms	Questionnaires from 412 (randomly selected) DPMA members	Educational commitment (uncommitted, passive, active, strategic as per McFarlan and McKenny's model)	Phase of diffusion significantly related to level of educational activities
Leonard-Barton and Deschamps (1988): Management Science	Adoption of an expert system by individual sales personnel	Telephone survey of 93 salespeople in dozens of sales sites of a multinational computer company	Personal characteristics (innovativeness, job-determined importance, subjective importance of task, task-related skills, software-use skills, sales performance) Managerial influences (perceived management support, management urging)	Management was more likely to be viewed as having "suggested" or "required" use of the system by people rating "low" on all personal characteristics (except software-use skills)
Davis (1989): MIS Quarterly	Study 1: Current use of mainframe productivity software by white-collar workers Study 2: Predicted future use of PC graphics software by MBA students	Study 1: Questionnaires from 112 users in IBM Canada's development laboratory Study 2: Questionnaires from 40 students attending a large university	Studies 1 and 2: Perceived technological characteristics (perceived usefulness, perceived ease of use)	Study 1: Perceived usefulness and ease of use, both highly correlated with self-reported current use Study 2: Perceived usefulness and ease of use, both highly correlated with self-reported predicted future use In both studies, ease of use appears to be a causal antecedent of usefulness, with little direct effect on use
Davis et al. (1989): Management Science	Current use and predicted future use of a word-processing package by MBA students	Two waves of questionnaires (14 weeks apart) from 107 MBA students attending a large Midwestern university	Perceived technological characteristics (perceived usefulness, perceived ease of use) Expectations of salient referents Attitudes Behavioural intentions	Perceived usefulness and ease of use have a significant direct effect on behavioural intentions over and above their effect transmitted through the mediating attitude construct Behavioural intention to use is significantly related to actual self-reported use
Gatignon and Robertson (1989): Journal of Marketing	Adoption of laptop computers by sales organizations	Questionnaires from 125 senior sales officers in US firms	Adopter industry competitive environment (concentration, price intensity, demand uncertainty, communication openness) Supply-side factors (vertical coordination, supplier incentives) Decision-maker characteristics (information preferences and exposure) Organizational characteristics (centralization, selling-task complexity)	Adoption is associated with high vertical integration and high supplier incentives in the supply industry and high industry concentration and low competitive price intensity in the adopter industry Decision-maker characteristics (preference for negative information and exposure to personal information sources) predict adoption
Huff and Munro (1989): Journal of Information Systems Management	Adoption of microcomputers by individuals	Personal interviews with several dozen microcomputer users	Perceived innovation characteristics (relative advantage, compatibility, complexity, triability, observability)	Anecdotal confirmation that microcomputers diffused quickly because of favourable perceived characteristics
Brancheau and Wetherbe (1990): Information Systems Research	Adoption of spreadsheet software by individual accountants and managers	Questionnaires from 70 accountants and managers in 18 Fortune 1000 firms	Adopter characteristics (age, education, exposure to media, interpersonal-communication exposure, opinion leadership, external social participation, etc.) Communication-channel types (mass media or interpersonal) Communication-channel sources (external or internal to company)	Cumulative adoption follows S-shaped curve using logistic function Early adopters are different from later adopters, as predicted by Rogers (1983) Mass-media channel types–external sources are more important at the knowledge stage; interpersonal channel types–internal sources are more important during persuasion
Cooper and Zmud (1990): Management Science	Adoption and diffusion of MRP systems within industrial firms	Telephone survey of 52 members of the American Production and Inventory Control Society	Innovative characteristics (task–technology compatibility, technical complexity)	High task–technology compatibility (continuous manufacturing methods, make-to-stock marketing strategies) and low technological complexity (e.g., fewer parts per bill of material and per finished good) positively related to MRP adoption but not diffusion
Gurbaxani (1990): Communications of the ACM	Cumulative adoption of the BITNET computing network by universities	Quarterly BITNET Network Information Center records and other sources (1981–88)	Adoption modeled as a function of the number of previous adopters and the time	Three functions were used: Gompertz, logistic, and exponential. The logistic clearly provided the best fit with significant t statistics for all model parameters
Gurbaxani and Mendelson (1990): Information Systems Research	Cumulative adoption of IT by US firms	Archival data on total IT spending by large US firms from industry publications (1960–87)	Adoption modeled as a function of the level of previous IT spending and the time	Three price-modified functions were used: Gompertz, logistic, and exponential. Confirmed that exponential (price) terms were significant in all three cases, implying that a purely behavioural explanation for IT adoption is incomplete
Kwon (1990): ICIS Proceedings	Diffusion of IT in the administrative offices of a southeastern university	Field survey of department heads, "opinion leaders," and "MIS coordination" for 74 administrative offices	MIS maturity (age, applications, equipment) MIS climate (management support, user involvement, management attitude) Work-unit size Network behaviour (centrality, sources, intensity, link sources, link intensities)	External-communication intensity positively correlated with IT diffusion for work groups with a favourable MIS climate
Nilakanta and Scamell (1990): Management Science	Initiation, adoption, implementation of database-requirements analysis and logical-design tools by industrial firms	Questionnaires from more than 70 lead database designers in 17 Houston-area organizations	Characteristics (perceived utility, skills to use, etc.) of 15 information sources (books, periodicals, etc.) and 13 communication channels (telephone, library, etc.)	Hypotheses linking characteristics of information sources and communication channels to diffusion not supported (only 12 of 90 regression coefficients significant at P values ranging from 0.05 to 0.15)

Source: Adapted from Fitchman (1992).
Note: DPMA, Data Processing Management Association; IBM, International Business Machines Corp.; ICIS, International Conference on Information Systems; MBA, master of business administration; MIS, management information science; MRP, material-requirements planning; PC, personal computer; R&D, research and development; SSA, structured systems analysis.

As outlined in Table 13, each empirical study shed light on a particular set of adoption factors in some specific contextual environment. The following two sections will attempt to present an exhaustive list of factors. Please note that a particular factor will be mentioned only if it played a significant role in more than one empirical study.

Internal factors (at the firm level)

Factors internal to the firm that may affect the adoption of technologies can be grouped into three categories: the firm's past experience with technology, the firm's characteristics, and the firm's pursued strategy.

Firm's past experience with technology

A firm's past experience with technology in terms of exposure and organizational learning ultimately affects its future choices in adopting technology (Burgelman and Rosenbloom 1989). This past experience can be captured through notions such as time since first acquisition, number and type of technologies or applications adopted, percentage of different classes of personnel familiar with the technologies, and the current level of assimilation and integration of the technologies.

Firm's characteristics

A firm's characteristics include size, but the influence of this on the adoption of IT applications remains unclear. The adoption of certain technologies may appear more appropriate for larger firms because of the generally large capital investments required and the skilled human resources involved in the implementation and operation of such technologies, but a strong case can be made for successful adoption by smaller firms. They react more quickly, both internally and externally, than larger firms because they are less affected by organizational inertia and because they show a greater degree of involvement by organizational members — especially top management — during implementation. Finally, readily available software and less expensive equipment are now making IT applications more attractive to smaller firms. However, the availability of financial resources (which is associated with size) can be a major stumbling block to the adoption of sophisticated technologies.

Structural characteristics can be captured by indicators such as the degree of centralization in the firm, the degree of formalization of the different activities in the firm, and the degree of technocratization, which measures the percentage of technical employees in the firm. All these characteristics[1] have been shown to be associated with the adoption of technology, particularly technocratization, which is a strong contributing factor.

Firm's pursued strategy

Our third group of internal factors deals with the firm's pursued strategy in both strategic orientation and technological policy. A firm's strategy reflects its actions vis-à-vis markets and technology, which ultimately modify its experience and consequently its overall characteristics and capabilities. The need for a strong technology–strategy connection (or fit) has been advocated by a number of authors (see, for example, Powell 1992), and investments in IT should therefore be closely aligned with overall corporate strategy.

These internal factors are summarized in Table 14. It should be noted that all of the perceptual measures found in the second and third groupings in Table 14 use multi-item constructs; these will be presented in "Operational Measures for Internal and External Adoption Factors."

Table 14. Summarizing the different dimensions of the internal factors.
I: Firm's past experience	II: Firm's characteristics	III: Firm's pursued strategy
Time since first acquisition Number of technologies or applications adopted Types of technologies or applications adopted Current level of assimilation and integration of technologies Percentage by class of personnel familiar with the technologies	Availability of financial resources Centralization Formalization Technocratization Size	Strategic orientation: Aggressive Analytic Defensive Futuristic Proactive Risky Technological policy Technological awareness Technological scanning

External factors

External factors are conditions that exist in a firm's external environment and may affect its technology-adoption decisions. These factors can be found at the industry level, in the macroeconomic environment, or in national policies.

Industry level

At the industry level, we are looking at characteristics such as the degree of diffusion of certain technologies, the availability of external know-how (for example, technology suppliers), the degree of innovativeness of the industry, the requirements imposed by major customers and external markets, and overall levels of competition and technological sophistication in the industry.

Macroeconomic environment

Regarding the macroeconomic environment, the concern is more with the availability of certain conditions such as capital and qualified human resources, as well as issues related to the general characteristics of the work force and the type and quality of industrial relations.

National policies

When considering national policies, we must look for actions that may ultimately affect technology adoption in a nation. These actions may come as a result of national policies implemented by the host nations — for example, tax policies, such as investment tax credits aimed at making adoption easier or more accessible to certain groups of firms; or trade agreements between nations, such as the North American Free Trade Agreement (NAFTA), which modify the competitive environment and force firms to react to new market conditions. The actions may also be the result of social programs that favour technical education in schools, colleges, and universities. In some countries, such as the United States, defence procurement practices have a significant impact on the technology-adoption practices of the firms that want to do business with government agencies such as the US Department of Defense. Finally, societal values (which can be partially altered by national policies) and cultural effects have a definite influence on the adoption of IT applications. This remains an underinvestigated field of research, and most efforts to date have been limited to the study of cultural differences between Asiatic and Western, English-speaking cultures (for example, Straub 1994). Societal values and culture remain diffuse concepts, and we propose to control for these concepts by simply taking into account the country in which adoption is studied.

Bearing in mind our three levels of intervention, we summarized these considerations in Table 15.

Table 15. Summarizing the different dimensions of the external factors.
I: Industry characteristics	II: Macroeconomic environment	III: National policies
Overall competition Type of competitors Number of competitor Proximity of competitors Characteristics of demand Type of customers Number of customers Location of customers Sophistication of demand Requirements imposed by major customers Degree of diffusion of technologies  By technology By type of competitor Availability of external know-how from  Government agencies Institutes Technology suppliers–vendors Trade associations	Availability of capital Availability of qualified human resources Quality of industrial relations Inflation Business cycle	Trade policies (free trade) Industry regulation Government buying practices Defence procurement practices Technology-adoption tax credits Corporate taxation Human-resource training policies and programs

Adoption factors in the specific context of SMEs

Are adoption factors in SMEs similar to the ones that affect larger firms? In general, this seems to be the case, but the relative importance and emphasis assigned to these factors differ. For example, SMEs depend more heavily on external technological know-how. Table 16 offers a summary of some empirical studies of adoption–diffusion of IT applications carried out in SMEs.

Table 16. Some examples of empirical studies of the adoption–diffusion of IT applications in the specific context of SMEs.
Authors	Adoption–diffusion phenomenon	Source of data	Adoption–diffusion factors	Major results
DeLone (1988): MIS Quarterly	Successful use of CBIS	Two questionnaires sent to two respondents (one for the CEO and the other for the person responsible for information systems) (n = 93 small manufacturing firms)	CBIS success related to greater use of external programing support, higher levels of CBIS planning CEO with greater computer knowledge CEO who is more deeply involved Higher levels of computer acceptance by employees More sophisticated computer controls Greater computer training, on-site computers	CEO is key to the realization of potential impact
Raymond (1985): MIS Quarterly	Computerized firms	Questionnaire addressed to the controller in small manufacturing firms (n = 464)	Relationship between organizational characteristics (EDP experience, development, operation, application, interface, MIS rank) and user satisfaction and system use	Firm size is not associated with user satisfaction or system use MIS success is related to sophistication level of applications
Alpar and Ein-Dor (1991): Information and Management	Information-system concerns	Questionnaire mailed to small high-technology firms (n = 636)	Ranking information-system concerns (reliability, system quality, change, cost, development, integration, control, people, data management, hardware, software)	Major concerns about information systems are system reliability, system quality, change,cost, development, integration, and control
Lefebvre and Lefebvre (1992): Journal of Engineering and Technology Management	Adoption of 28 computer-based administrative and manufacturing applications	Self-administered questionnaire from CEOs of 95 small manufacturing firms	CEO's personal characteristics CEO's attitudes and personality traits Characteristics of CEO's decision-making process Firm's characteristics	CEO characteristics and degree of firm innovativeness are closely related Variables related to the CEO are more important than structural characteristics
Doukidis et al. (1993): International Conference on Information Systems	Use of microcomputers for at least 6 months and up to 5 years	Semistructured interviews in 50 small firms in Greece (retail and distribution, services and manufacturing); longitudinal study (1984 vs 1989)	Previous experience with computers Factors influencing the initial decision to computerize (improved availability of information, time savings, improved stock-control procedures, improved accounting procedures, cost reduction, staff reduction) Major obstacles to adoption (lack of computer experience, software and hardware selection, implementation problems, cost and adequate service)	Improved processing and availability of information and time savings are the most important adoption factors Lack of computer experience is the major stumbling block
Kirby and Turner (1993): International Journal of Retail and Distribution Management	Use of computers in 147 small retail businesses	Survey questionnaire	Computer literacy of CEO Dependence on supplier Failure to appreciate the hard and soft benefits of IT	The greater the computer literacy of a small-business owner and the greater the dependence on the supplier, the more likely the firm will adopt IT through awareness of its benefits, especially for the strategic management of the business
Palvia et al. (1994): Information and Management	Adoption of computers, use of soft-ware packages and information systems	Questionnaires mailed to very small firms with fewer than 50 employees (n = 131)	Business characteristics (size, age, profitability) Individual characteristics of CEO (general education, computer knowledge)	Strongest determinants of computing in very small firms are size, computing skills of the owner–manager, and age of the business
Lefebvre et al. (1996): IEEE Transactions on Engineering Management	Adoption of advanced computer-based production applications (actual use and planned adoption)	Questionnaires mailed to SMEs (n = 116 independent SMEs)	Technical capabilities (of different categories of employee) Strategic motivations (in terms of costs, productivity, quality, flexibility) Influences of internal and external proponents	Strongest determinants of future adoption of advanced manufacturing technologies are the technical capabilities of blue-collar workers, the influence of customer and technology suppliers, and outward-oriented strategic motivations

Note: CBIS, computer-based information system; CEO, chief executive officer; EDP, electronic data processing; MIS, management information science; SMEs, small and medium-sized enterprises.

Operational measures for internal and external adoption factors

This section will present ways to measure the importance in a firm of the different factors listed in Tables 14 and 15. Some factors are factual (for example, time since first acquisition of an IT application), whereas others are perceptual (for instance, technological awareness). All perceptual factors are measured using multi-item constructs that have been previously tested, and exact references for these constructs are given in Table 17. However, references for factual factors are not offered because they represent traditional measures.

Table 17. Operational measures for internal and external adoption factors
Internal factors (Table 14)	Measures
Firm's past experience
Time since first acquisition	Exact date
Number of IT applications adopted	Simple count of IT applications, as listed in Table 12
Current level of assimilation and integration of technologies	Score, as proposed in "Proposed Measurement of the Level of Adoption of IT Applications"
Percentage by class of personnel familiar with the technologies	Percentage of employees actually using IT by category (clerical staff, secretarial staff, managers, professionals, blue-collar workers)
Firm's characteristics
Size	Volume of annual sales (actual and projected for each of the next 3 years)
Availability of financial resources	Actual amount spent on IT applications (hardware and software) on an annual basis Budgeted amount on IT applications for each of the next 3 years Relative importance of investments in IT applications (actual amount divided by annual sales; budgeted amount divided by projected annual sales)
Centralization	Multi-item construct first proposed by Miller and Friesen (1982) (see Appendix C)
Formalization	Multi-item construct used by Lefebvre and Lefebvre (1992) (see Appendix C)
Technocratization	Number of scientists, engineers, programmers, and technicians divided by the total number of employees
Firm's pursued strategy
Strategic orientation Aggressiveness Analysis Defensiveness Futurity Proactiveness Riskiness	The six dimensions of the strategic orientation are captured by multi-item constructs proposed by Venkatraman (1989) (see Appendix C)
Technology policy	Multi-item construct proposed by Ettlie and Bridges (1987) and adapted to the context of SMEs in Lefebvre et al. (1993) (see Appendix C)
Planned introduction of IT applications	Planned introduction of the applications listed in Table 12 within the next 3 years
Technological awareness	Multi-item construct first used by Miller and Friesen (1982) (see Appendix C)
External factors (Table 15)	Measures
Industry characteristics
Overall competition
Type of competitors	Direct competitors: mainly small, medium-sized, or large firms or multinationals
Number of competitors	Number of direct competitors
Proximity of competitors	Number of direct competitors in the region, in the country, and outside the country
Characteristics of demand
Type of customers	Industrial vs individual customers; mass vs customized products or services
Number of customers	Average number of customers by type
Location of customers	Average number of customers in local, national, and international markets Percentage of sales realized in local, national, and international markets
Sophistication of demand	Perceived level of sophistication of different types of customers
Requirements imposed by major customers	Perceived ease of predicting customers' demand and requirements
Degree of diffusion of technologies By technology By type of competitor	Comparison with existing national statistics (if available)
Availability of external know-how	Accessibility, usefulness, and cost of external know-how from agencies, institutes, technology suppliers–vendors, and trade associations
Macroeconomic environment
Availability of capital (including venture capital) Availability of qualified human resources Quality of industrial relations Inflation Business cycle	Porter (1980) discussed a wide variety of competitive advantages different countries can create for their firms; these measures are country specific
National policies
Trade policies (free trade) Industry regulation Government buying practices Technology-adoption tax credits Corporate taxation Social and economic policies Human-resource training policies and programs	Once again, measures are country specific. Baldwin et al. (1994) proposed a list of governmental programs and actions that were rated by firms (in terms of relative importance)

Note: SMEs, small and medium-sized enterprises.

Internal factors are universal, or generic, and their measurement can therefore be useful in any country. However, external factors (especially the ones pertaining to the macroeconomic environment and to national policies) are country specific. For international comparisons, identifying a common set of measures for different countries poses certain difficulties.

[1] A case for the reverse can be made here as well: the use of IT also has a definite impact on the organization of firms (Rabeau et al. 1994). The feedback loop provides an explanation for this phenomenon.

Document(s) 5 of 17