Document(s) 7 of 17

There is no doubt that the impact of IT is significant. However, "the real challenge is not technology (adoption) per se, but the ability to adapt to take advantage of its emerging functionality" (McKenny 1995, p. 37). Reaping the full benefits of IT adoption requires not only a full understanding of IT applications and their potential but also a readiness to change, all of which points to the importance of mobilizing human resources and constantly improving technical capabilities.

Moreover, as more and more firms successfully adopt and implement IT applications, the comparative competitive advantages derived from the adoption of these applications may very well disappear if firms do not stay ahead. For firms that lag behind, IT adoption becomes merely a question of survival.

This partially explains why contradictory results concerning the impacts of IT adoption have been observed. As we will explain, IT adoption as such is a necessary but not sufficient condition for increased productivity, key competitive and strategic benefits, and stronger financial and export performance. We will also try to assess the ambivalent effect of IT on work and employment.

Relationship between IT and productivity: the elusive connection

The IT–productivity paradox has generated considerable interest among practitioners, professionals, and theorists, especially economists. Because productivity is the fundamental economic measure of IT's contribution, it should be closely examined at the macrolevel and the industry level, as well as at the microlevel (or firm level).

Relationship between IT and productivity at the macrolevel and the industry level

In the last 10 years or so, capital spending was steady for industrial equipment, whereas it constantly increased for computers and communication equipment in the industrialized nations (see Figure 13 for the United States).

Figure 13. Rise of capital spending on ITs in the United States (1987 US dollars). Source: Fortune (13 Dec 1993).

As a result, computing power rose sharply in many countries, with a striking increase registered in the United States (Figure 14).

Figure 14. Worldwide growth in computing power. Source: Fortune (13 Dec 1993).

Despite these large investments, IT did not seem to help national productivity, even in the United States, where these investments were the most evident. As Robert Solow bluntly put it, "we see computers everywhere but in the economic statistics."[1]

If, instead of looking at productivity at the national level, we turn to specific sectors, we find a very different profile, depending on the specific sector (Figure 15). Communications, manufacturing, and utilities demonstrated the largest increases in labour productivity as measured by the ratio of IT investments to the value added for that sector. However, IT investments (ranging from 1 to 10% of the value added) in wholesale and retail trade, transportation, finance and insurance, and other services led only to marginal increases in labour productivity (between 0 and 1%). Mining and construction lagged behind, having the lowest rates in IT investments, along with negative productivity growth.

Figure 15. National productivity indicators based on capital assets in the United States. Source: NRC (1994).

Thus, it appears that the IT–productivity paradox is centred not on manufacturing but on the services sector. Overall, the US services sector spent more than 862 billion United States dollars (USD) in the last 10 years (representing about 85% of total US IT-hardware investments), but its average productivity growth was only 0.7%, significantly lower than the rate for the manufacturing sector. Furthermore, for the federal agencies, which also invested massively in computer hardware, software, networks, and peripherals in the last decade, total government output per employee–year from 1982 to 1990 only grew at a rate of 0.8%,[2] according to the US Bureau of Labor Statistics. What was happening? This paradox can be explained by a number of factors:

1. The measures used in conventional approaches are faulty. In particular, the traditional measurement of productivity, based on the ratio of output to input units, is arbitrarily set and not necessarily comparable from one type of service (for example, health services) to another (for example, financial services). The economy-wide productivity data produced by the US Bureau of Labor Statistics are also subject to severe criticism because 58% of service industries are not included in the national figures and because measurements are highly suspect in other service industries. Finally, when the standard measurement of output is expressed by profit or sales, highly deregulated industries, such as transportation, may show low productivity because their profit margins have shrunk, although their customer services have drastically improved. Multifactor or total-factor productivity may eliminate some biases and distortions by taking into account several inputs (labour, capital, and materials) for a given output, but the lack of data severely limits the availability of national indicators.
2. The distinction between the manufacturing sector and the services sector may be misleading because many manufacturers outsource their less productive activities, which are often related to services.
3. A lag effect may occur because IT adoption and implementation require extensive learning and adjustment. Benefits from IT may take several years to become apparent (Brynjolfsson 1993) and are cumulative (Lefebvre et al. 1995).
4. Mismanagement of IT is another possible explanation. The implementation of IT must not simply superimpose new technology on old processes. IT is also particularly vulnerable to misallocation and overconsumption by managers.
5. Redistribution and dissipation of benefits may occur at the macrolevel. IT adoption may be beneficial to individual firms but may be unproductive from the standpoint of the industry as a whole. (The metaphor usually used is "IT rearranges the shares of the pie without making the pie any bigger.")

We have listed the five most frequently mentioned causes of the IT–productivity paradox at the macrolevel. However, we strongly believe that the relationship between IT and productivity would be better observed at the firm level. The choice of the firm as the unit of analysis can be easily justified by the fact that no country is able to raise its national productivity over the long term without doing so at the firm level.[3] Furthermore, any national call for increased productivity will produce results only if concrete actions are undertaken in firms. Let us therefore examine the relationship between IT and productivity at the firm level.

Relationship between IT and productivity at the firm level

One of the first studies of the impact of IT was carried out by Cron and Sobol (1983). In a sample of 138 medical-supply wholesalers, they found that IT was associated with either very high or very low performers. This classic study led to the hypothesis that IT tends to reinforce existing management practices, whether they are efficient or inefficient. Several empirical studies are listed in Table 19.

Table 19. Principal empirical studies of IT and productivity.
Economy wide or cross sector	Manufacturing	Services
Osterman (1986) Baily and Chakrabarti (1988) Lefebvre and Lefebvre (1988) Roach (1989) Brooke (1991)	Loveman (1988) Weill (1990) Morrison and Berndt (1990) Barua et al. (1991) Siegel and Griliches (1991) Brynjolfsson and Hitt (1993)	Cron and Sobol (1983) Franke (1987) Harris and Katz (1989) Roach (1989) Alpar and Kim (1990) Noyelle (1990) Parsons et al. (1990) Strassmann (1990) Brynjolfsson and Hitt (1993)

Source: Adapted from Brynjolfsson (1993).

Tables 20 and 21 give some details on the data sources and the main findings of the empirical studies listed in Table 19. Some studies were based on government statistics (for instance, Roach 1989; Noyelle 1990; Siegel and Griliches 1991), but most analyzed data collected from individual firms.

Table 20. Studies of IT and productivity in manufacturing firms.
Study	Data source	Findings
Lefebvre and Lefebvre (1988)	667 manufacturing firms	The impact of IT on employee productivity was greater for clerical and secretarial personnel, managers, and professionals than for blue-collar workers
Loveman (1988)	PIMS–MPIT	IT investments added nothing to output
Morrison and Berndt (1990)	BEA	IT's marginal benefit was just 0.80:1 USD invested
Weill (1990)	Interviews and surveys	Contextual variables affected IT performance
Barua et al. (1991)	PIMS–MPIT	IT improved intermediate outputs, if not necessarily final output
Siegel and Griliches (1991)	Multiple government sources	IT-using industries tended to be more productive; government data were unreliable
Brynjolfsson and Hitt (1993)	IDG; Compustat; BEA	The return on IT investment was more than 50% per year in manufacturing

Source: Adapted from Brynjolfsson (1993).
Note: BEA, Bureau of Economic Analysis; IDG, International Data Group, Inc.; MPIT, Management Productivity and Information Technology Project; PIMS, Profit Impact of Market Strategy database of the Strategic Planning Institute.

Table 21. Studies of IT and productivity in services firms.
Study	Data source	Findings
Cron and Sobol (1983)	138 medical- supply wholesalers	Bimodal distribution among high IT investors was either very good or very bad
Lefebvre and Lefebvre (1988)	996 firms	The impact of IT on employee productivity was greatest for managers in wholesale or retail trade services and for secretarial and clerical personnel in other services firms
Harris and Katz (1989)	LOMA insurance data for 40 companies	Weak positive relationship was shown between IT and various performance ratios
Roach (1989)	Principally BLS, BEA	IT capital per information worker was vastly increased, but measured output decreased
Alpar and Kim (1990)	Federal Reserve data	Performance estimates were sensitive to methodology
Noyelle (1990)	US and French industry	Severe measurement problems occurred in services
Parsons et al. (1990)	Internal operating data from two large banks	IT coefficient in translog production function was small and often negative
Strassmann (1990)	Computerworld survey of 38 companies	No correlation was shown between various IT ratios and performance measures
Brynjolfsson and Hitt (1993)	IDG; Compustat; BEA	The return on IT investment was more than 60% per year in services

Source: Adapted from Brynjolfsson (1993).
Note: BEA, Bureau of Economic Analysis; BLS, Bureau of Labor Statistics; IDG, International Data Group, Inc.; LOMA, Life Office Management Association, Inc.
Based on the findings presented in Tables 20 and 21, the IT–productivity connection remains elusive, with contradictory results from study to study. It is therefore necessary to examine the impacts of IT in terms not strictly of productivity but of derived competitive advantage. For example, a firm can be very effective and efficient in its operations but not productive. This would be the case if the firm's products (manufactured goods or services) did not sell as well as expected (because of a recession, for instance); and because the firm's output represents the products sold and delivered, the ratio of input to outputs would remain low even if the firm had definite advantages for key competitive dimensions derived from IT applications.

Impact of IT on key competitive dimensions

The description of information systems as a "competitive weapon" became a cliché during the 1980s. Obviously, information systems do provide support for everyday business operations and activities and are also needed in the diverse decision-making processes in a service organization. They also play a major role in achieving and maintaining or improving strategic advantages (Neo 1988). Bakos and Treacy (1986) noted that there were more than 200 published articles that focused mainly on different frameworks proposing categories of competitive advantage derived from the use of information systems (for example, Porter and Miller 1985) and on success stories.

As technology evolved, numerous articles addressed the topic of EDI or interorganizational systems, which greatly improve customer services, reduce administrative costs, provide faster response to market needs, and allow more flexibility in product design, production, and delivery (Davidow and Malone 1992; De Toni et al. 1994). EDI is thus linked to the emergence of the virtual corporation (Davidow and Malone 1992), closer links binding buyers and suppliers, and higher levels of logistical integration in all activities of the production chain. This value-chain approach, first presented by Porter (1985), represents an important conceptual framework. It emphasizes the sequence of activities that add value to the product. These are the primary activities constituting a firm's core activities related to its product portfolio, as well as the activities that support these primary activities (Figure 16).

Figure 16. IT and the value chain. Source: O'Brien (1993). Note: SIS, strategic information systems.

As can be observed in Figure 16, all these activities need to be supported by IT applications, some of which are present in entities external to the firm. The model allows a firm to identify its core competencies, the competitive advantages over its direct competitors it wishes to pursue, and therefore the efforts it needs to make in certain activities along the value chain. This becomes particularly important when setting technology-adoption priorities.

To assess the extent of competitive advantage derived from the adoption of IT applications, Sethi and King (1994) identified five distinct dimensions: efficiency, functionality, threat, preemptiveness, and synergy (Table 22). These dimensions and their underlying theoretical concepts apply in the highly sophisticated context of very large firms but not necessarily in the context of SMEs.[4]

Table 22. Benefits derived from IT applications in large firms.
Key competitive dimension	Concepts described in maintenance
Efficiency	Use of IT to reduce cost in functional areas (McFarlan 1984) Internal and interorganizational efficiency (Bakos and Treacy 1986) Comparative efficiency (Bakos 1987) Productivity (Synnott 1987)
Functionality	New products and services (Parsons 1983; McFarlan 1984) Customer service (Ives and Learmonth 1984) Differentiation (Porter 1985) Adding value for customers (Clemons and Kimbrough 1986) Unique product features (Bakos 1987; Bakos and Treacy 1988)
Threat	Buyer and supplier power (Parsons 1983) Customer and supplier switching costs (Bakos 1987) Switching costs and search-related costs (Bakos and Treacy 1988)
Preemptiveness	Preemptive strikes (MacMillan 1983; Clemons 1986) Positional advantages and timing (Bakos 1987) First-mover effects (Clemons and Knez 1987)
Synergy	Integration with company strategy (King et al. 1986; Information Week 1987)

Source: Sethi and King (1994).

The potential benefits of AMTs have also received a great deal of attention. Several authors (Buffa 1985; Singhal et al. 1987; Williams and Novak 1990) argued that AMTs can provide multiple and simultaneous competitive advantages for those seeking cost performance, dependability, quality, and flexibility. North American firms with lower AMT adoption rates seem to lag continuously behind European and Japanese companies (Hottenstein and Dean 1992). However, cases of fruitless automation are well documented (for example, see Vieller 1989), and firms, especially small ones, appear to have difficulty gaining the full benefits of these technologies (Schroeder et al. 1989). Nevertheless, if "AMT is not a panacea, it does not have to be a disappointment" (Gerwin and Kolodny 1992, p. 16).

According to Naik and Chakravarty (1992), the acquisition and successful implementation of AMT are now indispensable for manufacturing firms, which have to cope with an increasingly competitive environment characterized by low production costs, smaller batch sizes, product-mix complexity, high-quality products, short product life cycles, and short delivery cycles. There is also evidence that AMTs generate a wide range of strategic advantages, even for small firms (Meredith 1987), resulting in stronger competitive positions for these small manufacturers. The adoption of AMTs therefore greatly improves the competitive performance of most manufacturing firms (Naik and Chakravarty 1992)

The use of computer-based technologies in the nonmanufacturing functional areas, referred to here as administrative applications, also profoundly changes and improves the way these manufacturing firms compete (Bradley et al. 1993). For example, time-based competition, which is now becoming a norm, relies heavily on ITs for the automation of common business processes, such as purchases, inventory, billings, and accounts receivable–payable. In manufacturing firms, it is increasingly difficult to dissociate the impacts derived from administrative and nonadministrative IT applications. Even small manufacturing firms have a mixed portfolio of IT applications (that is, administrative and nonadministrative types of application) in a very high proportion (90.5%), and empirical evidence from these firms shows that the two types of IT application have synergetic impacts on key competitive dimensions (Lefebvre et al. 1995).

Impact of IT on performance

The globalization of markets, capital, and human resources is now an inescapable reality, and internationalization has become a central theme for advocates of economic growth. Broad international trade agreements, such as the one signed by Canada, the United States, and Mexico (NAFTA), are providing firms with new opportunities to expand their market bases.

For SMEs, international markets can be very attractive, and numerous studies have reported that small firms are indeed active outside their national boundaries and capable of facing international competition (Bonaccorsi 1992; Samuel et al. 1992; Thurik 1993).

To what extent does IT contribute to export performance? Although there is ample evidence that IT is the main driving force behind the globalization of capital (almost complete deregulation of worldwide financial markets, instantaneous access to capital from most countries, and capital flows in any currency), the contribution of IT to export performance remains underinvestigated, especially in SMEs. In the age of virtual corporations, there is no doubt that export performance and success depend on "firms' ability to gather and integrate massive flows of information and to act intelligently on that information" (Davidow and Malone 1992, p. 59). Obviously, the link between IT and export performance should, intuitively and logically, be a strong one, especially when one considers the increasing diffusion of real-time manufacturing and service operations.

Financial performance is the bottom line for many firms. However, previous studies failed to convincingly demonstrate a link between financial performance and IT (see, for example, Harris and Katz 1989).

Do firms sacrifice short-term financial benefits by investing massively in IT for the long-term benefits it may provide? Is IT simply a prerequisite for continuing to operate in an increasingly competitive context? These questions have yet to be fully answered.

Impact of IT on work and employment

The impact of IT on the workplace and on organizations has been and will continue to be tremendous. The flattening of organizational structures and the increased vertical integration in the different sectors of economic activity are well-documented trends. These trends have been largely driven by technological advances, but they have also been driven by the need to bring the decision-making process closer to the customer. This was discussed in some detail by Rabeau et al. (1994).

However, one must go beyond these structural changes to look at the impact on different employee groups in certain industries. The impact of IT on employment has been an issue of great concern for policymakers. This concern was reinforced by pessimistic projections suggesting that IT will have a negative impact on overall employment. However, most empirical observations suggest that some of the negative effects of IT are offset by the redistribution of human resources and are only felt in certain types of jobs. It appears that the impacts were first felt at the secretarial and clerical levels and that middle managers and supervisors now constitute the most challenged group in many organizational contexts (Drucker 1993). Information-processing jobs, which were once the raison d'être of middle management, have been gradually taken over by ITs. As most members of the organization also become more "technology fluent," recent observations suggest that computer use is not merely a trend but a reality that will become even more pervasive in all organizational activities. Being computer literate is no longer a desirable quality for most workers but a necessary skill, as indicated by the major shift in the work force that has been taking place for many years (Tables 23 and 24).

This shift is taking place not only in industrialized countries but also, to a lesser extent, in the newly industrialized countries (NICs). However, the emerging trend (Tables 23 and 24) indicates that this is clearly a growing pattern and that NICs are gradually attaining the levels of IT adoption found in the industrialized countries. This will also have an impact on the expected skills of the ever-growing work force in the information sector.

Table 23. Information work force in four developed countries.
Country	Year (%)
	1840	1860	1880	1900	1920	1940	1960	1970	1980
United Kingdom	4.6	5.6	7.9	12.4	19.8	24.4	33.1	36.6
United States		5.8	6.5	12.8	17.7	24.9	42.0	46.4	46.6
Australia					11.5	16.3	22.5	27.5	30.2
Germany							24.6	30.7	33.2

Source: Adapted from Kim (1994).

Table 24. Information work force in the newly industrialized countries.
Country	Year (%)
	1960	1970	1980
Argentina	21.2	21.8	24.1
Brazil	12.0	12.2
Mexico	10.6	16.5	20.9
Venezuela	14.1	21.3	25.6
Hong Kong	14.2	15.8	23.5
Korea	6.3	10.1	14.6
Philippines	5.8	10.5	10.8
Singapore	17.1	24.1	30.0

Source: Kim (1994)

Beyond the fundamental changes to work-force structure and employment, there are also the sociological and psychological impacts created by technology in the workplace. These can be described at four levels:

• Work-group effectiveness;
• Organizational climate;
• Job description; and
• Job satisfaction.

The impact of the introduction of IT applications on work-group effectiveness relates to changes in the attitudes of workers in terms of group work, group conflict resolution, and group respect. The second level of description captures employee perceptions of the effects of IT on organizational climate, whereas the third focuses on how IT affects the actual job being performed. Finally, the fourth considers changes in all aspects of job satisfaction, including security, challenge, and personal growth and accomplishment.

As IT increasingly penetrates all firms in all industries the basic assumption of the specialization of labour may no longer be adequate, and the capacity of the work force to change (including the ability to adapt to the pervasive sociological and psychological impacts of technology) will remain essential in helping firms compete.

Operational measures for the impacts of IT

In this section, we will propose a variety of measures to assess the impacts of IT. Let us first turn to the impact of IT on productivity. There is still considerable confusion about many aspects of productivity, including its definition (Mohanty 1992), and measuring it is therefore a difficult task.

Measurement of productivity at the macrolevel

Two groups of indicators are usually chosen at the national or sectorial level:

1. Partial productivity index — this is the ratio of all outputs to one particular input, such as labour or capital. Although this definition makes the index easy to understand and evaluate, it also limits its use because of its restriction to only one input.
2. Multifactor or total-factor productivity index — this takes into account all inputs, rather than only one. Even though this indicator provides a better indication of the contribution of all factors to output variation, it remains difficult to calculate.

The distinction between the two kinds of indices is very important, as shown in one recent issue of the annual report on Canadian productivity (Statistics Canada 1992). It was reported that the Canadian labour productivity index (partial indicator) steadily increased after 1975 (total increase of 25% over the 1975 level), whereas, for the same period, the multifactor productivity index remained almost the same. The following example helps one to understand how this could have happened. In a case where a firm invested substantial amounts of money in new equipment, more output per worker (or person–hour worked) could reasonably be expected. Thus, the labour index would show an increase, especially if the level of input remained the same. On the other hand, this ratio would not indicate whether the level of output had increased substantially as a function of the capital invested, but the multifactor productivity index would.

Calculation of total-factor and total-productivity indices may become quite complex, and in the last few decades a great deal of effort has been expended on developing different procedures. The measurement of productivity for manufacturing systems seems to be well documented. Some studies published in the last decade (Sumanth 1984; Sink 1985) contributed to a better understanding of the various issues involved in this difficult but essential task. Recent research seems to emphasize the measurement of productivity in white-collar industries (Drucker 1993), such as education and services. This has become important because the productivity of these industries does not compare favourably with that of manufacturing and thus contributes to lowering productivity growth at the national level (Thurow 1992).

Measurement of productivity at the microlevel

The concept of productivity has also been studied and used at a microlevel as normally understood in management science and industrial engineering, namely, at the firm or departmental level. This distinction needs to be made because, according to Carlsson (1989), most microeconomists tend to direct their analyses to the sector level rather than the firm level.

At the firm level, productivity has a very tangible meaning because it relates to what is being produced by the firm, be it services or products. Because such productivity data present a good picture of the way resources are used, they provide managers with an essential tool for planning and control. The data are also used by industrial engineers, whose task is often oriented to the optimization of operations. Comparisons of productivity levels among firms remain difficult, especially if the firms are not part of the same industry. Corrective factors must often be used to account for differences, such as in the quality of labour, wages, levels of unionization, and location. Ratios using capital as an input can also distort the comparison, depending on how expenses are accounted for.

The main difficulty continues to be a lack of comprehension of what productivity really is. Sink (1985) found that very few measures identified by managers were real productivity measures, which led him to conclude that managers still did not distinguish between productivity and certain financial ratios, such as ROI, cost per unit, and profits per sales dollar. In this context, interfirm comparison remains a rather complex task.

Measurement of productivity at the individual level

Within a narrower focus, productivity can also be studied at the group and individual levels. Although the productivity problem has been more often addressed at the national level, part of the solution lies in each individual's attitude toward his or her job, and that is of primary interest to organizational or industrial psychologists.

Many psychologically based programs, such as goal setting, work redesign, financial incentives, and work rescheduling, were found by Campbell and Campbell (1988) to be in varying degrees effective in increasing productivity. Although these authors recognized that such practices do not eliminate the need for other prescriptions at other levels, they believed that more attention should be paid to these kinds of solutions.

In sum, the concept of productivity is better captured at the firm and individual levels than at the national level. Table 25 shows the corresponding proposed measures.

Table 25. Operational measures for assessing the impact of IT on productivity.
Impact of IT	Measures
Productivity at the microlevel	Multifactor or total-factor productivity index adapted to the firm (appropriate choice of inputs and outputs) Change in overall productivity that is due to IT applications, as perceived by the CEO
Productivity at the individual level	Ratio of appropriate outputs to hours worked by each employee Change in the productivity of each category of employees, as perceived by the CEO: Clerical employees Secretarial employees Managers Professionals Blue-collar workers

Note: CEO, chief executive officer.

The perceived change in productivity is less accurate than the factual measures (that is, the ratios) but is easier to compare from firm to firm. If factual measures are used, inputs and outputs are usually firm-specific and sector-specific ones (for example, outputs may be measured by the number of transactions or the number of units manufactured).

Measurement of the impact of IT on key competitive dimensions

Assessing the impact of IT applications on key competitive dimensions is a difficult but critical exercise (Kauffman and Weill 1989; Pedersen 1990). This exercise was undertaken recently in large firms by Sethi and King (1994), who provided a multidimensional index for competitive assessment of the IT applications (Table 22). Their proposed measurement is certainly valuable in the context of large companies.

In the context of SMEs, four key competitive dimensions emerge from the literature: reduced cost, increased quality, improved flexibility, and greater dependability. Each of these dimensions encompasses multiple concepts, as illustrated in Table 26.

Table 26. Operational measures for assessing the impact of IT on key competitive dimensions.
Impacts of IT	Measures
Cost reductionsa	Reduction in labour costs (direct and indirect) Reduction in equipment–machinery costs Reduction in core- and support-activity costs
Qualityb	Product Service Management Working conditions
Flexibilityc	Processes Labour and infrastructure Design and implementation
Dependabilityd	Dependability of the equipment Delivery performance

^aThe list of potential sources of reduced costs is given in Table E1.
^bAn extensive list of quality measures is presented in Table E2.
^cMore details on the exact measures and the corresponding references are given in Table E3.
^dTable E4 presents the detailed measures.

The list of measures provided in Appendix E is as exhaustive as possible. All these measures have been tested in detailed case studies of three Canadian SMEs. Some measures can be used in any sector (for example, increased billing or order accuracy), but others are more appropriate to the services sector (for example, reduced number of complaints regarding employee courtesy) or the manufacturing sector (for example, reduced number of reworks). In SMEs, formal and accurate information, even information as basic as the number of rejects, is sometimes difficult to obtain. One may therefore wish to turn to more subjective measures, such as the relative impact of IT (from no impact to very positive impact) along these key dimensions. Lefebvre et al. (1995) offered a list of potential benefits of the adoption of IT applications, which have been extensively tested in the specific context of SMEs (see Appendix F). The list of benefits was mainly derived from the work of Miller and Roth (1988).

Measurement of the impact of IT on performance

Firm performance was defined in "Impact of IT on Performance" as comprising export performance and financial performance. The corresponding measures are shown in Table 27.

Table 27. Operational measures for assessing the impact of IT on performance.
Impact of IT	Measures
Export performance	Percentage of sales realized in Local or regional markets National markets International markets
Financial performance	Increase during the last 3 or 5 years in Sales Assets ROI Profits

Note: ROI, return on investment.

Export performance is a frequently used factual measure (Bonaccorsi 1992), whereas financial performance can be either factual or perceptual. Because CEOs of smaller independent firms are often reluctant to disclose financial data (Sapienza et al. 1988), perceptual measures for financial performance may be preferable. Such measures could include increases in sales, assets, ROI, and profits for a 3- or 5-year period relative to those of direct competitors.

Measurement of the impact of IT on work and employment

Table 28 captures ways to measure the level of employment and the redistribution of the work force inside firms, as well as the sociological and psychological impacts on different categories of employee.

These factors all need to be measured before and after the adoption of technology if one is to fully grasp not only the quantitative changes that have taken place in the structure and composition of the work force but also the perceptual elements that often permit one to evaluate the success of the adoption and its ultimate effects on the organizational mind set.

Table 28. Operational measures for assessing the impact of IT on work and employment.
Impacts of IT	Measures
Impact on the level of employment and the redistribution of the work force	Increase or decrease in the number of employees in the following categories (before and after the adoption of IT applications): Clerical employees Secretarial employees Managers Professionals Blue-collar workers
Sociological and psychological impacts on the work force	Changes in the following perceptual evaluations before and after the adoption of IT applications:a Group effectiveness Organizational climate Job description Job satisfaction

^aThe changes are evaluated by perceptual measures using multi-item constructs in Appendix G.

[1] Quote from Nobel laureate economist, Robert Solow, from the MIS Quarterly (Jun 1994): editor's comments.

[2] For the longer period from 1967 to 1990, the rate was 1.4%. Therefore, investments in IT did not seem to be accelerating productivity growth; rather, they seemed to be having the opposite effect.

[3] This is, in fact, part of Porter's message when he mentions that "firms, not nations, compete in international markets" (Porter 1990, p. 33).

[4] These dimensions and their corresponding set of perceptual measures were tested in the largest manufacturing and service companies in the United States (one data source was Corporate 1000), with top information-systems executives acting as respondents.

Document(s) 7 of 17