The in uence of attitudes on personal computer utilization among knowledge workers: the case of Saudi Arabia

Transcription

1 Information & Management 36 (1999) 185±204 Research The in uence of attitudes on personal computer utilization among knowledge workers: the case of Saudi Arabia Muhammad A. Al-Khaldi *, R.S. Olusegun Wallace Department of Accounting and MIS, College of Industrial Management, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia Received 22 April 1998; accepted 24 March 1999 Abstract Since the introduction of personal computers (PCs) in the early 1980s, Saudi Arabia has made major investments in PCs to match its rapidly growing economy. As a result, the PC business has become one of the fastest growing sectors in the Kingdom of Saudi Arabia. Our paper reports on the results of a study which investigates the relationships between end-users' attitudes and PC utilization among knowledge workers in the context of Saudi Arabia. To gain a better understanding of the factors that in uence the use of PCs, we adopted Triandis' theory which suggests that behavior is determined by attitudes, social norms, habits and expected consequences of behavior. Our study is based on previous efforts to test the theory's validity in Saudi Arabia. Our results suggest that PC utilization is determined by individual attitudes, personal characteristics, such as PC experience, facilitating conditions, such as PC access and social factors. We also observed that respondents to our questionnaire differ in the level of importance they attribute to the factors hypothesized as in uencing PC utilization compared to Canadian respondents in a previous study. # 1999 Elsevier Science B.V. All rights reserved. Keywords: PC utilization; User attitudes; Social factors; Knowledge workers; Saudi Arabia 1. Introduction One aim of our study is to ascertain the attitudes of knowledge workers in Saudi Arabia [34] toward the use of PCs, and to determine whether those attitudes are similar to those reported by Thompson et al. [41, 42] for knowledge workers in Canada. There are reasons for replicating the Canadian study in the Kingdom of Saudi Arabia. Essentially, knowledge about the factors that promote the usage of PCs is useful to the global economyðfar too important to be *Corresponding author. Tel.: ; fax: ; makhaldi@kfupm.edu.sa /99/$ ± see front matter # 1999 Elsevier Science B.V. All rights reserved. PII: S (99) limited to the ndings from one national study. Different contexts allow us to understand variation across the world. The Canadian context is different from the Saudi context both from the point of view of economic development and cultural orientation. First, Canada is more developed than Saudi Arabia. In addition, Saudi Arabia has only recently started to develop the educational, organizational and institutional systems that have long existed in developed countries, such as Canada. Second, Canada is essentially a secular community, while Saudi Arabia is an Islamic society with a culture that manifests high power distance, uncertainty avoidant, collectivist, and femininity characteristics (along Hofstede's [23] cultural dimensions (see

2 186 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 [4, 5, 12]). Although the potential importance of PCs in the social and economic development of Saudi Arabia is recognized by Saudi authorities [11], the need to uphold the tenets of Islam was probably responsible for the delay (until January 1999) in allowing public access through the PC to the enormous potential of the internet within Saudi Arabia. Given these societal differences, we would expect the PC utilization attitudes of the respondents in Saudi Arabia to differ from those of Canadian respondents. Another aim of the study is to explore the importance of factors (such as attitudesðaffect, beliefs, behavior; societal and facilitating conditions) in promoting the usage of PCs in Saudi Arabia. The Kingdom of Saudi Arabia has a population of 12.3 million citizens and 4.6 million foreign nationals, mainly from the Indian sub-continent and East Africa. More than 50 percent of the Saudi population are under the age of 16. The country has a stable economy and is a conducive environment for commerce and business. Its commercial sector is relatively unregulated and the nancial sector is liberalized. Saudi Arabia's microcomputer and minicomputer market exhibits growth rates similar to the American market [2]. As a result, it would be interesting to learn whether the relative strength of attitudes towards PC usage in Canada holds in Saudi Arabia. It is also interesting because, in contrast to previous studies of the factors capable of in uencing PC utilization in the Kingdom (e.g., [1, 9, 10]), our study used practitioners rather students as subjects of enquiry. 2. Conceptual framework and research questions The link between end-user attitudes and PC utilization has occupied the attention of scholars in recent years. The different frameworks include: 1. The theory of reasoned action (proposed by Fishbein and Ajzen [18] and adopted by Thompson et al.) which seeks to investigate the reasoning that lies behind the decision to utilize PCs. This fact and the theory of perceived behavioral control [6, 7, 8] suggest that PC usage can be predicted by an individual's intention to use it. This intention is determined by some weighted combination of the individual's attitudes toward PC-related objects (hardware, software, etc.).; 2. The theory of perceived behavioral control, based on the individual's intention to perform a given task, is an extension of the theory of reasoned action to take account of behaviors over which people have incomplete control; 3. Technology acceptance model proposed and adopted by Davis et al. [14]. This model highlights perceived ease of use and perceived usefulness of the PC; 4. Expectancy model (proposed by Vroom [45] and adopted by DeSanctis [16]) based on the belief that the use of PCs leads to good performance, which in turn leads to desired outcomes or the valence of available outcomes; 5. Job diagnostic survey (utilized by Yaverbaum [47]); and 6. Computer attitude scale (developed by Loyd and Gressard [29] and used in experiments [20, 21, 30, 31] by them, Al-Jabri [3] and Al-Khaldi and Al- Jabri [9]). This framework examines four different factorsðanxiety or fear of PCs, con dence in ability to use or learn them, liking them, and their usefulness. Our study draws upon all these. Attitudes are determined by the individual's beliefs about the consequences of his or her behavior, based on the social norms and mores. The relationship is illustrated in Fig. 1. In this context, user attitude is construed as a learned predisposition toward PC-related objects. Once the concept is de ned thus, its operationalization requires the identi cation of all PC-related objects Fig. 1. End-user attitude as a determinant of PC usage.

3 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± affecting end-user's attitudes and the development of a measurement instrument to gauge the user's reaction. While Fishbein and Ajzen considered all beliefs about an act or behavior, Triandis [43, 44], in a modi cation of the Fishbein and Ajzen's theory, makes a clear distinction between beliefs that link emotion to the act (occurring at the moment of action) and beliefs that link the act to future consequences. Triandis argues that an individual's intended behavior is determined by his or her feelings toward the object (Affect), expected consequences of the behavior (cognition) and what she/he should do (social factors). The desire to understand end-users' behaviorð their attitudes and perceptions toward the availability of the PC, its costs and its ease of useðcompels the adoption of a multi-disciplinary approach. This requires the use of a cumulative research tradition by which theories and models borrowed from other disciplines serve as a foundation [19, 27, 38]. For example, a cognitive account of PC utilization is a theory about its functional capacitiesðthe things it can doðthat are involved during the completion of the questionnaire. There are numerous ways of describing the range and kinds of functional capacities involved in any aspect of PC utilization but most scholars have found it useful to describe these capacities in terms of attitudes. However, probably because of the minimal use of the knowledge accumulated in the social psychology literature, the empirical evidence on whether PC utilization is in uenced by end-users' attitudes is mixed and inconclusive; (e.g., see [40]). In addition, little evidence relates to developing countries in general, and the Arabian Gulf Region in particular. To facilitate our understanding of attitudinal factors of PC utilization, we proposed the `working model' depicted in Fig. 2. The proposed model is a simpli cation, as we are not attempting to cover all relevant aspects of PC utilization. The model groups many of the individual/ organizational motives for PC utilization into four parts: (1) individual attitudes toward the PC; (2) social factors capable of affecting PC usage; (3) individual pro les (age, experience, education, access and training of the respondents); and (4) organizational factors which facilitate its use. The motives that are described in the model as attitudes are disaggregated for analytical convenience into three portions, along the lines suggested by Fishbein and Ajzen: affect, behavior, and cognition. A theory of PC utilization would not be a complete theory of attitude if the emotional and intentional dimensions are excluded, thus previous studies have examined the role of the affective and cognitive faculties. In our study, these are referred to as affect and behavior, respectively. We separated the cognition motive into short-term and long-term consequences. The rst has two dimensionsðcomplexity (anxiety or fear of the PC) and usefulness (how it ts the tasks and job of the enduser). Speci cally, the study addresses two sets of questions: 1. What are the factors that have the highest in uence on the end-users' utilization of PCs in Saudi Arabia? and what is the comparative importance of attitudinal factors in different countries? For example, do end-users in different countries have similar attitudes? Do countryspeci c conditions imply different PC usage? 2. Are there within-country differences in the importance of the attitudinal factors? For example, Culpan [13] has shown that there are perceptual differences in the importance of attitudinal factors across industries in south-central Pennsylvania. On this basis, we investigate whether our respondents differ in their perceptions of the degree of importance of the factors which may in uence PC utilization. We also investigate whether any differences in the respondents' perceptions are due to the differences in their pro les. 3. Operationalization of constructs To operationalize the constructs we adopted and amended the instrument designed by Thompson et al. The constructs are: (1) Social factors. This set of factors deals with within-organization socialization on the use of PCs and comprises four items: (1) support of senior management of the department introducing PCs; (2) the CEOs and managers' support of the use of PCs for jobs; (3) the general support of the organization in the introduction of PCs; and (4) the proportion of departmental workers who use PCs. These factors are presumed to capture the signals and messages that an enduser receives from his/her peers and others about what

4 188 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 Fig. 2. Factors in uencing PC utilization. they should do. They deal with an individual's internalization of work ethics and mores in organizations and capture what individuals perceive as an acceptable mode of conduct, given their generally accepted organizational culture. In line with Thompson et al., we hypothesize that: H1: There is a positive relationship between social factors concerning the use of PCs and PC utilization. Each of the four factors was measured by a simple questionnaire item. For the rst three, the items were scaled by a ve-point Likert-type scale (1 ˆ strongly disagree to 5 ˆ strongly agree). The fourth item was scaled using a ve-point scale representing different proportions (1 ˆ 10% or less to 5 ˆ 90% or more). (2) Affect factors represent respondents' affection and disaffection for the PC. While we recognize that affective and cognitive components of attitude may overlap, we have adopted the strategy of separating the two as suggested by Thompson et al. Affection for the PC is a function of an individual's previous training and awareness of the PC. We hypothesize that:

5 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± H2: There is a positive relationship between affect and PC utilization. Affect relates to three items: (1) PCs make work more interesting; (2) working with PCs is fun; and (3) PCs are good for some tasks but not for the kind of task I want. A ve-point Likert-type scale was used (1 ˆ strongly disagree to 5 ˆ strongly agree). (3) Cognitive factors. This set of factors deals with the perceived consequences of adopting a PC for the individual, such as `working with the PC is complicated or it takes too long to learn how to use a PC to make it worth the effort.' As Thompson et al. suggest, the perceived consequences construct is consistent with the expectancy theory of motivation, proposed by Vroom, which suggests that individuals evaluate the consequences of their behavior in terms of potential rewards and base their actions on the attractiveness of the rewards. Perceived consequences may be positive or negative, just as they can be high or low. The consequences may be felt immediately on the use of a PC or may produce a valence whose effect may extend beyond the shortterm to the long-term. We examine two perceived short-term consequences and one perceived long-term consequence Short-term consequences (a) Complexity. Because complexity refers to the dif culty that an individual may experience while using the PC, we hypothesize that: H3: There is a negative relationship between perceived complexity and PC utilization. Four complexity items were given to the respondents and a ve-point Likert-type scale was used to capture their opinions on each (1 ˆ strongly disagree to 5 ˆ strongly agree). (b) Usefulness or job performance facilitation (JPF). This set of perceived behavioral control factors was captured, using six items that describe the potential outcomes and valences from using a PC; e.g., the use of a PC can decrease the time needed for my important job responsibilities. These refer to the PCs potential for enhancing the individual's job performance. We hypothesize that: H4: There is a positive relationship between perceived job t and PC utilization Long-term consequences The positive and negative effects of PC utilization can often be felt on work performed long after the PC was introduced. Such factors were captured with six items, using a ve-point Likert-type scale. Respondents were asked for their opinion on the perceived understanding of the long-term effect of using the PC. We hypothesize that: H5: There is a positive relationship between perceived long-term consequences of PC use and PC utilization. The six types of effect on job characteristics are: the level of challenge of the respondents' job; the opportunity for preferred future jobs; the amount of variety on the job; the opportunity for more meaningful work in the future; the exibility of changing jobs in the future; and the opportunity for job security. The effects that the respondents were asked to consider include the potential for increase, decrease, or no change in each of the six job characteristics. (4) Facilitating factors refer to the availability of support systems. Six items were also used to operationalize these factors. We adopt Triandis's de nition of facilitating factors as the ``objective factors, `out there' in the environment, that several judges or observers can agree make an act easy to do.'' We assumed that there was a positive association between supporting systems and PC utilization. We did not factor into our study conditions which impede PC utilization. As a result, we hypothesize that: H6: There is a positive relationship between supporting facilitating conditions and PC utilization. (5) PC utilization factors were captured using three dimensions: the intensity of PC use; frequency of PC use and diversity of software packages used. Intensity was measured by the number of minutes devoted to the use of PC per day at work. Frequency of use was measured by four categories, ranging from less than once per week to several times a day. The diversity of use was measured by counting the number of software

6 190 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 packages optionally used at work, which ranging from 1to5. (6) Other factors investigated include PC training, PC experience, and age. Training was indicated by Thompson et al. as an element that needs to be investigated with regard to PC attitude and it was later investigated by them. Respondents that are trained in the use of the PC would most probably tend to attribute greater importance to PC utilization motivators than those who are not. The more exposed to PC training, the more likely that there would be perceived positive long-term consequences. As a result, we hypothesize that: H7: There is a positive relationship between PC training and PC utilization. Other studies have found a signi cant effect of PC access and experience on reducing PC anxiety and enhancing its utilization. We predict PC utilization to increase as the individual respondent gains more access to the PC, or as he gains more experience working with the PC. PC familiarity and experience can reduce fears and negative attitudes toward the PC and can encourage PC utilization. We hypothesize that: H8: There is a positive relationship between the degree of access to the PC and PC utilization. H9: There is a positive relationship between the extend of PC experience and PC utilization. Given the relatively nascent usage of PCs in the Kingdom of Saudi Arabia, it is possible that the level of education and age may be major factors in the utilization of the PC. We predict that the level of education would be positively associated with PC utilization and that age would be negatively related to PC utilization. Younger employees are likely to have had some training in the use of PCs in their education, while older people would have gone to school at a time when PC education was not available. These speculations form the bases of following hypotheses: H10: There is a positive relationship between education level and PC utilization. H11: There is a negative relationship between age and PC utilization Organization size Organization size has been suggested as a predictor of PC adoption in organizations [15, 17, 25, 35, 36]. On the basis of empirical research on rms, we suggest that organization size may be equally signi cant for PC utilization and that it may have a stronger moderating in uence than individual attitudes on PC utilization by knowledge workers. The larger a rm is, the greater are the prospects of computerization. If this is true, this challenges one of the most central orthodoxies of PC utilization studies, and implies that those seeking to promote PC utilization ought, in choosing the method of motivating PC utilization, to give as much, or more weight to organization size, as to other motivating factors. Firms with substantial size can attain more effective transition from manual to PC systems through investment in training. Growth in size generates pressures for computerization. According to Raymond [37], smaller rms can hardly afford the enormous costs of PC utilization (employment of persons with specialized knowledge, training staff, transformation of manual to PC systems, acquisition). The activities of small rms are often below the level that is optimal for computerization. While previous studies have examined the factors that in uence PC utilization in small rms within a country (e.g., New Zealand, Saudi Arabia and Taiwan [24]), the studies have often assumed that the factors that promote PC utilization in small rms would be different from those in large rms. This assumption is based on intuitive and reasoned conclusion rather than empirical investigation. We use number of employees to measure organization size. This has been used as a measure of organization size in several studies in accounting (e.g., [46]). 4. Methodology 4.1. Sample The study was conducted in the Eastern Province of Saudi Arabia. The survey locality is typical of the

7 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± country. It is the headquarters of the dominant rms in the Kingdom and has a great number of organizations (light industries, retail outlets and many government administrative of ces). Most of the respondents work in semi-government pro t-seeking rms and private rms located in Dhahran and Dammam, the cities with the largest concentration of knowledge workers in the Eastern Province. A sample of 200 knowledge workers was targeted. Knowledge workers whose opinions are pooled for this study include accountants, treasurers and controllers, general managers, engineers, production analysts, and corporate planners. They generally use low-end applications software and not decision support or expert systems. However, the knowledge workers who participated in the study as end-users come within the rst three categories of the six end-user categories identi ed by Rockart and Flannery [39]: 1. non-programming end-users, who access data through predeveloped menu-driven software packages; 2. command level end-users, who generate unique reports for their own purposes, usually with simple query languages; and 3. end-user programmers, who utilize command and procedural languages to access, manipulate, and process data for their personal information needs. In total, after one follow-up (and telephone communication) with the contact persons in each participating rm, 151 (75.5%) useful responses to the questionnaire were collected from the participants. Every questionnaire which achieves less than 100 percent response rate has a potential non-response bias problem. Like most researchers, we have addressed this problem in two ways. 1. By attempting to obtain as high a response rate as possible. However, questionnaires dealing with sensitive personal issues may be more likely to result in non-response. Users who are not comfortable with the PC may be reluctant to respond, while competent users may be particularly interested in the subject and willing to participate in the study. Here, we attempted to reduce non-response bias by using a follow-up procedure and the coordinator within a participating rm to chase potential non-respondents. 2. By estimating qualitatively the potential effect of non-response on the ndings. On this basis, we conducted a comparative analysis of responses by date of response (or date of receipt of responses). This analysis is based on the presumption that late responders are reasonable `surrogates' of nonrespondents. The response rate of 75.5% is the average of responses from the entire sample; the response rates from participating rms vary from a low of 60 percent to a high of 100 percent. Every effort was made to minimize the occurrence of nonresponse within a returned questionnaire. Where one was noticed, the individual rm from where the incomplete questionnaire came was consulted and the contact person in that rm was asked to trace the individual respondent to get the required response. The questionnaire used to elicit opinions from respondents is a slightly modi ed version of an instrument used by Thompson, et al. for Canadian surveys. The present study differs from these studies in the following ways. First, it differs in terms of the spread of respondents. Whereas the Canadian study collected responses from participants drawn from a large multinational manufacturing rm, the respondents to our study were drawn from 10 of the leading rms in the Eastern Province of Saudi Arabia. Second, the questionnaires were not completed, using the DISKQ technique adopted by Thompson et al. Instead, we employed a paper and pencil technique. We concluded that an interactive questionnaire was not suitable for the present environment of Saudi Arabia. The use of the method would affect the response rate in an environment where people are not used to it. 5. Procedure In each participating rm (see Table 1 for the characteristics of the participating rms), a coordinator was appointed to arrange the distribution of questionnaires to (and collection of completed ones from) knowledge workers. The survey envelope included a cover letter from the researchers and from the coordinator in the participating rm, introducing the purpose of the study and guaranteeing con dentiality of individual responses. It also indicated that the results

8 192 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 Table 1 Characteristics of respondent companies Number of employees Type of firm would not refer to individual responses but would be published in summary form only. 6. Aggregation of responses No. of firms (%) Under 50 Small ±200 Medium Over 200 Large Industry classification 1. Manufacturing Construction Agriculture Services Oil and energy Trade, retailing, leasing The instrument is structured in a way that asked the respondents (see Table 2 for their pro le) to indicate the level of their agreement with perceptual anchors on the level of importance of each of the suggested factors capable of promoting PC utilization. The survey instrument used a Likert scale (varying from `strongly agree' ˆ 5 to `strongly disagree' ˆ 1, with room for equivocation in the middle, i.e., `neutral' ˆ 3). While factors are not independent, respondents were asked to treat each factor as independent of the others and to assign as many `5s', `4s', `3s' etc., as they felt were warranted by the factors included in the survey instrument; i.e., not to rank them. The responses to the items within each group were aggregated to produce indexes for each grouped variable. For example, the PC utilization index was derived by averaging the means of the responses to each of the three items that make up PC utilization. The validity of the survey instrument was assessed by a factor analysis. Table 3 contains rotated factor matrix (varimax) with eight speci ed factor loadings on their own constructs than on others. This is the case with rotated structure. However, there is one exception. Item JPF1 fails to load highly on Factor 2, which represents the construct job performance facilitation but loads highly on Factor 8, which captures the affect items. As a result, the rotated structure appears to be Table 2 Profile of respondent individuals Age No. % No. % 20±25 years ±30 years ±40 years ±50 years and above Total Access to a PC Ownership of a PC No access Yes Low No Average Total High Total Experience in using the PC Educational background None Less than High school Low High school Moderate Some years in college High Bachelor's degree Total Graduate degree Total

9 Table 3 Rotated factor matrix of attitude items M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± Attitude items LT LT LT LT LT LT JPF JPF JPF JPF JPF JPF FC FC FC FC SF SF SF SF COM COM COM COM TR TR UT UT UT AF AF AF consistent with the underlying theoretical constructs of the survey instrument. In further statistical analysis of the job performance facilitation items, JPF1 was not included. For example, the Cronbach's reported for the job performance facilitation does not include JPF1. The internal consistency of the eight scales was assessed using Cronbach's alpha (). We report two inter-rater correlation coef cients (ICCs) that are estimates of reliability and validity. ICC(1) is an estimate of the degree to which responses on each item are similar, is reported in Table 4, and ICC(2) is an estimate of the reliability of the mean scores [22], is reported in the last column of Table 8. ICC(1) and ICC(2) address two different issues [33]. If two respondents were randomly sampled from the same group and their two sets of scores correlate, the resulting correlations would approximately equal ICC(2) which is scaled as zero (0) when the observable level of agreement is minimal and one (1) when there is perfect agreement. For intermediate values, Landis and Koch [28] suggest the following interpretations: below 0.0 ˆ poor agreement; 0.00±0.20 ˆ slight agreement; 0.21±0.40 ˆ fair agreement; 0.41± 0.60 ˆ moderate agreement; 0.61±0.80 ˆ substantial agreement; and 0.81±1.00 ˆ almost perfect agreement. ICC(2) ratings of 0.60 and above suggest that one can reject the hypothesis that respondents were scoring an item randomly and that one can conclude that acceptable levels of mean score reliability exist [32]. ICC(1) indicates the extent to which respondents within the same group assign the same psychological meaning to, or agree in their perceptions of, the

10 Table 4 Intercorrelations, means and mean rankings of the importance of attitude items in Saudi Arabia compared with Canadian rankings from the [14] study (See Table 5 for description of variables) Alpha Mean Standard Mean rank Canada deviation Intercorrelations of social factors items Standard SF1 SF2 SF3 SF4 Mean Deviation Rank SF st th SF b th th SF b b th th SF a b b th th Intercorrelations of affect factors AF1 AF2 AF3 AF nd th AF b th th AF a a th n/a n/a n/a Intercorrelations of near-term consequences: complexity CO1 CO2 CO3 CO4 CO th nd CO b st st CO b b th th CO b b b th rd 194 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 Intercorrelations of near-term consequences: job fit (usefulness) UF1 UF2 UF3 UF4 UF5 UF6 JPF th th JPF th th JPF st th JPF b rd th JPF b b th th JPF b b b b th th

11 Intercorrelations of long-term consequences LT1 LT2 LT3 LT4 LT5 LT6 LT th th LT b th rd LT b b th th LT b b b th nd LT b b b b th th LT b b b b b th th Intercorrelations of facilitating conditions FC1 FC2 FC3 FC4 FC rd th FC b th th FC b b st th FC b b b th th Intercorrelations of training and experience factors TR1 TR2 EX1 EX2 TR th n/a n/a n/a TR b th n/a n/a n/a EX th th EX n/a th Intercorrelations of utilization UT1 UT2 UT3 UT UT b UT b a a p b p M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±

12 196 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 relevance of research results on a computer utilization factor. ICC(1) compares the between sample sum of squares to the total sum of squares from the results of a one-way analysis of variance. In past research, ICC(1) values have ranged from 0 to 0.5, with a median of 0.12 [26]. There are no de nite guidelines on acceptable ICC(1) values. The responses on each factor were averaged (aggregated) and these were used to determine the relative importance of each factor. This aggregation of responses suggests that respondents were agreed on mean scores though the reported standard deviations challenge the assumption of convergence. In fact, the mean scores do not reveal variability across situations, such as age of respondents or size of the rm in which a respondent is employed; nor do they permit prediction of speci c behaviors in given situations. To unveil the fac,ade of convergence from the pooled data, we analyzed the responses in two different ways. First, we used the responses showing agreement with the suggestion that a factor is important and those not agreeing with the suggestion of importance to derive an index of agreement that was introduced by Herbert and Wallace [22] in their study of the perceptions of U.K. Chief Finance Of cers on corporate nance research topics. An index of agreement is the ratio of total agreeing responses (i.e., 5s and 4s for positive questions or 1s and 2s for negative questions) to total disagreeing response (i.e., 1s and 2s for positive questions and 5s and 4s for negative questions). The index excludes equivocal (i.e., `not sure' ˆ 3) responses which vary from item to item. To make an index of agreement comparable in this study, each index was adjusted to re ect the ratio of unequivocal responses to all responses by multiplying that ratio with the index of agreement. Second, we disaggregated the responses on the basis of organization size into large, medium, and small rms. Although the pooled data suggests that many of the factors warranted more research, signi cant differences may exist among rms of different sizes. 7. Results The rst question is the comparative attitudes of Canadian and Saudi respondents toward the utilization of the PC. Since the questionnaire for Saudi respondents was similar to that for the Canadian respondents, we compared the mean responses from each. The settings, situations and contexts are our referential scopes because it is dif cult to delve into the minds of our subjects and to substantiate what seems to be within the realm of mere conjecture. The process of our reference must, therefore, rely heavily on perceived behavior and we have been concerned exclusively with organizationally constructed modes of behavior. The results of the comparison of the mean responses from the Saudi and Canadian respondents are reported in Table 4. While the three highest levels of Saudi respondents' agreement with our suggestible questions were, respectively, in respect of (1) the tness of the PC to respondents' job (Question JPF3 with mean response of 4.65, ˆ 0.67), (2) affect (AF1, mean response of 4.58, ˆ 0.29) and (3) job tness (JPF4, mean response of 4.51, ˆ 0.66), those of the Canadian respondents were mainly with the suggestible questions on complexity: (1) Question CO2 with mean response of 4.47, (2) Question CO1, mean response of 4.39, and (3) CO4, mean response of It is surprising that Saudis perceived the PC as relatively less dif cult to understand than Canadians. If this observation is true, we would expect to nd that the level of PC utilization in the two studies would show that the Canadians would reveal a lower PC utilization than the Saudis. The results con rm this expectation because on each of the PC utilization constructs, the mean responses from the Saudis were greater than those from the Canadians. The results from the use of a different procedure for aggregating the responses from the Saudi respondents are similar to those from the use of mean responses, except that affect item AF1 and job performance facilitation item JPF3 swapped positions, with job performance facilitation item JPF6 tying with job performance facilitation item JPF4 as the items with the third highest level of respondent agreement with the suggestible questions. To test the robustness of our ndings on the attitude items which are accorded highest level of importance on the basis of mean responses, we developed an index of agreement along the lines suggested in earlier discussion. Table 5 reports these indexes of agreement. The ranking of attitude items on the basis of indexes of agreement is similar to the one from mean

13 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± Table 5 Pooled sample indexes of agreement on the level of importance accorded attitude items (n ˆ 151) Attitude items Index of agreement Rank Adjusted index of agreement Rank Social SF1 The proportion of departmental co-workers who use a PC th th SF2 The senior management of this business unit has been helpful in introducing PCs th th SF3 My boss is very supportive of PC use for my job th th SF4 In general, the organization has supported the introduction of PCs th th Affect AF1 PCs make work more interesting st st AF2 Working with a PC is a fun th th AF3 PCs are okay for some tasks but not the kind of task I want (score reversed) th th Near-term consequences: complexity CO1 Using a PC takes too much time from my normal work duties th th CO2 Working with PCs is so complicated, it is difficult to understand what is going on th th CO3 Using a PC involves too much time doing mechanical operations th th (e.g., data input) CO4 It takes too long to learn how to use a PC to make it worth the effort th th JPF1 Use of a PC will have no effect on my work performance (score reversed) th th JPF2 Use of a PC can decrease the time needed for my important job responsibilities th th JPF3 Use of a PC can significantly increase the quality of output of my job nd nd JPF4 Use of a PC can increase the effectiveness of performing work tasks (e.g., analysis) rd rd JPF5 A PC can increase the quantity of output for same amount of effort th th JPF6 Considering all tasks, use of PCs could assist on work to a great extent rd th Long-term consequences LT1 Use of a PC will increase the level of challenge on my job th th LT2 Use of a PC will increase the opportunity for preferred future job assignments th th LT3 Use of a PC will increase the amount of variety on my job th th LT4 Use of a PC will increase the opportunity for more meaningful work th th LT5 Use of a PC will increase the flexibility of changing jobs th th LT6 Use of a PC will increase the opportunity to gain job security rd rd Facilitating conditions FC1 Guidance is available to me in the selection of hardware and software th th FC2 A specific person (or group) is available for assistance with software difficulties nd nd FC3 Specialized instruction concerning the popular software is available to me st st FC4 A specific person (or group) is available for assistance with hardware difficulties th th Utilization UT1 The intensity of job-related use (minutes per day, at work) UT2 The frequency of PC use UT3 The diversity of software packages used for work (number of packages) responses with a few exceptions. The rst three items in order of perceived level of agreement are AF1, JPF3, and JPF4 and JPF6 (both taking the third position), while the rst three attitude items according to mean responses are JPF3, AF1, and JPF4. The above analyses are based on pooled responses. The level of respondents' agreement may however diverge when responses are partitioned on the basis of organization size. Table 6 reports the results of such analysis. The rankings of the attitude items differ from one organization size to another. While respondents from small companies agreed that AF1, EX1, and JPF3 are the rst three in the order of importance, those from medium companies preferred AF1, LT2,

14 198 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 Table 6 Cross-size comparisons of means and indexes of agreements on importance of attitude items Attitude items Small companies n ˆ 100 Medium companies n ˆ 24 Large companies n ˆ 26 means adjusted index of agreement means adjusted index of agreement means adjusted index of agreement SF SF SF SF AF (96%) a (96%) AF AF CO CO CO CO JPF JPF JPF (100%) JPF (100%) JPF JPF (96%) LT LT (79%) (65%) LT (79%) LT LT (85%) LT FC FC FC FC TR EX EX UT UT (92%) (96%) UT Ave UT a Percentage of unequivocal responses to total responses. LT3 and EX1. Respondents from large companies suggest JPF3, and JPF4 as the most important item followed by Af1 and JPF Influence of respondents' profiles on perceptions of PC utilization factors To investigate the link between respondents' pro- les and their perceptions of PC utilization motivators, we employed two different model speci cations (MANOVA and F-statistic approximations). MAN- OVA was used to evaluate the causes of the differing responses from the respondents on the level of importance of each PC utilization factor. F-statistic approximation was used to test the hypothesis that each of the respondents' pro les has no overall effect on differences in their perceptions of a set of combined (dyad) PC utilization factors. The results of the MANOVA and Wilks' tests are shown in Table 7. Age seems to have no in uence on all (but affect and facilitating

15 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± Table 7 Influence of respondents profile on importance perceptions of PC utilization: ANOVA and F approximations results Motivating factors Access Age Education Experience Training Panel A: (F-statistics) Social 8.86 c c 3.32 b Affect 3.03 b b 1.84 Complexity 3.83 c b 2.75 b Job performance facilitation 2.59 b b 1.27 Long-term consequences 2.88 b c Facilitating conditions 5.81 c 2.83 b b 6.40 c Utilization 3.60 c c 1.12 Panel B: Comparison of PC utilization motivators (Wilks' ) Interacting motivators: Social/affect 5.41 c c 2.48 b Complexity/affect 3.10 c b 2.17 b Job performance facilitation/affect 2.26 b b 1.65 Long-term consequences/affect 2.28 b b 3.02 c Facilitating conditions/affect 4.23 c 2.13 b b 4.13 c Job performance facilitation/long-term consequences 1.98 a b Complexity/long-term consequences 3.01 c a 3.01 c Facilitating conditions/long-term consequences 3.85 c 2.26 b a 4.48 c Social/long-term consequences 4.99 c c 3.01 c Complexity/social 5.76 c c 2.71 c Job performance facilitation/social 4.81 c c 1.92 a Facilitating conditions/social 5.38 c c 3.94 c Complexity/job performance facilitation 3.00 c c 1.87 Facilitating conditions/job performance facilitation 3.90 c 1.97 a c 3.52 c Facilitating conditions/compexity 4.26 c b 4.18 c a p z b p z c p z The p-values reporting the signi cance of the F-statistics for the hypothesis that each of the respondent pro les has no overall effect on each of the sets of PC utilization motivators relate to Wilks' tests. The same results were obtained when the (a) the Pillai's Trace, (b) Hotelling Lawley Trace and (c) Roy's Greatest tests were conducted. The critical value of T ˆ conditions) of the PC utilization factors and each set of the combined interaction factors. A respondent's level of education seems to have no effect on any of the factors suggested to in uence PC utilization or any of the possible interaction factors. PC utilization is in uenced strongly by degree of PC Access (thus supporting H8), and experience (H9), but not respondents' age (H10), education (H11) and PC training (H7) and ownership of a PC. The non-signi cance of PC ownership is surprising but understandable. Some respondents may own a PC but may not use them. The PC may be acquired for the use of their children. Some respondents who do not own a PC may have one at home for of cial use. As a result, ownership of a PC is not a predictor of PC utilization and is different from having access to the PC The influence of attitude on PC utilization Table 8 reports the intercorrelations among summarized group of attitude items, their mean values and alphas. The results suggest that social factors, facilitating conditions, and Job Fit are signi cantly correlated with PC utilization, while Affect is mildly correlated with PC utilization. Table 9 suggests that Social Factors, Affect, Job Performance Facilitation and Facilitating Conditions are signi cant determinants of PC utilization. Complexity and Long-Term Consequences are not signi -

16 200 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 Table 8 Intercorrelations, means and alphas of summarized factors of computer utilization Factors Mean Standarddeviation 1. Social Affect a Job performance facilitation a a Complexity Facilitating conditions a a Long-term consequences a a a Utilization a a a a a p-value 1%. Table 9 Regression model of attitudes and PC utilization Attitudes Estimates t-value p-value Standard error Social factors Affect Complexity Job performance facilitation Long-term consequences Facilitating conditions Note: F-value ˆ 2.73, p-value ˆ 0.01, MSE ˆ 1.32, R 2 ˆ cant predictors of PC utilization. These results suggest that H1, H2, H4, and H6 are supported while H3 and H5 are not. The signi cant positive relationship between social factors and PC utilization is consistent with the theory of reasoned action and is similar to the nding in Canada. Our nding that the use of PC evokes mild positive emotions (Affect) among knowledge workers is inconsistent with Thompson et al. who found no signi cant relationship between Affect and PC utilization. It is, however, similar to the nding of Davis et al. In respect of cognitive components of attitudes as measured by Job Performance Facilitation, Complexity, and Long-Term Consequences, the rst is the only signi cant predictor of PC utilization. Although the relationship between complexity and PC utilization is not signi cant as was the case in Canada, the direction (negative) is consistent with previous studies. Unlike the Canadian study, the relationship between facilitating conditions and PC utilization is positive and signi cant. The relationship between each of Social Factors, Job Performance Facilitation, and Facilitating Conditions and PC Utilization is stronger than the relationship between Affect and PC utilization. These results are consistent with those reported for the Canadian study though Affect was not signi cant in that study. 8. Conclusion This paper has reported the results of a questionnaire study of perceived importance of suggested attitude items in promoting PC utilization by knowledge workers in Saudi Arabia. We were interested in two set of questions: 1. What are the essential differences between the perceptions of respondents in Saudi Arabia and of Canadian respondents? 2. Do different attitude constructs have differing effects on PC utilization in Saudi Arabia? Like Canadian respondents, the Saudis perceived Social Factors, Affect, Job Performance Facilitation, and Facilitating Conditions as signi cant contributors to PC utilization, but unlike the Canadians, they suggested the Complexity and Long-Term conse-

17 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185± Fig. 3. The impact of maturation (learning curve) on the perception of PC utilization. quences are not signi cant predictors of PC utilization. Based on mean scores, the Saudis perceived the PC as relatively less dif cult than the Canadians and revealed a higher PC utilization than them. The implication is that there are differing perceptions of PC appreciation and utilization: multinational corporations operating in different countries need to adopt several different motivation policies for PC utilization. The nding that Saudis report more PC utilization than Canadians is surprising. This nding relied on the responses (at different dates) of questionnaire subjects. Cross-national comparison of perceived attitudes assumes that respondents drawn from the two countries have identical understandings of the issues under investigation. However, the respondents from the two countries are not homogeneous, since there are

18 202 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 major differences between and within the samples from each country. In addition, it does not appear that the variables under investigation are homogeneous, because they may mean one thing to all respondents in a national sample but seem different between respondents in different nations. May be the measurement scales of Canadian respondents are different from those of Saudis. Scale homogeneity is generally not suf cient for cross-national comparison; it is also important that the topics being analyzed should be homogeneous in its content. Another possible explanation of the differing levels of perception of PC utilization is the differing stages in the PC utilization learning curve. As the PC is introduced, and individuals within a country try to use it, they begin to see some bene ts and feel happy about using it. This could result in an over-estimation of the value of the PC. As a result, the revealed perceptions (mean values) of PC utilization and its potential bene ts could vary between the two stages of the learning curve. These differences between the mean perceptions of the Saudis and the Canadians is encapsulated in Fig. 3 as a maturation dilemma. There is a need to investigate the existence of differences in levels of importance which end-users accord to PC utilization factors across time and space. More crossnational comparison is needed, just as more withincountry studies at different time intervals are needed. While the rankings accorded each PC motivation factor by respondents from companies belonging to one organization size group differed from those accorded by respondents from companies belonging to another organization size group in Saudi Arabia, organization size does not appear to be a signi cant discriminator of respondents' attitudes toward PC utilization. PC training, PC experience, and PC access have a strong in uence on PC utilization and its determinants. Age, education, and PC ownership reveal no signi cant in uence on PC utilization and its determinants. The low reliability coef cients of affect and utilization items may have arisen from the fact that these constructs capture only two and three items, respectively. Future research seeking to capture these constructs would probably need to extend the list of items that can be studied. The R 2 from the estimation of the regression model reported in Table 9 is low (0.101). This probably suggests that there are other important variables excluded from the model. Our ndings are based on quantitative analysis of Likert-scales responses. We advise caution here. Our questionnaire elicits information on whether each of the items was `very important'. It is possible for the respondents to answer that all items are very important, regardless of whether that information would affect PC utilization. So, our questionnaire could be eliciting less information than if the respondents were asked to rank the items. Another limitation is the general inability of persons to describe their information usageðrespondents may be using less PC than they say they do. Such behavior could, however, be culture-dependent. Acknowledgements The authors acknowledge the nancial support of King Fahd University of Petroleum and Minerals in the conduct of this research. The helpful comments and suggestions of Dr. Eid Sendi Shammari, Dr. Stephen Owusu-Ansah, Rosemary Wallace, the Editor (Dr. Edgar H. Sibley) and two anonymous reviewers are appreciated. The authors also thank the respondents for their willingness to participate in the study. Any remaining errors are the authors' responsibility. References [1] A.H. Abdul-Gader, End-user computing success factors: further evidence from a developing nation, Information Resources Management Journal 3(1), 1990, pp. 1±13. [2] A.H. Abdul-Gader, K.A. Kozar, The impact of computer alienation of information technology investment decisions: an exploratory cross-national analysis, MIS Quarterly 19(4), 1995, pp. 535±559. [3] I.M. Al-Jabri, Gender differences in computer attitudes among secondary school students in Saudi Arabia, Journal of Computer Information Systems 37(1), 1996, pp. 70±75. [4] I.M. Al-Jabri, A.H. Abdul-Gader, Software copyright infringements: an exploratory study of the effects of individual and peer beliefs, Omega, International Journal of Management Science 25(3), 1997, pp. 335±344. [5] I.M. Al-Jabri, M. Al-Khaldi, Effects of user characteristics on computer attitudes among undergraduate business students, Journal of End-User Computing 9(2), 1997, pp. 16±22. [6] I. Ajzen, From intentions to actions: a theory of planned behavior, in: J. Kuhl, J. Beckmann (Eds.), Action-control: From Cognition to Behavior. Springer, Heidelberg, 1985, pp. 11±39.

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20 204 M.A. Al-Khaldi, R.S.O. Wallace / Information & Management 36 (1999) 185±204 [46] R.S.O. Wallace, Disclosure of Accounting Information in Developing Countries: A Case Study of Nigeria. A doctoral thesis, University of Exeter, Devon [47] G. Yaverbaum, Critical factors in the user environment: an experimental study of users. Organizations and tasks, MIS Quarterly 12(1), 1988, pp. 75±88. Dr. Muhammad A. Al-Khaldi is the Chairman of the Department of Accounting and Management Information Systems at King Fahd University of Petroleum and Mineral (KFUPM), Dhahran, Saudi Arabia. His degrees include B.S. and MBA from KFUPM and PhD from Oklahoma State University. He has contributed articles to professional and academic journals and conferences at both national and international levels. His articles have appeared in Computer in Human Behavior and Journal of End-User Computing. His research interests include end-user computing, decision support systems, and applications of meta analysis. R.S. Olusegum Wallace is a Professor of Accounting and MIS in the Department of Accounting and MIS at KFUPM, Dhahran, Saudi Arabia. He received his PhD from the University of Exeter. His research interests include cross-national comparison of financial reporting practices and regulation, environmental auditing issues, methodology in accounting research and the enduser computing in business. His articles have appeared in a variety of journals including Accounting and Business Research, British Accounting Review, Accounting Education, Accounting, Business and Financial History, Journal of Business Finance and Accounting, Research in Third World Accounting, Research in Accounting in Emerging Economies, Journal of Accounting Literature, Accounting Horizons, Journal of Accounting and Public Policy, and International Journal of Accounting. Professor Wallace is the Managing Editor of Research in Accounting in Emerging Economies, Co-editor of The International Journal of Accounting and Associate Editor of British Accounting Review.