Transfer of Information Technology to the Arab World - Semantic Scholar

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Transfer of Information Technology to the Arab World: A Test of Cultural Influence Modeling DETMAR W. STRAUB, KAREN D. LOCH and CAROLE E. HILL Georgia State University, USA

The complex societal beliefs and values of the Arab world provide a rich setting to examine the hypothesized influence of culture on information technology transfer (ITT). Two research questions arise in this context: (1) Do cultural beliefs and values affect the transference of information technology in the Arab world? and (2) Does contact with technologically advanced societies impact ITT and systems outcomes? The present study addresses these research questions by conceptualizing and testing a cultural influence model of ITT. In this model, cultural beliefs and values are one major construct while a counterbalancing variable is the external influence of technologically advanced societies. These constructs along with the variable “national IT development” form the conceptual basis for the model. This study is the second part of a program of research investigating ITT. The setting of the study was Arab society, which allowed us to test our “cultural influence” model in, perhaps, one of the more complex cultural and social systems in the world. The program of research took place in several phases. In the early phases, Arab-American businessmen and women as well as Arabs studying in American universities were studied. In the latter phases, the cross-disciplinary research team gathered primary data in the Arab cultures of Jordan, Egypt, Saudi Arabia, Lebanon, and the Sudan. Both quantitative and qualitative techniques were used to explore the phenomenon of ITT. This paper reports quantitative findings from the latter phase. Findings suggest that the model has explanatory power. Arab cultural beliefs were a very strong predictor of resistance to systems and thus ITT; technological culturation was also a factor. These results have implications for future theory-testing and for technology policy-setting by responsible Arab leaders. Additionally, there are implications for transnational firms and managers charged with introducing IT in foreign ports, subsidiaries, offices, and plants. “Transfer means more than just technology....All too often, new technologies fail in the marketplace because of flawed assumptions about considerations totally unrelated to technical merit.” -Allan Kuchinsky (1996)

INTRODUCTION Organizations throughout the world experience difficulty and even failure in information technology transfer (ITT), defined as the movement of information technology from creators to users (Cunningham & Srayrah, 1994). This transference of systems, whether they are developed internally or purchased in the commercial software/ hardware marketplace, is plagued with problems (Kwon & Zmud, 1987).

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The ITT problem is even more acute in developing countries, such as the emerging economies in the Arab world (Antonelli, 1986; Goodman, 1991b; Knight, 1993; La Rovere & Goodman, 1992). Although developing countries are eager to adopt new technologies, the process of adoption has been slow and the current utilization of IT is far below that achieved in industrialized countries (Antonelli, 1986). This disparity in IT use between industrialized and developing countries can be explained in part by the high cost of building and implementing IT, but this explanation is not entirely satisfactory. Substantial anecdotal and descriptive evidence exists for failure in cases where financial hurdles have been overcome (Mahmood, Gemoets, & Gosler, 1995). While finances were

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not a problem for the affluent countries of Saudi Arabia and Kuwait, they have historically used far less than their available computing capacity (Atiyyah, 1989; Ibrahim, 1985; Yavas, Luqmani, & Quraeshi, 1992). With some notable exceptions (Al-Shanbari & Meadows, 1995; Kamel, 1995; Siddiqui, 1992), sporadic implementation and use are endemic throughout the Arab world (Cunningham & Srayrah, 1994; El-Sayed Noor, 1981; Goodman & Green, 1992; Odedra, Lawrie, Bennett, & Goodman, 1993). Why is ITT so problematic in developing countries like those in the Arab world? Anthropological studies suggest that much of the technology designed and produced in developed countries is ethnocentric, that is, culturally-biased in favor of their own social and cultural systems. Consequently, developing countries encounter cultural and social obstacles when attempting to transfer technology, created abroad, into practice at home (Yavas et al., 1992). There is a counterbalance, however, to cultural beliefs and values predisposing users to resist innovations. In anthropological studies, the assimilation of characteristics of another culture is known as “acculturation.” Extending the concept to IT, it can be argued that many individuals who have experience with technically advanced societies become technologically culturated and, thus, more accepting of IT. In the IT arena, this exposure occurs when people become informed or educated about computer systems and application software that are not widely diffused within their own culture. These experiences can be formal education experiences such as seminars and courses (Arbose & Bickerstaffe, 1982) or informal experiences such as traveling for business or pleasure. What are the effects of these two very different types of cultural variables on ITT? These constructs along with the variable “national IT development” form the conceptual basis for the cultural influence model. This study is the second part of a long-standing program of research investigating ITT. The setting of the study was Arab society, which allowed us to test the cultural influence model in, perhaps, one of the more complex cultural and social systems in the world. While both quantitative and qualitative methods were used to validate and test the model, data analysis in the present study was based primarily on an Arabic-English questionnaire utilizing scenarios (N = 274). Findings suggest that the model has good explanatory power. Arab cultural beliefs were a strong predictor of ITT. Technological culturation offered reasonable explanatory power. These results have implications for future theorytesting and for technology policy-setting by responsible Arab leaders, as shown by Khaled (1992). Additionally, there are implications for transnational firms and managers charged with introducing IT in foreign offices and plants. As globalization of markets and corporate multinationalism evolve, it is becoming clearer that more cross-cultural research is needed to assist managers (Burn, Saxena, Ma, & Cheung, 1993; Cash, McFarlan, McKenney,


& Applegate, 1992). In a large survey of information systems executives, more than half of the respondents felt that success in global IT was key to their firms’ future (Ives & Jarvenpaa, 1991). When increasing operations in the international arena, firms must be able to exploit the power of information technology (IT) to communicate among widespread locations and coordinate activities both within and across countries. Hence, it is important for the managers of these firms to learn as much as they can about the cross-cultural adoption and use of IT (Couger, 1986; Kumar & Bjorn-Andersen, 1990).

RESEARCH BACKGROUND AND THEORETICAL FRAMEWORK Although there is a substantial literature documenting U.S. experiences with ITT (Brancheau & Wetherbe, 1990; Cooper, 1994; Leonard-Barton & Deschamps, 1988; Moore & Benbasat, 1991; Prescott & Conger, 1995; Zmud, 1982), relatively few attempts have been made to delineate cultural and social variables that foster or impede the adoption of new information technology across national boundaries. Groundbreaking descriptive work by Goodman and colleagues (Ariav & Goodman, 1994; Danowitz, Nassef, & Goodman, 1995; Dedrick, Goodman, & Kraemer, 1995; Goodman, 1991a, 1991b, 1994; Goodman & Green, 1992; Goodman & McHenry, 1991; La Rovere & Goodman, 1992; Mesher, Goodman, Snyder, Briggs, & Press, 1992; Nidumolu & Goodman, 1993; Odedra et al., 1993; Wolcott & Goodman, 1993) has shown how IT diffusion differs significantly around the world, but these studies have not developed or tested scientific hypotheses that advance theory on the phenomenon of ITT. Moreover, only a few studies have empirically tested cross-cultural impacts on the adoption and diffusion of new information technologies (Gefen & Straub, 1997; Hill, Loch, Straub, & El-Sheshai, 1998; Ho, Raman, & Watson, 1989; Raman & Wei, 1992; Straub, 1994). While limited in number and scope, this work suggests strongly that links between culture and IT are not mere artifacts. In studying the effect of culture on the use of E-Mail and FAX in Japan, for example, Straub (1994) found significant differences in beliefs about IT between Japanese and U.S. knowledge workers in both perception and use of IT. Straub, Keil, and Brenner (1997) found these same effects in a three country study including Japan as did Gefen and Straub (1997). Ho et al. (1989) and Raman and Wei (1992) concluded that culture had a marked impact on how electronic meeting systems were perceived, used, and adapted. Thus, there is evidence to support that culture may be a barrier to ITT. What, then, is the nature of these cultural obstacles to ITT? Culture and Information Technology First, it must be recognized that transferring technology developed in one culture to another culture involves more

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than merely providing instruction about technical aspects of using the equipment. Given that cultural beliefs and values are a “collective programming of the mind which distinguishes one human group from another” (Hofstede, 1980, p. 25), the intricate relationship between people and machines in ITT means that culture impacts both how systems are designed and how they are received. Obstacles arise because people bring to the workplace what can be regarded as cultural baggage; that is, they come to their jobs with specific cultural biases about how the world functions, how their job works, and how employees and employers are supposed to conduct themselves. The computer systems they interact with can be built, and are often built, under a different set of cultural assumptions. Therefore, successful technology transfer involves communication and cooperation with the receiving country and understanding about the forms that resist the transference (Redmond, 1981; TEP [The Technology/ Economy Programme], 1991). We propose several ways by which cultural factors may interact with information technology. Cultural factors are likely to be powerful explanations for why those from technically advanced societies who attempt to implement technology transfer are often challenged in terms of their own ideas, beliefs, and values about how technology “should be” utilized in developing countries. Cultural factors also explain why persons, situated in the upper strata of the society who either work for international companies or who have spent time in industrialized countries (such as the U.S., Western Europe, or Japan), bring with them from abroad significant cultural biases when implementing systems at home. These experiences “culturate” them to the value of the technology. At home they experience cultural conflicts with mid-level managers and workers who, unlike the owners, directors, and top administrators in institutions and businesses, are not widely traveled and ultimately have the responsibility for daily use of technology (Danowitz et al., 1995). Cultural factors also likely explain why transference of IT to developing countries is fraught with problems. The transfer of information technology from industrialized to developing countries generally involves a process of injecting the technology of the industrialized world and its associated methodologies into a developing nation host. That technology, designed and produced in developed countries, is likely culturally-biased in favor of industrialized socio-cultural systems, and meets cultural resistance during the technology transfer process. Finally, cultural sensitivities of host environments are often ignored (Khalil & Elkordy, 1997). This is especially true in the workplace since the adoption decision is often negotiated by upper-level managers who either work for international companies or who have spent time in the industrialized countries. Yet it is the lower-level managers and workers who, without the diverse cultural experiences, have the responsibility of the daily use of the new technology, and

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ultimately accept or do not accept the new technology. The contributing discipline of anthropology provides additional insight as well as support for focusing on the relationship between cultural and information technology. Anthropologists like Bertolotti (1984) point out that the culture of a country or region greatly affects the acceptance of technology through its beliefs and values about modernization and technological development. Thus, ignoring the cultural context can result in delays, or, at worse, failures in the IIT process (Matta & Boutros, 1989). A brief review of the cultural anthropological literature is warranted. Theoretical Development of Cultural Influence Theme in Cultural Anthropology The study of the relationship between culture and technology has taken several directions in cultural anthropology. Earlier studies of technological “acculturation” assumed that the more “developed” countries unilaterally “gave” new technology to lesser developed countries (Ingold, 1996). The flow in information and practical knowledge was in one direction. Once the people and institutions in these countries adopted the technology, that country would “develop.” More recent studies have rejected this model of development in favor of a closer look at the “practice” of technological culturation (Ingold, 1996). The acquisition of new technical knowledge is personal ¾ the technical skill of a practitioner is embedded in the particularities of experiences and social identities of individuals within particular cultural contexts. Within the context of the world system, tools and knowledge are appropriated from more technologically sophisticated countries. The adoption and use of the new technological knowledge, however, varies according to local social and cultural contexts. Consequently, it is differentially adopted by people in a particular culture (or country). The research approach utilized here looks at how culture influences the adoption of new technology and the constraints placed on such adoption. Technological systems placed within the context of culture and social relations are heterogeneous constructs that stem from the successful modification of social and nonsocial factors, i.e., of the actions and choices of individuals (Pfaffenberger, 1992). Schaniel (1988) has stressed that the adoption of new tools does not necessarily imply the adoption of the system of logic that produces the technology. He states: “...the process of technological adaptation is one where the introduced technology is adopted to the social processes of the adopting society, and not vice-versa” (p. 498). Thus, culturation is likely a two-way process of change. Any study of technological culturation must then consider the meaning of sociotechnical activities in which the appropriating culture engages as it reinterprets the new tools (Kedia & Bhagat, 1988).


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Cultural Influence Modeling We term these high level constructs and linkages “cultural influence modeling.” This modeling attempts to show how cultural, social, and technology variables can predict and influence the outcomes of the ITT process in culturally diverse settings. As originally presented in Hill, Straub, Loch, Cotterman, and El-Sheshai (1994) and studied qualitatively in Hill, Loch, Straub, and El-Sheshai (1998), the model assumes that national IT development initiatives are important in predicting the success or failure of the adoption process, but that cultural beliefs and technological culturation are also key independent variables (see Figure 1). The model integrates understanding of specific users’ notions about technology with more general knowledge regarding the social correlates of technology use. It also reflects the cultural context of public and private policy-making processes that affect ITT. Components of the Model in the Context of the Arab World Cultural influence modeling assumes an interdependency between IT and the culture of people using the systems. Technology is determined by and, at the same time, becomes a determining factor of networks of interacting human, organizational, and artifactual entities or actors (Hakken, 1991). Culture, more properly termed culture-specific beliefs (CB), is defined as specific patterns of thinking that are reflected in the meanings people attach to their behavior (Hofstede, 1980). In our model, it refers to those specific beliefs, values and meanings that are thought to have a downstream effect on the use of information systems. Cultural influence modeling takes the approach that we can best understand the effect of ethnic culture in the context of specific cultural beliefs. To ensure that there is no ambiguity about which aspect of culture we are talking about, let us stress that while Arab culture represents a huge set of beliefs, we are focusing on only a Figure 1. A Cultural Influence Model of Information Technology Transfer Domain of Present Study Culture-Specific Beliefs & Values

ITT/ System Outcomes

Technological Acculturation

National IT Policies & Technological Infrastructure


small subset of cultural beliefs that are influential in IT settings (i.e., the dependent variable, IT outcomes). Even more specifically, in the present study we are focusing on those beliefs and values having to do with the Arab sense of time. The model tries to make this clear by calling the construct “culture-specific beliefs and values,” not simply “culture.” The addition of the hyphenated word “specific” conveys the sense that we are examining one cultural value at a time in the model, not a generic construct of “Culture.” Moreover, the cultural beliefs being referred to are beliefs, pervasive in the culture, and not those restricted to a particular setting, such as organizational cultural beliefs or IT cultural beliefs. While the latter two cultural beliefs can be extremely important in how people respond to computer systems, they are exogenous to this work. Technological culturation (TC) refers to influential experiences that individuals have had with technologically advanced cultures. In anthropological studies, this concept typically refers to the assimilation by members of a subculture of the values and beliefs of a pre-existing culture or by the adoption of some of their cultural characteristics (Mendoza & Martinez, 1981). Berry (1980) suggests that contact with a new culture results in adaptation in such areas as cognitive style, attitudes, and stress. In the present research, it simply designates beliefs and behavior that originated outside traditional Arab culture and society and have been incorporated or not incorporated into the belief sets of Arabs. The assumption is that the cultural and social lives of our respondents influence their attitudes toward and use of technology. The theoretical framework assumes that Arabs continually negotiate their technological world within the context of their social and cultural world and that the contact between these worlds are transforming in nature. In the IT arena, culturation occurs when people become informed or educated about computer systems and application software that are not presently diffused within their own culture. These experiences range from formal experiences such as long term studying in a technically advanced society or informal experiences such as travel abroad. National IT Development (DEV) refers to specific technology policies that guide the development of information systems in a specific country together with the existing structure of computing and communication capabilities and the ability of the population to operate and utilize these capabilities. The overall construct reflects the level of support for technological development within a given nation. For this reason and the fact that there is a lively discussion centering around this link with ITT (Gurbaxani et al., 1990a; Gurbuxani et al., 1990b; Kamel, 1995, 1997; King et al., 1994; King & Kraemer, 1995; Kraemer, Gurbaxani, & King, 1992), DEV is modeled as predicting ITT/system outcomes in a specific country. As shown in Figure 1, DEV is not being examined in the present study, although it does remain an important element in the model.

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ITT/System Outcomes refers to the actual use or intention to use new technology within specific institutions/ organizations of a country as well as to the success or failure of the diffusion of new technologies (Cunningham & Srayrah, 1994; Hassan, 1994; Kedia & Bhagat, 1988). It can also refer to the outcomes of a system development methodology or process during which systems are specified, designed, and implemented. As shown in Figure 1, the model formulates relationships between cultural beliefs and values (CB), national IT development (DEV), and ITT. It further proposes that technological culturation (TC) is a key driver of systems outcomes. Two key research questions emerge from the theoretical discussion and the testing of the proposed cultural influence model in the Arab world: Research Question 1. Do cultural beliefs influence the transference of information technology in the Arab world? Research Question 2. Does contact with technologically advanced cultures impact ITT and systems outcomes? This study adopts a critical approach to the relationship between the industrialized world and Arab culture, and information technology transfer. The Arab world is knit together culturally by trade, religion, and a history that precede European imperialism by millennia (Eickelman, 1981). Although few of its inhabitants identify themselves with a culture in regional or national terms, there are recognizable continuities from Morocco to the Indus, such as urban life, translocal networks, and social/moral traditions (Anderson, 1996). This fact about the Arab world leads us to conceptualize not a series of national or separate ethnic cultures but one ethnic Arab culture that transcends national boundaries. ITT is placed in the context of selective diffusion from technologically advanced socieities. The transfer of technology does not transform Arabs into techno-philes. On the contrary, ITT is fitted to Arab culture in a way that allows Arabs to remain independent and self-determining. Through their decision-making about the transfer of technology, a people chooses its own history. Using the critical approach as its conceptual framework, this program of research attempts to factor out variables that enhance or obstruct the transfer of technology in Arab countries. Arab Culture and Technology Mismatch Given this theoretical background, what are the issues and conflicts involved in information technology transfer (ITT) peculiar to developing countries, with a particular emphasis on Arab countries? Al-Sulimani (1994), Bukhari and Meadows (1992), and Atiyyah (1988) and (1989) have found that ITT is often hampered by technical, organizational,

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and human problems in Arab cultures. Cultural conflicts between the organization and management style of western and Arab institutional leaders and workers have impacted the system development process and produced unsuccessful approaches to computer use and policy (Ali, 1990; Atiyyah, 1989; Goodman & Green, 1992). Moreover, there appears to be wide variation in the Arab use of IT. Egypt, for example, with the largest and most internationally oriented computer system in the area (Goodman & Green, 1992), uses IT in most, if not all governmental agencies and non-governmental organizations (Meskell, 1997). Jordan, while using computers in public and private domains, also utilizes them to maintain extensive archaeological inventories and other forms of cultural heritage (Goodman & Green, 1992). Although the institutional leaders in oil-rich Saudi Arabia view computers as symbols of modernity and progress, many of their systems are incompatible which has led to a “lack of consistency among hardware and applications in use in pubic organizations, and even within the same agency” (Atiyyah, 1989). More recently, diffusion in Saudi Arabia still remains low (Yavas et al., 1992), which according to Atiyyah (1989), reflects a general slowness in diffusion of advanced technology. Computers in particular industries such as the construction industry are still being characterized by phrases like “under-utilization” and in “limited” use (Shash & Al-Amir, 1997, p. 195). Arab Cultural Values and ITT Which Arab cultural values would lead managers and office workers to resist ITT? Several stand out. Preference in Arab culture for face-to-face dealings, for instance, mitigates against certain technology interfaces like email and groupware as does the cultural tendency to build consensus and create family-like environments within organizations (Ali, 1990; Matta & Boutros, 1989). Moreover, technologies and computer systems which demand a change in workers’ perceptions of time also encounter resistance. It is this latter characteristic that is the focus of this study. The Arab attitude toward time is complex. Some cultures view time as a static phenomenon, where events simply transpire, without necessarily being tightly coupled to antecedents (Hall, 1973). Hall terms this cultural characteristic as polychronic and argues that certain cultures such as Arab culture see time as a complex unfolding of events which occur in parallel. In that “polychronic cultures tend to view problems in a more holistic fashion and …work on all components simultaneously” (Hall, 1966, p. 173), they tend not to plan for any single event. Nydell (1987) reinforces the assessment that Arabs are polychronic by observing that: …among Arabs, time is not as fixed and rigidly segmented as it tends to be among Westerners. It flows from past to present to future, and Arabs flow with it. Social occasions and even appointments need not have fixed


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beginning or endings. Arabs are thus much more relaxed about the timing of events than they are about other aspects of their lives. These attitudes are beginning to change as they respond to the demands of economic and technological development. If a task is not done when promised, it is assumed that delays are expected (p. 27). There are other reasons why we focused on time as the first culture-specific belief to test using the cultural-influence modeling approach. Based on reading of the literature having to do with Arab cultural values, perception of time was most frequently mentioned as a major differentiating factor between the Arab world and the developed world (Feghali, 1997; Mackey, 1987). As the present work is presenting the theory and initial testing of the model, we felt it wise to begin with a single, clearly important cultural belief. Time, then, provides a reference point for the Arab culture where the need for planning is viewed very differently (Safadi & Valentine, 1990). Mackey claims that “the importance of maintaining pride and face is related to …problems associated with long range planning” (Mackey, 1987, p. 129, emphasis added). As a result of the experience of time being so radically different for Arabs, the need for long range planning and forecasting is valued less than it is by Western cultures, for instance. Systems that support long range planning, thus, should be of correspondingly lesser importance to Arabs who have not had prior exposure to the persuasiveness of these systems throughout technologically advanced cultures. Considering Rival Hypotheses There are two rival hypotheses that need to be discussed in this context. The first of these we term “traditional” implementation factors in that they commonly arise when assessing IT effects (Nidumolu, Goodman, Vogel, & Danowitz, 1996; Swanson, 1988). The second is differential effects of national culture. Traditional Implementation Factors Traditional implementation factors are expected to explain many outcomes in systems work. Three factors were selected to represent rival hypotheses to our cultural influence model constructs. These were: (a) the attractiveness of the pricing of the system, (b) top management support for the project, and (c) the amount of staff time required to learn and operate the system. These key elements are derived from the literature (Culnan, 1986; Lucas, 1978; Nidumolu et al., 1996; Robey & Zeller, 1978) and chosen for our selective study of IT in the Arab world. There is little reason to elaborate on why and how these variables are thought to interact with systems outcomes and the IVs in our cultural influence model. The reason for including them in the study is to test rival hypotheses (internal validity) and not to argue for or against their place in the model.


National Culture (Birthplace or Sample Site) A second viable rival hypothesis to our model is that national culture interacts with or confounds the effect of cultural beliefs on ITT. In this case, there could be subcultural or sample country-by-country differences which affect how strongly Arab cultural beliefs are held by individual respondents and by how they evaluated the possible systems outcomes of the scenarios. In other words, there could be systematic effects from a sub-cultural belief that differs substantially from that of other Arabs. Or this systematic bias could derive from country characteristics of where the sample was drawn. As a result of working with Arab-Americans, Arab students, and native Arabs and reading the literature on Arab culture, the research team came to believe that in this part of the world, a distinct set of cultural beliefs has emerged from a common linguistic, historical, and religious background. At the same time, we also saw the merit in not relying on this evidence alone. So this rival hypotheses needs to be counterposed against cultural beliefs and technological culturation variables.

RESEARCH METHODS AND DESCRIPTIVE STATISTICS To investigate these managerially and theoretically important questions, a program of research involving a team of interdisciplinary researchers has been underway for more than five years now. Among the team members were researchers with expertise in anthropology, Arabic languages and cultures, and qualitative and quantitative research methods. Because the study of IT and cultural artifacts calls for a diversity of approaches (Escobar, 1995; Hakken, 1990), various methods, including techniques favored in anthropological research, were used to develop and test the cultural influence model. These included: ethnography and systematic observation, interviews, focus groups, and a structured research instrument consisting of a series of open- and close-ended questions and scenarios describing the development and implementation of different types of information systems and technologies in a range of organizational settings. Early Phases: The project used several techniques in the early phases. After immersion in the literature for this area of inquiry, formulating the conceptual basis for the study, and identifying key constructs, we convened three focus groups of Arab students. An evolving set of open-ended questions were posed to each group and the ensuing conversations recorded and transcribed. Our goal was to ascertain beliefs, values, and attitudes about ITT. Because these individuals had not lived in the U.S. for very long, they served as surrogates for the views and values of Arabs who are still in residence in the Arab world. Transcripts of focus groups were content analyzed for themes, constructs, and relationships, and also used

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as the basis for development of a questionnaire instrument and interview questions. The structured portion of an evolving quantitative research instrument consisted of a series of open-ended and close-ended questions. Additionally, scenarios were incorporated for participant response. Each scenario, which described the development and implementation of different information systems in varying organizational settings, had embedded within it cultural beliefs and values. Questions about the scenario tried to determine which of these beliefs were considered to be salient by the participants. In a pilot study of several dozen Arab-American business persons, participants were asked to read scenarios and respond to a series of questions regarding their cultural beliefs and norms and their assessment of the likely success or failure of the information system described in the scenarios. Much thought was given to this, especially in the areas of language and instrument administration. English, for instance, was the language of choice for the pilot studies in Atlanta. Since the respondents in this phase were all native Arabic speakers with a high level of competency in the English language, this choice seemed to be reasonable. Language fluency questions verified our suppositions in this regard. Two versions of the instrument ¾ one in Arabic and one in English ¾ were used for administration of the instrument in Arab countries. Later phases: A mailed survey methodology has the advantage of gathering a relatively large sample, but it is important that the survey be pre-tested (Straub, 1989). Validation of the instrument with the Arab-American pilot group allowed us to prepare an English and Arabic form of the questionnaire. The Arabic version incorporated dialectical differences for each country in which the data were to be collected, and then back-translated for accuracy. Five Arab countries including Jordan, Egypt, Saudi Arabia, Lebanon, and the Sudan were selected for data gathering. In Jordan, researchers administered many of the surveys in person and also gathered ethnographic and other qualitative data. In Egypt, Saudi Arabia, Lebanon, and the Sudan, survey administration was handled by colleagues. In studying culture and its impacts, anthropologists have historically preferred ethnographic techniques, and, for this reason, much of the foundation work and data gathering in Jordan were qualitative. To empirically test the cultural influence model, however, we felt the need for a sample size of several hundred individuals. This is most efficiently achieved through a questionnaire. Importantly, we feel that the use of multiple methods and samples allowed us to better triangulate on the phenomenon of culture and IT. The structured research instrument consisted of a series of closeand open-ended questions. The portion of the instrument relevant to variables contained in our research model is shown in Appendix A.

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Scenario Creation Technique and Embedded Cultural Beliefs In the “scenario creation” technique, researchers use short scenarios to give respondents real world settings to which they can react. In this case, a planning scenario embedded a clear dimension of time to which the respondents reacts. Prior work utilizing the technique indicates that the stimulus is sufficient to invoke participant reactions. Given that one of the objectives of the study was to assess Arab cultural values and attitudes about computer technology in a real world situation, scenario creation provided a good methodological option. The scenario created described the possible adoption and implementation of a planning information system. Participants were asked to read the scenario and respond to a series of questions regarding their reaction to the causal factors embedded in the scenario and their assessment of the likely success or failure of the information system described in the scenario. Since cultural beliefs and values are a “collective programming of the mind” (Hofstede, 1980, p. 25), cultural beliefs intended to elicit a response to the Arab sense of time were not made obvious except through the basic nature of the planning system described in the scenario (Nydell, 1987; see Appendix A for the wording in the English version of this scenario). Asking participants outright if they felt that a particular element like sense of time represented a cultural attribute would not collect useful data since culture is latent, or, as Hofstede puts it, “unconscious.” Following the stimulus, respondents were asked if certain factors were important in the final acceptance or rejection of the systems. We reasoned that individuals whose sense of time was polychronic would see less value in a system that called for planning and a belief that time was linear, with causes and effects. To ensure that respondents would not simply select planning factors because they were the only choices, economic factors such as price and staff time involved were also included (Davidson & McFetridge, 1985) as were Arab cultural values that would be more salient in other contexts, such as prior consultation with titular heads of the organization. Hypothetical scenarios (or scenario creation) offer the advantage of large sample sizes by having subjects evaluate real world situations. It stimulates the respondents to react to the independent variables through the wording of the scenarios (see Webster and Trevino, 1995, for a critique of the advantages of the approach). The technique has been previously used in IS research in studies by Daft, et al. (1987), Zmud, et al. (1990), Webster and Trevino (1995), and Straub and Karahanna (1998). Scenarios have also been used to measure decisions and choices of knowledge workers in the administrative sciences of marketing (Batsell & Lodish, 1981), finance (Slovic, 1972), human resources (Fedor, Eder, & Buckley, 1989), and strategy (Hitt & Tyler, 1991).


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Sampling The quantitative sample for the study reported here was drawn from 274 knowledge workers in Jordan, Egypt, Saudi Arabia, Lebanon, and the Sudan. This was composed of 121 in Jordan; 45 in Egypt; 28 in Saudi Arabia; 35 in Lebanon; and 45 in the Sudan. From a macro perspective, IT penetration varies across these nations with Egypt and Saudi Arabia at the high end and the Sudan at the low end. In order to maximize the variance in both the endogenous and exogenous variables, samples were drawn from countries, organizations, and individuals across the spectrum of IT penetration. Our sampling strategy in Jordan gives some sense for how the goals of the research program were met in one particular situation. Here, contact was made with a top Jordanian government official who arranged for the research team to interview and survey managers and professionals in the public and health care sectors. Arrangements were also made to include a sizable group of private sector employees in the study. IT use was widespread in one of the private firms and in the public organization. One of the health care organizations had low rates of diffusion while a private firm and a second health care organization fell somewhere in the middle. The sample was composed of a relatively homogeneous group of organizational knowledge workers in urban areas across these countries. Users of computer systems are typically highly educated in many Arab countries (Danowitz et al., 1995) so this was a representative sample of the population of interest, as shown in Table 1. This educated group, moreover, would be least likely to show the effects of culture on IT, less so than a rural sample, for instance. Thus, gathering data from this sample permits a robust test of cultural influence modeling. Finally, we wanted to sample from a wide variety of Arab countries to draw on a broad base of experience with Arab culture. We wanted to see if this group, regardless of widely different economic and social circumstances, would show

similar patterns of cultural acceptance of and resistance to information system. Table 2 shows that the sample did draw from persons who were born in a variety of Arab countries. Other Relevant Descriptive Statistics The data gathering was representative in several other respects. When we examine the amount of time the sampled group had lived in other Arab countries, it is clear that the sample was drawn from a professional, mobile workforce. A large percentage of those responding to the instrument in Saudi Arabia, for example, were Egyptians, Sudanese, or Kuwaitis. This accurately reflects the large ex-patriate contingent working in Saudi Arabia. Likewise, in Lebanon, several respondents were Syrians whereas the Jordanian sample showed a sizable number of Palestinians, both sampling statistics reflecting historical events. Finally, the time Arabs in the sample spent abroad in non-Arab countries was highly correlated with work on higher degrees. Although the overall average time abroad for the entire dataset was not high at 1.15 years, the more years of education individuals had, the more likely they were to have spent time in non-Arab countries (r = .238, p-value < .01). Validation of Technological Culturation Scale While technological culturation, per se, has not been previously measured, culturation measures have been validated in the context of Hispanic studies. Padilla (1980) created an Ethnic Loyalty Scale, which was based on factors of language knowledge, cultural affiliation, and social behavior orientation. Along a similar line, Olmedo, Martinez, and Martinez (1978) measured culturation through items on nationality and language, socioeconomic status, and semantic potency. Finally, Cuellar, Harris, and Jasso (1980) devised an Acculturation Rating Scale composed of language familiarity, usage, and preferences; ethnic identification and generation; language of reading and writing; and ethnic interaction.

Table 1. Educational Demographics of Study Participants (based on Hill, et al.,(1998) Degrees

Location Degree Conferred

High School Diploma Undergraduate Masters Doctorate

10.4% ( 28) 69.3% (187) 13.3% ( 36) 7.0% ( 19)

Arab Country Developed Country

81.0% (218) 19.6% ( 51)

Table 2. Respondent Countries of Birth Algeria Bahrain Egypt Iraq Jordan Kuwait Lebanon

  79  78 7 35

Libya Mauritania Morocco Oman Palestine Qatar Saudi Arabia


    10  7

Sudan Syria Tunisia United Arab Emirates West Bank Yemen

44 3    

Oct-Dec 2001

13

Their recent revised version of this scale still employs the same basic components (Cuellar, Arnold, & Maldonado, 1995). As with previous scales, our technological culturation scale stressed linguistic skills and ethnic background and interactions, but it also added dimensions that attempt to measure sources of contact with technically advanced societies. Participants supplied information about their educational degrees, for instance, but also about the country in which these degrees were earned. The not unreasonable assumption was made that degrees received in a technologically-advanced culture would result in a higher level of TC. Work affiliations were other possible sources of influence, that being if an individual worked for a “technology” firm for many years or for a firm headquartered in a technically-advanced nation. Less formal measures of culturation were also included in the scale. Readings in foreign technology journals or other information sources were, again, thought to be possible components of TC as were travel abroad, for business or pleasure. Contacts with family abroad was another, more personal element that was included. Questionnaire Instrument Validation The research instrument was tested for content validity, reliability, and construct validity, in accordance with the suggestions of Straub (1989). During the focus groups and interviews with Arab-American business persons, an attempt was made to qualitatively assess the content of the instrument by ensuring that the scenarios drew representatively from the cultural experiences of the participants. Focus group participants were asked, for example, to discuss in depth why IT was

not always accepted in Arab countries. Interpretation of these transcribed responses was useful in validating the cultural beliefs that were embedded in the scenarios. A similar assessment of content validity was made during the pilot study with Arab-American business persons. Construct Validity and Reliability Construct validity was tested through principal components factor analysis. Considering only loadings greater than .40, cultural beliefs, two technological culturation variables, and ITT or system outcomes loaded separately from each other (Varimax rotation). Reliabilities and factor loadings for the final set of endogenous and exogenous variables are shown in Table 3 below. In all cases, these exceed Nunnally’s rule of thumb heuristic (1967) for Cronbach as in exploratory research. One TC factor stressed informal contacts such as travel and contacts with family abroad. The other factor emphasized formal educational and work experiences. Neither language skills nor reading loaded at the minimum .40 level, however. It is not surprising that technological culturation did not load on a single factor. Several sub-scales make up the culturation construct in anthropological research, and these sub-scales are not highly interrelated; they are reflective rather than formative (Gerbing & Anderson, 1988), just as in our dataset. It may be that participants are more cognizant of formal contacts because they are so tangible, such as conferences and formal education. By the same token, informal contacts are subtler and have more in common with each other than with formal contacts. Thus, within the items that were created to represent

Table 3. Variable Reliabilities and Factor Loadings Construct

Items

ITT/ Systems • Strength of belief that the scenario Outcomes system will be successfully implemented • Belief that this system will be successful Cultural • Focus on long range planning is factor in Beliefs and final outcome Values • The fact that the system supports long range planning is important Technological • Extent of travel for business Culturation: Informal • Extent of travel for pleasure Culturation • Extent of contact with family members • Reading in foreign technology journals residing abroad Technological • Total attendance at conferences on Culturation: computer technology Culturation • Conferences on computer technology in Formal technically advanced countries • Number of years of educational degrees taken in technically advanced cultures • Employment by computer-related firm or foreign-owned firm • Speaking and writing proficiency in foreign tongues of technically advanced cultures

14

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#

II.2 II.3c

Factor 1 Loadings

Factor 2 Loadings

Factor 4 α Loadings

.8396 .8161

.720

II.1c

.8507

II.3a I.12a

.8392

I.12b I.14b I.15

Factor 3 Loadings

.652 .8988

.644

.8956 .4729 __

I.16

.9398

I.16

.9201

I.8

.4730

I.10 & I.11

.4609

I.9

__

.723


Vol. 9, No. 4

technological culturation, there was a clear distinction between variables that related to impersonal/formal processes of culturation versus personal/informal processes. Since it was not clear as to exactly why respondents separated these items as they did, we examined the two factors in separate LISREL runs to see if and how they related to systems outcomes.

Figure 2. Results of Testing LISREL Preliminary Model with Technological Culturation (1) = Personal/Informal Factor and Technological Culturation (2) = Impersonal/ Formal Factor (* p < .05; T-values are in parentheses) Culture-Specific Beliefs & Values

.91* (6.20)

DATA ANALYSIS Several types of data collected in this initial study of Arabs and Arab-Americans in Atlanta triangulated, indicating that our model covers the key variables that could predict success or failure for ITT. Findings from each set of data provide indications that knowledge about the cultural and social context of ITT is critical for the success or failure of ITT (See Appendix C for descriptive statistics). LInear Structural RELations modeling (LISREL) was used to investigate measurement characteristics and the simultaneous effects of CB and TC on ITT in the survey of Arab knowledge workers. Use of structural equation modeling analysis provides researchers with a comprehensive means of assessing and modifying theoretical models and, therefore, it offers a great potential for furthering theory development (Anderson & Gerbing, 1988). Structural equation modeling facilitates testing of a theoretical model as a whole as well as comparisons among competing theories (Bagozzi, 1980). In the case of the present dataset, it also allowed constructs with multiple indicator variables to be statistically manipulated without resorting to procedures for averaging across variable sets, creating indices, or transforming/adding incompatible values. Preliminary Model Analysis An initial LISREL model was run to determine the relative effect of the two technological culturation variables (for fitted covariance matrix, see Appendix B). The results, presented in Figure 2, show that the informal technological culturation factor had a significant impact on system outcomes whereas the formal factor did not. The overall model fit is relatively good and the squared multiple correlation indicates that 44% of the variance is explained. Thus the model is worthy of further consideration. Given these preliminary results, the theoretical model is specified with informal TC and CB as the exogenous latent variables and ITT as the endogenous latent variable, as shown in Figure 2. Nested Model Analysis Anderson and Gerbing (1988) recommend assessing a theoretical model of interest through estimation of five nested models, each representing a plausible alternative specification. Model M2 is said to be nested within a model M1 if its set of freely estimated parameters are a subset of those estimated in M1. The denotation is M2 < M1. In LISREL, this is achieved


.11* (1.97)


Technological Culturation (1)

.13 (.80) Technological Culturation (2)

2

= 53.62* df = 29 GFI = .96 AGFI = .93 RMR = .045 SMC = .44

by setting the constrained parameters in M2 to zero. The five nested models suggested by Anderson and Gerbing (1988) are: (1) the saturated model (Ms) which links all constructs to one; (2) the null model Mn which posits no linkages; (3) the theoretical model Mt, which is the theoretical model to be tested; (4) the constrained model Mc which constrains one of the theoretically defensible paths in Mt; and (5) the unconstrained model Mu which, based on theory, frees one or more parameters constrained in Mt. The five structural models are represented in the following nested sequence: Mn < Mc < Mt < M u < M s . Since differences between the null and saturated models and the other models have no basis in theory, a more parsimonious comparison procedure of the models can be adopted (Anderson & Gerbing, 1988). Testing these alternative models involves a set of sequential C2 difference tests (SCDT). These tests are asymptotically independent (Steiger, Shapiro, & Browne, 1985), each testing a null hypothesis of no difference between two nested structural models. With degrees of freedom equal to differences between the degrees of freedom for the two models, the difference between the C2s for two nested models is itself asymptotically distributed as C2 (Anderson & Gerbing, 1988). Because the value of the SCDTs depends on sample size, significant C2s can result when there are only trivial differences between the two nested models (Anderson & Gerbing, 1988) and (Bentler & Bonett, 1980). A statistic that deals with this issue and yields an indicator of practical significance is the normed fit index ¾ d (Bentler & Bonett, 1980). Bentler and Bonnet (1980) propose that any candidate model Mi can be compared to a base model M0 by means of a goodness of fit index, d, which is calculated as: δ = ((C2 M0 )- (C2 Mi ))/( C2 M0 ) where M0 = the base model Mi = one of several alternative candidate models The δ index indicates how practically significant the

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15

difference in C2s is (Bentler & Bonett, 1980). Ranging from 0 to 1, this δ index represents the increment in fit obtained in evaluating two hierarchical step-up models. Even if the SCDT between the theoretical model and the unconstrained model is statistically significant, the theoretical model should be preferred if dtu is practically insignificant. That is, from a practical point of view, the more parsimonious model is superior because it provides an adequate explanation for the data (Anderson & Gerbing, 1988). The theoretical model of interest, Mt , has already been presented in Figure 1. Based on previous research on culture and IT, the constrained model, Mc , was specified by removing the path from the TC latent construct to systems outcomes. For the unconstrained model, Mu , an additional plausible path has been postulated. As shown in Figure 3, the path between TC and CB has been added based on the argument in anthro-

pology that culturation challenges established cultural beliefs and knowledge, social structures, and technologies (Bertolotti, 1984). LISREL8 (Hayduk, 1987; Jöreskog & Sörbom, 1993) was used to analyze the data. Through structural equations, LISREL generates causal coefficients that maximize the likelihood of the fit between constructs. Results are presented in Figure 3, which also shows the C2 and fit indices ¾ Goodness of Fit (GFI) and Adjusted Goodness of Fit (AGFI) ¾ for the theoretical, unconstrained, and constrained models. Figure 3 shows that the paths between CB and ITT as well as TC and ITT are significant (p < .05) in both the theoretical and the unconstrained models. The path between CB and ITT is also significant in the constrained model. The best fit to the data was the theoretical model. As presented in Table 4, none of the C2s comparing the constrained (Mc), the theoretical (Mt), and the unconstrained (Mu) models are significant. Moreover, in that the d statistics are not particularly high, we can conclude that none of the improvements in fit between the constrained and theoretical model and the constrained and unconstrained models is practically significant. As a result, the most parsimonious model that fits the data, i.e., the theoretical specification, is preferred. The theoretical model fits the covariance in the data well, as demonstrated by a GFI of .95 and an AGFI of .88, where 1.00 is a perfect fit. Moreover, the modification indices do not indicate any means by which to improve the model fit. Finally, the squared multiple correlation for the structural equations was .50 for IIT. This may be interpreted to mean that 50% of the variance in ITT is explained by the theoretical model. It is important to note that the coefficient for the linkage between cultural beliefs and ITT is nearly four times as large as that of the coefficient between technological culturation and ITT. These statistics suggest that the former of these relationships (CB Þ ITT) offers more explanatory and predictive power than does the latter (TC Þ ITT). While noteworthy, this of course, may be an artifact of the measurement itself.

Figure 3. Results of Testing LISREL Nested Models with Technological Culturation (1) = Personal/Informal Factor (* p < .05) Theoretical Model

2

Culture-Specific Beliefs & Values

.58* Technological Acculturation (1)

Unconstrained Model

.14*


.01 .14*

Technological Acculturation (1)

Constrained Model

= 54.26* df = 12 GFI = .95 AGFI = .88 SMC = .50


2

= 54.27* df = 11 GFI = .95 AGFI = .88 .58* SMC = .50 ITT/ System Outcomes

2


.59* Technological Acculturation (1)

= 56.92* df = 13 GFI = .95 AGFI = .88 SMC = .48

Testing Rival Hypotheses Two rival hypotheses need to be accounted for before concluding that culture clearly has an impact on systems outcomes. Of the traditional implementation factors, three factors were tested against culture-specific beliefs. These were: (a) the attractiveness of the pricing of the system, (b) top


Table 4. Nested Model Comparisons

16

Model Comparison

Χ2(1) - Χ2(2)

Χ2

df

δ

Mc-Mt Mu -Mt Mc-Mu

56.92-54.26 54.27-54.26 56.92-54.27

2.66 .01 2.65

1 1 2

.04673 1 .04655

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Table 5. Constructs and Measures for Rival Hypothesis #1 Construct

Items

#

α

Attractiveness of Pricing

• Focus on moderate price is factor in final outcome • The fact that the system has a moderate price is important

II.1a II.3d

.850

Top Management Support Staff Time Req'd

• Focus on lack of top management support is factor in final outcome • The fact that the system was not presented to top management is important • Focus on staff time required for implementation is factor in final outcome • The fact that the system will require staff time is important

II.1b II.3b II.1d II.3e

.901

management support for the project, and (c) the amount of staff time required to learn and operate the system. Measures of these constructs along with Cronbach as are shown in Table 5 below. Testing of Rival Hypotheses What is valuable to determine with respect to the traditional implementation rival hypotheses is whether partialing out the effects of these factors will severely diminish the impact of cultural beliefs on systems outcomes. To test this possibility, a LISREL model was run which posed CB against these traditional factors. The results are shown in Figure 4. What is compelling in this analysis is that CB remains highly significant even when pitted against traditional factors, two of the three of which are significant in the analysis. Our interpretation of this pattern of significance is that systems outcomes depend on a series of factors, some of which are culturally-neutral, such as relative pricing of hardware and software and internal support of innovations by opinion leaders like top managers (Rogers, 1995). Culture-specific beliefs, however, will exert a powerful influence on perceptions, even when compared against such traditional factors. The size of the path coefficients in the LISREL run indicates Figure 4. Results of Testing LISREL Model Comparing Traditional Implementation Factors Against CultureSpecific Beliefs (* p < .05) Culture-Specific Beliefs & Values

.82* (4.84) Attractiveness of Pricing

.69* (3.07) ITT/ System Outcomes

-.40* (-2.97) Top Mgmt Support

Staff time Requirements

-.19 (-.73)

2

= 57.02* df = 25 GFI = .96 AGFI = .91 RMR = .054 SMC = .55


.780

that CB is the largest standardized value of the three significant values, offering twice as much explanatory power with respect to systems outcomes as top management support. National Culture Tests We also examined a rival hypothesis that sub-cultural or country-by-country differences could influence the major constructs in our model. As can be seen from Table 6, Comparison of Birthplace and Sample Site, there were only 34 respondents of the 270+ from whom data was collected who were not residents of the country of their origin. For the most part, people were still living where they were born and, presumably, have become fully integrated into their dominant national culture. But there is a legitimate concern that if the 34 individuals are part of a sub-culture that is national in origin, then these 34 participants could conceivably create a systematic bias in the data that would diminish the strength of the tests that look at sample site. The 34 respondents who were not living where they were born (or at the sample site) are easily explained by current conditions in the Middle East, which gives us some comfort that the data are truly representative. For instance, seven Palestinians are living in Jordan, and, with exception of the sixty-two year old, have lived there their entire lives (for all intents and purposes). This is an accurate reflection of the large Palestinian population in Jordan. Moreover, there are many Egyptians working in Saudi Arabia, and even some Sudanese. This also is a good description of the present working conditions and immigrant worker flows that have characterized this region for a long time. To look at these issues statistically, the five Arab countries in our sample–Egypt, Saudi Arabia, Lebanon, Jordan, and the Sudan–were treated as nominal, fixed factors independently affecting the variables that compose our research constructs. Country of birth was also included as a fixed factor in that sub-cultures derive, to a large extent, from childhood experiences, which are most likely to be associated with culture of birth. MANOVA findings are shown in Table 7. In this table, it is clear that neither overall F test was significant at the .05 a protection level. Moreover, there were no univariate country-by-country significant differences for

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Table 6. Comparison of Birthplace and Sample Site Sample #

Sample Site

Birthplace

Age

1 2 3 4 3 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

Jordan

Palestine (7)

49 28 35 33 36 62 33 47 30 27 25 24 29 31 31 23 40 19 33 22 31 34 40 31 27 37 47 42 40 52 33 48 45 43 27

Kuwait (4)

Lebanon

Egypt Syria Lybia Germany Syria Kuwait (2)

Saudi Arabia

Syria Egypt (11)

Sudan (3)

Sudan

Egypt

either cultural beliefs or systems outcomes other than for one of the outcome measures. This provides empirical evidence that the sample was generally homogeneous with respect to these key constructs. Thus, findings strongly support the contention that these culture-specific beliefs and outcomes are not confounded by sub-culture or country sampling biases and that Arabs, in general, are of like cultural mind on these variables. The issue regarding sub-cultures is extremely important and difficult to tease out. What we can say is that the sample was drawn from working adults who are generally from a higher socio-economic and educated segment of the general population. This would mean, for example, that it is highly unlikely that there are Bedouins or Berbers in the Egyptian sample (Hobbs, 1990). The same logic holds for the Sudan

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Years Living in Other Arab Countries 47 28 35 33 33 34 33 43 0 3 3 4 4 16 0 23 12 17 7 22 20 22 12 18 3 7 10 3 2 6 9 7 8 8 0

Years Living in Non-Arab Countries 2 0 0 0 3 3 0 4 5 0 0 8 0 4 2 1.50 0 0 0 0 0 0 0 0 0 0 1 2 0 8 0 7 5 2 0

where the sample was drawn from University-educated people who are ethnically Arab and typically not members of African tribes. Indeed, the percentages of the populations that are ethnically Arab in the figures cited indicate that there is probably no problem with sampling in Saudi Arabia, Lebanon, and Jordan.

DISCUSSION: LIMITATIONS, CONTRIBUTIONS, AND FUTURE RESEARCH Although the only culture-specific belief that was examined in this work was the Arab sense of time, the examination of a single belief in its context is consistent with the cultural influence modeling approach. A broader assortment


Vol. 9, No. 4

Table 7. MANOVA Test of Birth and Sample Site Countryby-Country Differences Construct

Dependent Variable

Birthplace F

Culture-specific Beliefs ITT/ Systems Outcomes Technological Culturation

V3A V1C V2 V3C 14B TRAVELA TRAVELB Overall F Test Birthplace Sample Site

.152 .859 .493 .688 .157 .855 .191 .902 4.067 .019 3.608 .015 1.294 .277 1.262 .289 .857 .426 1.087 .356 .347 .707 .721 .541 1.130 .325 .307 .821 1.35 .174 1.29 .170 (1 through 4 for Egypt, Sudan, Lebanon, and Jordan) (1 through 5 for Egypt, Sudan, Saudi Arabia, Lebanon, and Jordan)

Fixed Factors

of beliefs and new methods of capturing these beliefs would surely be useful in that the current study examined only one, albeit a powerful explanator. Sense of time could be supplemented with other beliefs in order to test the model via a more robust procedure. Larger sample sizes are always desirable, as are samples from Arab cultures that are less tied to the West, countries like the United Arab Emirates, Yemen, and Algeria, for example. By using samples from countries that are more westernized, the conditions for testing our theory were more robust, but lacked the representativeness of a sample that included all Arab countries, for instance. As viable a technique as scenario creation is, qualitative methods are also excellent for exploring the phenomenon of interest. Quantitative methods have their strengths, but also their weaknesses, and a multi-pronged approach, where there are good measures of cultural impacts from qualitative sources would be extremely helpful. Contributions In spite of the limitations outlined above, we feel that cultural-influence modeling is a research innovation that has now been empirically demonstrated for the first time in this paper. This work represents a departure from generalized cultural belief perspectives that have been deployed in prior work. The specific-cultural belief that we have studied in the present research is the Arab sense of time. The planning scenario used was explicitly designed to evoke a cultural response as related to time. We expected that Arabs reading and reacting to the scenario would resist the value of the system. In spite of the fact that the sample group was highly attuned to the advantages of the technology, the correlations were significant, indicating that this specific cultural belief had a strong impact on IT outcomes. Rival hypotheses to our interpretation indicate that this particular cultural belief does have a bearing in this context.


p-value

Sample Site F

p-value

What are other specific contributions of this study? The findings from this study provide scholars and managers with valuable information. Analysis of the dataset suggests that both culture-specific beliefs and technological culturation significantly affect ITT, and that CB showed a much stronger effect than did TC. Based on the results of this study, we extrapolate that successful transfer of IT into organizational/ business workplaces in culturally and socially diverse countries requires an understanding of micro-level beliefs, norms, and actions within the framework of national and international macrostructures. Culture is an independent variable that impacts ITT and is reflected in formal and informal organizations/businesses. Culture gives people the sense of order they have to their everyday lives; cultural beliefs and values of different cultures differ markedly in terms of how they construct a meaning for technology. In this way our findings generally support the contemporary critical theory literature on Arab society and culture. The cultural influence model attempts to represent the important cultural influences on ITT. Three kinds of cultural variables were conceptualized in the present work, and relationships between two of these and ITT/systems outcomes were explored. National IT development, including technological policies and IT infrastructure, vary by nation and, consequently, countries will differ in how well they can encourage technological innovation. Future studies can and should integrate the national IT development component into tests of the model. Preliminary findings indicate that specific cultural components of Arab culture have an influence on how IT is viewed and the extent to which it might be utilized. Culture does not necessarily need to be viewed as a barrier that obstructs ITT. Indeed, culturally appropriate IT design and implementation which considers the differential influence of culture on ITT can enhance its transfer. This process can effectively “Arabize” technology. Instead of blaming the workers or culture for ITT failure, we propose that using specific cultural components of

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culture in the ITT process will encourage the transfer process. When individuals hold cultural beliefs that are at variance with the dominant cultural beliefs and values, they have been influenced, more often than not, by an external factor, such as personal and informal exposure to the technology of the nonArab industrialized world. Moreover, cultural influence modeling is a research innovation because it argues that researchers should provide evidence for specific cultural beliefs holding in particular cultures and then testing the effects of those beliefs. The approach is more demanding and intensive in that it requires researchers to examine the beliefs in the field as well as in the literature. Nevertheless, it represents a viable, new approach that differs significantly from the Hofstede-style of cultural variables study. The literature documenting U.S. experiences with ITT (Brancheau & Wetherbe, 1990; Cooper, 1994; LeonardBarton & Deschamps, 1988; Moore & Benbasat, 1991; Prescott & Conger, 1995; Zmud, 1982) is increased by the findings in the current work. Culture is a factor in how systems are viewed, but this IT literature is relatively light on work that delineates cultural and social variables that foster or impede the adoption of new information technology. In keeping with the spirit of the descriptive work by Goodman and colleagues (Ariav & Goodman, 1994; Danowitz et al., 1995; Dedrick et al., 1995; Goodman, 1991a, 1991b; Goodman & Green, 1992; Goodman & Press, 1995; La Rovere & Goodman, 1992; Mesher et al., 1992; Nidumolu & Goodman, 1993; Odedra et al., 1993; Wolcott & Goodman, 1993), IT diffusion differs significantly around the world, and researchers need to develop and test scientific hypotheses that advance theory on the phenomenon of ITT. The present study attempts to respond to this void. Indeed, it adds evidence to those studies that have already empirically tested cultural impacts on the adoption and diffusion of new information technologies, such as Ho et al. (1989), Straub (1994), and Raman and Wei (1992). This work is tied in closely with prior research, but also extends it by stimulating and measuring cultural attributes and their affect on IT acceptance. While new methods can also be deployed, the scenario creation method served its purpose in this study. The practical implication of the empirical findings is for managers to acknowledge cultural differences and adapt the technology to the cultural context. Since technological culturation is experientially-based, firms in developing countries might be advised to expose their employees more to high technology cultures, for instance. While education, training, and strengthening of entrepreneurship have been shown to have significant implications for entrepreneurs in underdeveloped Arab countries such as Jordan (Yasin, 1996), preliminary evidence from our study does not support the idea that formal culturation is effective. Ironically, it appears that informally-derived experiences are more valuable.

20

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From the standpoint of practical implications of the finding that cultural beliefs significantly impact ITT, there is a general principle that can be tentatively espoused and then several specific suggestions. First, managers should attempt to work with, rather than against prevailing cultural patterns, especially in the case of managers and workers who have not been technologically culturated. In a strongly patriarchal, tribal, and communal society like the Arab culture, for example, top management buy-in and championship must be ensured before attempting to introduce new IT, as Yavas et al. (1992) have found. If further studies find that the Arabic cultural preference for face-to-face communication works against the use of certain technologies, it does not make sense to stress the face-to-face replacement value of any system, such as E-Mail or Electronic Meeting Systems. To do so is likely a blueprint for disaster. Rather E-Mail, for example, may be “sold” to management as a supplemental system to enhance information exchanges in support of their face-toface meetings. Future Research Culture influence modeling takes the stance that the only way to understand the effect of cultural beliefs is to examine them individually in their respective cultural contexts. We postulate that cultural beliefs should not always be measured and tested in the aggregate, á la Hofstede (1980). The scientific approach will allow us to understand the phenomenon through the accumulation of studies, each of which examines different cultural beliefs. Time is only one of the culture-specific beliefs. Future research should test other culture-specific beliefs to determine how these distinctly different themes in Arab culture impact technology transfer. This research will hopefully spur others to investigate the generalizability of these findings across different cultures and different IT innovations. There are certainly at least three levels of culture ¾ ethnic, organizational, and IT ¾ and these should be explored for conjunctive (Lincoln, Hanada, & Olson, 1981) as well as separate effects on ITT. As firms internationalize, there is a growing need to understand how cultural factors might affect a multinational organization’s ability to adopt and utilize IT. Further studies that expand upon this one may lead to knowledge that will help IT researchers and practitioners in improving the technology transfer process. Such knowledge will be valuable to practitioners because it may spell the difference between success and failure in implementing IT in the Arab world and other developing nations and regions.

REFERENCES


Vol. 9, No. 4

APPENDIX A Relevant and Background Portions of Questionnaire [Lines in open format answers reduced in size for sake of brevity] Section I. Personal and Professional Information 1a. Country of birth:________________________ 1b. Occupation: ____________________ 1c. Nationality: ___________________________ 2. How many years have you lived in each of the following Arab countries? Algeria Bahrain Egypt Iraq Jordan Kuwait

No. of Yrs _______ _______ _______ _______ _______ _______

Lebanon Libya Mauritania Morocco Oman Qatar

No. of Yrs _______ _______ _______ _______ _______ _______

No. of Yrs _______ _______ _______ _______ _______ _______ _______

Saudi Arabia Sudan Syria Tunisia United Arab Emirates West Bank Yemen

3. How many years, in total, have you lived abroad in non-Arab industrialized countries? _____ (# of years) 8.

Education:

Degree Obtained _________________ _________________ _________________ 9.

Field of Study ____________________ ____________________ ____________________

Institution _________________ _________________ _________________

Country __________________ __________________ ….. __________________

Please check off, where appropriate, information about your language fluency below:

Language Arabic English French _________________ _________________

I can read it easily. ! ! ! ! !

I can write it easily. ! ! ! ! !

I can speak it easily. ! ! ! ! !

10. Please list the names of the companies you’ve worked for in the last five years: Name of Company ________________________ ________________________ 11.

Number of Total Years Employed with This Company _______ _______

Home Office Location __________________ ….. __________________

Have you ever worked in a computer-related industry? If so, for whom and for how long?

Name of Company ________________________

Number of Total Years Employed with This Company _______


Home Office Location __________________

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21

________________________ 12.

_______

__________________ …..

How much have you traveled in the non-Arab industrialized world?

12a. Travel for business purposes? 12b. Traveled for pleasure?

A great deal of travel

A fair amount of travel

A small amount of travel

"! !

"! !

"! !

Have not traveled at all "! !

14. Please indicate your agreement or disagreement with the following statements about use of computer technology by checking off the appropriate response:

14b. I have maintained close contacts with family members living abroad in non-Arab countries.

Strongly Agree

Agree

Neutral or Not Sure

Disagree

Strongly Disagree

!

!

!

!

!

15. Which, if any, of the following computerrelated publications do you read? I read it regularly 15a. Computer-related magazines such as Byte 15b. Computer-related newspapers such as ComputerWorld 15c. Academic journals such as the MIS Quarterly 15d. Computer vendor information and brochures 16.

"! ! ! !

I read it occasionally

I never read it.

"! ! ! !

"! ! ! !

Which, if any, conferences, seminars, or training programs in your home country or abroad have you attended in the last five years? If yes, please list below: Topic of Conference, Seminar, Training, etc. __________________________________________ __________________________________________

Country where held ___________________ ___________________…….

Section III. Scenario Please read and answer questions about the following scenario involving computers: Scenario. PLANNING SYSTEM

A consultant is employed by a medium-sized (1000 employees) manufacturing organization. As a result of his investigation, he has determined that there is a need for more long-range planning. He is aware of a moderately priced long-range planning system. The package includes computer software that will run on the firm’s existing hardware, and detailed operating procedures that carefully prescribe each step of the planning process. The system will not require a separate planning staff, but will require moderate investments of time by department heads and staff members of each of the various divisions. After presenting his ideas to the president of the company, he asks if the president would like him to make a presentation to the company’s top management. The president replies that that would not be necessary.

Using the scale below, please indicate how important you believe each of the following factors would be in the ultimate success or

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Vol. 9, No. 4

failure of this system? Very Important 1

Fairly Important 2

Somewhat Not Important Important 3 4

1a._____The system’s moderate price 1b._____The fact that no presentation was made to top management 1c._____The system’s focus on long-range planning 1d._____The amount of staff time 2. Please complete the sentence below by indicating how successful or unsuccessful you believe this new system will be in this firm. Please circle the most appropriate response.

In this organization, this system will be.... 3.

Very Successful 1

Successful 2

Neither successful nor unsuccessful 3

Unsuccessful 4

Very unsuccessful 5

Please indicate your agreement or disagreement with the following statements by checking off the appropriate response:

3a. The fact that the system supports long-range planning is an important element in its ultimate success or failure. 3b. One thing that will affect the success or failure of the system is the fact that the system was not presented to the company’s top management before being implemented. 3c. The chances are good that the firm will be successful in implementing this system. 3d. A factor that will have a major impact on whether the system is successful is its moderate price. 3e.An important characteristic of this situation in its ultimate success or failure is the amount of staff time required.

Strongly Agree

Agree

Neutral or Not Sure

Disagree

Strongly Disagree

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

APPENDIX B Fitted Covariance Matrix

V2 ITT TC

CB

V2

V3C

TRAVELA

TRAVELB

V14B

V1C

V3A

1.09

V3C

0.65

1.07

TRAVELA

0.09

0.08

1.00

TRAVELB

0.11

0.10

0.78

1.00

V14B

0.03

0.02

0.19

0.23

1.00

V1C

0.59

0.53

-0.01

-0.01

0.00

1.54

V3A

0.51

0.46

-0.01

-0.01

0.00

0.86


1.19

Oct-Dec 2001

23

APPENDIX C Descriptive Statistics

Construct

Items

#

DB Code

Mean

SD

ITT/ Systems

• Strength of belief that the scenario

Outcomes

system will be successfully implemented

II.2

V8

1.94

.77

• Belief that this system will be successful

II.3c

V9c

2.17

.80

II.1c

V7c

1.55

.72

range planning is important

II.3a

V9a

1.66

.71

Technological

• Extent of travel for business

I.12a

V12a

1.41

.61

Culturation:

• Extent of travel for pleasure

I.12b

V12b

2.08

1.09

Cultural Beliefs and Values

• Focus on long range planning is factor in final outcome • The fact that the system supports long

Informal Culturation • Extent of contact with family members residing abroad

I.14b

V14b

2.33

1.57

• Reading in foreign technology journals

I.15

Average of

2.27

1.09

V15a-d Technological

• Total attendance at conferences on

Culturation:

computer technology

Formal Culturation

• Number of years of educational degrees

I.16

Total of V16

.00148

.1210

I.8

Degree_tot

1.1704

.7009

I.10 & I.11

Foreign_co

.00185

.1351

societies

I.9

Lang_tot

3.0111

1.2803

• Moderate pricing of h/w, s/w

II.1a

V7a

1.76

.84

II.3d

V9d

2.15

1.02

• Presented to execs for top

II.1b

V7b

2.07

1.04

management support

II.3b

V9b

2.27

1.09

• The amount of staff time

II.1d

V7d

1.68

.78

required

II. 3e

V9e

1.85

.76

Time Spent In

• Years outside Arab countries

Total of I.2

Years_non

1.1975

2.9384

Non-Arab World

• Years spent in industrialized countries I.3

Years_West

.92

3.62

taken in technically advanced societies • Employment by computer-related firm or foreign-owned firm • Speaking and writing proficiency in foreign tongues of technically advanced

Traditional Implementation Factors

(Western-style)

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nication Media Choices: Two Policy-Capturing Studies. Academy of Management Journal, 38(6, December), 1544-1572. Wolcott, P., & Goodman, S. E. (1993). Under the Stress of Reform: High-Performance Computing in the Former Soviet Union. Communications of the ACM, 36(10 (October), 25-29. Yasin, M. (1996). Entrepreneurial Effectiveness and Achievement in Arab Culture. Journal of Business Research, 35(1, January), 69-77. Yavas, U., Luqmani, M., & Quraeshi, Z. A. (1992). Facilitating the Adoption of Information Technology in a Developing Country. Information & Management, 23(2, August), 75-82. Zmud, R. W. (1982). Diffusion of Modern Software Practices: Influence of Centralization and Formalization. Management Science, 28(12), 1421-1431. Zmud, R. W., Lind, M., & Young, F. (1990). An Attribute Space for Organizational Communication Channels. Information Systems Research, 1(4, December), 440457. Acknowledgments: We are grateful to Dr. Yousef A. Nusseir, Director General of the National Information Center in Amman, Jordan for his support and assistance in conducting the work in Jordan, and to Dr. Omar M. Lattouf for his assistance as well. We also are grateful to Dr. Malik Bashir Malik for his help in data collection in the Sudan, and to Dr. Ismail I. Gomaa for conducting data collection in Egypt, Lebanon, and Saudi Arabia. We thank William Cotterman for his invaluable input on the conceptual and implementation stages of the research. This project was partially funded by a Georgia State University Research Initiation Grant and the Business and International Education Program of the U.S. Department of Education. Further funding has been secured to advance this research stream from the National Science Foundation. We would also like to thank the anonymous reviewers and the editor for their very insightful and helpful comments.

Detmar W. Straub is the J. Mack Robinson Distinguished Professor of Information Systems at Georgia State University, Detmar has conducted research in the areas of e-Commerce, computer security, technological innovation, and international IT studies. He holds a DBA in MIS from Indiana and a PhD in English from Penn State. He has published over 80 papers in journals such as Journal of Global Information Management, Management Science, Information Systems Research, MIS Quarterly, Organization Science, Communications of the ACM, Journal of MIS, Information & Management, Communications of the AIS, Academy of Management Executive, and Sloan Management Review . Karen D. Loch is an Associate Professor and Director of the Institute of International Business in the J. Mack Robinson College of Business at Georgia State University, Karen’s current research interests span international IT studies, security and ethical concerns, and global ecommerce. She holds a Ph.D. in MIS from the University of Nebraska. Loch has published in journals such as Journal of Global Information Management, Communications of the ACM, MIS Quarterly, Information Systems Journal, Academy of Management Executive, Data Base, and Journal of Informatics and Education. She is a co-editor and contributor of Global Information Technology Education: Issues and Trends. She serves as Associate Editor for Journal of Global Information Management, The Journal of Global Information Technology Management, and as review board member for Information Resources Management Journal. Carole E. Hill is a Professor Emeritus of Anthropology at Georgia State University, Carole has published research in the areas of health care policy, health behavior, and cultural knowledge in Costa Rica, the U.S. South, and the Middle East. She holds a Ph.D. from the University of Georgia and a post-doctorate from the University of California at Berkeley. She has published 8 books and over 60 articles in journals such as American Anthropologist, Social Science and Medicine, Human Organization, and Anthropological Quarterly. She has served as President of the Society of Applied Anthropology.

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