Adapted Technology Acceptance Model (TAM)

MIS research provided a wealth of research streams in which to gather information relevant to the factors influencing DSS implementation and use. The streams included IT infrastructure, database, IS success and IS planning. All of these areas identified factors that could potentially affect DSS implementation and use in making decisions. The literature review identified ten factors that affect IS implementation (see Table 1).

Table 1: Key factors identified in IS implementation literature

No.	Factor
1	Management support
2	Having the right resources
3	Planning for the DSS implementation
4	Having the right skills
5	User expectation
6	Having the right development tools
7	Quality of the data resources
8	Champion
9	User participation
10	Prototyping

Figure 1 depicts the research model employed in the study. It is a reduced TAM model, excluding attitude and intention to use, because this research targeted only the local authorities that had already adapted DSS systems in their organizations. The basic idea for the model is predicting DSS usage in making strategic decisions as a dependent variable, by using both perceived ease of use and perceived usefulness with the different contextual variables. In this context, the model hypothesises that DSS usage, and the attitudes of decision makers towards this usage, can be accurately predicted by means of a host of relevant contextual factors.

Figure 1: Towards a conceptual DSS adoption model for SDM

The perceived ease of use is instrumental in driving DSS usage. The perception of the user friendliness of software applications (ease of use) is viewed as a major intermediary latent variable, along with context specific variables that consider a wide range of issues that are clearly country specific. The adapted TAM model provides the necessary conceptual underpinning to ascertain the factors of importance in facilitating DSS usage. The constructs composing the research model were operationalized using a combination of items extracted from previous relevant research.

System Usage

It is now self-evident that computer technology is being increasingly utilized in the workplace. The extent to which decision makers use information systems or engage in other computer-related activities is most economically determined by asking them directly. This method is frequently used (Deane, Podd, and Henderson, 1998). Based on previous research examining the usage of IT in the workplace, which relied very heavily on defining usage based on self-reported estimates (Birdi, Pennington, and Zapf, 1997; DeLone and McLean, 1992; Igbaria, Pavri, and Huff, 1989), three dimensions of DSS usage were included in this study:

• Actual usage of DSS: This dimension is widely used in MIS studies. For the purpose of this study, it is indicated by the self-reported percentage of use of DSS in SDM compared to the whole SD made during a period.

• Frequency of use: Many researchers suggest this measure, for example, DeLone (1988), Raymond (1985), and Sirnivasan (1985). Frequency of use was measured on a five-point scale ranging from "several times a month" to "once a year."

• Level of use: This serves to measure proficiency of use of the DSS. The respondents were asked to indicate their level of DSS usage in SDM on a five-point scale ranging from "no use" to "extensive use." Many researchers have used this measure, for example, Igbaria et al. (1989) and Maish (1979). The ranges of use have been changed from days to months and from months to years because the nature of SDM makes the frequency of its use more sporadic.

Perceived Ease of Use (PEU) and Perceived Usefulness (PU)

These two constructs, originally proposed by Davis, define the PU as the degree to which a person believes that using a particular system would enhance his or her job performance. The PEU is the degree to which a person believes that using a particular system would be free of effort (Davis, 1989). The validity of these two in Davis's model was re-examined in a number of other studies. Adams et al. (1992) replicated Davis's study with a focus on evaluating the psychometric properties of the two scales, while they examined the relationship between ease of use, usefulness, and system usage. The results showed that the reliability and validity of the two scales were very high. Another test of the reliability of the PEU and PU scales using two software packages showed that the instrument exhibited a high degree of test-re-test reliability (Hendrickson, Massey, and Cronan, 1993). As Davis (1989) pointed out, psychometricians emphasise that the validity of the measurement scale is built from the outset. To ensure the content validity of the scales, the items selected must represent the concept about which generalizations are to be made (Bohmstedt, 1970). Statements used in this research to operationalize the PEU and PU were basically adapted from Davis's study (1989), with minor changes in wording and the addition of one item to PU: "lower cost," which reflects the developing world's environment, where cost is an important factor in using DSS.

Task Characteristics

Several studies have attempted to develop conceptual models of the strategic decision-making process based on studies of multiple decision situations (Fahey, 1981; Mazzolini, 1981; Mintzberg, 1976). They have broadly viewed the process in three steps: problem formulation and objective setting, identification and generation of alternative solutions, and the analysis and choice of a feasible alternative. These models appear to be variations or extensions of the intelligence-design-choice phases discussed by Simon (1965). Most strategic decisions are characterised by uncertainty and complexity. Complexity means the existence of multiple and conflicting interpretations of the problem definition, which is particularly troublesome for the decision maker in using DSS. With highly complex decision situations, "...the answers are obtained through subjective opinions rather than from objective data" (Daft and Lengel, 1986). Thus, characteristics of the task (i.e., strategic decision) are generally seen to be an important element likely to affect DSS usage in making effective strategic decisions. To operationalize the concept of task characteristics, the researcher combined the complexity of the task as one of the most important characteristics of strategic decisions and the different stages of this process. The respondents were requested to indicate, on a five-point scale, their degree of agreement or disagreement with each item (number five being strongly agree and one strongly disagree). Although researchers expected that information technology would increase the amount of information available for strategic decision-making, the soft, personal information often used by management (El Sawy, 1985; Mintzberg, 1975) is not easily captured by a computer-based system (Karten, 1987). To measure what the CEO in local authorities think about the possibility of computerizing SDM, the respondents were asked to indicate, on a five-point scale, their degree of agreement or disagreement (5 being strongly agree and 1 strongly disagree) with the following two statements: "strategic decision process is too complex to be computerized" and "strategic decision making tasks are too person-centred to be computerized."

Cultural Characteristics

This construct investigates how the psychological context on both the individual and organizational level affects the perception and use of DSS in SDM. Hofstede's dimensions of cultures, power distance, individualism and uncertainty avoidance were adopted in general to measure this construct. Power Distance (PD) is the extent to which the less powerful members of organizations within a country expect and accept that power is distributed unequally. In large PD situations, superiors and subordinates consider themselves unequal; hierarchy is important. Centralization and structure are also important. Subordinates expect to be told what to do or directed. In small power distance countries, there is limited dependence of subordinates on their bosses. Malaysia, Guatemala, Panama, the Philippines and Mexico are, according to Hofstede's work, the strongest in PD, while the Scandinavian nations, New Zealand, Israel and Austria are the weakest. The Arab countries ranked seventh.

Individualism (IDV) pertains to societies in which the ties between individuals are loose; everyone looks after himself or herself and his or her immediate family. Collectivism as its opposite pertains to societies in which people from birth onwards are integrated into strong, cohesive groups, which throughout people's lifetime continue to protect them in exchange for unquestioning loyalty. In highly individualistic cultures, speaking one's mind is a virtue. In the collectivist or low IDV culture, on the other hand, harmony is more important. High IDV nations include the USA, Australia, UK, Canada and Netherlands. The lowest IDV nations are the nations of the Pacific Rim and several Central American countries. The Arab countries ranked 27^th.

Nations high in masculinity (MAS) index attach the most importance to earnings, recognition for doing a job well, the opportunity for advancement, and challenging work. A low MAS index reflects the importance of a good working relationship with the direct supervisor, co-operation with fellow employees, an acceptable family space, and employment security. High MAS countries include Japan, Austria, Venezuela and Italy. Low MAS nations are Denmark, Netherlands, Norway and Sweden. The Arab countries ranked 23^rd.

Uncertainty Avoidance (UA) is defined as the extent to which the members of a culture feel threatened by uncertain or unknown situations. A need for predictability and a predisposition for written and unwritten rules express this dimension. UA leads to a reduction of ambiguity. According to Hofstede, the emotional need for rules in strong UA nations can result in a talent for precision and punctuality, especially where the PD is relatively small. Strategic planning demands a greater tolerance for ambiguity. Weak UA cultures are more likely to stimulate innovation and to tolerate deviant ideas. Greece, Portugal, Guatemala, Uruguay and Belgium are the strongest in UA, while Hong Kong, Sweden, Denmark, Jamaica and Singapore score the lowest. The Arab countries ranked 27^th.

The literature indicates that the gap between the DSS professional and CEO may play an important role in DSS usage in SDM (Hatten and Hatten, 1997), and therefore the researcher has added this to the cultural dimensions of Hofestede. Although other dimensions may also be important, these were chosen as most obvious to the CEO in both the two countries. The respondents were asked to indicate, on a five-point scale, their degree of agreement or disagreement (number one being "strongly disagree" and five being "strongly agree") as to the effect of these items on DSS usage in SDM.

DSS Characteristic

Previous studies have found that certain DSS characteristics seem to have an important influence on the effectiveness of the systems: user-friendliness; ease of use; size (cost) of DSS; range of alternatives; timeliness, accuracy and relevancy of output (Igbaria et al., 1989; Udo and Davis, 1992a; Udo and Davis, 1992b). Executives' access to computerised information systems has arisen as an issue in the strategic use of these systems (Hasan and Lampitsi, 1995). Some researchers attempting to measure IS success have put forward factors related to DSS characteristics like system quality, information quality, information use and user satisfaction with the information (DeLone and McLean, 1992; Li, 1997). Based on the literature, the research instrument asked the respondents to indicate their agreement or disagreement with 12 statements reflecting the different DSS characteristics that might affect DSS usage in SDM. The response options are anchored on a five-point Likert-type scale, ranging from number one (strongly disagree) to five (strongly agree).

Environmental Characteristics

The government plays a major role in local authorities in both developed and developing countries, as regulator and/or investor (Blanning, Bui and Tan, 1997). Government policies on human resources development could include developing technical skills for building a computer literate society, which in turn will create favourable market conditions for using DSS strategically (Blanning et al., 1997). Both "favourable government policies" and "uncertainty in environment" were mentioned as one of the key facilitators of the strategic use of IT (King and Teo, 1996). In addition to the previous items, pressure from competition was mentioned in many studies as one of the factors for using IT strategically (Blanning et al., 1997), for example (Benjamin, Rockart, Morton, and Wyman, 1984; Johnston and Carrico, 1988; Neo, 1988). Based on this literature, the instrument asked the respondents to indicate their agreement or disagreement with four statements reflecting the different environmental characteristics that might affect DSS usage in SDM. The response options are anchored onto a five-point Likert-type scale, ranging from number one (strongly disagree) to five (strongly agree).

Organizational Characteristics

Many studies have investigated the influence of organizational attributes on the effectiveness of information systems in general (Cheney, Mann, and Amoroso, 1986; Lind, Zmud, and Fischer, 1989) and DSS in particular (Guimaraes, Igbaria, and Lu, 1992; Sanders and Courtney, 1985). Based on previous literature, the instrument asked the respondents to indicate their agreement or disagreement with seven statements reflecting the different organizational characteristics that might affect DSS usage in SDM. The response options are anchored on a five-point Likert-type scale, ranging from number one (strongly disagree) to five (strongly agree).

Internal Support Characteristics

Internal support given to decision makers within the organization either through training within the organization or other sources of support is critical, especially in developing countries where there is lack of resources. As a result, some decision makers rely on help from unspecialised persons (i.e., their colleagues), manuals, books, and help screens. Based on previous literature, the instrument asked the respondents to indicate their agreement or disagreement with five statements reflecting the different internal support characteristics that might affect DSS usage in SDM. The response options are anchored on a five-point Likert-type scale, ranging from number one (strongly disagree) to five (strongly agree).

External Support Characteristics

Due to insufficient internal technical expertise, especially in developing countries, the availability and quality of external support could be considered as an important determinant of DSS effectiveness in SDM. Recommendations from outside consultants were found to be an important variable in using IT strategically (Neo, 1988). In addition, the support that decision makers get from government agencies is important and varies from one country to another. For example, some governments may wish to maintain tighter control over their information infrastructure, as is the case in most developing countries, while others may prefer to take the market approach (Blanning et al., 1997). In addition, a good relationship with external vendors was one of the facilitators of success of end user computing (Shayo, Guthrie and Igbaria, 1999). Based on this literature, the instrument asked the respondents to indicate their agreement or disagreement with three statements reflecting the different external support characteristics that might affect DSS usage in SDM. The response options are anchored on a five-point Likert-type scale ranging from number one (strongly disagree) to five (strongly agree).

Decision Maker Characteristics

The importance of decision maker characteristics as determinants of information systems success has been emphasized by several authors (Guimaraes et al., 1992; Igbaria et al., 1989; Sanders and Courtney, 1985). Computer experience and user training have been found to have strong effects on microcomputer usage (Cheney et al., 1986). The importance of user training has long been proposed as a critical component of MIS success, in general, and for microcomputer usage in particular (Igbaria, 1992). Cognitive style as a decision maker characteristic has probably received the most attention. Huber (1983) reviews these studies and concludes that cognitive style is not a sufficient basis for driving DSS design guidelines because cognitive style is only one of many individual differences (Huber and Robey, 1983). Computer anxiety was found to have an effect on IS usage (Igbaria et al., 1989). In addition to that, some studies regard motivation as the key to MIS success (DeSanctis, 1982). Others find a positive relationship between user attitude and the successful use of information systems (Toubkin and Simis, 1980). In addition, some managers will have a more positive attitude toward change and a greater willingness to implement new ways of doing things. Innovative decision-makers are more eager to try new ideas, have more favorable attitudes toward change, are less dogmatic, and are more able to cope with uncertainty and ambiguity (Brancheau and Wetherbe, 1990; Rogers, 1995). Decision makers' characteristics were measured by asking managers to indicate their agreement or disagreement with 12 statements reflecting the previously mentioned different dimensions of these characteristics in DSS usage in SDM. The response options are anchored on a five-point Likert-type scale ranging from number one (strongly disagree) to five (strongly agree).

Top Management Support Characteristics

It is important that top management participation be active and not merely symbolic. Simply giving the go-ahead for the DSS implementation in the organization is not sufficient (Ang and Teo, 1997). Some ways that top management can demonstrate its support could be by providing necessary resources and leadership, by setting goals and policies for DSS and showing interest by participating in DSS design and development (Ang and Teo, 1997; King, 1996). Based on previous studies responses to six statements on a five-point scale format, ranging from number one (strongly disagree) to five (strongly agree) were used to determine top management support.