Research paper due Thursday noon 28th Dec

FOUAD MEER 20038236 QM 650

RELATIONSHIP OF SOCIAL CLASS AND ATTITUDE TOWARDS TECHNOLOGY IN THE MINISTRY OF DEFENSE, BAHRAIN

1. Introduction & Justification of the Research Problem

The importance of technology in our lives doesn’t need any elaboration. Not only the private sector but also the public sector has taken an initiative towards adoption of information technology to the extent of their capability to ease the daily workflow. To maintain Bahrain’s 2030 economic vision and national economic strategy which are the ways to provide good jobs and raise standards of living , the government plans to technologize its economy which not only relies on private sector but also include public sector as well (Cisco, 2011). It was observed that the execution of new business advancements have spreading as their choice is directly thought to be a routine in ordinary operations (Baker, 2007). With various sorts of advances utilized as a part of the work environment, the appropriation of another innovation might be seen as just an overhaul of existing innovation instead of as a substitution of some obsolete classical business techniques. As a result of the continued technology affluence incorporated in the workplace, increasing numbers of employees need to be either trained or retrained in order to keep up with the changes in their job demands (Czaja, S. J., Hammond, K., Blascovich, J. J., & Sw, 1989). Lucas (1981) observed that different associations grasping and utilizing development, is basic to understand the mindsets of specialists towards advancement since such attitudes are essential to the productive use of systems. Status of person’s education, gender, age, etc. may play an important role in the attitude of the person towards information technology (Hubona, 2006). Therefore, the end result of the person, who is been told to implement the information technology into his day to day work and at the same is having positive approach towards technology, would be much different from the person who is opponent of technology. To meet up the digital requirements of the modern world, had lead the Ministry of Defense to adopt information technology into its working culture. With the integration of Technology into the Ministry, employees’ resistance or reluctance has grown due to the way the information technology being used. Employees are facing problems as the technology was expected to ease the workflow for employees but rather employees are found complaining of wasting a lot of time on queues for services in the concerned departments, work halt due to system crash and other technological related problems. This study focus on the effects of education level, monthly, and age of the Bahrain military employees on the relationship between attitude and technology in their day to day work.

2. Literature Review

Attitude can be defined as “a relatively enduring organisation of beliefs, feelings, and behavioral tendencies towards socially significant objects, groups, events or symbols" (Saul McLeod, 2009).Or according to Eagly “a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor (Eagly, 1993). This study examines employee’s age, sex and education level effect on his attitude towards acceptance of technology. An employee's attitude towards technology in the job is important because such attitudes are critical to the successful implementation of technological systems (Lucas Jr, H. C, 1981).

As Culpan (1995) has stated, 'There is a significant relationship between end users' attitudes and their degree of command over the use of an information system. Employees must react favorably to a system to ensure that it will be used widely and effectively'. Furthermore, when an employee has a negative attitude towards technology, he or she is likely to view technology at the job as a source of pain rather than a relief (Marquié, J. C., Thon, B., & Baracat, B, 1994). The Technology Acceptance Model developed by Davis in 1989 was specifically developed with the primary aim of identifying the determinants involved in computer acceptance in general; secondly, to examine a variety of information technology usage behaviors; and thirdly, to provide a parsimonious theoretical explanatory model (Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. , 1989). The Technology Acceptance Model states that a system will be accepted if it is easy to use. People tend to use an application to the extent that they believe it will help them with their job performance. Further, even if people believe that a given application is useful, they may believe that the systems are too difficult to work with, thereby efforts to operate the system outweighs the ease to use. The digital divide differentiates between those people have an access to digital technology at home or not. The factors causing the gap include cultural, social and demographic factors (Mason, C. Y., & Dodds, R., 2005).

3. Hypothesis

· H0: There is no significant relationship between education & attitude towards acceptance of technology. (β1 = 0)

· H1: There is significant relationship between education & attitude towards acceptance of technology. (β1≠ 0)

· H0: There is no significant relationship between income & attitude towards acceptance of technology. (β2 = 0)

· H2: There is a significant relationship between income & attitude towards acceptance of technology. (β2 ≠ 0)

· H0: There is no significant relationship between age & attitude towards acceptance of technology. (β3 = 0)

· H3: There is significant relationship between age & attitude towards acceptance of technology.(β3 ≠ 0)

4. Measurement of Variables

A survey questionnaire was designed to measure the research model variables. Our Independent variables are level of education, monthly income and age whereas dependent variable is employee’s attitude in relation to technology. Likert scale questions are used to measure attitude of employees (strongly agree = 5, agree = 4, moderate = 3, disagree = 2, strongly disagree =1).

5. Sampling

A population size of 500 employees was chosen from Information Technology Department in Ministry of Defense, Bahrain. A sample size is 50 employees. 50 employees were chosen via probability sampling i.e. Simple Random Sample).

6. Data Collection , and the analytical technique

300 questionnaires were distributed over a period of 10 days from 1.5.2017 to 10.5.2017. Only 100 valid responses were considered. Simple Random Sampling method was used to choose 50 employees (25 Male & 25 Female) for the study. Questionnaires were distributed to all respondents by hand. Eventually to examine the data, MS Excel was used.

7. Analysis

TABLE 1.

Multiple Regression Analysis :

A. THE REGRESSION STATISTICS:

R-Squared & adjusted R-Squared : R2 is the coefficient of determination and measures the proportion of variation in dependent variable (Y) that is explained by the variation in the independent variable. About 14.48% of the variation in Y is explained by the Independent variables, leaving about 85.52% unexplained. The adjusted R-squared compares the explanatory power of regression models that contain more than one variable. In this case 8.9% is explained by the independent variables, 91.1% is not explained. The unexplained variation is potentially related to factors that were not considered in this study. Multiple R : The square root of R2. It measures the strength of correlation between the dependent variable with the combination of the independent variables, which is in our case 38.1%. Standard Error: is the estimate of the common standard deviation, which measures the dispersion of the errors around the conditional mean and standard error is 8.67 as mentioned above in the table.

B. ANOVA:

To assess the overall significance of this study, F-test has been calculated. The calculated F-test is 2.927 while the critical F-test is 2.837; this value from F-Distribution Table using α=0.05, D1= 3, D2=45. Thus, the model is significance because the calculated F-test is greater than the critical F-test, which means that at least one variable of the Independent variables, is important to determine the attitude towards acceptance of technology.

C. Estimated Model:

Regression model is Y = β0 + β1X1 + β2X2 + β3X3 +ε, the estimated model will be ý= 40.918+ .689x1 – .003x2 – 0.169 x3. The equation line represents that if X1 increased by 1 unit holding other variables constant, then the expected value of Y increase by 0.689 (coefficient). If X2 increased by 1 unit, the expected value of Y will decrease by 0.003. If X3 increased by 1 unit, the expected value of Y will decrease by 0.169.

D. Testing the hypothesis:

In order to test our hypothesis and to determine either to reject or accept the null hypothesis, we need to find the significance of the independent variables on the dependent variable. Based on t-value taken from t-distribution table is 2.021 which will be compared with the t-Stat output for each variable. Therefore, if t-Stat > 2.021 & P-value < 0.05, the null hypothesis will be rejected and alternative hypothesis will be accepted and vice versa.

TABLE 2	SIGNIFICANCE TEST
VARIABLES	TEST	RESULT
EDUCATION	2.079>2.021 & 0.043<0.05	REJECT THE NULL HYPHOTHESIS
MONTHLY INCOME	0.045<2.021 & 0.64>0.05	ACCEPT THE NULL HYPOTHESIS
AGE	1.597<2.021 & 0.11>0.05	ACCEPT THE NULL HYPOTHESIS

Table 3 below shows the mean and the standard deviation for our data we collected from 50 students. Standard deviation has been calculated to measure the dispersion of data from the mean. As shown, all of the variables are close to their means.

TABLE 3	MEAN & STANDARD DEVIATION
Variables	Attitude	Education	Monthly Income	Age
Mean	40.18	11.78	559.26	40.12
Std. Deviation	9.09292167	3.824144562	182.1642912	9.913174083

The correlation between the independent variables with the dependent variable and the correlation amongst the independent variables is depicted in table 4. It can be seen low correlation between independent and dependent and correlation amongst independent variables.

TABLE 4	CORRELATION
	Attitude	Education	Monthly Income	Age
Attitude	1
Education	0.310459834	1
Monthly Income	0.022037637	0.170673626	1
Age	-0.20009602	0.029662969	-0.048221704	1

8. Interpretation of results demonstrating how the analysis provides a solution to research problem

According to data analysis done above, all the alternative hypothesis have been rejected except the education, which has shown a significant relationship with employees attitude towards acceptance of technology. Therefore, the employees should be trained properly and periodic update and support should be given to employees during the course of their work. The rejected variables could also be significant provided that large sample and variables are considered.

9. A brief conclusion

Employees’ attitudes towards technology in the ministry of defense have been analyzed. Relationship between two independent variables (monthly income and age) and the dependent variable is not established. However, a relationship between education and attitude towards technology is indicated significant. The independent variables contributed 38% of the variation in the dependent variable whereas the remaining 62% variations in attitude towards technology were due to other variables outside the regression model.

In the organization the e-services are implemented to increase the work performance of staff and to provide quick services to the employees of the organization, it is therefore recommended that the Ministry of Defense should give attention and priority to those variables that contribute to employee’s attitude towards technology. The Ministry and its departments should encourage accommodate innovation, staff training, and user support for e-services. If all these recommended could be integrated and executed well by the Ministry of Defense, staff positive attitude towards technology could be developed and enhanced.

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