The effect of Role Stressors, and Job satisfaction on Turnover intention among IT professionals in Jordan

By Mohammad Mahmoud Ghaleb Al-DehneeSupervisor : Prof Mohammad Al-Tarawneh

Introduction:The loss of key IT personnel can severely impact an organizations competitive advantage and ultimately its survival (LeRogue et al.,2006). The special, unique and hard-to-replace skills of IT professionals, maximizes turnover expenses (McKnight et al., 2009).(Young,2002) stated that the average cost of replacing talented IT workers is twice their annual salaries. Most of the time, IT employees has a strong tendency to leave current job and work for another employer (Korunka et al.,2008). On top of what has been mentioned, it is not easy to satisfy IT professionals as they are able to easily find a new job based on the increasing demand for their skills and qualifications (McKnight et al.,2009 ). Accordingly, it is very important to study and identify the factors that affect IT professionals decision to leave their jobs.Voluntary turnover intention is the best and most immediate predictor of turnover. Voluntary turnover intention is a conscious and deliberate willfulness to leave the organization(Tett and Meyer 1993,p.262). Steel and Ovalles (1984) meta-analysis suggests that turnover intentions and turnover are related and that turnover intentions are better predictors of turnover than affective variables such as job satisfaction and organizational commitment. Also, there is consistent evidence to prove that turnover intentions are the strongest cognitive precursor of ( actual) turnover (Tett and Meyer, 1993, p.262; Hom and Griffeth, 1995; and Griffeth et al., 2000).Since pre-turnover studies provide clearer insights into decision processes (Steers and Mowday,1981; and Steel and Ovalle, 1984) than post-exit interviews, turnover intentions have been accepted as the focal construct to understand turnover of software professionals ( Bal and Gulati, 2006).This study aims to explore the effect of Job stressors, and job satisfaction on IT professionals intention to leave their jobs in Jordan.This paper contributes to the existing literature as it will provide evidence to the impact of Role Stressors, and job satisfaction on voluntary turnover intention among IT professionals in Jordan.

Literature ReviewJob satisfactionIt is the extent to which an employee likes his/her current job (Carsten and Spector 1987; Spector 1996). Job satisfaction has been extensively studied since the 1930s, with more than 12,400 studies published on the topic by the year 1991 (Lacityet al. 2008).Substantial evidence from several meta-analyses has found that job satisfaction is negatively related to turnover intentions (Cotton and Tuttle 1986; Homet al. 1992; Tett and Meyer 1993). Within the Information Systems literature, the basic model of turnover intentions shows the proximal variables of organizational commitment and job satisfaction directly affecting turnover intentions (Goldstein and Rockhardt 1986; Igbaria and Guimaraes 1992; Niedermanet al. 2002; Niederman and Sumner 2003). Joseph et al. (2007) conducted a meta-analysis of IS turnover research among IS professionals and found that job satisfaction was the most frequently studied determinant of turnover. In the 16 IS studies that used this construct, all 16 found a negative relationship between job satisfaction and turnover. Lacityet al. (2008) conducted two statistical tests (Somers d, and Kendalls tau) and found job satisfaction to be negatively related to turnover intentions in their sample of 25 Indian IS professionals. Bal and Gulati (2006) found job satisfaction affecting turnover intentions through organizational commitment in their study of Indian IS professionals.Based on the above we hypothesize:H1: Job satisfaction is negatively related to turnover intentions among IT professionals in Jordan.

Job-related stress, Stressors (Role Ambiguity, Role Conflict, Work overload or perceived load)Employees who experience high levels of role ambiguity and role conflict tended to be dissatisfied with their jobs and therefore tended to hold strong leave intentions (Igbria and Greenhaus, 1992).Perceived workload is the strongest predictor of work exhaustion which is the key driver of turnover (Rutner et al., 2008).The stress an individual perceives in the work environment has been linked to an individuals job satisfaction and intention to quit (Rasch and Harrell, 1989)Baroudi (1985) put forth a model of turnover intention that includes role stressors (role ambiguity and role conflict) and boundary spanning activities as important antecedents to turnover intention, mediated by attitudes of job satisfaction and organizational commitment. In a sample of 229 IT personnel working in 9 U.S. companies, Baroudi (1985) found role ambiguity to be the most dysfunctional variable for IT personnel explaining 10.3%, 20.2% and 22.2% of the variance in turnover intention, commitment, and job satisfaction respectively.Exploring job satisfaction among Information Center (IC) personnel in 38 companies from the Ohio region of U.S., Igbaria and Guimaraes (1992) found role ambiguity to be most dysfunctional in relation to job satisfaction. In addition, the relationship between role ambiguity and some components of job satisfaction were found to be education and age dependent.Goldstein and Rockart (1984) also found role conflict and role ambiguity to be significantly related to job satisfaction (turnover intention and organizational commitment) amongst analysts and programmers in 3 companies in Northeast U.S., and one company in Midwest U.S. Taken as a pair, role conflict and role ambiguity accounted for 30% of the variance in job satisfaction. They advocated for inclusion of role variables in the job characteristics' model to improve the prediction of job satisfaction among IT professionals.In a sample of IT personnel from 38 companies in Ohio, Guimaraes and Igbaria (1992) found that boundary spanning activities affect turnover intention indirectly, via job satisfaction and organizational commitment.Research has also sought to see how turnover intention differs among different kinds of IT personnel. For example, Gupta et al. (1992) examined the antecedents of turnover intention amongst information center personnel working in 30 organizations in Cleveland, U.S. They found that role ambiguity and role conflict were most dysfunctional for them.A very important contribution to IT turnover research was the inclusion of work exhaustion and burnout as potential antecedents to turnover. Moore (2000) findings show that perceived work overload is the strongest cause of work exhaustion which explained more variance than the other commonly cited antecedents that were tested in the model (role ambiguity and role conflict, fairness of rewards, and autonomy). In a subsequent qualitative analysis, the biggest cause of work exhaustion among IT professionals was found to be insufficient staff and resources (sample of 252 U.S. members of AITP). The work exhaustion model has been further validated by Ahuja et al. (2007) and Rutner et al. (2008). Building on Moores (2000) work on turnover intention, Ahuja et al. (2007) tested a model that is context-specific to IT road warriors who are IT consultants spending most of their workweek (including overnight) at distant client sites, representing their employer (survey of 171 IT consultants in a Midwestern U.S. city). The model highlights the effects of workfamily conflict, fairness of rewards, perceived work overload and job autonomy on turnover intention among IT road warriors.Based on the above we hypothesize the following:H2: Stressors (Role ambiguity, Role conflict, and work overload) will have a negative effect on job satisfaction among IT professionals.H3: Job satisfaction will mediate the effect of work stressors and intention to quit among IT professionals.

Theoretical Framework

Figure 1: Theoretical ModelOperational DefinitionRole Conflict :( Rizzo et.al, 1970) defined role conflict is terms of compatibility-incompatibility requirements of the role, where compatibility is judged to a set of standards or conditions which impinge upon role performance. Based on the work of others (Khan et al. 1964, Gross et.al, 1958), Rizzo et al stated the following dimensions:1. Person-role conflict: demands placed by an employees job/role that are incompatible with his or her personality or skills.2. IntraRole conflict: incompatible requirements within the same role.3. Conflict between time, resources, or capabilities (TRC ) of the focal person and defined role behavior4. Role Overload: Conflict between several roles for the same person which require different or incompatible behaviors, or changes in behavior as a function of the situation. This is interRole conflict for the focal person as he fills more than one position in the role system.5. Incompatible policies6. Conflicting requests from others 7. Incompatible standards of evaluation Figure 2 shows the dimensions of the role conflict construct.

Figure 2: Role Conflict DimensionsRole Ambiguity: Is not elaborately defined in the literature. The definition of Rizzo et al. used her in terms of:1. Predictability of the outcome or responses to ones behavior2. The existence or clarity of behavioral requirements, often in terms of inputs from the environment, which would serve to guide behavior and provide knowledge that the behavior is appropriate .Therefore, the items reflect certainty about duties, authority, allocation of time, and relationships with others; the clarity or existence of guides, directives, policies; and the ability to predict sanctions as outcomes of behavior.Figure 3 shows the dimensions of Role Ambiguity construct.

Figure 3: Role Ambiguity dimensions

Work overload or perceived loadBased on the work of (Kirmeyer and Dougherty, 1988) perceived load was divided into four dimensions:1. Feeling of being busy and rushed2. Feeling of pressure3. Amount Quality of work tradeoff4. Load underestimatedFigure 4 shows perceived workload dimensions:

Figure 4: Perceived Work loadJob SatisfactionThe concept of job satisfaction is generally defined as ones cognitive, emotional, and behavioral response to a job as a result of evaluation of job features and job-related events (Locke, 1976). Spector (1997, p.2) defined job satisfaction as How people feel about their jobs and different aspects of their jobs. It is the extent to which people like or dislike their jobs.One of the most comprehensive definitions of job satisfaction is Spectors ( 1997). He describes the nine aspects to evaluate in the context of job satisfaction. The nine aspects are pay, promotion, supervision, benefits provided, contingent rewards as means of recognition and appreciation, operating procedures and policies, dealing with coworkers, nature of the work, and communication within the organization. This study uses Spectors (1985) Job Satisfaction Survey (JSS ) to gather data or analysis.Figure 5 shows the dimensions of Job satisfaction.

Figure 5: Job satisfaction dimensionsTurnover IntentionTurnover intensions dimensions identified in Figure 6 are based on the work of Moor 2000.

Figure 6: Turnover intensions

MethodologyThe survey method is used in this study. IT professionals working in IT-related jobs werethe target population. A questionnaire was formulated based on an extensive review ofthe literature related with IT, stress factors, satisfaction, and employee turnover. The following section contains the Questionnaire details. Questionnaire:Role Conflict(Scale: 1 = strongly disagree to 7 = strongly agree)1- I perform tasks that are easy or boring2- I have to do things that should be done differently3- I work on unnecessary things4- I perform work that suits my values5- I have enough time to complete my work6- I receive an assignment without manpower to complete it7- I receive assignments that are within my training and capability8- I have just the right amount of work to do9- I receive an assignment without adequate resources and materials to execute it.10- I am able to act the same regardless the group I am with11- I work with two or more groups who operate quite differently12- I work under incompatible policies and guidelines13- I have to buck a rule or policy in order to carry our an assignment14- I receive incompatible requests from two or more people15- I do things that are apt to be accepted by one person and not accepted by others.

Role Ambiguity(Scale: 1 = strongly disagree to 7 = strongly agree)1 I am corrected or rewarded when I really dont expect it

2 I feel certain how I will be evaluated for a raise or promotion

3 I am told how well I am doing my job

4 I dont know if my work will be acceptable to my boss

5 I feel certain about how much authority I have

6 Clear, planned goals and objectives for my job

7 Lack of policies and guidelines to help me

8 I know that I have divided my time properly

9 I know what my responsibilities are

10 I have to feel my way in performing my duties

11 I know exactly what is expected of me

12 I am uncertain as to how my job is linked

13 Explanation is clear of what has to be done

14 I have to work under vague directives or orders

Perceived work load(Scale: 1 = strongly disagree to 7 = strongly agree)1- I feel that the number of requests, problems, or complaints I deal with is more than expected.2- I feel that the amount of work I do interferes with how well it is done.

(Scale: 1 = daily; 2 = almost every day; 3 = about once a week; 4 = 2-3 times a month; 5 = about once a month; 6 = a few times a year; 7 =once a year or less)

3- I feel busy or rushed. (R)

4- I feel pressured. (R)

Job Satisfaction(Scale: 1 = strongly disagree to 7 = strongly agree)1 I feel I am being paid a fair amount for the work I do

2 My supervisor is quite competent in doing his/her job

3 When I do a good job, I receive the recognition for it that I should receive

4 I like the people I work with

5 Communications seem good within this organization

6 The benefits we receive are so good as most other organizations offer

Turnover Intention(Scale: 1 = very unlikely to 7 = very likely)1 I will be with this company five years from now. (R)

2 How likely is it that you will be working with this company this 1232 time next year? (R)

3 I will probably look for a job at a different company in the next 123213123 year.

4 How likely is it that you will take steps during the next year to 132123 secure a job at a different company?

Data AnalysisThis chapter is to deal with research data analysis. As been mentioned in chapter three, the used methodology will determine the analysis type that should be applied for certain gathered data.Quantitative analysis is used for analyzing the gathered data from spreading the designed surveys on the selected samples, and analysed by using SPSS software for hypothesis' testing (Radhakrishna, 2007). Validity and Reliability test To test the stability of the measurement tool, Cronbach's Alpha was used according to the answers of the study sample totaling (100) persons, and table (1) shows Cronbach alpha of the instrument ranged between (87.3 90.9%), which is considered acceptable research and Studies in the Humanities (zikmund et al,2010).

Table (1): Cronbach's Alpha testVariablesNumber of questionsAlpha

Role Conflict1588.4%

Role Ambiguity1490.9%

Perceived work load488.2%

Job Satisfaction689.1%

Turnover Intention487.3%

Mean and standard deviation

Mean and standard deviation were used to describe attitudes of the sample toward study questionnaire respondents were required to rate how important they considered each factor to be in the recruitment and selection process. Factors importances were ordered according to the arithmetic mean as follow.Table (2): mean and standard deviation for the sample attitude according to Role ConflictNo.ItemMeanStd. Deviation

1 I perform tasks that are easy or boring5.690.96786

2 I have to do things that should be done differently5.570.90286

3 I work on unnecessary things4.500.93279

4 I perform work that suits my values4.750.86734

5 I have enough time to complete my work5.500.90596

6 I receive an assignment without manpower to complete it4.460.90518

7 I receive assignments that are within my training and capability5.580.72547

8 I have just the right amount of work to do5.640.89353

9 I receive an assignment without adequate resources and materials to execute it.5.680.90750

10 I am able to act the same regardless the group I am with5.550.92485

11 I work with two or more groups who operate quite differently5.441.00314

12 I work under incompatible policies and guidelines5.461.12791

13 I have to buck a rule or policy in order to carry our an assignment4.610.94003

14 I receive incompatible requests from two or more people4.590.90112

15 I do things that are apt to be accepted by one person and not accepted by others.5.390.94207

General mean and standard deviation5.230.87211

Table 2 shows that the general mean for role conflict (5.23) with standard deviation (0.872), its mean there are positive attitudes toward this factor because the mean was more than scale mean (4).Also, results indicate that the highest mean was for I perform tasks that are easy or boring (5.69) with (0.967) standard deviation so we can consider that this factor is the highest importance in role conflict, while the lowest importance that for I receive an assignment without manpower to complete it with mean equal to (4.46) and (0.905) standard deviation. Table (3): mean and standard deviation for the sample attitude according to Role AmbiguityNo.ItemMeanStd. Deviation

1 I am corrected or rewarded when I really dont expect it5.491.00610

2 I feel certain how I will be evaluated for a raise or promotion5.591.07315

3 I am told how well I am doing my job4.611.17227

4 I dont know if my work will be acceptable to my boss5.570.96352

5 I feel certain about how much authority I have5.590.85822

6 Clear, planned goals and objectives for my job4.660.82416

7 Lack of policies and guidelines to help me4.711.11565

8 I know that I have divided my time properly5.770.86147

9 I know what my responsibilities are 4.870.93256

10 I have to feel my way in performing my duties4.851.03536

11 I know exactly what is expected of me5.830.82098

12 I am uncertain as to how my job is linked5.620.70725

13 Explanation is clear of what has to be done5.610.90421

14 I receive incompatible requests from two or more people5.121.01442

General mean and standard deviation5.270.96623

Table 3 shows that the general mean for role ambiguity (5.27) with standard deviation (0.966), its mean there are positive attitudes toward this factor because the mean was more than scale mean (4).Also, results indicate that the highest mean was for I know exactly what is expected of me (5.83) with (0.966) standard deviation so we can consider that this factor is the highest importance in role ambiguity, while the lowest importance that for I am told how well I am doing my job with mean equal to (4.61) and (1.172) standard deviation.

Table (4): mean and standard deviation for the sample attitude according to Perceived work loadNo.ItemMeanStd. Deviation

1I feel that the number of requests, problems, or complaints I deal with is more than expected.4.650.84173

2 I feel that the amount of work I do interferes with how well it is done.5.520.93723

3I feel busy or rushed.5.660.70226

4 I feel pressured. 5.811.07612

General mean and standard deviation5.411.07632

Table 4 shows that the general mean for Perceived work load (5.41) with standard deviation (1.076), its mean there are positive attitudes toward this factor because the mean was more than scale mean (4).Also, results indicate that the highest mean was for I feel pressured (5.81) with (1.076) standard deviation so we can consider that this factor is the highest importance in Perceived work load, while the lowest importance that for I feel that the number of requests, problems, or complaints I deal with is more than expected with mean equal to (4.65) and (0.841) standard deviation. Table (5): mean and standard deviation for the sample attitude according to Job SatisfactionNo.ItemMeanStd. Deviation

1 I feel I am being paid a fair amount for the work I do5.570.58116

2 My supervisor is quite competent in doing his/her job5.790.94935

3 When I do a good job, I receive the recognition for it that I should receive4.341.02801

4 I like the people I work with5.460.92113

5 Communications seem good within this organization5.420.83937

6 The benefits we receive are so good as most other organizations offer5.260.92599

General mean and standard deviation5.31.15233

Table 5 shows that the general mean for job satisfaction (5.3) with standard deviation (1.152), its mean there are positive attitudes toward this factor because the mean was more than scale mean (4).Also, results indicate that the highest mean was for My supervisor is quite competent in doing his/her job (5.79) with (0.949) standard deviation so we can consider that this factor is the highest importance in job satisfaction, while the lowest importance that for When I do a good job, I receive the recognition for it that I should receive with mean equal to (4.34) and (1.028) standard deviation. Table (6): mean and standard deviation for the sample attitude according to Turnover IntentionNo.ItemMeanStd. Deviation

1I will be with this company five years from now. 5.850.85711

2 How likely is it that you will be working with this company this time next year? 4.951.18325

3 I will probably look for a job at a different company in the next year.5.180.93120

4 How likely is it that you will take steps during the next year to secure a job at a different company?5.441.20045

General mean and standard deviation5.350.98472

Table 6 shows that the general mean for Turnover Intention (5.35) with standard deviation (0.984), its mean there are positive attitudes toward this factor because the mean was more than scale mean (4).Also, results indicate that the highest mean was for I will be with this company five years from now (5.85) with (0.857) standard deviation so we can consider that this factor is the highest importance in Turnover Intention, while the lowest importance that for How likely is it that you will be working with this company this time next year with mean equal to (4.95) and (1.183) standard deviation.

Factor AnalysisTable (7): KMO and Bartlett's TestKaiser-Meyer-Olkin Measure of Sampling Adequacy.0.842

Bartlett's Test of SphericityApprox. Chi-Square1061.340

df253

Sig.0.000

Table (7) shows that KMO value is (84.2%) which great (Hutcheson, 1999), so we should be confident that factor analysis is appropriate for these data.

Table (8) indicate the eigenvalue in terms of the percentage of variance explained (factor 1 explains 55.46% of total variance). The shows that the first few factors explain relatively large amount of variance, whereas subsequent factors explain only small amounts of variance. Here it should be extracts all factors with eigenvalues greater than 1, which leaves us with four factors, and table (9) shows the factors before and after extraction.

Table (8): Total Variance ExplainedComponentInitial EigenvaluesExtraction Sums of Squared LoadingsRotation Sums of Squared Loadings

Total% of VarianceCumulative %Total% of VarianceCumulative %Total% of VarianceCumulative %

dimension0112.75755.46655.46612.75755.46655.4667.04530.63130.631

21.3685.94861.4131.3685.94861.4134.47219.44350.074

31.1735.09866.5121.1735.09866.5123.78116.43766.512

4.9934.31970.830

5.8933.88574.715

6.8203.56778.282

7.6832.97181.253

8.6652.89184.144

9.5612.44086.583

10.5282.29588.879

11.4121.78990.668

12.3611.56992.237

13.3011.30793.544

14.2671.15994.703

15.2441.06195.764

16.211.91996.683

17.202.87697.560

18.162.70298.262

19.143.62398.886

20.121.52499.410

21.089.38599.795

22.036.15499.949

23.012.051100.000

24.173.40298.795

25.142.33199.126

26.116.27099.396

27.091.21299.608

28.075.17499.782

29.054.12799.909

30.039.091100.000

313.375E-7.850E-16100.000

321.465E-3.407E-16100.000

339.951E-2.314E-16100.000

349.033E-2.101E-16100.000

355.432E-1.263E-16100.000

362.027E-4.714E-17100.000

37-8.038E--1.869E-17100.000

38-2.823E--6.565E-17100.000

39-5.830E--1.356E-16100.000

40-8.965E--2.085E-16100.000

41-1.151E--2.677E-16100.000

42-1.438E--3.343E-16100.000

43-1.838E--4.274E-16100.000

Table (9): communalities before and after extractionFactorInitialExtraction

a11.000.778

a21.000.894

a31.000.860

a41.000.719

a51.000.714

a61.000.757

a71.000.913

a81.000.807

a91.000.915

a101.000.908

a111.000.829

a121.000.861

a131.000.856

a141.000.934

a151.000.875

b11.000.847

b21.000.948

b31.000.907

b41.000.890

b51.000.809

b61.000.874

b71.000.880

b81.000.807

b91.000.748

b101.000.819

b111.000.780

b121.000.794

b131.000.742

b141.000.692

c11.000.761

c21.000.913

c31.000.807

c41.000.915

d11.000.908

d21.000.829

d31.000.861

d41.000.856

d51.000.934

d61.000.875

e11.000.847

e21.000.948

e31.000.907

e41.000.890

Test of hypothesisH1: Job satisfaction is negatively related to turnover intentions among IT professionals in Jordan.Table (10): test of the first hypothesis FactorF calculatedSigRR

Job satisfaction * turnover intentions48.280.00-0.6940.481

Simple Regression was used to test the first hypothesis, table 10 shows F calculated value (48.28), and this value is significant due to the Sig (0.00). Table shows R which indicate how the independent variable (turnover intentions) affects the dependent variable (job satisfaction), here it was (0.481). On the other hand; Pearson correlation (R) determine how the variables are correlated for each other, it was (-0.649), which mean these variable were negatively correlated.. Our rule indicates that when the significant level was less than (0.05) we suggest that the model is a statistically significant. Through those results it can be concluded that job satisfaction is negatively related to turnover intentions among IT professionals in Jordan.

H2: Stressors (Role ambiguity, Role conflict, and work overload) will have a negative effect on job satisfaction among IT professionals.Multiple Regression was used to test the second hypothesis, before test the effect of multivariables it should be to test the collinearity between the variables to know how each variable independency from others, table 11 shows the VIF values, here, if the VIF were less than (2.5), its mean we can do the multiple regression.

Table (11): collinearity testFactorVIF

Role ambiguity1.54

Role conflict1.12

work overload1.74

Multiple regressions indicate F calculated value (29.64) is significant due to the Sig (0.00). Table shows R which indicate how the independent variables (Role ambiguity, Role conflict, work overload) affect the dependent variable (job satisfaction), here it was (0.625). On the other hand; pearson correlation (R) determine how the variables are correlated for each other, it was (-0791), which mean these variable were negatively correlated. Our rule indicates that when the significant level was less than (0.05) we suggest that the model is a statistically significant. Through those results it can be concluded that Stressors (Role ambiguity, Role conflict, and work overload) will have a negative effect on job satisfaction among IT professionals. On the other hand, we found that (work overload) has the most effect on job satisfaction where = -0.435.Table (12): test of the second hypothesis DependentIndependentBeta ()F calculatedSigRR

Job satisfactionRole ambiguity-0.34629.640.00-0.7910.625

Role conflict-0.197

work overload-0.435

H3: Job satisfaction will mediate the effect of work stressors and intention to quit among IT professionals.Multiple Regression was used to test the third hypothesis. Results indicate F calculated value (36.71) is significant due to the Sig (0.00). Table shows R which indicate how the Job satisfaction will mediate the effect of work stressors here it was (0.602). On the other hand; pearson correlation (R) determine how the variables are correlated for each other, it was (-0.776), which mean these variable were negatively correlated. Our rule indicates that when the significant level was less than (0.05) we suggest that the model is a statistically significant. Through those results it can be concluded that Job satisfaction will mediate the effect of work stressors and intention to quit among IT professionals..Table (12): test of the second hypothesis DependentIndependentBeta ()F calculatedSigRR

Job satisfactionRole ambiguity-0.34636.710.00-0.7760.602

Role conflict-0.197

work overload-0.435

ConclusionThis study has examined the impact of job stress, stressors (role ambiguity, role conflict, work-overload), and job satisfaction on intention to quit job among IT professionals in Jordan. A total of 150 questionnaires were distributed on 12 IT companies in Jordan. Due to time constraints the selection of sampled companies was based on convenient sampling. A total of 100 surveys were collected at the end.

Based on the statistical analysis above we conclude that:1. Job satisfaction is negatively related to turnover intentions among IT professionals in Jordan.2. Stressors (Role ambiguity, Role conflict, and work overload) have a negative effect on job satisfaction among IT professionals in Jordan.3. Job satisfaction mediates the effect of work stressors and intention to quit among IT professionals.Managerial Implications:Role Stressors are found to be vitally important for intention to quit job. Role ambiguity is an important factor for quitting job. The clarity of job responsibilities and jobobjectives should be defined prior to the beginning of the job by the managers. Thedefinition of job responsibilities and job objectives may also be important for the highperformance of the workers. Since Knight et al. (2007) explored the negative significanteffect of role ambiguity on job performance. Generally , the IT firms should take into considerations the dimensions of each stressor and try to avoid those that negatively impact the job satisfaction of their employees in order to avoid higher turnover rates.

Limitations and Future Studies:Due to time and accessibility constraints we couldnt distribute questionnaires to a larger pool of IT companies in Jordan. Convenient sampling method was used to select the sample companies.One more thing, there are still other factors that contributes to the IT Professionals turnover intention, which we couldnt study due to time limitations. In the Future, we intend to build on our work and study other factors such organizational commitment, and many others.Also, the factors studied can be investigated in other industries as well.

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