A. Research Model

A. Research Model After presenting the theoretical background and the proposed hypotheses, the research depicts Figure (I) which illustrates all the relationships among the constructs under study.

Fig. I The Research Model

The model includes three hypotheses to be investigated, which represent the following constructs: emotional intelligence as the independent variable, retention as the dependent variable, and job involvement as the moderator between the two constructs.

II. RESEARCH METHODOLOGY A. Participants A total of 245 employees working with hotels and tourism corporations listed in Amman Stock Exchange in Jordan filled out a distributed survey; however 4 were excluded due to incomplete responses, leaving a total of 241 usable questionnaires. A five-point scale was employed for ranging from 1 (strongly disagree) to 5 (strongly agree). A single, open-ended item was used to separately measure age and income as values. The sample of participants had a mean age of 31.10 years and a standard deviation of 11.031 years, while in terms of income; the sample had a mean of JD526.28 and a standard deviation of JD252.184. B. Measures The questionnaire covered four sections as follows:

Control variables. Age was included as a control variable. Previous research had shown that demographic variables such as age [30] influence individuals’ attitudes toward other people or subjects, and, thus, might influence emotional intelligence or employee involvement. Income also, was included with age as control variables. Our reasoning was that income may correlate with emotional intelligence or employee involvement. Dependent variable: Retention, as the dependent variable, was measured using a 5-item scale developed by the author based on the study literature. Independent variable: Emotional intelligence was measured using a 10-item scale based on the Trait Meta-Mood Scale [31] and Schutte Self-Report Inventory [32]. Moderating variable: As for employee involvement, six items were adopted and partially adjusted from the study of Lodahl and Kejner [33] along with three additional items developed by the author.

III. DATA ANALYSIS AND FINDINGS A. Descriptive Statistics and Pearson Correlation Analysis The first step in the analyses was to conduct means, standard deviations, and correlations for the emotional intelligence, job involvement, and retention, and the demographic variables (age and income) as well. Descriptive statistics of the constructs are conducted through using SPSS 16, and the results are shown in the following table TABLE I DISCRIPTIVE STATISTICS FOR VARIABLES Mean S.D. 1. Age 31.10 11.031 2. Income 526.28 252.184 3. Emotional Intelligence 3.658 .661 4. Job Involvement 3.419 .653 5. Retention 3.506 .795

The highest mean was (3.658) for emotional intelligence with a standard deviation (.661), followed by retention (3.506) with a standard deviation of (.795). In addition, a bivariate correlation matrix among all the constructs is shown in the following table:

TABLE II INTERCORRELATIONS AND RELIABILITIES OF VARIABLES 1 2 3 4 5 1. Age ( - ) 2. Income .101 ( - ) 3. Emotional .017 .138* (.809) Intelligence 4. Job Involvement .050 .131* .559** (.827) 5. Retention .127* .154* .726** .644** (.801) Note: Alpha is represented in parentheses along diagonal *p < .05, **p < .01

An examination of the correlation matrix provides insight on the bivariate relationships among the variables under study. These coefficients also indicate no problem of multicollinearity because the independent variables are not highly correlated. At the same time, all Cronbach’s alpha values represented on the diagonal exceed the suggested 0.7 threshold, which can be considered as demonstrating a good level of reliability. As also shown on Table (II), retention was significantly correlated with age (r ＝ .127, p ＜ .05) and experience (r ＝ .154, p ＜ .05). Furthermore, there was a significant correlation between retention and emotional intelligence (r＝.726, p＜.01), and between retention and job involvement (r＝.644, p＜.01). A. Statistical Analyses for Study Hypotheses The hypothesis was tested using hierarchical regression analysis, through which three steps were estimated. The first step regressed retention on the control variables (age and income), the second added the effects of emotional intelligence and job involvement; while the third included the interaction of emotional intelligence and job involvement. The results were shown on Table (III). The current study applied the centering method to reduce the probabilities of multicollinearity. Following Aiken and West [34], emotional intelligence and job involvement were centered (i.e. by subtracting the mean from each score) and the interaction term was based on these centered scores. TABLE III HIERARCHICAL REGRESSION RESULTS FOR THE MODERATING EFFECTS

Variables Entered Model Model Model 1 2 3 Control Variables Age .144** .106* .101* Income .169** .048 .046

Independent Variable and .259** .892** Moderator .336** .683** Emotional Intelligence (EI) Job Involvement (JI) -.631* Interaction Term EI x JI .044 .577 .006 .005 .000 .048 Note: Δ R2 Sig. F Δ = .048 *p< .05, **p< .01, N=241

Examining the results of Table (III) revealed that emotional intelligence exhibited a significant effect on retention (β =.892, p <.01); thus, hypothesis 1 was supported. The results also exhibited that job involvement (β = .683, p < .01) significantly influenced retention; thus, Hypothesis 2 was supported. Hypothesis 3 posited that the effect of emotional intelligence on retention was moderated by job involvement. The results indicated that job involvement moderated the effects of emotional intelligence on retention (β = -.631, p < .05) Therefore, H3 is confirmed in the current study. To identify the trend of the interaction, the high and low levels of all variables, a plot was drawn with the help of Stats Tools Package. In fact, the moderation role in the effect of emotional intelligence (E.I.) on retention is dependent on the level of job involvement. Figure (II) presented the joint effect of emotional intelligence and job involvement levels on retention.

Fig. II The Effect of Emotional Intelligence on Retention by Levels of Job Involvement

As Figure (II) shows, participants perceiving high association of emotional intelligence and retention are significantly different from participants perceiving low association of emotional intelligence and retention. This means that the nature of emotional intelligence and retention relationship changes depending on the level of job involvement.