The Effects of Emotional Intelligence and Job Stress on Task Performance

Chapter 3: Research Methods 

The chapter gives an overall outline of the methodology employed in the study including key study areas such as the population of study, the research design, sample frame, sample size, methods of data collection, research procedures as well as data analysis and presentation. The correlation paper seeks to look into the problem of whether inadequate job performance of logistical mariners in the area of fuel accountability is related to high job stress and emotional intelligence. Managers and staff in charge of the petroleum have notices that the inconsistencies have increased and are further reflected in the dollar irregularities reported to DLA-Energy auditors each month (MSC Government Operations Safety Management System, 2017; Bar-On, Brown, Kirkcaldy & Thome, 2018). The poor performance among staff members in charge may be attributed to potentially stress levels of stress and low Emotional Intelligence levels (Extremera, Merida-Lopez, Sanchez-Alvarez, & Quintana-Orts, 2018; Macht, Nembhard, & Leicht, 2019). The ramifications of a workforce identified to have low Emotional intelligence, and high-stress traits could negatively impact productivity, offset reachable goals, or cause a costly turnover of critical positions (O’Connor, Nguyen, & Anglim, 2019; Boa, Xue & Kong, 2015), due to disciplinary assessments or from those employees who were dissatisfied with their employer. 

This correlation research hence seeks to investigate if the model variables (job stress and emotional intelligence) affect task performance of civilian mariners (Ahmadpanah, Keshavarz, Haghighi, Jhanaard, Bajoghi, Saheghi, Holsbeer-Trachsler & Brand, 2016). The chapter hence looks into the methods used in the research to determine the study population, collect data and analyze the data collected using a multivariate linear regression model that determines the existence of correlation between the model variables. The study takes into consideration a population of 30 CLF vessels and uses a sample size comprised of 239 supply department personnel. The chapter also presents the research design and gives a detailed description of how data will be analyzed and presented to meet the study objective. 

Research Methodology and Design 

The research design is the methods and techniques employed by the researcher in data collection and analysis meet the research objective stated out in the project or to answer research questions ( Lune & Berg, 2018) . It hence aims at improving the ability of the study in conceptualizing an operational plan to be able to embark on the various techniques available and required tasks for the completion of the study while at the same time ensuring that the procedures used are sufficient enough to acquire accurate, objective and precise responses to the research questions. 

Descriptive designs used in this research require that the researcher collects data and reports findings without any manipulations to the individual variables. The appropriateness of this design is that it will allow the researcher to utilize quantitative research methods to establish the existence of a relationship between emotional intelligence, task performance, and job stress for the study population. A Quantitative research approach is selected for this study because it is conclusive in that it aims at quantifying a problem and how it affects the population of study from the sample results obtained. Other methods of investigation such a qualitative approach would be inadequate for this study. 

Population and Sample 

The target population refers to subjects of a real or hypothetical set of events, objects or people which a researcher is interested in during a study depending on the relationship between the target and the research problem. The population of the study, in this case, consists of 30 CLF vessels, each consisting of from 100 – 130 personnel working in different departments. The Supply representative only ranges from five (T-AO manning numbers) to possibly 14 (T-AKE manning levels). 

The sample size of a survey is a very crucial element of research since it helps determine the accuracy of the results obtained, and hence the conclusions and recommendations made ( Fisher, 2017) . A sample thus refers to the percentage of the population chosen for purposes of a survey. The right sample size should be a fair representation of the target population, and hence the need for selecting a reasonable size that allows for accuracy, represents the population and is achievable ( Fisher, 2017) . Sampling, as a technique refers to the act of choosing a smaller proportion of the target population subjects to act as a representative of that population. It is, however, agreed that the larger the sample, the smaller the sampling error and the better the sample represents the population. However, large sample sizes made data collection time consuming and difficult for the research. As such, a researcher has to come up with the most appropriate sample size for the study depending on the study. This study uses random sampling to obtain 239 supply Department employees as respondents. During the study, the sample size is considered an optimal one because it is reliable, flexible, efficient and representative. 

The recommended sample size for any research study lies between 10% - 30% of the target population. Such restrictions ensure that an adequate sample is selected to avoid collection of too much data that becomes hard to analyse. The study used the Cochran method to calculate an accurate sample size depending according to the study confidence level, which has been selected at 5%. The sample size is hence calculated as: 

In the above formula 

e = error term 

p = % of the population having the attributes in study 

q = 1 – p. 

z is obtained from the Z tables depending on the confidence level selected 

A sample of 239 participants represents 12% of the total population from the 30 vessels is obtained for the study. Comparisons were made on the effectiveness of the strategies used to help the researcher identify the most effective approach. The research makes use of stratified convenient sampling methods. Stratified here is essential in that it helps in grouping the target population in categories based on the departments such as the manning department and purchasing department. Each of these classifications is considered a strum samples are then collected from each of the groups using the method of convenience sampling. 

Stratified random sampling is used to ensure that there are no cases of bias concerning who is included in the survey and that the sample collected was an accurate representation of the entire population ( Fisher, 2017) . This research combines both stratified and convenience sampling methods to come up with an appropriate sample. Stratified sampling is appropriate because it helps to group the target population into strata/categories based on different factors of study such as department, number of years in service, and training level. Each of these classifications is considered a stratum. From each of the stratum/category, samples were selected using the convenience sampling method. Convenience sampling helps the researcher to target those respondents that are available and willing to respond in each stratum as well as those most suitable for the research. Stratified random sampling reduces bias into the survey ensuring that data collected is accurate and represents the population fairly. By so doing, conclusions made are accurate and apply to the whole target population. 

Materials and Instrumentation 

This study will use questionnaires to gather the information required for the study. The questionnaires are designed and structured in a way that allows the research to communicate clearly to the respondent hence allowing them to collect accurate information from their subjects. At the same time, the questionnaires allow respondents to not only answer questions asked but also give their views and opinions on the study problem. A questionnaire refers to a research tool that is used by researchers to collect information from respondents through asking them to answer or respond to pre-determined questions. In this case, the research study seeks respond to the stated research questions: To what extent, if any, is there a correlation between Emotional intelligence and task-performance? And to what extent, if any, is there a correlation between Emotional Intelligence and job stress? 

The validity of research tools used in the survey is a crucial element of the research as it determines the accuracy of data collected, results obtained, and conclusions made. Validity of an instrument is accuracy degree with which the tool measures elements of the study. For validity testing, expert opinions will be sought from research experts to help improve the content validity of the instrument. The questionnaires handed out to the subjects were meant for research purposes only, and only the researcher and other authorized people are allowed to access the information collected. 

Before questionnaires are handed out to participants in the field, the researcher will carry out a pilot study because it is an important element of any study. A pilot study entails handing out of research questionnaire to a fraction of the sample and collecting responses prior to the actual data collection exercise. Pilot testing gives insights to the researcher on what to expect during the study and helps them improve the instruments of study such as questionnaires to enable them reach the study objective. The data collected during the pilot survey is also important as it enables the researcher determine early in advance whether or not there may be problems with analyzing the data. 

Operational Definition of Variables 

The study used a multivariate linear regression model to determine the existence of a relationship or correlation between the criterion (task performance) and predictor variables (job stress and emotional intelligence) ( Fisher, 2017) . The multivariate linear regression model used is indicated as: 

Y= β 0 +β 1 X 1 +β 2 X 2 + Ɛ 

Where; 

Y= Task performance 

β 0 = Constant Term; The constant equals the value of Y if all the x values in the model are zero 

β 1 and β 2 = Coefficients of variable 

X 1 =Emotional Intelligence 

X 2 = Job stress 

Ɛ=Error term 

All the predictor variables in the model have a different impact on the criterion variable such that a change in one variable results to a change in the criterion variable. The multivariate linear regression model is used to determine the factor that has the biggest impact on the criterion variable, making it possible to make conclusions on the most influential variable affecting task performance. 

Study Procedures 

The study sample will consist of 239 mariners, whereas the actual surveys will be completed aboard 30 US Navy CLF vessels. Data will be collected using validated surveys, including the TEIQue-SF to gather trait Emotional Intelligence information, the Trait Anxiety Inventory to measure trait anxiety data, and the IWPQ (Koopmans, et al., 2016) to measure task performance (Wei, Li, Zhang & Liu, 2018). Demographic data on each participant will be collected, including age, ethnicity, gender, the highest level of education completed, and length of employment. The data containing participant demographics, will only be used for the reporting of descriptive statistics. SPSS v.25 and Nvivo statistical software will be used for both descriptive and inferential data analysis, whereas the results will be reported using graphs and tables as well as in text format. 

This study sought to analyze Emotional Intelligence, task-performance, and stress levels for a potential relationship, and as such as multivariate regression will be used to analyze the data. More than one type of study was considered, e.g., experimental. Still, the primary focus will be to investigate if a relationship exists between task performance, EI and stress. The study also uses stratified sampling to get the population of study and a proportion of the study population as a sample. Once the population and the sample size have been determined, a pilot test is conducted where questionnaires are administered to the subjects and responses collected. The pilot study aims at identifying any challenges that the researcher may experience during data collection, as well as give insight into the nature and type of data they expect to collect. Positive results from the pilot study indicate that data collection can take place. Revised questionnaires are administered to the sample selected (239 respondents selected from 30 vessels) and responses collected. 

An informed consent form will be sent to participants inviting them to partake in the study. Data will be collected in hopes of generalizing the results to the MSC CIVMAR logistical population. These data will further help expand the existing knowledge of decision-makers and other workers' activities involving MSC's high demanding logistical work setting, which may have been impacted by EI factors (Miao, Humphrey & Qian, 2017). The evaluation of Emotional Intelligence, task-performance, and stress levels will generate in-depth awareness of variables impacting job performance (O’Connor et al., 2017), and further, reveal if EI can help diminish similar signs in other CIVMAR capacities. The data collected is then coded in a manner that allows analysis using SPSS v.25 and nVIVO statistical software. 

Data Collection and Analysis 

Questionnaires with both open questions and closed-ended questions will be used to collect primary data. Closed questions administered in the questionnaire enable the researcher to collect data relevant to the study, such as the gender of the respondent, their years of experience, level of education, and age. Such data helps the researcher come up with evidence to answer the research questions. Open ended questions on the other hand give the respondent a chance to express their views on the problem of study. 

Once data is collected, it is cleaned and coded using the quantitative coding method. This entails categorizing the collected data into related groups and assigning numerical codes to these groups. The numerical codes assigned to the non-numerical data helps the data analysis software understand the data and hence use the research model to give accurate results. Closed questions in the questionnaire such as those requiring a Yes or No answer, Male and Female are coded using numbers ones and zeros as decided by the researcher to represent each. The research study proposes the following hypotheses for each of the predictor variables. 

H1 o : There is no significant relationship between EI and task-performance. 

H1 a : There is a significant relationship between EI and task-performance. 

H2 o : There is no significant relationship between EI and job stress. 

H2 a : There is a significant relationship between EI and job stress. 

Once data has been coded, SPSS V.25 and nVIVO will be used to analyze the data. The research hypothesis will then be tested to find out whether claims made by the study are statistically true or false ( Bell, Bryman, Harley& Bryman, 2019) . An alpha value to help validate or invalidate the claim is set at α=0.05. From the data obtained and analyzed, a decision criterion to either validate or invalidate the null hypothesis is determined. This is based on the null hypothesis and the selected statistical method used to analyze the data. In this case, we use a 0.05 significance level, at a 95% confidence level and then proceed to collect data using experimental design. A p-value is then obtained, and we construct a construct acceptance and rejection region. Based on the test statistic obtained a decision on whether to accept the null hypothesis or not is made. If the p- value obtained from the ANOVA is less than α, then Reject H1 0 and H2 0 and Accept H1 a and H2 a. 

Assumptions 

This study will assume that emotional intelligence is related to task performance and job stress and influences the performance of maritime staff (Vashisht, Singh & Sharma, 2018). It is also assumed that the respondents selected for the study will be able to understand the questionnaires and give genuine responses. The research also assumes that the research findings will cut across all other marine departments and agencies and that it does not only apply to specific people in the procurement department but other employees. It is also assumed that the data obtained from the field will be enough for the study, and hence no data replication will be needed. 

Limitations 

The study is expected to face limitations in terms of time and resources available to complete it in time. Such limitations, if not put on check can lead to collection of inaccurate or irrelevant data or in delays in completion of the project. The researcher carries out a pilot study prior to the actual data collection exercise to ensure that all bottlenecks that could delay the project are identified early, and measures such as revising questionnaires, changing the sample or target population are taken in advance. 

Delimitations 

A single study cannot cover all the aspects of any subject area. Delimitation is the act of restricting a survey to a particular geographical area or subject. This study will, therefore, be carried out on a sample of marine staff working on 30 vessels. The study will not be generalized to address other factors affecting job performance for maritime workers, such as motivation and level of training. The research decision is to carry out a study on two factors (job stress and emotional intelligence) to determine their influence on task performance for staff handling petroleum products. However, no studies have been found to relate task performance to Emotional Intelligence and stress concerns in a non-traditional work environment, such as the MSC and in a specialized field such as the MSC merchant mariner (Lemisiou, 2018; Macht et al., 2019). 

MSC is a diverse and challenging environment, and improving accountability of the fuel inventory across all MSC CLF platforms has been identified as a constant challenge (MSC Government Operations Safety Management System, 2017). Poor performance can be associated with a lack of motivation, lack of focus, signs of anxiety, frustration, and poor compliance with set management protocols (Branscum et al., 2016; Weinzimmer et al., 2017) and this research will be designed to address the gaps regarding the role of EI not only in MSC but extend existing literature to now include working environments similar to MSC. 

Ethical Assurance 

Ethical procedures are an integral part of any study and need to be adhered to. Informed consent will be sought from all the participants that agreed to participate. The researcher will seek approval from Northcentral University’s Institutional Review Board (IRB) before data collection and shared with all participants as evidence of permission to carry out the study and as a way of assuring them that information given out will be used for study purposes only. Questionnaires administered to respondents are coded to ensure that there is no direct identification of a respondent. The data collected is stored safely, and no unauthorized personnel is allowed to access the data according to guidelines given by the university on data handling, storage and access. At the same time, assurance is given to all participants that all the data collected is also used for the intended purpose only. 

While carrying out the research and analyzing the data collected from the field, the researcher is likely going to face bias challenges, mainly because the research topic is essential to the researcher. Such kind of bias may influence data analysis through a biased interpretation of responses. To avoid such risks, the researcher may involve expert opinion in coding responses from the questionnaires to avoid both bias and errors. At the same time, the researcher needs to be fully aware of their opinion on the same and work objectively. 

Summary 

The quantitative research study aims to examine statistical relationships between Emotional Intelligence, task performance, and stress levels leading to the multiple inadequate assessments discovered globally during normal fueling operations in different marine vessels. The chapter assesses task performance to determine if high-stress levels and/or low Emotional Intelligence impacts the needed outcome for CIVMARs working in a high demanding work setting. MSC's performance standards are endogamous to that of the US Navy (Defense Logistics Agency ,2019). Task performance proficiency and endeavors of improving accountability expectations can be explained by the impact EI may have on stress levels amongst CIVMARs, ultimately, improving the job performance of afloat logistical workers (Borst, 2018). The research study identifies potential variables expected to have contributed towards the existing reduced productivity levels, the proposed instruments to assess relations between task-performance, stress, and EI include the TEIQue-SF, the Trait Anxiety Inventory, and the IWPQ. Once data is collected and coded, it is then analyzed using SPSS V.25 and nVIVO to make sense of it and determine whether or not a job performance is influence by emotional intelligence and job stress. Conclusions will be drawn from the results obtained and recommendations made on some of the most effective strategies to deal with low emotional intelligence and job stress among employees so as to increase productivity on assigned tasks. 

References

Ahmadpanah, M., Keshavarz, M., Haghighi, M., Jhanaard, L., Bajoghi, H., Saheghi, D., Holsbeer-Trachsler, E., & Brand, S. (2016). Higher emotional intelligence is related to lower test anxiety among students. Neuropsychiatric Disease and Treatment , 2016(1), 133-136, doi: 10.2147/NDT.S98259 

Bar-On, R., Brown, J. M., Kirkcaldy, B. D., & Thome, E. P. (2018). Emotional expression and implications for occupational stress: An application of the emotional quotient inventory (EQ-i). Personality and Individual Differences , 28, 1107-1118, doi: 10.1016/S0191-8869(99)00160-9 

  Bell, E., Bryman, A., Harley, B., & Bryman, A. (2019).  Business research methods . Oxford: Oxford University Press. 

Boa, X., Xue, S., & Kong, F. (2015). Dispositional mindfulness and perceived stress: The role of emotional intelligence. Personality and Individual Differences , 78, 48-52, doi: 10.1016/j.paid.2015.01.007 

Borst, R. T. (2018). Comparing work engagement in people-changing and people-processing service providers: A mediation model with red tape, autonomy, dimensions of PSM, and performance. Public Personnel Management , 47(3), 287-313, doi: 10.1177/0091026018770225 

Branscum, P., Haider, T., Brown, D., & Sharma, M. (2016). Using EI and social support to predict job performance of health educators. American Journal of Health Education , 47(5), 309-314, doi: 10.1080/19325037.2016.1203840 

Defense Logistics Agency (2019). Bulk Petroleum Products: Military Specification Fuels. https://www.dla.mil/Energy/Offers/Products/BulkPetroleum/ 

Extremera, N., Merida-Lopez, S., Sanchez-Alvarez, N., & Quintana-Orts, C. (2018). How does emotional intelligence make one feel better? The meditational role of work engagement. International Journal of Environmental Research and Public Health , 15(9), 1-13, doi: 10.3390/ijerph15091909 

Fisher, R. (2017).  Statistical methods for research workers . 

Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., Lerner, D., de Vet, H. C. W., & van der Beek, A. J. (2016). Individual Work Performance Questionnaire--American-English Version. PsycTESTS , doi : 10.1037/t64239-000 

Lemisiou, M. A. (2018). The effectiveness of person-centered coaching intervention in raising emotional and social intelligence competencies in the workplace. International Coaching Psychology Review , 13(2), 6-26, ProQuest. 

Lune, H., & Berg, B. L. (2018).  Qualitative research methods for the social sciences . 

Miao, C., Humphrey, R. H., & Qian, S. (2017). A meta-analysis of emotional intelligence and work attitudes. Journal of Occupational and Organizational Psychology , 90, 177-202, doi: 10.1111/joop.12167 

Military Sealift Command Government Operations Safety Management System. (2017). Cargo fuel management and accountability (MSC Report No. 6.8-002-ALL). Norfolk, VA: Author. 

O’Connor, P. J., Hill, A., Kaya, M., & Martin, B. (2019). The measurement of emotional intelligence: A critical review of literature and recommendations for researchers and practitioners. Frontiers in Psychology , 10(1116), 1-19, doi: 10.3389/fpsyg.2019.01116 

O’Connor, P., Nguyen, J., & Anglim, J. (2017). Effectively coping with task stress: A study of the validity of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF). Journal of Personality Assessment , 99(3), 304-314, doi: 10.1080/00223891.2016.1226175 

Vashisht, R., Singh, K., & Sharma, S. (2018). Emotional intelligence and its relationship with conflict management and occupational stress: A meta-analysis. Pacific Business Review International , 11(4), 30-38, EBSCohost. 

Wei, F., Li, Y., Zhang, Y., & Liu, S. (2018). The interactive effect of authentic leadership and leader competency on followers’ job performance: The mediating role of work engagement. Journal of Business Ethics , 153(3), 763-773, doi: 10.1007/s10551-016-3379-0 

Weinzimmer, L. G., Baumann, H. M., Gulliford, D. P., & Koubova, V. (2017). Emotional intelligence and job performance: The mediating role of work-family balance. The Journal of Social Psychology , 157(3), 322-337. doi: 10.1080/00224545.2016.1208141