Open access peer-reviewed chapter

The Effect of Emotional Intelligent on Team Performance: A Case Study of a Government Hospital

Written By

Lukman Setiawan

Submitted: 24 February 2021 Reviewed: 21 May 2021 Published: 15 September 2021

DOI: 10.5772/intechopen.98516

From the Edited Volume

The Science of Emotional Intelligence

Edited by Simon George Taukeni

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Abstract

Organizational development requires human resources. Professional organizations manage systems and the organizational mechanisms of existing resources to support flexible responses of change. Hospitals are a part of the service industry and have extraordinarily complex business processes, and a large potential for optimization and efficiency improvements. The aim of this study is to explore the relationship between emotional intelligence and team performance during the inter-institutionalized collaboration work process. This study was conducted in the South Sulawesi and Central Sulawesi Province’s hospitals. The study lasted for six months in 2017. The sampling was done by using the cluster method and stratified random sampling, which was based on hospital type and the level of health officers. The data analysis approach used in this study was the partial least square (PLS), using WarpPLS software. The results show that emotional intelligence significantly and positively affected team performance with a path coefficient value of 0.138 and a p-value of 0.050. Based on the results of the data analysis, it can be concluded that there is a significant direct influence of emotional intelligence on team performance.

Keywords

  • Emotional Intelligence
  • Team Performance
  • Government Hospital

1. Introduction

Hospitals are a part of the service industry and have overly complex business processes, and a large potential for optimisation and efficiency improvements [1]. The public demands for better health services indirectly requires the hospital to continuously develop [2]. To improve the quality of health services for the customer, the work should be done effectively and efficiently, and it requires continuous improvement with the least amount of resistance that is possible [3]. In the last decade hospitals and technical services for health care in Indonesia rapidly expanded; in 2012, the number of public hospitals was 1.608 and by 2013, the number of hospitals was 1.725.

The progressive development of health care services correlates with a decrease in the readiness of health personnel resources which can affect the quality of health services [4]. It is generally known that the level of knowledge and skills of health service providers can affect the performance of officers in the hospital sector and can directly affect the quality of service to customers, including patients and their families [5]. For this reason, hospital managers must integrate various potential existing resources to achieve maximum employee performance. Hospital management should implement a series of operational policies and standards that require the cooperation of all departments and divisions [6]. The tools that are arranged and implemented will benefit hospitals that have limited resources if all departments and divisions work together [7].

The quality of collaboration and interdepartmental team performance is expensive for the knowledge sharing function of a collaborative team [8]. Collaboration ability, competence and culture are the backgrounds of team performance in every organization, including hospitals [9]. In addition, variations in knowledge and motives among work team members will also have the potential to cause conflict as a necessity in every organization [10]. Internal conflict within the team at a hospital will have a detrimental effect on the harmonization of interaction and communication [11]. To reduce unwanted conflicts in work teams in government hospitals, the emotional intelligence of each team member is a dominant factor that must be cultivated [12].

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2. Materials and methods

This study applies an explanatory approach which is oriented to describe the position of each variable involved in the study [13]. At a further level, the study aims to analyze the relationship between variables using the appropriate unit analysis. Data collection was carried out for six months from May to September in 2017 at two government hospitals located in the provinces of South Sulawesi and Central Sulawesi. Information was obtained through interviews using a structured questionnaire on selected respondents according to the criteria set by the researcher [14]. In addition, additional information is obtained through observing the work atmosphere to obtain the real conditions of the work team at the hospital. Literature studies from various sources were also carried out to obtain secondary data to complement the research analysis [15]. Determination of respondents as the study sample was carried out by applying the cluster method and stratified random sampling [16], which was based on the type of hospital and the level of occupation of a health worker. The decision to use two sampling methods was based on the objective of obtaining a very heterogeneous representation of the information [17] through interviews with representatives of health workers. Methods of processing and data analysis using the WarpPLS software with the partial least square (PLS) method [18]. The data analysis design is illustrated in Figure 1.

Figure 1.

Data analysis design.

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3. Results

3.1 Validity and reliability testing

Data collection uses a questionnaire that has been tested to guarantee its reliability and validity [19]. The perception score was determined using the Likert scale. The Likert scale is a scale applied to assess behavior, attitudes and opinions [20]. This scale is particularly useful for application in survey research because it helps researchers to operationalize personality traits or perceptions. Likert scales usually use 5 or 7 answer items. The answer choices used most often ranged from Strongly Agree to Strongly Disagree. The Likert scale allows survey researchers to obtain a holistic picture of their opinion and level of agreement. Person Correlation Value is used to test the validity of the research instrument [21]. Person Correlation Value (r) is greater than 0.30, indicating that the item is valid and meets the requirements for use at a later stage in the field. Conversely, if the value of Pearson (r) is less than 0.30, it indicates that the item is not valid for use. The reliability test of the data collection instrument used Cronbach’s alpha analysis [22]. The Cronbach alpha coefficient value is above 0.60, indicating that the research instrument meets reliability principles; Conversely, if the Cronbach alpha coefficient value is below 0.60, it indicates that the data to be obtained will be biased because the instrument is not reliable. The validity and reliability test scheme is provided in Table 1 below.

VariablesIndicatorsValidityReliability
Emotional Intelligence (X1)X110.421Valid0.702Reliable
X120.423Valid
X130.472Valid
X140.446Valid
X150.422Valid
X160.373Valid
X170.509Valid
X180.375Valid
Team Performance (Y3)Y310.626Valid0.774Reliable
Y320.702Valid
Y330.664Valid
Y340.612Valid
Y350.620Valid
Y360.597Valid
Y370.479Valid
Y380.612Valid

Table 1.

Validity and Realibility of Indicators.

The results of the analysis show that all indicators for each variable have a value greater than 0.30 which indicates that the research instrument is valid. Likewise, the Cronbach’s alpha value is greater than 0.60 on all variables which indicates that the research instrument is declared reliable.

3.2 Goodness of fit test

The goodness-of-fit test uses the predictive-relevance (Q2) value in statistical hypothesis testing to analyze how well the sample data fits a distribution from a normally distributed population [23]. In addition, the difference between the observed value and the expected value of the normal distribution can be done by applying the Goodness-of-fit test [24]. The analysis showed that the predictive-relevance value reached 0.787 (78.7%); which indicates that the research model or design has a relevant predictive value. The level of prediction relevance at the value of 78.7% indicates that the level of diversity of research data that can be explained by the model is 78.7. Statistical interpretation explains that the information contained in the data can be explained by 78.7% through the model and the remaining 21.3% is interpreted by other variables not explained by the model) and error. The value of Q2> 75% indicates that the research model used is in an exceptionally good category and can be interpreted for further hypothesis testing [25].

3.3 Partial least square analysis results

Partial least squares (PLS) is a statistical method used to build a predictive model when various factors interact and collide [26]. PLS focuses on predicting responses and should not try to understand the underlying relationships between variables [27]. Another terminology of PLS is the inner model testing (structural model) [28] to test the research hypothesis using the t-test (TStatistic) on each of the partial direct influence pathways. The results of statistical analysis (WarpPLS) on the detailed data model are presented in Table 1. The Table 2 presents the results of hypothesis testing.

RelationshipPath Coefficientp-valueInformation
Emotional Intelligence (X1) → Team Performance (Y3)0.1380.050Significant

Table 2.

Inner model result in WarpPLS: Direct effect.

The results of testing the indirect effect of the emotional intelligence variable on team performance (health workers in the hospital) show that the path coefficient value reaches 0.138 with a p-value of 0.050. The p-value level of 0.05 indicates a significant direct effect of emotional intelligence on team performance (see Table 2). In addition, the path coefficient value which is positive indicates that there is a positive relationship between emotional intelligence and the level of performance of health workers. Statistical interpretation states that the higher the emotional intelligence of health workers in the hospital, the more optimal their performance will be.

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4. Discussion

The results of data analysis indicate that the intelligence variable has an empirically significant effect on team performance in government hospitals in two provinces. The path coefficient value of 0.138 with a p-value of 0.050 in direct testing indicates a significant direct effect between emotional intelligence and team performance in government hospitals [28]. Given that the path coefficient is positive, this indicates that the relationship is positive. The results of the study found that the emotional intelligence of a leader in a work team in the hospital had an impact on the performance of the staff, the effect of which was to mediate the emotional level and creativity of the team members. The results determined that health care quality correlated positively with emotional regulation. Emotional regulation was also positively correlated with group cohesion. It is surprising that emotional assessment was negatively correlated with the quality of health care provided by the team. This result indicates that EI and, more specifically, the emotional regulation can provide a new, interesting way to improve team cohesion [29].

Transactional leadership models basically work from the idea that managers give employees what they want in return for getting what they want [30]. In the case of the hospital, the staff providing health services are not independently motivated and thus require structure, instruction, and monitoring to complete tasks correctly and on time. The transformative leadership style that has emerged in government hospitals [31], generally displays a managerial leadership style, focusing on the role of supervisory, organization, and group performance [32, 33]. Leaders who adopt this style focus on a specific task and use rewards and punishments to motivate followers [34]. In addition, transactional and transformational leadership styles sending messages have a symbiotic relationship with emotional intelligence in the leadership style domain [35, 36].

The results of research which recommends that transactional/transformational leadership styles act as strong predictors of leadership strength [37] and abilities [38]. Several study have investigated the relationship between emotional intelligence and team performance and found that only emotional understanding and emotional management were positively correlated with multiple measures of team performance [39, 40, 41]. However, another fact stated by Hansenne (2008) indicated that emotional intelligence (EI) is assessed using a modified version of the Schutte Emotional Intelligence Scale and the cohesiveness with the Group Cohesiveness Scale [42]. Finally, the performance of the nurse team was measured at four different levels: job satisfaction.

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5. Conclusions

Emotional Intelligence Plays an Important Role in Improving Team Performance in an organization including hospitals. Based on the results of data analysis, it can be concluded that there is a direct and significant effect of emotional intelligence on team performance. It is important for leaders to understand, analyzed the emotions of themselves and the team members who work at a hospital. Emotionally intelligent team leaders will have useful insights into how to focus the interests and needs of team members. Including how to use and regulate emotions effectively to achieve maximum team performance. This study found that continuous and comprehensive handling of emotional intelligence for all teams within the hospital area is needed. Knowledge factors, team conflict and structural mechanisms strengthen the influence of Emotional Intelligence on team performance. Application of new ideas and processes, continuous innovation, application of skills, cognition, roles, key ideas, interpersonal relationships, division of labor, hierarchies of authority, rules of rights and obligations, and interpersonal relationships will drive the optimization of team performance. This research contributes to the development of theories of emotional intelligence and team performance. As a recommendation, the organization should ensure that the indicators are applied in the resource development planning system. The work team must be able to manage their negative emotions through emotional intelligence to reduce conflict, which in turn encourages creativity, facilitates effective communication, exchanges knowledge and is able to solve complex problems.

5.1 Significant statement

This study found that the emotional intelligence of team leaders had an impact on team performance. Emotional intelligence can be a mediating factor between the emotional level of team members and work team creativity. That can be beneficial for the head of the hospital and the ministry of health of the Republic of Indonesia to formulate a strategic policy related to increasing human resources in the Government Hospital. This study will help the researcher to cover the critical areas of the relationship between emotional intelligence on team performance during the inter-institutionalized collaboration work process. Thus, a new theory on the effect of emotional intelligence on team performance is arrived at.

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Acknowledgments

Bosowa University partially supported this research. The authors wish to thank the ministry of the health Republic of Indonesia for allowing us to conduct research. We thank our supervisor from Indonesia Bosowa University, who provided insight and expertise that greatly assisted the research. We thank Haris Maupa as a supervisor as a PhD supervisor supervised the analyses and edited the manuscript analysis.

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Conflict of interest

The authors whose names are listed in this article state that they have no affiliation or involvement in any organization or entity with any financial. The author declares that the article is the Authors’ original work and has not received prior publication and is not under consideration for publication elsewhere. This research has not been submitted for publication nor has it been published in whole or in other parts.

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Written By

Lukman Setiawan

Submitted: 24 February 2021 Reviewed: 21 May 2021 Published: 15 September 2021